Bio

Bio

Dr. Themistocles (Tim) Assimes, MD PhD, is a board-certified adult cardiologist and an Associate Professor of Medicine at Stanford University in the Division of Cardiovascular Medicine. Tim grew up in Montreal, Canada, where he received his medical degree from McGill University in 1994. He then pursued training in surgery for nearly two years before switching into internal medicine. He completed his residency in internal medicine as well as a masters degree in Epidemiology and Biostatistics at McGill before moving to Stanford University in 2001 to pursue fellowship training in cardiology. During his fellowship and initial faculty years at Stanford University, he also completed a PhD in Epidemiology and Biostatistics. Dr. Assimes currently devotes a majority of his time performing advanced population based research on the genomic causes of heart attacks and the common conditions that predispose people to heart attacks including high cholesterol, smoking, diabetes, obesity, high blood pressure, and insulin resistance. He has gained substantial experience collaborating with scientists at the international level by representing Stanford in large consortia meta analyzing genetic and genomic data. These efforts go beyond the standard SNP by SNP analyses and include analyses, interpretation, and integration of expression and allelic imbalance SNPs, genetic risk scores, Mendelian randomization, epigenetic, and gene set enrichment analyses for the identification of novel pathways of CHD in multi-ethnic populations. Concurrently, he teaches general cardiology as well as echocardiography to medical students, residents, and cardiology fellows-in-training at the Stanford affiliated Palo Alto VA hospital.

Academic Appointments

Administrative Appointments

  • Associate Director, Palo Alto Epidemiology Research and Information Center for Genomics, Palo Alto VA Hospital (2018 - Present)
  • Steering Committee, Project Baseline (2017 - Present)
  • Leadership Committee, Council of Functional Genomics and Translational Biology, American Heart Association (2016 - 2018)
  • Membership and Communications Committee, Council of Epidemiology and Prevention, American Heart Organization (2016 - 2018)
  • Steering Commitee, CARDIoGRAMplusC4D (http://www.cardiogramplusc4d.org/) (2012 - Present)
  • Co-chair, Women's Health Initiative Scientific Interest Group for Genetics, Proteomics & Biomarkers (2010 - Present)
  • Member, Ancillary Studies Committee, Women's Health Initiative (2010 - Present)

Honors & Awards

  • Fellow of the American Heart Association (FAHA), council of Epidemiology and Prevention, American Heart Association (03/01/2016)
  • Edwin L. Alderman award for excellence in Clinical Cardiovascular Research, Stanford University School of Medicine (2004, 2005)
  • Fellow of the Royal College of Physicians of Canada, Royal College of Physicians and Surgeons of Canada (2000-)
  • Chief Medical Resident, McGill University Medical Center - Royal Victoria Hospital (1999-2000)
  • J.W. McConnell Scholarship, McGill Universtiy (1989-1994)

Professional Education

  • PhD, McGill University, Epidemiology & Biostatistics (2008)
  • MS, McGill University, Epidemiology & Biostatistics (2001)
  • ABIM, Internal Medicine, (certification not maintained beyond 2009) (1999)

Contact

Research & Scholarship

Current Research and Scholarly Interests

Dr. Assimes investigative focus is the design, conduct, analysis, and interpretation of human molecular epidemiology studies of complex cardiovascular disease (CVD) related traits including coronary atherosclerosis, a condition that causes heart attacks, the number one killer in the US and many other countries, and risk factors for coronary atherosclerosis. In addition to performing discovery and validation population genomic studies, Dr. Assimes uses contemporary genetic studies to gain important insight on the causal and mechanistic nature of associations between purported risk factors and adverse cardiovascular related health outcomes through instrumental variable analyses and genetic risk score association studies of intermediate phenotypes. Dr. Assimes is also actively involved in studies assessing the clinical utility of novel genetic markers in isolation or in combination with other biomarkers. Lastly, Dr. Assimes communicates the significance of genomic findings at the population level to molecular biologists who may lack a strong background in human genetics as well as human geneticists who lack a strong background in clinical medicine. His broad translational knowledge base in this respect allows him to serve as a key collaborator in multidisciplinary investigative groups involved in the design and the interpretation of important functional experiments that will shed light on the biology behind these new genetic associations, as well as clinical trials the will help further delineate the utility of genomics in clinical practice.

Dr. Assimes currently has 2 openings for postdoctoral training in molecular epidemiology. If you are interested, please send a cover letter, your CV, and the names of 3 references to tassimes@stanford.edu. Candidates can read about funded projects Dr. Assimes is leading or is contributing substantially to below. Past funded proposals are also listed and described.

Clinical Trials

  • Personal Genomics for Preventive Cardiology Not Recruiting

    The purpose of this study is to see if providing information to a person on their inherited (genetic) risk of cardiovascular disease (CVD) helps to motivate that person to change their diet, lifestyle or medication regimen to alter their risk.

    Stanford is currently not accepting patients for this trial. For more information, please contact Josh Knowles, 650-804-2526.

    View full details

Projects

  • Integrative multi-omics in whole genome studies of HLBS disorders, Stanford University School of Medicine (5/1/2018 - 4/30/2020)

    Whole genome data will soon be available for tens to hundreds of thousands of individuals. This information is unprecedented in its ability to understand individual risk factors for disease. However, the volume of these data presents several major challenges to its interpretation. One powerful approach for interpreting genomes and identifying functional variants is to combine whole genome data with functional genomics or multi-omics data. Our research project focuses on multi-omics analyses in the TOPMED project to improve our understanding of individual and environmental genetic risk factors in heart, lung, blood and sleep (HLBS) disorders. In Aim 1, we will apply multi-omic outlier analysis to identify rare variants with large effects on multi-omics phenotypes. We will apply approaches we have developed in GTEx and SardiNIA that integrate genome and functional genomics data. Our premise is that rare genetic variants with large effects on -omics phenotypes will be strong candidates to contribute to an individual?s risk of genetic disease. Using these rare variants, we propose to improve understanding of the combined effects of common and rare variants in HLBS disorders. In Aim 2, we will apply and advance software we have developed to improve the mapping of gene-by-environment (GxE) and gene-by-gene (GxG) effects. Specifically, we have demonstrated that allele-specific signals have improved power for identifying both GxE and GxG genes and variants and we will apply our model to both transcriptome and methylome data in TOPMED to identify diverse hits for observed and latent environments. We will further conduct analyses to identify GxE hits for measured metabolites and, overall, with respect to differences in ancestry. Our premise is that GxE variants identified through multi-omics data analysis will define or modify genetic risk factors for HLBS and other disorders. The impact of discovered GxE and GxG variants will be evaluated through association analyses in the entire TOPMED cohort.
    Our activities will bring new opportunities to study and understand both individual and gene-by-environment effects influencing disease risk. By leveraging multi-omics data, we will integrate rare variant and gene-by-environment analyses within TOPMED; an activity that would typically require enormous investment and hundreds of thousands of samples if conducted with only genetic data. All software, pipelines and research results developed by our group will be rapidly available on standard websites, in the Cloud and available to support collaborative efforts within TOPMED and the larger research community. Further, as our team has extensive experience with large-scale genomics and functional genomics analysis, we will provide assistance and effort in implementing world-class analytical pipelines and further complement TOPMED with data from GTEx, MoTrPAC, DGN, WHI and other project data to enhance the power of analyses. Our effort will provide multiple avenues, from rare variants to environmental genetics, to aid in interpreting whole genomes and the impact of genetic variation in health and disease

    Location

    Stanford, CA

    Collaborators

    • Stephen Montgomery, Assistant Professor of Pathology, Genetics and, by courtesy, of Computer Science, Stanford University School of Medicine
    • Themistocles Assimes, Associate Professor of Medicine (Cardiovascular Medicine) and, by courtesy, of Health Research and Policy (Epidemiology), Palo Alto VA Healthcare System
    • Jonathan Pritchard, Professor of Genetics and of Biology, Stanford University School of Medicine
  • Proteomic Determinants of direct measures of insulin sensitivity, Stanford University School of Medicine (4/1/2018 - 3/31/2023)

    The consequences of insulin resistance (IR) include not only type 2 diabetes mellitus but also a cluster of metabolic abnormalities that double the risk of developing life-threatening complications of atherosclerosis including myocardial infarction, ischemic strokes, and peripheral arterial disease. The prevalence IR is increasing at an alarming rate as western populations become heavier and more sedentary. When one further considers the ongoing epidemiological transitions in developing countries in addition to the obesity epidemic in developed countries, the worldwide public health impact of IR is undoubtedly profound. Few pharmacological options exist that improve one?s insulin sensitivity and decrease the risk of complications from IR and recent genomic studies of surrogate measures of IR have yielded a disappointing number of new leads. Furthermore, a critical need exists for the development of more accurate blood-based diagnostic tests for IR. The long-term objective of the proposed research is to discover and validate novel protein markers of IR circulating in the blood of individuals who have undergone either one of the two ?gold standard? direct measures of insulin sensitivity: an insulin suppression test (IST) or a euglycemic clamp (EC). This information will be used to identify novel molecular pathways of IR that can be targeted pharmacologically and to develop statistical models that correlate highly with the degree of IR as estimated by direct measures of insulin sensitivity. In aim 1 of this proposal, the blood of 2100 white/European subjects who have undergone an IST at Stanford or an EC in the Relationship between Insulin Sensitivity and Cardiovascular Disease (RISC) and the Uppsala Longitudinal Study of Adult Men (ULSAM) studies will be measured for the presence of 981 proteins using an emerging platform that leverages novel technology referred to as the proximity extension assay. This technology allows for the accurate and reliable quantification of proteins in plasma down to the femtomolar or attomolar level. We will further validate the top signals identified in these subjects in an additional ~300 non-European subjects and a subset of 300 subjects from Stanford who underwent a second IST after weight loss or use of a thiazolidinedione. In aim 2, we will examine validated signals from Aim 1 for causality using the principal of Mendelian randomization, and we will quantify improvements afforded by validated markers over conventional measures in identifying subjects at risk of complications from IR. In aim 3, validated associations between proteins that appear causal in nature will be further examined through knockdown of the genes producing these proteins in human cell lines relevant to IR. These cell lines will include adipocytes, hepatocytes, and skeletal myocytes. This study is the largest study of the plasma proteome in relation to direct measures of insulin sensitivity ever proposed. Findings are expected to yield important mechanistic insights into the molecular basis of IR and provide the foundation for the development of a blood-based diagnostic test that can very reliably detect subjects at low or high risk of complications from IR.

    Location

    Stanford, CA

    Collaborators

    • Themistocles Assimes, Associate Professor of Medicine (Cardiovascular Medicine) and, by courtesy, of Health Research and Policy (Epidemiology), Palo Alto VA Healthcare System
    • Erik Ingelsson, Professor of Medicine (Cardiovascular Medicine) and, by courtesy, of Health Research and Policy (Epidemiology), Stanford University School of Medicine
    • Laura Lazzeroni, Professor (Research) of Psychiatry and Behavioral Sciences and of Biomedical Data Science, Stanford University School of Medicine
    • Joshua Knowles, Assistant Professor, Stanford University School of Medicine
    • Fahim Abbasi, Clinical Assistant Professor, Medicine - Cardiovascular Medicine, Medicine - Cardiovascular Medicine
    • John Petrie, Professor of Diabetic Medicine (Institute of Cardiovascular and Medical Sciences), University of Glasgow
  • Efficient electronic phenotyping using APHRODITE in the Million Veteran Program, Palo Alto VA Health Care System (4/1/2018 - 3/30/2020)

    The Million Veteran Program (MVP) is currently the largest biobank study in the world. The resource provides an unprecedented opportunity to identify the genetic causes of a variety of human diseases that disproportionally affect our veterans including diseases that affect the neurological, cardiovascular, pulmonary, gastrointestinal, endocrine, and musculoskeletal organs. Fast-paced technological progress over the last 10 years now allows us to reliably and densely profile individuals across their entire genome. Such data has already been generated and linked to a wide spectrum of human diseases and physiologic traits. However, many more links remain to be made which will provide the scientific community with additional important clues on the root causes of many life-threatening diseases as well as valuable insights on how to develop new drugs to treat or prevent these same diseases. The current challenge in making these additional discoveries is no longer the generation of high quality genetic data in large numbers but rather the organization and querying of very large and complex electronic health records (EHR) being leveraged by these large biobank studies. Until now, much effort and time has been expended to painstakingly develop and validate rules-based definitions to identify individuals with a specific disease, syndrome, or state across a variety of EHR platforms. However, the recent mapping of the VA corporate data warehouse to the Observational Medical Outcomes Partnership common data model (OMOP-CDM) provides us with unprecedented opportunities to apply new ?electronic phenotyping? tools that can identify individuals with a specific disease, syndrome, or state in a much more efficient manner than rules-based methods. The goal of this proposal is to comprehensively test the ability of one of these new tools named APHRODITE (Automated PHenotype Routine for Observational Definition, Identification, Training and Evaluation) to identify established genetic links among MVP participants. APHRODITE was developed at Stanford by one of our co-investigators and uses state of the art machine learning algorithms to identify individuals with a condition in a fraction of the time it takes to identify them through rules-based definitions. The algorithm has shown great promise within the Stanford clinical data warehouse but requires validation in other EHR cohorts. In aim 1, we will test the accuracy of an APHRODITE classifier to that of a rules-based classifier for at least 5 diseases using gold-standard sets in the VA. In aim 2, we will test whether APHRODITE classifiers from aim 1 can be applied to MVP participants to replicate established genetic associations. If automated methods in APHRODITE perform equally well or better than rules-based methods for multiple diseases, automated methods may be leveraged for phenotypes where rules based methods may not exist, maximizing the efficiency of genetic discovery in MVP and facilitating rapid replication of findings within MVP in other EHRs mapped to the OMOP-CDM.

    Location

    Palo Alto Health Care System, Palo Alto

    Collaborators

    • Themistocles Assimes, Associate Professor of Medicine (Cardiovascular Medicine) and, by courtesy, of Health Research and Policy (Epidemiology), Palo Alto VA Healthcare System
    • Jennifer Lee, Associate Professor, Stanford University School of Medicine
    • Philip Tsao, Professor (Research) of Medicine (Cardiovascular Medicine), Stanford University School of Medicine
    • Nigam Shah, Associate Professor of Medicine (Biomedical Informatics Research) and of Biomedical Data Science, Stanford University School of Medicine
    • Scott Duvall, Director, VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System
    • Julie Lynch, Investigator, Center for Healthcare Organization & Implementation Research, Veteran Affairs Administration
  • Whole Genome Sequence Analysis of Ischemic Stroke in the Women?s Health Initiative, Fred Hutchinson Cancer Research Center (4/5/2017 - 1/31/2021)

    Stroke is among the understudied disorders despite its high burden to morbidity and mortality in the US. Ischemic stroke, which is due to cerebral vessel occlusion, accounts for 80% of cases. Ischemic stroke is a complex, multi-factorial disease, with heterogeneity by age, sex, and stroke subtype. A substantial proportion of stroke risk remains unexplained. The relatively low yield of stroke genetic studies to date may reflect the heterogeneous causes and clinical presentations of the various subtypes. Many of the studies participating in stroke GWAS have included have had little or no data available on stroke-specific risk factors or other CVD outcomes, which are key to understanding causal mechanisms and potential gene?environment interactions. Next generation sequencing (NGS) and multi-omics integrative biology research offer new opportunities in the way we research and understand stroke. Whole genome sequence (WGS) data, including both coding and functional non-coding variants, are required to identify the full spectrum of contributions of uncommon variants to stroke risk. Deep WGS data are currently being generated in over 11,000 WHI participants through the NHLBI TOPMed project, including over 4,000 ischemic stroke cases. Here we propose to apply innovative statistical approaches to perform a well-powered analysis to discover, replicate, and functionally characterize new loci (particularly rare or low frequency coding and non-coding regulatory variants) for ischemic stroke (and its subtypes) using WGS and imputation. Discovery will be performed in ~4,000 incident ischemic stroke cases and over 5,000 controls from WHI with WGS through TOPMed. Single variant and gene-based tests will be performed, prioritizing ~100 genomic regions based on prior GWAS and current epigenomic and proteomic analyses. Replication will be performed through state-of-the art WGS-based exome and GWAS imputation in up to ~77,000 additional ischemic stroke cases (and controls) obtained through UKBiobank, Million Veteran Program, and the SiGN and METASTROKE stroke genomics consortia. To assess the biologic mechanism of stroke-associated genetic loci, we will further test any newly identified stroke loci for association with: (1) a rich set of CVD risk factors and ~40 plasma biomarkers related to atherosclerosis, thrombosis, inflammation, and hormones available in WHI; (2) a new, commercial panel of 184 emerging biomarkers related to neurovascular disease and CVD in 2000 WHI TOPMed samples selected on the basis of genotype. Using casual inference methodology, we will perform mediation analyses to determine mechanistic relationships between genotype, intermediate biomarker phenotype, and stroke outcome.

    Location

    Seattle, WA

    Collaborators

    • Alexander Reiner, Professor, Department of Epidemiology , University of Washington
    • Charles Kooberberg, Member and Program Head, Biostatistics Program, Fred Hutchinson Cancer Research Center
    • Themistocles Assimes, Associate Professor of Medicine (Cardiovascular Medicine) and, by courtesy, of Health Research and Policy (Epidemiology), Palo Alto VA Healthcare System
    • Rebecca Jackson, Professor of Medicine; Associate Dean for Clinical and Translational Research; Director, Center for Clinical and Translational Science, Ohio State University
    • Paul Auer, Assistant Professor , University of Wisconsin-Milwaukee
    • Braxton Dallam Mitchell Jr., Professor of Medicine and Epidemiology; Vice Division Chief, Endocrinol, Diabetes & Nutr, Univ of Maryland School of Medicine
    • Sylvia Wassertheil-Smoller, Distinguished University Professor and Dorothy and William Manealoff Foundation and Molly Rosen Professor of Social Medicine Emerita, Albert Einstein College of Med

    For More Information:

  • Genetics of Cardiometabolic Diseases in the VA Population, Veterans Health Administration (10/1/2016 - Present)

    Obesity, Type 2 diabetes (T2DM), and dyslipidemia are metabolic disorders that promote the development of coronary artery (CAD) and peripheral arterial disease (PAD). Collectively, these cardiometabolic conditions are leading causes of illness and death among Veterans. A substantial proportion of the variation in risk of clinical complications related to these conditions remains unexplained despite an understanding of the root factors involved. The VA Million Veteran Program (MVP) links information from Veterans? electronic heath record (EHR) to biomarker data measured from blood and provides an unparalleled opportunity to further explore the genetic basis of cardiometabolic diseases. We propose to use the genome wide genotyping data from the first 200,000 participants in MVP linked to the EHR to uncover novel associations between genetic variation and risk of cardiometabolic disease. To perform this research, we have assembled a team of investigators with extensive experience in VA based clinical research and population genetics. Many members of our team have not only participated in, but also have led, the most productive international collaborations over the last 10 years that have studied the genetic basis of cardiometabolic diseases. Our consortium includes investigators from 5 VISNs based at Palo Alto, Philadelphia, Phoenix, Bedford, and Albany as well as from Stanford University and the University of Pennsylvania. In Aim 1, we will establish optimal definitions of five cardiometabolic traits: body mass index, blood levels of cholesterol, as well as diagnoses of Type 2 diabetes (T2DM), CAD, PAD, using EHR derived information on medical diagnoses and treatments, physical exam and lab measures, and medication usage. Preliminary results of our queries of VA EHR data using the most liberal definitions of the traits have identified approximately 160,000 participants with lipid measurements, 195,000 participants with measurements of body-mass index, 100,000 participants with T2DM or prediabetes, 46,000 participants with CAD, and 9,000 participants with PAD. For quantitative traits, we will derive and study not only single time point measures but also long term averages for each individual. For outcomes, we will optimize our definitions by assessing the relationship between established risk factors including phenotype specific genetic risk scores and case-control status. In Aim 2, we will perform a series of genome wide association studies to confirm known loci and to identify novel genetic variation associated with our traits of interest. We will also use the comprehensive VA EHR to examine for the presence of gene-environment interactions. Finally, in Aim 3, we will apply novel statistical algorithms that will improve our understanding of the genetic variation that contributes to the risk of cardiometabolic diseases in both the African American and the Hispanic American populations by leveraging similarities in the genetic architecture among different race/ethnic groups. Successful completion of this project will help us to more thoroughly comprehend the underlying causes of cardiometabolic disease and to develop novel therapies that are safe, effective, and personalized. These discoveries will also result in the more reliable identification of individuals at risk for these disorders, allowing for the more optimal delivery of primary prevention strategies within the VA population.

    Location

    3801 Miranda 94304

    Collaborators

    • Philip Tsao, Professor (Research) of Medicine (Cardiovascular Medicine), Stanford University School of Medicine
    • Kyong-Mi Chang, Associate Professor of Medicine, University of Pennsylvania
    • Themistocles Assimes, Associate Professor of Medicine (Cardiovascular Medicine) and, by courtesy, of Health Research and Policy (Epidemiology), Palo Alto VA Healthcare System
    • Hua Tang, Professor of Genetics and, by courtesy, of Statistics, Stanford University School of Medicine
    • Jennifer Lee, Associate Professor, Stanford University School of Medicine
    • Daniel Rader , Seymour Gray Professor of Molecular Medicine, University of Pennsylvania
    • Scott Damrauer, Assistant Professor Of Surgery, University of Pennsylvania
    • Danish Salaheen, Assistant Professor, Department of Biostatistics and Epidemiology, University of Pennsylvania

    For More Information:

  • The Baseline Study, Stanford University School of Medicine (6/1/2016 - Present)

    To perform extensive phenotypic and integrative omic profiling of up to 10,000 newly enrolled individuals at risk of or with existing CHD or cancer.

    Location

    stanford, ca

    Collaborators

    • Sanjiv Gambhir, Professor, Stanford University School of Medicine
    • Kenneth Mahaffey, Professor, Stanford University School of Medicine
    • Themistocles Assimes, Associate Professor of Medicine (Cardiovascular Medicine) and, by courtesy, of Health Research and Policy (Epidemiology), Palo Alto VA Healthcare System
    • Millie Das, Clinical Assistant Professor, Stanford University School of Medicine
    • David Maron, Clinical Professor, Stanford University School of Medicine
    • George Sledge, Professor, Stanford University School of Medicine

    For More Information:

  • Causal associations of circulating biomarkers with cardiovascular disease, Stanford University School of Medicine (2/1/2017 - 1/31/2020)

    Cardiovascular diseases (CVD) comprise the global leading cause of morbidity and mortality, and in the United States, CVD account for more than one-third of all deaths, of which ~150,000 deaths per year occurs in individuals younger than 65 years. Over the past decades, hundreds of circulating biomarkers have been associated with CVD, but their relative importance and potential involvement in the actual disease processes have been less investigated. Using a very large cohort study that recently became available to the scientific community, we will deploy Mendelian randomization methods to study the causal role of biomarkers proposed to be associated with CVD. In 2006-2010, the UK Biobank recruited 502,650 participants aged 37-73 years to undergo physical measurements, detailed assessments about risk factors and future disease events, and sampling of blood, urine and saliva. Genome-wide genotyping on the UK Biobank Axiom Array (820,967 genetic markers) and measurement of 36 circulating biomarkers with relevance for CVD will be finished during 2016. We will study the associations of 36 circulating biomarkers representing coagulation and inflammation (fibrinogen, D-dimer, hsCRP, rheumatoid factor), glucose homeostasis (HbA1c, glucose, IGF-1), lipid metabolism (total cholesterol, LDL-C, HDL-C, triglycerides, ApoAI, ApoB, Lp(a)), liver function (ALT, AST, ALP, direct and total bilirubin, GGT, albumin, total protein), kidney function (creatinine, cystatin C, phosphate, urate, urea, urinary sodium, potassium, microalbumin and creatinine), reproductive system (SHBG, testosterone, oestradiol), and mineral metabolism (calcium, vitamin D) with incidence of coronary heart disease, stroke, heart failure, atrial fibrillation and type 2 diabetes in traditional observational multivariable-adjusted analyses. We will then perform genome-wide association studies (GWAS) of all 36 biomarkers to establish common genetic variation associated with respective biomarker. With a sample size of ~390,000 individuals, we will have excellent statistical power to uncover a substantial fraction of common genetic variants associated with the biomarkers. These associations will be used to develop robust instrumental variables. Finally, using instrumental variable analyses, we will study the causal roles of these circulating biomarkers for development of cardiovascular disease. The large sample size of the present study will allow for unprecedented possibilities of Mendelian randomization studies of CVD biomarkers with adequate statistical power and with low risk of pleiotropy. Knowledge about the causal roles of CVD-related biomarkers for development of coronary heart disease, stroke, heart failure, atrial fibrillation and type 2 diabetes will provide important insights regarding the etiological understanding of these diseases and accelerate new prevention strategies, including druggable targets.

    Location

    Stanford, CA

    Collaborators

    • Erik Ingelsson, Professor of Medicine (Cardiovascular Medicine) and, by courtesy, of Health Research and Policy (Epidemiology), Stanford University School of Medicine
    • Themistocles Assimes, Associate Professor of Medicine (Cardiovascular Medicine) and, by courtesy, of Health Research and Policy (Epidemiology), Palo Alto VA Healthcare System

    For More Information:

  • The Epigenetics Leads To Age-Related Diseases (Gilga-Mesh) Network, University of California Los Angeles (10/1/2015 - 3/31/2018)

    While life expectancy continues to rise, healthspan is not keeping pace because current disease treatments often decrease mortality without preventing the decline in overall health. It is crucial to understand how the underlying processes of aging affect susceptibility to chronic disease and related conditions. Epigenetic mechanisms have arguably become an important frontier in geroscience. We and others have shown that epigenetic biomarkers tend to be more strongly related with chronological age than existing biomarkers of aging. Importantly, we have recently demonstrated that epigenetic biomarkers of aging are prognostic of all-cause mortality in later life and correlate with measures of physical and cognitive fitness in older age. These data suggest that epigenetic mechanisms may play a role in mediating the effect of age on disease susceptibility. In this planning grant we lay out th framework needed to design a large-scale study that tests the overall hypothesis that epigenetic changes during aging collectively underlie aging as a risk factor for chronic diseases and degenerative conditions. We will generate preliminary results by leveraging existing epigenetic and phenotypic data available to our team of co-investigators and collaborators. These resources include data from the ENCODE project, various epigenetic data generated in multiple tissues, and richly phenotyped cohorts, such as the Baltimore Longitudinal Study of Aging (BLSA), InCHIANTI, the Women's Health Initiative, and the Lothian Birth Cohorts. We will evaluate different platforms for measuring epigenetic age, DNA methylation levels, chromatin states, and non-coding RNAs in terms of their relevance to our overall hypothesis, data quality, coverage, and price. While there exists a large body of literature on epigenetics and aging, our proposal is novel in terms of its breadth and depth: we will lay the groundwork for a study that investigates multiple epigenetic processes (DNA methylation, histone modifications, non-coding RNAs), multiple human tissues, multiple chronic conditions, at multiple time points using multiple well characterized human cohort studies and state-of-the-art statistical and bioinformatics techniques. Using pilot data from these and other studies, we will assess the reliability and precision of cutting-edge epigenetic measures and to estimate the resources needed for a future study. We will also assess to what extent epigenetic features in accessible human tissues (e.g., blood, buccal epithelium) can serve as surrogates for affected tissues and cell types. By organizing two workshops at UCLA, we will establish a research network comprised of leading researchers in the fields of aging research, epigenetics, epidemiology, genomics, and systems biology.

    Location

    Los Angeles

    Collaborators

    • Steven Horvath, Professor of Human Genetics & Biostatistics, University of California Los Angeles
    • Themistocles Assimes, Associate Professor of Medicine (Cardiovascular Medicine) and, by courtesy, of Health Research and Policy (Epidemiology), Palo Alto VA Healthcare System

    For More Information:

  • Coronary Artery Disease Genetics in Large Sample of Taiwan Chinese, Harbor-UCLA Medical Center (10/1/2015 - 3/31/2018)

    The major goal of this project is to conduct large-scale whole exome sequencing in multiple Taiwanese cohorts to identify novel genetic determinants of CAD related traits in Han Chinese. The main sponsor of this study is the Regeneron Genetics Center - Regeneron Pharmaceuticals

    Location

    Los Angeles, California

    Collaborators

    • Frederick Dewey, Senior Director and Head of the Translational Genetics , Regeneron Genetics Center
    • Ida Chen, Professor of Pediatrics & Medicine, Harbor-UCLA Medical Center
    • Jerome Rotter, Professor of Pediatrics, Medicine, and Human Genetics, Harbor-UCLA Medical Center
    • Themistocles Assimes, Associate Professor of Medicine (Cardiovascular Medicine) and, by courtesy, of Health Research and Policy (Epidemiology), Palo Alto VA Healthcare System
    • Thomas Quertermous, William G. Irwin Professor in Cardiovascular Medicine, Stanford University School of Medicine
  • Women's Health Initiative - Regional Centers 2015-2020, Stanford University School of Medicine (10/15/2015 - 10/14/2020)

    This represents the third extension study of the WHI involving 5 additional years follow-up for cardiovascular, cancer and other health outcomes in participants and a continued leveraging of the bioresource to conduct genomic and other biomarker studies. This contract supports the western regional center based at Stanford University.

    Location

    Stanford, CA

    Collaborators

    • Marcia Stefanick, Professor (Research) of Medicine (Stanford Prevention Research Center) and of Obstetrics and Gynecology, Stanford University School of Medicine
    • Themistocles Assimes, Associate Professor of Medicine (Cardiovascular Medicine) and, by courtesy, of Health Research and Policy (Epidemiology), Palo Alto VA Healthcare System
    • Mark Hlatky, Professor, Stanford University School of Medicine
    • Marco Perez, Assistant Professor, Stanford University School of Medicine

    For More Information:

  • A pilot RNA-seq study among Long Life Study participants of the WHI, Stanford University School of Medicine (3/1/2015 - 8/31/2015)

    RNAseq on whole blood from 100 participants of the Women's Health Initiative Long Life Study

    Location

    Stanford, CA

    Collaborators

    • Themistocles Assimes, Associate Professor of Medicine (Cardiovascular Medicine) and, by courtesy, of Health Research and Policy (Epidemiology), Palo Alto VA Healthcare System
    • Stephen Montgomery, Assistant Professor of Pathology, Genetics and, by courtesy, of Computer Science, Stanford University School of Medicine

    For More Information:

  • Determinants of Insulin mediated glucose update in South Asians, Stanford University School of Medicine (4/1/2011 - 1/31/2015)

    The purpose of this award is to provide Dr. Themistocles (Tim) Assimes, Assistant Professor of Medicine at Stanford University, the support necessary to transition him from a junior investigator to an independent physician scientist studying the genetic determinants of various human complex traits related to cardiovascular medicine. Dr. Assimes is an adult cardiologist with an advanced degree in epidemiology and biostatistics and significant experience conducting human genetic studies using existing sample sets. Career development activities focus on consolidating his expertise by 1) designing and implementing his first human subjects clinical research study involving handling of biospecimens, 2) increasing his involvement in several international genetic epidemiology collaborations, and 3) attending didactic courses to expand his knowledge base in contemporary genetics, molecular biology, advanced statistical genetics and the pathophysiology of insulin resistance (IR). An advisory committee, which includes his mentors, Drs. Thomas Quertermous and Gerald Reaven, will carefully monitor his progress towards independence. The research proposal builds on ongoing efforts in the candidate?s division to identify the root causes of IR by studying South Asians, a racial/ethnic group known to be strongly predisposed to IR and its adverse consequences for unclear reasons. In this context, Specific Aim 1 proposes to quantify IR and its primary established determinants of adiposity and physical fitness in ~330 South Asians and ~100 white/Europeans using ?gold standard? measuring tools. These include an insulin suppression test to assess insulin mediated glucose uptake, DXA and abdominal MRI scans to determine total and regional body fat, pedometers to estimate current physical activity, and a symptom limited cardiopulmonary stress test to estimate maximum oxygen uptake (max VO2). A new research partnership between the non-profit South Asian Heart Center at El Camino Hospital, Mountain View, CA, and Division of Cardiovascular Medicine at Stanford University will facilitate recruitment. This aim will test the hypothesis that a predisposition to IR in South Asians is evident even after taking into account significant differences between the two racial/ethnic groups in adiposity and physical fitness not captured by more traditional methods of assessment of these variables (e.g., BMI and physical activity questionnaires). In Specific Aim 2, the candidate will perform genome wide genotyping in ~400 South Asians followed by gene/SNP set pathway analyses using innovative analytical techniques developed by collaborators at SAGE Bionetworks. The same analytical techniques will be applied to multiple other sample sets with GWAS and direct measures of IR representing 3 other race/ethnic groups including Europeans, East Asians, and Hispanics. This aim will compare and contrast pathways associated with IR across all groups and test the hypothesis that South Asians are more IR because they have inherited a relatively inefficient cellular mechanism of handling glucose compared to other racial/ethnic groups.

    Location

    Stanford, CA

    Collaborators

    • Themistocles Assimes, Associate Professor of Medicine (Cardiovascular Medicine) and, by courtesy, of Health Research and Policy (Epidemiology), Palo Alto VA Healthcare System
    • Stephen Fortmann, C.F. Rehnborg Professor in Disease Prevention, Emeritus, Stanford University School of Medicine
    • Fahim Abbasi, Clinical Assistant Professor, Medicine - Cardiovascular Medicine, Medicine - Cardiovascular Medicine
    • Latha Palaniappan, Professor, Stanford University School of Medicine
    • Thomas Quertermous, William G. Irwin Professor in Cardiovascular Medicine, Stanford University School of Medicine
    • Philip Tsao, Professor (Research) of Medicine (Cardiovascular Medicine), Stanford University School of Medicine
    • Gerald M Reaven, Stanford University School of Medicine
  • Utility of the Aviir risk score in predicting incident coronary heart disease in the WHI, Stanford University School of Medicine (8/1/2011 - 7/31/2013)

    To test the ability of serum levels of 7 novel biomarkers to improve prediction for incident CHD over standard risk scores in the WHI observational study.

    Location

    Stanford, CA

    Collaborators

    • Themistocles Assimes, Associate Professor of Medicine (Cardiovascular Medicine) and, by courtesy, of Health Research and Policy (Epidemiology), Palo Alto VA Healthcare System
  • A randomized trial of personal genomics for preventive cardiology, Stanford Research Pilot Grant, Innovation Awards in Population Medicine (5/1/2011 - 4/30/2012)

    To test the hypothesis that giving patients information about their genetic risk of CAD will increase their adherence to therapy, behavior or help them affect lifestyle changes.

    Location

    Stanford, CA

    Collaborators

    • Joshua Knowles, Assistant Professor, Stanford University School of Medicine
    • Themistocles Assimes, Associate Professor of Medicine (Cardiovascular Medicine) and, by courtesy, of Health Research and Policy (Epidemiology), Palo Alto VA Healthcare System
    • John Ioannidis, C. F. Rehnborg Professor in Disease Prevention in the School of Medicine and Professor of Health Research and Policy (Epidemiology) and, by courtesy, of Statistics and of Biomedical Data Science, Stanford University School of Medicine
    • Michael McConnell, Clinical Professor, Stanford University School of Medicine
    • Euan Ashley, Professor, Stanford University School of Medicine
    • Shirin Jimenez, Clinical Assistant Professor, Stanford University School of Medicine

    For More Information:

  • Integrative genomics and risk of CHD and related phenotypes in the Women?s Health Initiative, Stanford University School of Medicine (3/29/2013 - 3/28/2016)

    To identify genomic signatures and pathways relevant to CHD and its risk factors through large scale methylation and circulating micro-RNA profiling in the WHI

    Location

    Stanford, CA

    Collaborators

    • Themistocles Assimes, Associate Professor of Medicine (Cardiovascular Medicine) and, by courtesy, of Health Research and Policy (Epidemiology), Palo Alto VA Healthcare System
    • Devin Absher, Faculty Investigator, Hudson Alpha Institute for Biotechnology
    • Philip Tsao, Professor (Research) of Medicine (Cardiovascular Medicine), Stanford University School of Medicine
    • Steve Horvath, Professor of Human Genetics & Biostatistics, UCLA

    For More Information:

  • Whole Genome Association for Early Coronary Artery Disease and Related Phenotypes, Stanford University School of Medicine / Kaiser Permanente DOR (10/1/2006 - 7/31/2010)

    Perform a whole genome association study on the ADVANCE study in search of novel genetic determinants of CAD and CAD risk factors.

    Location

    Stanford, CA

    Collaborators

    • Thomas Quertermous, William G. Irwin Professor in Cardiovascular Medicine, Stanford University School of Medicine
    • Themistocles Assimes, Associate Professor of Medicine (Cardiovascular Medicine) and, by courtesy, of Health Research and Policy (Epidemiology), Palo Alto VA Healthcare System
    • Joshua Knowles, Assistant Professor, Stanford University School of Medicine
    • Neil Risch, Professor, Division of Biostatistics / Director, Institute for Human Genetics, UCSF
    • Alan Go, Director, Comprehensive Clinical Research Unit , Kaiser Permanente Northern California Division of Research
    • Carlos Iribarren, Research Scientist, Kaiser Permanente Northern California Division of Research

    For More Information:

Teaching

2017-18 Courses

Stanford Advisees

Graduate and Fellowship Programs

Publications

All Publications

  • Trans-ethnic fine-mapping of genetic loci for body mass index in the diverse ancestral populations of the Population Architecture using Genomics and Epidemiology (PAGE) Study reveals evidence for multiple signals at established loci HUMAN GENETICS Fernandez-Rhodes, L., Gong, J., Haessler, J., Franceschini, N., Graff, M., Nishimura, K. K., Wang, Y., Highland, H. M., Yoneyama, S., Bush, W. S., Goodloe, R., Ritchie, M. D., Crawford, D., Gross, M., Fornage, M., Buzkova, P., Tao, R., Isasi, C., Aviles-Santa, L., Daviglus, M., Mackey, R. H., Houston, D., Gu, C. C., Ehret, G., Nguyen, K. H., Lewis, C. E., Leppert, M., Irvin, M. R., Lim, U., Haiman, C. A., Le Marchand, L., Schumacher, F., Wilkens, L., Lu, Y., Bottinger, E. P., Loos, R. J., Sheu, W. H., Guo, X., Lee, W., Hai, Y., Hung, Y., Absher, D., Wu, I., Taylor, K. D., Lee, I., Liu, Y., Wang, T., Quertermous, T., Juang, J. J., Rotter, J. I., Assimes, T., Hsiung, C. A., Chen, Y. I., Prentice, R., Kuller, L. H., Manson, J. E., Kooperberg, C., Smokowski, P., Robinson, W. R., Gordon-Larsen, P., Li, R., Hindorff, L., Buyske, S., Matise, T. C., Peters, U., North, K. E. 2017; 136 (6): 771-800

    Abstract

    Most body mass index (BMI) genetic loci have been identified in studies of primarily European ancestries. The effect of these loci in other racial/ethnic groups is less clear. Thus, we aimed to characterize the generalizability of 170 established BMI variants, or their proxies, to diverse US populations and trans-ethnically fine-map 36 BMI loci using a sample of >102,000 adults of African, Hispanic/Latino, Asian, European and American Indian/Alaskan Native descent from the Population Architecture using Genomics and Epidemiology Study. We performed linear regression of the natural log of BMI (18.5-70 kg/m(2)) on the additive single nucleotide polymorphisms (SNPs) at BMI loci on the MetaboChip (Illumina, Inc.), adjusting for age, sex, population stratification, study site, or relatedness. We then performed fixed-effect meta-analyses and a Bayesian trans-ethnic meta-analysis to empirically cluster by allele frequency differences. Finally, we approximated conditional and joint associations to test for the presence of secondary signals. We noted directional consistency with the previously reported risk alleles beyond what would have been expected by chance (binomial p < 0.05). Nearly, a quarter of the previously described BMI index SNPs and 29 of 36 densely-genotyped BMI loci on the MetaboChip replicated/generalized in trans-ethnic analyses. We observed multiple signals at nine loci, including the description of seven loci with novel multiple signals. This study supports the generalization of most common genetic loci to diverse ancestral populations and emphasizes the importance of dense multiethnic genomic data in refining the functional variation at genetic loci of interest and describing several loci with multiple underlying genetic variants.

    View details for DOI 10.1007/s00439-017-1787-6

    View details for Web of Science ID 000401341500009

    View details for PubMedID 28391526

  • Fifteen new risk loci for coronary artery disease highlight arterial-wall-specific mechanisms. Nature genetics Howson, J. M., Zhao, W., Barnes, D. R., Ho, W., Young, R., Paul, D. S., Waite, L. L., Freitag, D. F., Fauman, E. B., Salfati, E. L., Sun, B. B., Eicher, J. D., Johnson, A. D., Sheu, W. H., Nielsen, S. F., Lin, W., Surendran, P., Malarstig, A., Wilk, J. B., Tybjærg-Hansen, A., Rasmussen, K. L., Kamstrup, P. R., Deloukas, P., Erdmann, J., Kathiresan, S., Samani, N. J., Schunkert, H., Watkins, H., Do, R., Rader, D. J., Johnson, J. A., Hazen, S. L., Quyyumi, A. A., Spertus, J. A., Pepine, C. J., Franceschini, N., Justice, A., Reiner, A. P., Buyske, S., Hindorff, L. A., Carty, C. L., North, K. E., Kooperberg, C., Boerwinkle, E., Young, K., Graff, M., Peters, U., Absher, D., Hsiung, C. A., Lee, W., Taylor, K. D., Chen, Y., Lee, I., Guo, X., Chung, R., Hung, Y., Rotter, J. I., Juang, J. J., Quertermous, T., Wang, T., Rasheed, A., Frossard, P., Alam, D. S., Majumder, A. A., Di Angelantonio, E., Chowdhury, R., Chen, Y. I., Nordestgaard, B. G., Assimes, T. L., Danesh, J., Butterworth, A. S., Saleheen, D. 2017

    Abstract

    Coronary artery disease (CAD) is a leading cause of morbidity and mortality worldwide. Although 58 genomic regions have been associated with CAD thus far, most of the heritability is unexplained, indicating that additional susceptibility loci await identification. An efficient discovery strategy may be larger-scale evaluation of promising associations suggested by genome-wide association studies (GWAS). Hence, we genotyped 56,309 participants using a targeted gene array derived from earlier GWAS results and performed meta-analysis of results with 194,427 participants previously genotyped, totaling 88,192 CAD cases and 162,544 controls. We identified 25 new SNP-CAD associations (P < 5 × 10(-8), in fixed-effects meta-analysis) from 15 genomic regions, including SNPs in or near genes involved in cellular adhesion, leukocyte migration and atherosclerosis (PECAM1, rs1867624), coagulation and inflammation (PROCR, rs867186 (p.Ser219Gly)) and vascular smooth muscle cell differentiation (LMOD1, rs2820315). Correlation of these regions with cell-type-specific gene expression and plasma protein levels sheds light on potential disease mechanisms.

    View details for DOI 10.1038/ng.3874

    View details for PubMedID 28530674

  • Effect of Common Genetic Variants of Growth Arrest-Specific 6 Gene on Insulin Resistance, Obesity and Type 2 Diabetes in an Asian Population. PloS one ; 10 (8): e0135681

    Abstract

    Growth arrest-specific 6 (Gas6), a vitamin K-dependent protein, has been implicated in systemic inflammation, obesity, and insulin resistance (IR). Data from recent studies suggest that polymorphisms in the Gas6 gene are associated with cardiovascular disorders and type 2 diabetes (T2D). However, the association of Gas6 gene variants with obesity, IR, and T2D development has not been explored.Four common single nucleotide polymorphisms (SNPs) in the Gas6 gene were genotyped in 984 participants from the Stanford Asia-Pacific Program for Hypertension and Insulin Resistance (SAPPHIRe) family cohort. An insulin suppression test was performed to determine IR based on steady-state plasma glucose (SSPG). Associations between IR indices and obesity, and SNP genotypes, based on previously-reported data for this cohort (Phase I), were analyzed. In the present follow-up study (Phase II), the effects of gene variants of Gas6 on the progression to T2D were explored in individuals who were free of T2D in Phase I. The mean follow-up period for Phase II was 5.7 years.The mean age of the study population in Phase I was 49.5 years and 16.7% of individuals developed T2D during follow-up. After adjusting for covariates, three SNPs (rs8191973, rs8197974, and rs7323932) were found to be associated with SSPG levels (p = 0.007, p = 0.03, and p = 0.011, respectively). This association remained significant after multiple testing and showed a significant interaction with physical activity for SNP rs8191973. However, no other significant correlations were observed between Gas6 polymorphisms and other indices of IR or obesity. A specific haplotype, AACG (from rs8191974, rs7323932, rs7331124, and rs8191973), was positively associated with SSPG levels (p = 0.0098). None of the polymorphisms were associated with an increased risk of T2D development.Our results suggest that Gas6 gene variants are associated with IR, although their effects on subsequent progression to T2D were minimal in this prospective Asian cohort.

    View details for DOI 10.1371/journal.pone.0135681

    View details for PubMedID 26284522

  • Association analyses of East Asian individuals and trans-ancestry analyses with European individuals reveal new loci associated with cholesterol and triglyceride levels HUMAN MOLECULAR GENETICS Spracklen, C. N., Chen, P., Kim, Y. J., Wang, X., Cai, H., Li, S., Long, J., Wu, Y., Wang, Y. X., Takeuchi, F., Wu, J., Jung, K., Hu, C., Akiyama, K., Zhang, Y., Moon, S., Johnson, T. A., Li, H., Dorajoo, R., He, M., Cannon, M. E., Roman, T. S., Salfati, E., Lin, K., Guo, X., Sheu, W. H., Absher, D., Adair, L. S., Assimes, T. L., Aung, T., Cai, Q., Chang, L., Chen, C., Chien, L., Chuang, L., Chuang, S., Du, S., Fan, Q., Fann, C. S., Feranil, A. B., Friedlander, Y., Gordon-Larsen, P., Gu, D., Gui, L., Guo, Z., Heng, C., Hixson, J., Hou, X., Hsiung, C. A., Hu, Y., Hwang, M. Y., Hwu, C., Isono, M., Juang, J. J., Khor, C., Kim, Y. K., Koh, W., Kubo, M., Lee, I., Lee, S., Lee, W., Liang, K., Lim, B., Lim, S., Liu, J., Nabika, T., Pan, W., Peng, H., Quertermous, T., Sabanayagam, C., Sandow, K., Shi, J., Sun, L., Tan, P. C., Tan, S., Taylor, K. D., Teo, Y., Toh, S., Tsunoda, T., van Dam, R. M., Wang, A., Wang, F., Wang, J., Wei, W. B., Xiang, Y., Yao, J., Yuan, J., Zhang, R., Zhao, W., Chen, Y. I., Rich, S. S., Rotter, J. I., Wang, T., Wu, T., Lin, X., Han, B., Tanaka, T., Cho, Y. S., Katsuya, T., Jia, W., Jee, S., Chen, Y., Kato, N., Jonas, J. B., Cheng, C., Shu, X., He, J., Zheng, W., Wong, T., Huang, W., Kim, B., Tai, E., Mohlke, K. L., Sim, X. 2017; 26 (9): 1770-1784

    Abstract

    Large-scale meta-analyses of genome-wide association studies (GWAS) have identified?>175 loci associated with fasting cholesterol levels, including total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG). With differences in linkage disequilibrium (LD) structure and allele frequencies between ancestry groups, studies in additional large samples may detect new associations. We conducted staged GWAS meta-analyses in up to 69,414 East Asian individuals from 24 studies with participants from Japan, the Philippines, Korea, China, Singapore, and Taiwan. These meta-analyses identified (P?

    View details for DOI 10.1093/hmg/ddx062

    View details for Web of Science ID 000400912200015

    View details for PubMedID 28334899

  • Coffee consumption is associated with DNA methylation levels of human blood EUROPEAN JOURNAL OF HUMAN GENETICS Chuang, Y., Quach, A., Absher, D., Assimes, T., Horvath, S., Ritz, B. 2017; 25 (5): 608-616

    Abstract

    Beneficial health effects have been attributed to coffee consumption, but it is not yet known whether epigenetics may have a role in this process. Here we associate epigenome-wide DNA methylation levels to habitual coffee consumption from two studies with blood (2100 and 215 participants), and one with saliva samples (256 participants). Adjusting for age, gender, and blood cell composition, one CpG (cg21566642 near ALPPL2) surpassed genome-wide significance (P=3.7 × 10(-10)) and from among 10 additional CpGs significant at P?5.0 × 10(-6), six were located within 1500?bps of a transcriptional start site. Results for these 11 top-ranked CpGs remained significant after further adjusting for smoking. Also, methylation levels of another 135 CpGs were influenced by both coffee drinking and smoking (P?1.0 × 10(-7)). Functional enrichment analysis suggested that coffee-associated CpGs were located near transcription factor binding (P=1.2 × 10(-6)) and protein kinase activity genes (P=2.9 × 10(-5)). Interestingly, when we stratified by menopausal hormone therapy (MHT), methylation differences with coffee consumption were observed only in women who never used MHT. We did not replicate any of the associations found in blood in our saliva samples, suggesting that coffee may affect DNA methylation levels in immune cells of the blood but not in saliva.

    View details for DOI 10.1038/ejhg.2016.175

    View details for Web of Science ID 000399406200014

    View details for PubMedID 28198392

  • Leveraging information from genetic risk scores of coronary atherosclerosis. Current opinion in lipidology Assimes, T. L., Salfati, E. L., Del Gobbo, L. C. 2017; 28 (2): 104-112

    Abstract

    Genome-wide association studies (GWAS) have identified ?60 loci for coronary artery disease (CAD). Through genetic risk scores (GRSs), investigators are leveraging this genomic information to gain insights on both the fundamental mechanisms driving these associations as well as their utility in improving risk prediction.GRSs of CAD track with the earliest atherosclerosis lesions in the coronary including fatty streaks and uncomplicated raised lesions. In multiple cohort studies, they predict incident CAD events independent of all traditional and lifestyle risk factors. The incorporation of SNPs with suggestive but not genome-wide association in GWAS into GRSs often increases the strength of these associations. GRS may also predict recurrent events and identify patients most likely to respond to statins. The effect of the GRS on discrimination metrics remains modest but the minimal degree of improvement needed for clinical utility is unknown.Most novel loci for CAD identified through GWAS facilitate the formation of coronary atherosclerosis and stratify individuals based on their underlying burden of coronary atherosclerosis. GRSs may one day be routinely used in clinical practice to not only assess the risk of incident events but also to predict who will respond best to established prevention strategies.

    View details for DOI 10.1097/MOL.0000000000000400

    View details for PubMedID 28207434

  • Epigenetic clock analysis of diet, exercise, education, and lifestyle factors. Aging Quach, A., Levine, M. E., Tanaka, T., Lu, A. T., Chen, B. H., Ferrucci, L., Ritz, B., Bandinelli, S., Neuhouser, M. L., Beasley, J. M., Snetselaar, L., Wallace, R. B., Tsao, P. S., Absher, D., Assimes, T. L., Stewart, J. D., Li, Y., Hou, L., Baccarelli, A. A., Whitsel, E. A., Horvath, S. 2017; 9 (2): 419-446

    Abstract

    Behavioral and lifestyle factors have been shown to relate to a number of health-related outcomes, yet there is a need for studies that examine their relationship to molecular aging rates. Toward this end, we use recent epigenetic biomarkers of age that have previously been shown to predict all-cause mortality, chronic conditions, and age-related functional decline. We analyze cross-sectional data from 4,173 postmenopausal female participants from the Women's Health Initiative, as well as 402 male and female participants from the Italian cohort study, Invecchiare nel Chianti.Extrinsic epigenetic age acceleration (EEAA) exhibits significant associations with fish intake (p=0.02), moderate alcohol consumption (p=0.01), education (p=3x10(-5)), BMI (p=0.01), and blood carotenoid levels (p=1x10(-5))-an indicator of fruit and vegetable consumption, whereas intrinsic epigenetic age acceleration (IEAA) is associated with poultry intake (p=0.03) and BMI (p=0.05). Both EEAA and IEAA were also found to relate to indicators of metabolic syndrome, which appear to mediate their associations with BMI. Metformin-the first-line medication for the treatment of type 2 diabetes-does not delay epigenetic aging in this observational study. Finally, longitudinal data suggests that an increase in BMI is associated with increase in both EEAA and IEAA.Overall, the epigenetic age analysis of blood confirms the conventional wisdom regarding the benefits of eating a high plant diet with lean meats, moderate alcohol consumption, physical activity, and education, as well as the health risks of obesity and metabolic syndrome.

    View details for DOI 10.18632/aging.101168

    View details for PubMedID 28198702

    View details for PubMedCentralID PMC5361673

  • Association analyses based on false discovery rate implicate new loci for coronary artery disease. Nature genetics Nelson, C. P., Goel, A., Butterworth, A. S., Kanoni, S., Webb, T. R., Marouli, E., Zeng, L., Ntalla, I., Lai, F. Y., Hopewell, J. C., Giannakopoulou, O., Jiang, T., Hamby, S. E., Di Angelantonio, E., Assimes, T. L., Bottinger, E. P., Chambers, J. C., Clarke, R., Palmer, C. N., Cubbon, R. M., Ellinor, P., Ermel, R., Evangelou, E., Franks, P. W., Grace, C., Gu, D., Hingorani, A. D., Howson, J. M., Ingelsson, E., Kastrati, A., Kessler, T., Kyriakou, T., Lehtimäki, T., Lu, X., Lu, Y., März, W., McPherson, R., Metspalu, A., Pujades-Rodriguez, M., Ruusalepp, A., Schadt, E. E., Schmidt, A. F., Sweeting, M. J., Zalloua, P. A., AlGhalayini, K., Keavney, B. D., Kooner, J. S., Loos, R. J., Patel, R. S., Rutter, M. K., Tomaszewski, M., Tzoulaki, I., Zeggini, E., Erdmann, J., Dedoussis, G., Björkegren, J. L., Schunkert, H., Farrall, M., Danesh, J., Samani, N. J., Watkins, H., Deloukas, P. 2017; 49 (9): 1385?91

    Abstract

    Genome-wide association studies (GWAS) in coronary artery disease (CAD) had identified 66 loci at 'genome-wide significance' (P < 5 × 10(-8)) at the time of this analysis, but a much larger number of putative loci at a false discovery rate (FDR) of 5% (refs. 1,2,3,4). Here we leverage an interim release of UK Biobank (UKBB) data to evaluate the validity of the FDR approach. We tested a CAD phenotype inclusive of angina (SOFT; ncases = 10,801) as well as a stricter definition without angina (HARD; ncases = 6,482) and selected cases with the former phenotype to conduct a meta-analysis using the two most recent CAD GWAS. This approach identified 13 new loci at genome-wide significance, 12 of which were on our previous list of loci meeting the 5% FDR threshold, thus providing strong support that the remaining loci identified by FDR represent genuine signals. The 304 independent variants associated at 5% FDR in this study explain 21.2% of CAD heritability and identify 243 loci that implicate pathways in blood vessel morphogenesis as well as lipid metabolism, nitric oxide signaling and inflammation.

    View details for DOI 10.1038/ng.3913

    View details for PubMedID 28714975

  • Leukocyte telomere length, T cell composition and DNA methylation age. Aging Chen, B. H., Carty, C. L., Kimura, M., Kark, J. D., Chen, W., Li, S., Zhang, T., Kooperberg, C., Levy, D., Assimes, T., Absher, D., Horvath, S., Reiner, A. P., Aviv, A. 2017

    Abstract

    Both leukocyte telomere length (LTL) and DNA methylation age are strongly associated with chronological age. One measure of DNA methylation age? the extrinsic epigenetic age acceleration (EEAA)? is highly predictive of all-cause mortality. We examined the relation between LTL and EEAA. LTL was measured by Southern blots and leukocyte DNA methylation was determined using Illumina Infinium HumanMethylation450 BeadChip in participants in the Women's Health Initiative (WHI; n=804), the Framingham Heart Study (FHS; n=909) and the Bogalusa Heart study (BHS; n=826). EEAA was computed using 71 DNA methylation sites, further weighted by proportions of naïve CD8(+) T cells, memory CD8(+) T cells, and plasmablasts. Shorter LTL was associated with increased EEAA in participants from the WHI (r=-0.16, p=3.1x10(-6)). This finding was replicated in the FHS (r=-0.09, p=6.5x10(-3)) and the BHS (r=-0.07, p=3.8x 10(-2)). LTL was also inversely related to proportions of memory CD8(+) T cells (p=4.04x10(-16)) and positively related to proportions of naive CD8(+) T cells (p=3.57x10(-14)). These findings suggest that for a given age, an individual whose blood contains comparatively more memory CD8(+) T cells and less naive CD8(+) T cells would display a relatively shorter LTL and an older DNA methylation age, which jointly explain the striking ability of EEAA to predict mortality.

    View details for DOI 10.18632/aging.101293

    View details for PubMedID 28930701

  • Impact of a Genetic Risk Score for Coronary Artery Disease on Reducing Cardiovascular Risk: A Pilot Randomized Controlled Study. Frontiers in cardiovascular medicine Knowles, J. W., Zarafshar, S., Pavlovic, A., Goldstein, B. A., Tsai, S., Li, J., McConnell, M. V., Absher, D., Ashley, E. A., Kiernan, M., Ioannidis, J. P., Assimes, T. L. 2017; 4: 53

    Abstract

    We tested whether providing a genetic risk score (GRS) for coronary artery disease (CAD) would serve as a motivator to improve adherence to risk-reducing strategies.We randomized 94 participants with at least moderate risk of CAD to receive standard-of-care with (N?=?49) or without (N?=?45) their GRS at a subsequent 3-month follow-up visit. Our primary outcome was change in low density lipoprotein cholesterol (LDL-C) between the 3- and 6-month follow-up visits (?LDL-C). Secondary outcomes included other CAD risk factors, weight loss, diet, physical activity, risk perceptions, and psychological outcomes. In pre-specified analyses, we examined whether there was a greater motivational effect in participants with a higher GRS.Sixty-five participants completed the protocol including 30 participants in the GRS arm. We found no change in the primary outcome between participants receiving their GRS and standard-of-care participants (?LDL-C: -13 vs. -9?mg/dl). Among participants with a higher GRS, we observed modest effects on weight loss and physical activity. All other secondary outcomes were not significantly different, including anxiety and worry.Adding GRS to standard-of-care did not change lipids, adherence, or psychological outcomes. Potential modest benefits in weight loss and physical activity for participants with high GRS need to be validated in larger trials.

    View details for DOI 10.3389/fcvm.2017.00053

    View details for PubMedID 28856136

    View details for PubMedCentralID PMC5558259

  • Leveraging Multi-ethnic Evidence for Risk Assessment of Quantitative Traits in Minority Populations. American journal of human genetics Coram, M. A., Fang, H., Candille, S. I., Assimes, T. L., Tang, H. 2017; 101 (2): 218?26

    Abstract

    An essential component of precision medicine is the ability to predict an individual's risk of disease based on genetic and non-genetic factors. For complex traits and diseases, assessing the risk due to genetic factors is challenging because it requires knowledge of both the identity of variants that influence the trait and their corresponding allelic effects. Although the set of risk variants and their allelic effects may vary between populations, a large proportion of these variants were identified based on studies in populations of European descent. Heterogeneity in genetic architecture underlying complex traits and diseases, while broadly acknowledged, remains poorly characterized. Ignoring such heterogeneity likely reduces predictive accuracy for minority individuals. In this study, we propose an approach, called XP-BLUP, which ameliorates this ethnic disparity by combining trans-ethnic and ethnic-specific information. We build a polygenic model for complex traits that distinguishes candidate trait-relevant variants from the rest of the genome. The set of candidate variants are selected based on studies in any human population, yet the allelic effects are evaluated in a population-specific fashion. Simulation studies and real data analyses demonstrate that XP-BLUP adaptively utilizes trans-ethnic information and can substantially improve predictive accuracy in minority populations. At the same time, our study highlights the importance of the continued expansion of minority cohorts.

    View details for DOI 10.1016/j.ajhg.2017.06.015

    View details for PubMedID 28757202

    View details for PubMedCentralID PMC5544393

  • Identification of new susceptibility loci for type 2 diabetes and shared etiological pathways with coronary heart disease. Nature genetics Zhao, W., Rasheed, A., Tikkanen, E., Lee, J. J., Butterworth, A. S., Howson, J. M., Assimes, T. L., Chowdhury, R., Orho-Melander, M., Damrauer, S., Small, A., Asma, S., Imamura, M., Yamauch, T., Chambers, J. C., Chen, P., Sapkota, B. R., Shah, N., Jabeen, S., Surendran, P., Lu, Y., Zhang, W., Imran, A., Abbas, S., Majeed, F., Trindade, K., Qamar, N., Mallick, N. H., Yaqoob, Z., Saghir, T., Rizvi, S. N., Memon, A., Rasheed, S. Z., Memon, F. U., Mehmood, K., Ahmed, N., Qureshi, I. H., Iqbal, W., Malik, U., Mehra, N., Kuo, J. Z., Sheu, W. H., Guo, X., Hsiung, C. A., Juang, J. J., Taylor, K. D., Hung, Y. J., Lee, W. J., Quertermous, T., Lee, I. T., Hsu, C. C., Bottinger, E. P., Ralhan, S., Teo, Y. Y., Wang, T. D., Alam, D. S., Di Angelantonio, E., Epstein, S., Nielsen, S. F., Nordestgaard, B. G., Tybjaerg-Hansen, A., Young, R., Benn, M., Frikke-Schmidt, R., Kamstrup, P. R., Jukema, J. W., Sattar, N., Smit, R., Chung, R. H., Liang, K. W., Anand, S., Sanghera, D. K., Ripatti, S., Loos, R. J., Kooner, J. S., Tai, E. S., Rotter, J. I., Chen, Y. I., Frossard, P., Maeda, S., Kadowaki, T., Reilly, M., Pare, G., Melander, O., Salomaa, V., Rader, D. J., Danesh, J., Voight, B. F., Saleheen, D. 2017

    Abstract

    To evaluate the shared genetic etiology of type 2 diabetes (T2D) and coronary heart disease (CHD), we conducted a genome-wide, multi-ancestry study of genetic variation for both diseases in up to 265,678 subjects for T2D and 260,365 subjects for CHD. We identify 16 previously unreported loci for T2D and 1 locus for CHD, including a new T2D association at a missense variant in HLA-DRB5 (odds ratio (OR) = 1.29). We show that genetically mediated increase in T2D risk also confers higher CHD risk. Joint T2D-CHD analysis identified eight variants-two of which are coding-where T2D and CHD associations appear to colocalize, including a new joint T2D-CHD association at the CCDC92 locus that also replicated for T2D. The variants associated with both outcomes implicate new pathways as well as targets of existing drugs, including icosapent ethyl and adipocyte fatty-acid-binding protein.

    View details for DOI 10.1038/ng.3943

    View details for PubMedID 28869590

  • Genetics: Implications for Prevention and Management of Coronary Artery Disease JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY Assimes, T. L., Roberts, R. 2016; 68 (25): 2797-2818

    Abstract

    An exciting new era has dawned for the prevention and management of coronary artery disease (CAD) utilizing genetic risk variants. The recent identification of over 60 susceptibility loci for CAD confirms not only the importance of established risk factors, but also the existence of many novel causal pathways that are expected to improve our understanding of the genetic basis of CAD and facilitate the development of new therapeutic agents over time. Concurrently, Mendelian randomization studies have provided intriguing insights on the causal relationship between CAD-related traits, and highlight the potential benefits of long-term modifications of risk factors. Last, genetic risk scores of CAD may serve not only as prognostic, but also as predictive markers, and carry the potential to considerably improve the delivery of established prevention strategies. This review will summarize the evolution and discovery of genetic risk variants for CAD and their current and future clinical applications.

    View details for DOI 10.1016/j.jacc.2016.10.039

    View details for Web of Science ID 000392990600011

    View details for PubMedID 28007143

  • Fine-mapping of lipid regions in global populations discovers ethnic-specific signals and refines previously identified lipid loci HUMAN MOLECULAR GENETICS Zubair, N., Graff, M., Ambite, J. L., Bush, W. S., Kichaev, G., Lu, Y., Manichaikul, A., Sheu, W. H., Absher, D., Assimes, T. L., Bielinski, S. J., Bottinger, E. P., Buzkova, P., Chuang, L., Chung, R., Cochran, B., Dumitrescu, L., Gottesman, O., Haessler, J. W., Haiman, C., Heiss, G., Hsiung, C. A., Hung, Y., Hwu, C., Juang, J. J., Le Marchand, L., Lee, I., Lee, W., Lin, L., Lin, D., Lin, S., Mackey, R. H., Martin, L. W., Pasaniuc, B., Peters, U., Predazzi, I., Quertermous, T., Reiner, A. P., Robinson, J., Rotter, J. I., Ryckman, K. K., Schreiner, P. J., Stahl, E., Tao, R., Tsai, M. Y., Waite, L. L., Wang, T., Buyske, S., Chen, Y. I., Cheng, I., Crawford, D. C., Loos, R. J., Rich, S. S., Fornage, M., North, K. E., Kooperberg, C., Carty, C. L. 2016; 25 (24): 5500-5512

    Abstract

    Genome-wide association studies have identified over 150 loci associated with lipid traits, however, no large-scale studies exist for Hispanics and other minority populations. Additionally, the genetic architecture of lipid-influencing loci remains largely unknown. We performed one of the most racially/ethnically diverse fine-mapping genetic studies of HDL-C, LDL-C, and triglycerides to-date using SNPs on the MetaboChip array on 54,119 individuals: 21,304 African Americans, 19,829 Hispanic Americans, 12,456 Asians, and 530 American Indians. The majority of signals found in these groups generalize to European Americans. While we uncovered signals unique to racial/ethnic populations, we also observed systematically consistent lipid associations across these groups. In African Americans, we identified three novel signals associated with HDL-C (LPL, APOA5, LCAT) and two associated with LDL-C (ABCG8, DHODH). In addition, using this population, we refined the location for 16 out of the 58 known MetaboChip lipid loci. These results can guide tailored screening efforts, reveal population-specific responses to lipid-lowering medications, and aid in the development of new targeted drug therapies.

    View details for DOI 10.1093/hmg/ddw358

    View details for Web of Science ID 000397063900019

    View details for PubMedID 28426890

  • DNA methylation signatures of chronic low-grade inflammation are associated with complex diseases GENOME BIOLOGY Ligthart, S., Marzi, C., Aslibekyan, S., Mendelson, M. M., Conneely, K. N., Tanaka, T., Colicino, E., Waite, L. L., Joehanes, R., Guan, W., Brody, J. A., Elks, C., Marioni, R., Jhun, M. A., Agha, G., Bressler, J., Ward-Caviness, C. K., Chen, B. H., Huan, T., Bakulski, K., Salfati, E. L., Wahl, S., Schramm, K., Sha, J., Hernandez, D. G., Just, A. C., Smith, J. A., Sotoodehnia, N., Pilling, L. C., Pankow, J. S., Tsao, P. S., Liu, C., Zhao, W., Guarrera, S., Michopoulos, V. J., Smith, A. K., Peters, M. J., Melzer, D., Vokonas, P., Fornage, M., Prokisch, H., Bis, J. C., Chu, A. Y., Herder, C., Grallert, H., Yao, C., Shah, S., McRae, A. F., Lin, H., Horvath, S., Fallin, D., Hofman, A., Wareham, N. J., Wiggins, K. L., Feinberg, A. P., Starr, J. M., Visscher, P. M., Murabito, J. M., Kardia, S. L., Absher, D. M., Binder, E. B., Singleton, A. B., Bandinelli, S., Peters, A., Waldenberger, M., Matullo, G., Schwartz, J. D., Demerath, E. W., Uitterlinden, A. G., van Meurs, J. B., Franco, O. H., Chen, Y. I., Levy, D., Turner, S. T., Deary, I. J., Ressler, K. J., Dupuis, J., Ferrucci, L., Ong, K. K., Assimes, T. L., Boerwinkle, E., Koenig, W., Arnett, D. K., Baccarelli, A. A., Benjamin, E. J., Dehghan, A. 2016; 17

    Abstract

    Chronic low-grade inflammation reflects a subclinical immune response implicated in the pathogenesis of complex diseases. Identifying genetic loci where DNA methylation is associated with chronic low-grade inflammation may reveal novel pathways or therapeutic targets for inflammation.We performed a meta-analysis of epigenome-wide association studies (EWAS) of serum C-reactive protein (CRP), which is a sensitive marker of low-grade inflammation, in a large European population (n?=?8863) and trans-ethnic replication in African Americans (n?=?4111). We found differential methylation at 218 CpG sites to be associated with CRP (P?

    View details for DOI 10.1186/s13059-016-1119-5

    View details for Web of Science ID 000390199000001

    View details for PubMedID 27955697

    View details for PubMedCentralID PMC5151130

  • Associations between a Genetic Risk Score for Clinical CAD and Early Stage Lesions in the Coronary Artery and the Aorta PLOS ONE Salfati, E. L., Herrington, D. M., Assimes, T. L. 2016; 11 (11)

    Abstract

    The correlation between the extent of fatty streaks, more advanced atherosclerotic lesions, and community rates of coronary artery disease (CAD) is substantially higher for the coronary artery compared to the aorta. We sought to determine whether a genetic basis contributes to these differences.We conducted a cluster analysis of 6 subclinical atherosclerosis phenotypes documented in 564 white participants of the Pathobiological Determinants of Atherosclerosis in Youth study including the extent of fatty streaks and raised lesions in the coronary artery (CF and CR), thoracic aorta (TF and TR), and abdominal aorta (AF and AR) followed by a genetic association analysis of the same phenotypes. Our cluster analysis grouped all raised lesions and fatty streaks in the coronary into one cluster (CF, CR, TR, and AR) and the fatty streaks in the aorta into a second cluster (TF and AF). We found a genetic risk score of high-risk alleles at 57 susceptibility loci for CAD to be variably associated with the phenotypes in the first cluster (OR: 1.30 p = 0.009 for being in top quartile of degree of involvement of CF, 1.34 p = 0.005 for CR, 1.25: p = 0.11 for TR, and 1.19 p = 0.08 for AR) but not at all with the phenotypes in the second cluster (OR: 1.01, p = 0.95 for TF and 0.98, p = 0.82 for AF).The genetic determinants of fatty streaks in the aorta do not appear to overlap substantially with the genetic determinants of fatty streaks in the coronary as well as raised lesions in both the coronary and the aorta. These findings may explain why a larger fraction of fatty streaks in the aorta are less likely to progress to raised lesions compared to the coronary artery.

    View details for DOI 10.1371/journal.pone.0166994

    View details for Web of Science ID 000388350300141

    View details for PubMedID 27861582

  • Genome-wide linkage analysis and regional fine mapping identified variants in the RYR3 gene as a novel quantitative trait locus for circulating adiponectin in Chinese population MEDICINE Chang, Y., Chiu, Y., He, C., Sheu, W. H., Lin, M., Seto, T. B., Assimes, T., Jou, Y., Su, L., Lee, W., Lee, P., Tsai, S., Chuang, L. 2016; 95 (44)

    Abstract

    Adiponectin is adipocyte-secreted cytokine with potent insulin-sensitizing action in peripheral tissues. The heritability of plasma adiponectin is high in Han Chinese population.To identify genetic loci influencing plasma adiponectin levels in Chinese population, we performed a genome-wide linkage scan in 1949 Chinese participants of the Stanford Asia-Pacific Program for Hypertension and Insulin Resistance family study and mapped a quantitative trail locus located on chromosome 15 at 31?cM (logarithm of odds?=?3.04) with 1-logarithm of odds support interval at 24 to 34?cM. Within this mapped region, we further genotyped a total of 68 single-nucleotide polymorphisms in 12 genes. Association analysis revealed that haplotypes composed of single-nucleotide polymorphisms in the ryanodine receptor 3 (RYR3) gene had strongest association with plasma adiponectin. RYR3 haplotypes were also associated with systolic (P?=?0.001) and diastolic (P?=?7.1?×?10) blood pressure and high-density lipoprotein cholesterol (P?=?1.4?×?10). Furthermore, an inverse relationship between expression of RYR3 and adiponectin was observed in human abdominal adipose tissue. In conclusion, a genome-wide linkage scan and regional association fine-mapping identified variants in the RYR3 gene as a quantitative trail locus for plasma adiponectin levels in Chinese population.

    View details for DOI 10.1097/MD.0000000000005174

    View details for Web of Science ID 000388566200018

    View details for PubMedID 27858853

  • No Association of Coronary Artery Disease with X-Chromosomal Variants in Comprehensive International Meta-Analysis SCIENTIFIC REPORTS Loley, C., Alver, M., Assimes, T. L., Bjonnes, A., Goel, A., Gustafsson, S., Hernesniemi, J., Hopewell, J. C., Kanoni, S., Kleber, M. E., Lau, K. W., Lu, Y., Lyytikainen, L., Nelson, C. P., Nikpay, M., Qu, L., Salfati, E., Scholz, M., Tukiainen, T., Willenborg, C., Won, H., Zeng, L., Zhang, W., Anand, S. S., Beutner, F., Bottinger, E. P., Clarke, R., Dedoussis, G., Do, R., Esko, T., Eskola, M., Farrall, M., Gauguier, D., Giedraitis, V., Granger, C. B., Hall, A. S., Hamsten, A., Hazen, S. L., Huang, J., Kahonen, M., Kyriakou, T., Laaksonen, R., Lind, L., Lindgren, C., Magnusson, P. K., Marouli, E., Mihailov, E., Morris, A. P., Nikus, K., Pedersen, N., Rallidis, L., Salomaa, V., Shah, S. H., Stewart, A. F., Thompson, J. R., Zalloua, P. A., Chambers, J. C., Collins, R., Ingelsson, E., Iribarren, C., Karhunen, P. J., Kooner, J. S., Lehtimaki, T., Loos, R. J., Maerz, W., McPherson, R., Metspalu, A., Reilly, M. P., Ripatti, S., Sanghera, D. K., Thiery, J., Watkins, H., Deloukas, P., Kathiresan, S., Samani, N. J., Schunkert, H., Erdmann, J., Koenig, I. R. 2016; 6

    Abstract

    In recent years, genome-wide association studies have identified 58 independent risk loci for coronary artery disease (CAD) on the autosome. However, due to the sex-specific data structure of the X chromosome, it has been excluded from most of these analyses. While females have 2 copies of chromosome X, males have only one. Also, one of the female X chromosomes may be inactivated. Therefore, special test statistics and quality control procedures are required. Thus, little is known about the role of X-chromosomal variants in CAD. To fill this gap, we conducted a comprehensive X-chromosome-wide meta-analysis including more than 43,000 CAD cases and 58,000 controls from 35 international study cohorts. For quality control, sex-specific filters were used to adequately take the special structure of X-chromosomal data into account. For single study analyses, several logistic regression models were calculated allowing for inactivation of one female X-chromosome, adjusting for sex and investigating interactions between sex and genetic variants. Then, meta-analyses including all 35 studies were conducted using random effects models. None of the investigated models revealed genome-wide significant associations for any variant. Although we analyzed the largest-to-date sample, currently available methods were not able to detect any associations of X-chromosomal variants with CAD.

    View details for DOI 10.1038/srep35278

    View details for Web of Science ID 000385004200001

    View details for PubMedID 27731410

    View details for PubMedCentralID PMC5059659

  • The genetics of blood pressure regulation and its target organs from association studies in 342,415 individuals. Nature genetics Ehret, G. B., Ferreira, T., Chasman, D. I., Jackson, A. U., Schmidt, E. M., Johnson, T., Thorleifsson, G., Luan, J., Donnelly, L. A., Kanoni, S., Petersen, A., Pihur, V., Strawbridge, R. J., Shungin, D., Hughes, M. F., Meirelles, O., Kaakinen, M., Bouatia-Naji, N., Kristiansson, K., Shah, S., Kleber, M. E., Guo, X., Lyytikäinen, L., Fava, C., Eriksson, N., Nolte, I. M., Magnusson, P. K., Salfati, E. L., Rallidis, L. S., Theusch, E., Smith, A. J., Folkersen, L., Witkowska, K., Pers, T. H., Joehanes, R., Kim, S. K., Lataniotis, L., Jansen, R., Johnson, A. D., Warren, H., Kim, Y. J., Zhao, W., Wu, Y., Tayo, B. O., Bochud, M., Absher, D., Adair, L. S., Amin, N., Arking, D. E., Axelsson, T., Baldassarre, D., Balkau, B., Bandinelli, S., Barnes, M. R., Barroso, I., Bevan, S., Bis, J. C., Bjornsdottir, G., Boehnke, M., Boerwinkle, E., Bonnycastle, L. L., Boomsma, D. I., Bornstein, S. R., Brown, M. J., Burnier, M., Cabrera, C. P., Chambers, J. C., Chang, I., Cheng, C., Chines, P. S., Chung, R., Collins, F. S., Connell, J. M., Döring, A., Dallongeville, J., Danesh, J., de Faire, U., Delgado, G., Dominiczak, A. F., Doney, A. S., Drenos, F., Edkins, S., Eicher, J. D., Elosua, R., Enroth, S., Erdmann, J., Eriksson, P., Esko, T., Evangelou, E., Evans, A., Fall, T., Farrall, M., Felix, J. F., Ferrières, J., Ferrucci, L., Fornage, M., Forrester, T., Franceschini, N., Franco, O. H., Franco-Cereceda, A., Fraser, R. M., Ganesh, S. K., Gao, H., Gertow, K., Gianfagna, F., Gigante, B., Giulianini, F., Goel, A., Goodall, A. H., Goodarzi, M. O., Gorski, M., Gräßler, J., Groves, C. J., Gudnason, V., Gyllensten, U., Hallmans, G., Hartikainen, A., Hassinen, M., Havulinna, A. S., Hayward, C., Hercberg, S., Herzig, K., Hicks, A. A., Hingorani, A. D., Hirschhorn, J. N., Hofman, A., Holmen, J., Holmen, O. L., Hottenga, J., Howard, P., Hsiung, C. A., Hunt, S. C., Ikram, M. A., Illig, T., Iribarren, C., Jensen, R. A., Kähönen, M., Kang, H. M., Kathiresan, S., Keating, B. J., Khaw, K., Kim, Y. K., Kim, E., Kivimaki, M., Klopp, N., Kolovou, G., Komulainen, P., Kooner, J. S., Kosova, G., Krauss, R. M., Kuh, D., Kutalik, Z., Kuusisto, J., Kvaløy, K., Lakka, T. A., Lee, N. R., Lee, I., Lee, W., Levy, D., Li, X., Liang, K., Lin, H., Lin, L., Lindström, J., Lobbens, S., Männistö, S., Müller, G., Müller-Nurasyid, M., Mach, F., Markus, H. S., Marouli, E., McCarthy, M. I., McKenzie, C. A., Meneton, P., Menni, C., Metspalu, A., Mijatovic, V., Moilanen, L., Montasser, M. E., Morris, A. D., Morrison, A. C., Mulas, A., Nagaraja, R., Narisu, N., Nikus, K., O'Donnell, C. J., O'Reilly, P. F., Ong, K. K., Paccaud, F., Palmer, C. D., Parsa, A., Pedersen, N. L., Penninx, B. W., Perola, M., Peters, A., Poulter, N., Pramstaller, P. P., Psaty, B. M., Quertermous, T., Rao, D. C., Rasheed, A., Rayner, N. W., Renström, F., Rettig, R., Rice, K. M., Roberts, R., Rose, L. M., Rossouw, J., Samani, N. J., Sanna, S., Saramies, J., Schunkert, H., Sebert, S., Sheu, W. H., Shin, Y., Sim, X., Smit, J. H., Smith, A. V., Sosa, M. X., Spector, T. D., Stancáková, A., Stanton, A. V., Stirrups, K. E., Stringham, H. M., Sundstrom, J., Swift, A. J., Syvänen, A., Tai, E., Tanaka, T., Tarasov, K. V., Teumer, A., Thorsteinsdottir, U., Tobin, M. D., Tremoli, E., Uitterlinden, A. G., Uusitupa, M., Vaez, A., Vaidya, D., van Duijn, C. M., van Iperen, E. P., Vasan, R. S., Verwoert, G. C., Virtamo, J., Vitart, V., Voight, B. F., Vollenweider, P., Wagner, A., Wain, L. V., Wareham, N. J., Watkins, H., Weder, A. B., Westra, H., Wilks, R., Wilsgaard, T., Wilson, J. F., Wong, T. Y., Yang, T., Yao, J., Yengo, L., Zhang, W., Zhao, J. H., Zhu, X., Bovet, P., Cooper, R. S., Mohlke, K. L., Saleheen, D., Lee, J., Elliott, P., Gierman, H. J., Willer, C. J., Franke, L., Hovingh, G. K., Taylor, K. D., Dedoussis, G., Sever, P., Wong, A., Lind, L., Assimes, T. L., Njølstad, I., Schwarz, P. E., Langenberg, C., Snieder, H., Caulfield, M. J., Melander, O., Laakso, M., Saltevo, J., Rauramaa, R., Tuomilehto, J., Ingelsson, E., Lehtimäki, T., Hveem, K., Palmas, W., März, W., Kumari, M., Salomaa, V., Chen, Y. I., Rotter, J. I., Froguel, P., Jarvelin, M., Lakatta, E. G., Kuulasmaa, K., Franks, P. W., Hamsten, A., Wichmann, H., Palmer, C. N., Stefansson, K., Ridker, P. M., Loos, R. J., Chakravarti, A., Deloukas, P., Morris, A. P., Newton-Cheh, C., Munroe, P. B. 2016; 48 (10): 1171-1184

    Abstract

    To dissect the genetic architecture of blood pressure and assess effects on target organ damage, we analyzed 128,272 SNPs from targeted and genome-wide arrays in 201,529 individuals of European ancestry, and genotypes from an additional 140,886 individuals were used for validation. We identified 66 blood pressure-associated loci, of which 17 were new; 15 harbored multiple distinct association signals. The 66 index SNPs were enriched for cis-regulatory elements, particularly in vascular endothelial cells, consistent with a primary role in blood pressure control through modulation of vascular tone across multiple tissues. The 66 index SNPs combined in a risk score showed comparable effects in 64,421 individuals of non-European descent. The 66-SNP blood pressure risk score was significantly associated with target organ damage in multiple tissues but with minor effects in the kidney. Our findings expand current knowledge of blood pressure-related pathways and highlight tissues beyond the classical renal system in blood pressure regulation.

    View details for DOI 10.1038/ng.3667

    View details for PubMedID 27618452

    View details for PubMedCentralID PMC5042863

  • DNA methylation-based measures of biological age: meta-analysis predicting time to death. Aging Chen, B. H., Marioni, R. E., Colicino, E., Peters, M. J., Ward-Caviness, C. K., Tsai, P., Roetker, N. S., Just, A. C., Demerath, E. W., Guan, W., Bressler, J., Fornage, M., Studenski, S., Vandiver, A. R., Moore, A. Z., Tanaka, T., Kiel, D. P., Liang, L., Vokonas, P., Schwartz, J., Lunetta, K. L., Murabito, J. M., Bandinelli, S., Hernandez, D. G., Melzer, D., Nalls, M., Pilling, L. C., Price, T. R., Singleton, A. B., Gieger, C., Holle, R., Kretschmer, A., Kronenberg, F., Kunze, S., Linseisen, J., Meisinger, C., Rathmann, W., Waldenberger, M., Visscher, P. M., Shah, S., Wray, N. R., McRae, A. F., Franco, O. H., Hofman, A., Uitterlinden, A. G., Absher, D., Assimes, T., Levine, M. E., Lu, A. T., Tsao, P. S., Hou, L., Manson, J. E., Carty, C. L., LaCroix, A. Z., Reiner, A. P., Spector, T. D., Feinberg, A. P., Levy, D., Baccarelli, A., van Meurs, J., Bell, J. T., Peters, A., Deary, I. J., Pankow, J. S., Ferrucci, L., Horvath, S. 2016; 8 (9): 1844-1865

    Abstract

    Estimates of biological age based on DNA methylation patterns, often referred to as "epigenetic age", "DNAm age", have been shown to be robust biomarkers of age in humans. We previously demonstrated that independent of chronological age, epigenetic age assessed in blood predicted all-cause mortality in four human cohorts. Here, we expanded our original observation to 13 different cohorts for a total sample size of 13,089 individuals, including three racial/ethnic groups. In addition, we examined whether incorporating information on blood cell composition into the epigenetic age metrics improves their predictive power for mortality. All considered measures of epigenetic age acceleration were predictive of mortality (p?8.2x10(-9)), independent of chronological age, even after adjusting for additional risk factors (p<5.4x10(-4)), and within the racial/ethnic groups that we examined (non-Hispanic whites, Hispanics, African Americans). Epigenetic age estimates that incorporated information on blood cell composition led to the smallest p-values for time to death (p=7.5x10(-43)). Overall, this study a) strengthens the evidence that epigenetic age predicts all-cause mortality above and beyond chronological age and traditional risk factors, and b) demonstrates that epigenetic age estimates that incorporate information on blood cell counts lead to highly significant associations with all-cause mortality.

    View details for DOI 10.18632/aging.101020

    View details for PubMedID 27690265

    View details for PubMedCentralID PMC5076441

  • The associations of leptin, adiponectin and resistin with incident atrial fibrillation in women. Heart Ermakov, S., Azarbal, F., Stefanick, M. L., LaMonte, M. J., Li, W., Tharp, K. M., Martin, L. W., Nassir, R., Salmoirago-Blotcher, E., Albert, C. M., Manson, J. E., Assimes, T. L., Hlatky, M. A., Larson, J. C., Perez, M. V. 2016; 102 (17): 1354-1362

    Abstract

    Higher body mass index (BMI) is an important risk factor for atrial fibrillation (AF). The adipokines leptin, adiponectin and resistin are correlates of BMI, but their association with incident AF is not well known. We explored this relationship in a large cohort of postmenopausal women.We studied an ethnically diverse cohort of community-dwelling postmenopausal women aged 50-79 who were nationally recruited at 40 clinical centres as part of the Women's Health Initiative investigation. Participants underwent measurements of baseline serum leptin, adiponectin and resistin levels and were followed for incident AF. Adipokine levels were log transformed and normalised using inverse probability weighting. Cox proportional hazard regression models were used to estimate associations with adjustment for known AF risk factors.Of the 4937 participants included, 892 developed AF over a follow-up of 11.1?years. Those with AF had higher mean leptin (14.9?pg/mL vs 13.9?pg/mL), adiponectin (26.3?ug/mL vs 24.5?ug/mL) and resistin (12.9?ng/mL vs 12.1?ng/mL) levels. After multivariable adjustment, neither log leptin nor log adiponectin levels were significantly associated with incident AF. However, log resistin levels remained significantly associated with incident AF (HR=1.57 per 1 log (ng/mL) increase, p=0.006). Additional adjustment for inflammatory cytokines only partially attenuated the association between resistin and incident AF (HR=1.43, p=0.06 adjusting for C-reactive protein (CRP); HR=1.39, p=0.08 adjusting for IL-6). Adjusting for resistin partially attenuated the association between BMI and incident AF (HR=1.14 per 5?kg/m(2), p=0.006 without resistin; HR=1.12, p=0.02 with resistin).In women, elevated levels of serum resistin are significantly associated with higher rates of incident AF and partially mediate the association between BMI and AF. In the same population, leptin and adiponectin levels are not significantly associated with AF.

    View details for DOI 10.1136/heartjnl-2015-308927

    View details for PubMedID 27146694

  • Menopause accelerates biological aging. Proceedings of the National Academy of Sciences of the United States of America Levine, M. E., Lu, A. T., Chen, B. H., Hernandez, D. G., Singleton, A. B., Ferrucci, L., Bandinelli, S., Salfati, E., Manson, J. E., Quach, A., Kusters, C. D., Kuh, D., Wong, A., Teschendorff, A. E., Widschwendter, M., Ritz, B. R., Absher, D., Assimes, T. L., Horvath, S. 2016; 113 (33): 9327-9332

    Abstract

    Although epigenetic processes have been linked to aging and disease in other systems, it is not yet known whether they relate to reproductive aging. Recently, we developed a highly accurate epigenetic biomarker of age (known as the "epigenetic clock"), which is based on DNA methylation levels. Here we carry out an epigenetic clock analysis of blood, saliva, and buccal epithelium using data from four large studies: the Women's Health Initiative (n = 1,864); Invecchiare nel Chianti (n = 200); Parkinson's disease, Environment, and Genes (n = 256); and the United Kingdom Medical Research Council National Survey of Health and Development (n = 790). We find that increased epigenetic age acceleration in blood is significantly associated with earlier menopause (P = 0.00091), bilateral oophorectomy (P = 0.0018), and a longer time since menopause (P = 0.017). Conversely, epigenetic age acceleration in buccal epithelium and saliva do not relate to age at menopause; however, a higher epigenetic age in saliva is exhibited in women who undergo bilateral oophorectomy (P = 0.0079), while a lower epigenetic age in buccal epithelium was found for women who underwent menopausal hormone therapy (P = 0.00078). Using genetic data, we find evidence of coheritability between age at menopause and epigenetic age acceleration in blood. Using Mendelian randomization analysis, we find that two SNPs that are highly associated with age at menopause exhibit a significant association with epigenetic age acceleration. Overall, our Mendelian randomization approach and other lines of evidence suggest that menopause accelerates epigenetic aging of blood, but mechanistic studies will be needed to dissect cause-and-effect relationships further.

    View details for DOI 10.1073/pnas.1604558113

    View details for PubMedID 27457926

  • Epigenetic Aging and Immune Senescence in Women With Insomnia Symptoms: Findings From the Women's Health Initiative Study. Biological psychiatry Carroll, J. E., Irwin, M. R., Levine, M., Seeman, T. E., Absher, D., Assimes, T., Horvath, S. 2016

    Abstract

    Insomnia symptoms are associated with vulnerability to age-related morbidity and mortality. Cross-sectional data suggest that accelerated biological aging may be a mechanism through which sleep influences risk. A novel method for determining age acceleration using epigenetic methylation to DNA has demonstrated predictive utility as an epigenetic clock and prognostic of age-related morbidity and mortality.We examined the association of epigenetic age and immune cell aging with sleep in the Women's Health Initiative study (N = 2078; mean 64.5 ± 7.1 years of age) with assessment of insomnia symptoms (restlessness, difficulty falling asleep, waking at night, trouble getting back to sleep, and early awakenings), sleep duration (short sleep 5 hours or less; long sleep greater than 8 hours), epigenetic age, naive T cell (CD8+CD45RA+CCR7+), and late differentiated T cells (CD8+CD28-CD45RA-).Insomnia symptoms were related to advanced epigenetic age (? ± SE = 1.02 ± 0.37, p = .005) after adjustments for covariates. Insomnia symptoms were also associated with more late differentiated T cells (? ± SE = 0.59 ± 0.21, p = .006), but not with naive T cells. Self-reported short and long sleep duration were unrelated to epigenetic age. Short sleep, but not long sleep, was associated with fewer naive T cells (p < .005) and neither was related to late differentiated T cells.Symptoms of insomnia were associated with increased epigenetic age of blood tissue and were associated with higher counts of late differentiated CD8+ T cells. Short sleep was unrelated to epigenetic age and late differentiated cell counts, but was related to a decline in naive T cells. In this large population-based study of women in the United States, insomnia symptoms are implicated in accelerated aging.

    View details for DOI 10.1016/j.biopsych.2016.07.008

    View details for PubMedID 27702440

  • Lean body mass and risk of incident atrial fibrillation in post-menopausal women EUROPEAN HEART JOURNAL Azarbal, F., Stefanick, M. L., Assimes, T. L., Manson, J. E., Bea, J. W., Li, W., Hlatky, M. A., Larson, J. C., LeBlanc, E. S., Albert, C. M., Nassir, R., Martin, L. W., Perez, M. V. 2016; 37 (20): 1606-1613

    Abstract

    High body mass index (BMI) is a risk factor for atrial fibrillation (AF). The aim of this study was to determine whether lean body mass (LBM) predicts AF.The Women's Health Initiative is a study of post-menopausal women aged 50-79 enrolled at 40 US centres from 1994 to 1998. A subset of 11 393 participants at three centres underwent dual-energy X-ray absorptiometry. Baseline demographics and clinical histories were recorded. Incident AF was identified using hospitalization records and diagnostic codes from Medicare claims. A multivariable Cox hazard regression model adjusted for demographic and clinical risk factors was used to evaluate associations between components of body composition and AF risk. After exclusion for prevalent AF or incomplete data, 8832 participants with an average age of 63.3 years remained for analysis. Over the 11.6 years of average follow-up time, 1035 women developed incident AF. After covariate adjustment, all measures of LBM were independently associated with higher rates of AF: total LBM [hazard ratio (HR) 1.24 per 5 kg increase, 95% confidence intervals (CI) 1.14-1.34], central LBM (HR 1.51 per 5 kg increase, 95% CI 1.31-1.74), and peripheral LBM (HR 1.39 per 5 kg increase, 95% CI 1.19-1.63). The association between total LBM and AF remained significant after adjustment for total fat mass (HR 1.22 per 5 kg increase, 95% CI 1.13-1.31).Greater LBM is a strong independent risk factor for AF. After adjusting for obesity-related risk factors, the risk of AF conferred by higher BMI is primarily driven by the association between LBM and AF.

    View details for DOI 10.1093/eurheartj/ehv423

    View details for Web of Science ID 000376168100013

    View details for PubMedID 26371115

  • The glycolytic enzyme PKM2 bridges metabolic and inflammatory dysfunction in coronary artery disease JOURNAL OF EXPERIMENTAL MEDICINE Shirai, T., Nazarewicz, R. R., Wallis, B. B., Yanes, R. E., Watanabe, R., Hilhorst, M., Tian, L., Harrison, D. G., Giacomini, J. C., Assimes, T. L., Goronzy, J. J., Weyand, C. M. 2016; 213 (3): 337-354

    Abstract

    Abnormal glucose metabolism and enhanced oxidative stress accelerate cardiovascular disease, a chronic inflammatory condition causing high morbidity and mortality. Here, we report that in monocytes and macrophages of patients with atherosclerotic coronary artery disease (CAD), overutilization of glucose promotes excessive and prolonged production of the cytokines IL-6 and IL-1?, driving systemic and tissue inflammation. In patient-derived monocytes and macrophages, increased glucose uptake and glycolytic flux fuel the generation of mitochondrial reactive oxygen species, which in turn promote dimerization of the glycolytic enzyme pyruvate kinase M2 (PKM2) and enable its nuclear translocation. Nuclear PKM2 functions as a protein kinase that phosphorylates the transcription factor STAT3, thus boosting IL-6 and IL-1? production. Reducing glycolysis, scavenging superoxide and enforcing PKM2 tetramerization correct the proinflammatory phenotype of CAD macrophages. In essence, PKM2 serves a previously unidentified role as a molecular integrator of metabolic dysfunction, oxidative stress and tissue inflammation and represents a novel therapeutic target in cardiovascular disease.

    View details for DOI 10.1084/jem.20150900

    View details for Web of Science ID 000373390300005

    View details for PubMedID 26926996

  • Integrative functional genomics identifies regulatory mechanisms at coronary artery disease loci. Nature communications Miller, C. L., Pjanic, M., Wang, T., Nguyen, T., Cohain, A., Lee, J. D., Perisic, L., Hedin, U., Kundu, R. K., Majmudar, D., Kim, J. B., Wang, O., Betsholtz, C., Ruusalepp, A., Franzén, O., Assimes, T. L., Montgomery, S. B., Schadt, E. E., Björkegren, J. L., Quertermous, T. 2016; 7: 12092-?

    Abstract

    Coronary artery disease (CAD) is the leading cause of mortality and morbidity, driven by both genetic and environmental risk factors. Meta-analyses of genome-wide association studies have identified >150 loci associated with CAD and myocardial infarction susceptibility in humans. A majority of these variants reside in non-coding regions and are co-inherited with hundreds of candidate regulatory variants, presenting a challenge to elucidate their functions. Herein, we use integrative genomic, epigenomic and transcriptomic profiling of perturbed human coronary artery smooth muscle cells and tissues to begin to identify causal regulatory variation and mechanisms responsible for CAD associations. Using these genome-wide maps, we prioritize 64 candidate variants and perform allele-specific binding and expression analyses at seven top candidate loci: 9p21.3, SMAD3, PDGFD, IL6R, BMP1, CCDC97/TGFB1 and LMOD1. We validate our findings in expression quantitative trait loci cohorts, which together reveal new links between CAD associations and regulatory function in the appropriate disease context.

    View details for DOI 10.1038/ncomms12092

    View details for PubMedID 27386823

  • Genetic cardiovascular risk prediction: are we already there? European heart journal Assimes, T. L., Goldstein, B. A. 2016; 37 (43): 3279?81

    View details for DOI 10.1093/eurheartj/ehw498

    View details for PubMedID 27940815

  • An epigenetic clock analysis of race/ethnicity, sex, and coronary heart disease. Genome biology Horvath, S., Gurven, M., Levine, M. E., Trumble, B. C., Kaplan, H., Allayee, H., Ritz, B. R., Chen, B., Lu, A. T., Rickabaugh, T. M., Jamieson, B. D., Sun, D., Li, S., Chen, W., Quintana-Murci, L., Fagny, M., Kobor, M. S., Tsao, P. S., Reiner, A. P., Edlefsen, K. L., Absher, D., Assimes, T. L. 2016; 17 (1): 171-?

    Abstract

    Epigenetic biomarkers of aging (the "epigenetic clock") have the potential to address puzzling findings surrounding mortality rates and incidence of cardio-metabolic disease such as: (1) women consistently exhibiting lower mortality than men despite having higher levels of morbidity; (2) racial/ethnic groups having different mortality rates even after adjusting for socioeconomic differences; (3) the black/white mortality cross-over effect in late adulthood; and (4) Hispanics in the United States having a longer life expectancy than Caucasians despite having a higher burden of traditional cardio-metabolic risk factors.We analyzed blood, saliva, and brain samples from seven different racial/ethnic groups. We assessed the intrinsic epigenetic age acceleration of blood (independent of blood cell counts) and the extrinsic epigenetic aging rates of blood (dependent on blood cell counts and tracks the age of the immune system). In blood, Hispanics and Tsimane Amerindians have lower intrinsic but higher extrinsic epigenetic aging rates than Caucasians. African-Americans have lower extrinsic epigenetic aging rates than Caucasians and Hispanics but no differences were found for the intrinsic measure. Men have higher epigenetic aging rates than women in blood, saliva, and brain tissue.Epigenetic aging rates are significantly associated with sex, race/ethnicity, and to a lesser extent with CHD risk factors, but not with incident CHD outcomes. These results may help elucidate lower than expected mortality rates observed in Hispanics, older African-Americans, and women.

    View details for DOI 10.1186/s13059-016-1030-0

    View details for PubMedID 27511193

  • Genetics of Coronary Artery Disease in Taiwan: A Cardiometabochip Study by the Taichi Consortium. PloS one Assimes, T. L., Lee, I., Juang, J., Guo, X., Wang, T., Kim, E. T., Lee, W., Absher, D., Chiu, Y., Hsu, C., Chuang, L., Quertermous, T., Hsiung, C. A., Rotter, J. I., Sheu, W. H., Chen, Y. I., Taylor, K. D. 2016; 11 (3)

    Abstract

    By means of a combination of genome-wide and follow-up studies, recent large-scale association studies of populations of European descent have now identified over 46 loci associated with coronary artery disease (CAD). As part of the TAICHI Consortium, we have collected and genotyped 8556 subjects from Taiwan, comprising 5423 controls and 3133 cases with coronary artery disease, for 9087 CAD SNPs using the CardioMetaboChip. We applied penalized logistic regression to ascertain the top SNPs that contribute together to CAD susceptibility in Taiwan. We observed that the 9p21 locus contributes to CAD at the level of genome-wide significance (rs1537372, with the presence of C, the major allele, the effect estimate is -0.216, standard error 0.033, p value 5.8x10-10). In contrast to a previous report, we propose that the 9p21 locus is a single genetic contribution to CAD in Taiwan because: 1) the penalized logistic regression and the follow-up conditional analysis suggested that rs1537372 accounts for all of the CAD association in 9p21, and 2) the high linkage disequilibrium observed for all associated SNPs in 9p21. We also observed evidence for the following loci at a false discovery rate >5%: SH2B3, ADAMTS7, PHACTR1, GGCX, HTRA1, COL4A1, and LARP6-LRRC49. We also took advantage of the fact that penalized methods are an efficient approach to search for gene-by-gene interactions, and observed that two-way interactions between the PHACTR1 and ADAMTS7 loci and between the SH2B3 and COL4A1 loci contribute to CAD risk. Both the similarities and differences between the significance of these loci when compared with significance of loci in studies of populations of European descent underscore the fact that further genetic association of studies in additional populations will provide clues to identify the genetic architecture of CAD across all populations worldwide.

    View details for DOI 10.1371/journal.pone.0138014

    View details for PubMedID 26982883

  • Susceptibility Loci for Clinical Coronary Artery Disease and Subclinical Coronary Atherosclerosis Throughout the Life-Course. Circulation. Cardiovascular genetics Salfati, E., Nandkeolyar, S., Fortmann, S. P., Sidney, S., Hlatky, M. A., Quertermous, T., Go, A. S., Iribarren, C., Herrington, D. M., Goldstein, B. A., Assimes, T. L. 2015; 8 (6): 803-811

    Abstract

    -Recent genome wide association studies (GWAS) have identified 49 single nucleotide polymorphisms (SNPs) associated with clinical CAD. The mechanism by which these loci influence risk remains largely unclear.-We examined the association between a genetic risk score (GRS) composed of high-risk alleles at the 49 SNPs and the degree of subclinical coronary atherosclerosis in 7,798 participants from six studies stratified into four age groups at the time of assessment (15-34, 35-54, 55-74, >75 years). Atherosclerosis was quantified by staining and direct visual inspection of the right coronary artery in the youngest group, and by scanning for coronary artery calcification in the remaining groups. We defined cases as subjects within the top quartile of degree of atherosclerosis in three groups and as subjects with a CAC>0 in the fourth (35-54 years) where less than one quarter had any CAC. In our meta-analysis of all strata, we found one SD increase in the GRS increased the risk of advanced subclinical coronary atherosclerosis by 36% (p=8.3×10(-25)). This increase in risk was significant in all four age groups including the youngest group where atherosclerosis consisted primarily of raised lesions without macroscopic evidence of plaque rupture or thrombosis. Results were similar when we restricted the GRS to 32 SNPs not associated with traditional risk factors (TRFs) and/or when we adjusted for TRFs.-A GRS for clinical CAD is associated with advanced subclinical coronary atherosclerosis throughout the life-course. This association is apparent even at the earliest, uncomplicated stages of atherosclerosis.

    View details for DOI 10.1161/CIRCGENETICS.114.001071

    View details for PubMedID 26417035

  • A comprehensive 1000 Genomes-based genome-wide association meta-analysis of coronary artery disease NATURE GENETICS Nikpay, M., Goel, A., Won, H., Hall, L. M., Willenborg, C., Kanoni, S., Saleheen, D., Kyriakou, T., Nelson, C. P., Hopewell, J. C., Webb, T. R., Zeng, L., Dehghan, A., Alver, M., Armasu, S. M., Auro, K., Bjonnes, A., Chasman, D. I., Chen, S., Ford, I., Franceschini, N., Gieger, C., Grace, C., Gustafsson, S., Huang, J., Hwang, S., Kim, Y. K., Kleber, M. E., Lau, K. W., Lu, X., Lu, Y., Lyytikainen, L., Mihailov, E., Morrison, A. C., Pervjakova, N., Qu, L., Rose, L. M., Salfati, E., Saxena, R., Scholz, M., Smith, A. V., Tikkanen, E., Uitterlinden, A., Yang, X., Zhang, W., Zhao, W., de Andrade, M., de Vries, P. S., Van Zuydam, N. R., Anand, S. S., Bertram, L., Beutner, F., Dedoussis, G., Frossard, P., Gauguier, D., Goodall, A. H., Gottesman, O., Haber, M., Han, B., Huang, J., Jalilzadeh, S., Kessler, T., Koenig, I. R., Lannfelt, L., Lieb, W., Lind, L., Lindgren, C. M., Lokki, M., Magnusson, P. K., Mallick, N. H., Mehra, N., Meitinger, T., Memon, F., Morris, A. P., Nieminen, M. S., Pedersen, N. L., Peters, A., Rallidis, L. S., Rasheed, A., Samuel, M., Shah, S. H., Sinisalo, J., Stirrups, K. E., Trompet, S., Wang, L., Zaman, K. S., Ardissino, D., Boerwinkle, E., Borecki, I. B., Bottinger, E. P., Buring, J. E., Chambers, J. C., Collins, R., Cupples, L. A., Danesh, J., Demuth, I., Elosua, R., Epstein, S. E., Esko, T., Feitosa, M. F., Franco, O. H., Franzosi, M. G., Granger, C. B., Gu, D., Gudnason, V., Hall, A. S., Hamsten, A., Harris, T. B., Hazen, S. L., Hengstenberg, C., Hofman, A., Ingelsson, E., Iribarren, C., Jukema, J. W., Karhunen, P. J., Kim, B., Kooner, J. S., Kullo, I. J., Lehtimaki, T., Loos, R. J., Melander, O., Metspalu, A., Maerz, W., Palmer, C. N., Perola, M., Quertermous, T., Rader, D. J., Ridker, P. M., Ripatti, S., Roberts, R., Salomaa, V., Sanghera, D. K., Schwartz, S. M., Seedorf, U., Stewart, A. F., Stott, D. J., Thiery, J., Zalloua, P. A., O'Donnell, C. J., Reilly, M. P., Assimes, T. L., Thompson, J. R., Erdmann, J., Clarke, R., Watkins, H., Kathiresan, S., McPherson, R., Deloukas, P., Schunkert, H., Samani, N. J., Farrall, M. 2015; 47 (10): 1121-?

    Abstract

    Existing knowledge of genetic variants affecting risk of coronary artery disease (CAD) is largely based on genome-wide association study (GWAS) analysis of common SNPs. Leveraging phased haplotypes from the 1000 Genomes Project, we report a GWAS meta-analysis of ?185,000 CAD cases and controls, interrogating 6.7 million common (minor allele frequency (MAF) > 0.05) and 2.7 million low-frequency (0.005 < MAF < 0.05) variants. In addition to confirming most known CAD-associated loci, we identified ten new loci (eight additive and two recessive) that contain candidate causal genes newly implicating biological processes in vessel walls. We observed intralocus allelic heterogeneity but little evidence of low-frequency variants with larger effects and no evidence of synthetic association. Our analysis provides a comprehensive survey of the fine genetic architecture of CAD, showing that genetic susceptibility to this common disease is largely determined by common SNPs of small effect size.

    View details for DOI 10.1038/ng.3396

    View details for Web of Science ID 000361969900007

    View details for PubMedID 26343387

    View details for PubMedCentralID PMC4589895

  • Leukocyte Telomere Length and Risks of Incident Coronary Heart Disease and Mortality in a Racially Diverse Population of Postmenopausal Women ARTERIOSCLEROSIS THROMBOSIS AND VASCULAR BIOLOGY Carty, C. L., Kooperberg, C., Liu, J., Herndon, M., Assimes, T., Hou, L., Kroenke, C. H., LaCroix, A. Z., Kimura, M., Aviv, A., Reiner, A. P. 2015; 35 (10): 2225-2231

    Abstract

    Telomeres are regions at the ends of chromosomes that maintain chromosomal structural integrity and genomic stability. In studies of mainly older, white populations, shorter leukocyte telomere length (LTL) is associated with cardiometabolic risk factors and increased risks of mortality and coronary heart disease (CHD). On average, blacks have longer LTL than whites, but the LTL-CHD relationship in blacks is unknown. We investigated the relationship of LTL with CHD and mortality among blacks.Using a case-cohort design, 1525 postmenopausal women (667 blacks and 858 whites) from the Women's Health Initiative had LTL measured in baseline blood samples by Southern blotting. CHD or mortality hazards ratios were estimated using race-stratified and risk factor-adjusted Cox proportional hazards models. There were 367 incident CHD (226 mortality) events in whites, whereas blacks experienced 269 incident CHD (216 mortality) events during median follow-up of 13 years. Shorter LTL was associated with older age, current smoking, and white race/ethnicity. In whites, each 1 kilobase decrease in LTL was associated with 50% increased hazard of CHD, hazard ratio=1.50 (95% confidence interval, 1.08-2.10), P=0.017. There was no association between CHD and LTL in blacks. White women with shorter LTL had higher risks of mortality. In contrast, shorter LTL was weakly associated with decreased mortality hazard in blacks.As one of the largest prospective studies of LTL associations with incident CHD and mortality in a racially diverse sample, our study suggests differences in LTL associations with CHD and mortality between white and black postmenopausal women.

    View details for DOI 10.1161/ATVBAHA.115.305838

    View details for Web of Science ID 000361610700019

    View details for PubMedID 26249011

  • The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study. PLoS genetics Winkler, T. W., Justice, A. E., Graff, M., Barata, L., Feitosa, M. F., Chu, S., Czajkowski, J., Esko, T., Fall, T., Kilpeläinen, T. O., Lu, Y., Mägi, R., Mihailov, E., Pers, T. H., Rüeger, S., Teumer, A., Ehret, G. B., Ferreira, T., Heard-Costa, N. L., Karjalainen, J., Lagou, V., Mahajan, A., Neinast, M. D., Prokopenko, I., Simino, J., Teslovich, T. M., Jansen, R., Westra, H., White, C. C., Absher, D., Ahluwalia, T. S., Ahmad, S., Albrecht, E., Alves, A. C., Bragg-Gresham, J. L., de Craen, A. J., Bis, J. C., Bonnefond, A., Boucher, G., Cadby, G., Cheng, Y., Chiang, C. W., Delgado, G., Demirkan, A., Dueker, N., Eklund, N., Eiriksdottir, G., Eriksson, J., Feenstra, B., Fischer, K., Frau, F., Galesloot, T. E., Geller, F., Goel, A., Gorski, M., Grammer, T. B., Gustafsson, S., Haitjema, S., Hottenga, J., Huffman, J. E., Jackson, A. U., Jacobs, K. B., Johansson, Å., Kaakinen, M., Kleber, M. E., Lahti, J., Mateo Leach, I., Lehne, B., Liu, Y., Lo, K. S., Lorentzon, M., Luan, J., Madden, P. A., Mangino, M., McKnight, B., Medina-Gomez, C., Monda, K. L., Montasser, M. E., Müller, G., Müller-Nurasyid, M., Nolte, I. M., Panoutsopoulou, K., Pascoe, L., Paternoster, L., Rayner, N. W., Renström, F., Rizzi, F., Rose, L. M., Ryan, K. A., Salo, P., Sanna, S., Scharnagl, H., Shi, J., Smith, A. V., Southam, L., Stancáková, A., Steinthorsdottir, V., Strawbridge, R. J., Sung, Y. J., Tachmazidou, I., Tanaka, T., Thorleifsson, G., Trompet, S., Pervjakova, N., Tyrer, J. P., Vandenput, L., van der Laan, S. W., van der Velde, N., van Setten, J., van Vliet-Ostaptchouk, J. V., Verweij, N., Vlachopoulou, E., Waite, L. L., Wang, S. R., Wang, Z., Wild, S. H., Willenborg, C., Wilson, J. F., Wong, A., Yang, J., Yengo, L., Yerges-Armstrong, L. M., Yu, L., Zhang, W., Zhao, J. H., Andersson, E. A., Bakker, S. J., Baldassarre, D., Banasik, K., Barcella, M., Barlassina, C., Bellis, C., Benaglio, P., Blangero, J., Blüher, M., Bonnet, F., Bonnycastle, L. L., Boyd, H. A., Bruinenberg, M., Buchman, A. S., Campbell, H., Chen, Y. I., Chines, P. S., Claudi-Boehm, S., Cole, J., Collins, F. S., de Geus, E. J., de Groot, L. C., Dimitriou, M., Duan, J., Enroth, S., Eury, E., Farmaki, A., Forouhi, N. G., Friedrich, N., Gejman, P. V., Gigante, B., Glorioso, N., Go, A. S., Gottesman, O., Gräßler, J., Grallert, H., Grarup, N., Gu, Y., Broer, L., Ham, A. C., Hansen, T., Harris, T. B., Hartman, C. A., Hassinen, M., Hastie, N., Hattersley, A. T., Heath, A. C., Henders, A. K., Hernandez, D., Hillege, H., Holmen, O., Hovingh, K. G., Hui, J., Husemoen, L. L., Hutri-Kähönen, N., Hysi, P. G., Illig, T., De Jager, P. L., Jalilzadeh, S., Jørgensen, T., Jukema, J. W., Juonala, M., Kanoni, S., Karaleftheri, M., Khaw, K. T., Kinnunen, L., Kittner, S. J., Koenig, W., Kolcic, I., Kovacs, P., Krarup, N. T., Kratzer, W., Krüger, J., Kuh, D., Kumari, M., Kyriakou, T., Langenberg, C., Lannfelt, L., Lanzani, C., Lotay, V., Launer, L. J., Leander, K., Lindström, J., Linneberg, A., Liu, Y., Lobbens, S., Luben, R., Lyssenko, V., Männistö, S., Magnusson, P. K., McArdle, W. L., Menni, C., Merger, S., Milani, L., Montgomery, G. W., Morris, A. P., Narisu, N., Nelis, M., Ong, K. K., Palotie, A., Pérusse, L., Pichler, I., Pilia, M. G., Pouta, A., Rheinberger, M., Ribel-Madsen, R., Richards, M., Rice, K. M., Rice, T. K., Rivolta, C., Salomaa, V., Sanders, A. R., Sarzynski, M. A., Scholtens, S., Scott, R. A., Scott, W. R., Sebert, S., Sengupta, S., Sennblad, B., Seufferlein, T., Silveira, A., Slagboom, P. E., Smit, J. H., Sparsø, T. H., Stirrups, K., Stolk, R. P., Stringham, H. M., Swertz, M. A., Swift, A. J., Syvänen, A., Tan, S., Thorand, B., Tönjes, A., Tremblay, A., Tsafantakis, E., van der Most, P. J., Völker, U., Vohl, M., Vonk, J. M., Waldenberger, M., Walker, R. W., Wennauer, R., Widén, E., Willemsen, G., Wilsgaard, T., Wright, A. F., Zillikens, M. C., van Dijk, S. C., van Schoor, N. M., Asselbergs, F. W., de Bakker, P. I., Beckmann, J. S., Beilby, J., Bennett, D. A., Bergman, R. N., Bergmann, S., Böger, C. A., Boehm, B. O., Boerwinkle, E., Boomsma, D. I., Bornstein, S. R., Bottinger, E. P., Bouchard, C., Chambers, J. C., Chanock, S. J., Chasman, D. I., Cucca, F., Cusi, D., Dedoussis, G., Erdmann, J., Eriksson, J. G., Evans, D. A., de Faire, U., Farrall, M., Ferrucci, L., Ford, I., Franke, L., Franks, P. W., Froguel, P., Gansevoort, R. T., Gieger, C., Grönberg, H., Gudnason, V., Gyllensten, U., Hall, P., Hamsten, A., van der Harst, P., Hayward, C., Heliövaara, M., Hengstenberg, C., Hicks, A. A., Hingorani, A., Hofman, A., Hu, F., Huikuri, H. V., Hveem, K., James, A. L., Jordan, J. M., Jula, A., Kähönen, M., Kajantie, E., Kathiresan, S., Kiemeney, L. A., Kivimaki, M., Knekt, P. B., Koistinen, H. A., Kooner, J. S., Koskinen, S., Kuusisto, J., Maerz, W., Martin, N. G., Laakso, M., Lakka, T. A., Lehtimäki, T., Lettre, G., Levinson, D. F., Lind, L., Lokki, M., Mäntyselkä, P., Melbye, M., Metspalu, A., Mitchell, B. D., Moll, F. L., Murray, J. C., Musk, A. W., Nieminen, M. S., Njølstad, I., Ohlsson, C., Oldehinkel, A. J., Oostra, B. A., Palmer, L. J., Pankow, J. S., Pasterkamp, G., Pedersen, N. L., Pedersen, O., Penninx, B. W., Perola, M., Peters, A., Pola?ek, O., Pramstaller, P. P., Psaty, B. M., Qi, L., Quertermous, T., Raitakari, O. T., Rankinen, T., Rauramaa, R., Ridker, P. M., Rioux, J. D., Rivadeneira, F., Rotter, J. I., Rudan, I., Den Ruijter, H. M., Saltevo, J., Sattar, N., Schunkert, H., Schwarz, P. E., Shuldiner, A. R., Sinisalo, J., Snieder, H., Sørensen, T. I., Spector, T. D., Staessen, J. A., Stefania, B., Thorsteinsdottir, U., Stumvoll, M., Tardif, J., Tremoli, E., Tuomilehto, J., Uitterlinden, A. G., Uusitupa, M., Verbeek, A. L., Vermeulen, S. H., Viikari, J. S., Vitart, V., Völzke, H., Vollenweider, P., Waeber, G., Walker, M., Wallaschofski, H., Wareham, N. J., Watkins, H., Zeggini, E., Chakravarti, A., Clegg, D. J., Cupples, L. A., Gordon-Larsen, P., Jaquish, C. E., Rao, D. C., Abecasis, G. R., Assimes, T. L., Barroso, I., Berndt, S. I., Boehnke, M., Deloukas, P., Fox, C. S., Groop, L. C., Hunter, D. J., Ingelsson, E., Kaplan, R. C., McCarthy, M. I., Mohlke, K. L., O'Connell, J. R., Schlessinger, D., Strachan, D. P., Stefansson, K., van Duijn, C. M., Hirschhorn, J. N., Lindgren, C. M., Heid, I. M., North, K. E., Borecki, I. B., Kutalik, Z., Loos, R. J. 2015; 11 (10)

    Abstract

    Genome-wide association studies (GWAS) have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHRadjBMI), a measure of body shape. Body size and shape change as people grow older and these changes differ substantially between men and women. To systematically screen for age- and/or sex-specific effects of genetic variants on BMI and WHRadjBMI, we performed meta-analyses of 114 studies (up to 320,485 individuals of European descent) with genome-wide chip and/or Metabochip data by the Genetic Investigation of Anthropometric Traits (GIANT) Consortium. Each study tested the association of up to ~2.8M SNPs with BMI and WHRadjBMI in four strata (men ?50y, men >50y, women ?50y, women >50y) and summary statistics were combined in stratum-specific meta-analyses. We then screened for variants that showed age-specific effects (G x AGE), sex-specific effects (G x SEX) or age-specific effects that differed between men and women (G x AGE x SEX). For BMI, we identified 15 loci (11 previously established for main effects, four novel) that showed significant (FDR<5%) age-specific effects, of which 11 had larger effects in younger (<50y) than in older adults (?50y). No sex-dependent effects were identified for BMI. For WHRadjBMI, we identified 44 loci (27 previously established for main effects, 17 novel) with sex-specific effects, of which 28 showed larger effects in women than in men, five showed larger effects in men than in women, and 11 showed opposite effects between sexes. No age-dependent effects were identified for WHRadjBMI. This is the first genome-wide interaction meta-analysis to report convincing evidence of age-dependent genetic effects on BMI. In addition, we confirm the sex-specificity of genetic effects on WHRadjBMI. These results may provide further insights into the biology that underlies weight change with age or the sexually dimorphism of body shape.

    View details for DOI 10.1371/journal.pgen.1005378

    View details for PubMedID 26426971

    View details for PubMedCentralID PMC4591371

  • Contemporary Considerations for Constructing a Genetic Risk Score: An Empirical Approach. Genetic epidemiology Goldstein, B. A., Yang, L., Salfati, E., Assimes, T. L. 2015; 39 (6): 439-445

    Abstract

    Genetic risk scores are an increasingly popular tool for summarizing the cumulative risk of a set of Single Nucleotide Polymorphisms (SNPs) with disease. Typically only the set of the SNPs that have reached genome-wide significance compose these scores. However recent work suggests that including additional SNPs may aid risk assessment. In this paper, we used the Atherosclerosis Risk in Communities (ARIC) Study cohort to illustrate how one can choose the optimal set of SNPs for a genetic risk score (GRS). In addition to P-value threshold, we also examined linkage disequilibrium, imputation quality, and imputation type. We provide a variety of evaluation metrics. Results suggest that P-value threshold had the greatest impact on GRS quality for the outcome of coronary heart disease, with an optimal threshold around 0.001. However, GRSs are relatively robust to both linkage disequilibrium and imputation quality. We also show that the optimal GRS partially depends on the evaluation metric and consequently the way one intends to use the GRS. Overall the implications highlight both the robustness of GRS and a means to empirically choose the best set of GRSs.

    View details for DOI 10.1002/gepi.21912

    View details for PubMedID 26198599

  • Genetic variants primarily associated with type 2 diabetes are related to coronary artery disease risk. Atherosclerosis Jansen, H., Loley, C., Lieb, W., Pencina, M. J., Nelson, C. P., Kathiresan, S., Peloso, G. M., Voight, B. F., Reilly, M. P., Assimes, T. L., Boerwinkle, E., Hengstenberg, C., Laaksonen, R., McPherson, R., Roberts, R., Thorsteinsdottir, U., Peters, A., Gieger, C., Rawal, R., Thompson, J. R., König, I. R., Vasan, R. S., Erdmann, J., Samani, N. J., Schunkert, H. 2015; 241 (2): 419-426

    Abstract

    The mechanisms underlying the association between diabetes and coronary artery disease (CAD) risk are unclear. We aimed to assess this association by studying genetic variants that have been shown to associate with type 2 diabetes (T2DM). If the association between diabetes and CAD is causal, we expected to observe an association of these variants with CAD as well.We studied all genetic variants currently known to be associated with T2DM at a genome-wide significant level (p < 5*10(-8)) in CARDIoGRAM, a genome-wide data-set of CAD including 22,233 CAD cases and 64,762 controls. Out of the 44 published T2DM SNPs 10 were significantly associated with CAD in CARDIoGRAM (OR>1, p < 0.05), more than expected by chance (p = 5.0*10(-5)). Considering all 44 SNPs, the average CAD risk observed per individual T2DM risk allele was 1.0076 (95% confidence interval (CI), 0.9973-1.0180). Such average risk increase was significantly lower than the increase expected based on i) the published effects of the SNPs on T2DM risk and ii) the effect of T2DM on CAD risk as observed in the Framingham Heart Study, which suggested a risk of 1.067 per allele (p = 7.2*10(-10) vs. the observed effect). Studying two risk scores based on risk alleles of the diabetes SNPs, one score using individual level data in 9856 subjects, and the second score on average effects of reported beta-coefficients from the entire CARDIoGRAM data-set, we again observed a significant - yet smaller than expected - association with CAD.Our data indicate that an association between type 2 diabetes related SNPs and CAD exists. However, the effects on CAD risk appear to be by far lower than what would be expected based on the effects of risk alleles on T2DM and the effect of T2DM on CAD in the epidemiological setting.

    View details for DOI 10.1016/j.atherosclerosis.2015.05.033

    View details for PubMedID 26074316

  • Systems Genetics Analysis of Genome-Wide Association Study Reveals Novel Associations Between Key Biological Processes and Coronary Artery Disease ARTERIOSCLEROSIS THROMBOSIS AND VASCULAR BIOLOGY Ghosh, S., Vivar, J., Nelson, C. P., Willenborg, C., Segre, A. V., Maekinen, V., Nikpay, M., Erdmann, J., Blankenberg, S., O'Donnell, C., Maerz, W., Laaksonen, R., Stewart, A. F., Epstein, S. E., Shah, S. H., Granger, C. B., Hazen, S. L., Kathiresan, S., Reilly, M. P., Yang, X., Quertermous, T., Samani, N. J., Schunkert, H., Assimes, T. L., McPherson, R. 2015; 35 (7): 1712-1722

    Abstract

    Genome-wide association studies have identified multiple genetic variants affecting the risk of coronary artery disease (CAD). However, individually these explain only a small fraction of the heritability of CAD and for most, the causal biological mechanisms remain unclear. We sought to obtain further insights into potential causal processes of CAD by integrating large-scale GWA data with expertly curated databases of core human pathways and functional networks.Using pathways (gene sets) from Reactome, we carried out a 2-stage gene set enrichment analysis strategy. From a meta-analyzed discovery cohort of 7 CAD genome-wide association study data sets (9889 cases/11 089 controls), nominally significant gene sets were tested for replication in a meta-analysis of 9 additional studies (15 502 cases/55 730 controls) from the Coronary ARtery DIsease Genome wide Replication and Meta-analysis (CARDIoGRAM) Consortium. A total of 32 of 639 Reactome pathways tested showed convincing association with CAD (replication P<0.05). These pathways resided in 9 of 21 core biological processes represented in Reactome, and included pathways relevant to extracellular matrix (ECM) integrity, innate immunity, axon guidance, and signaling by PDRF, NOTCH, and the transforming growth factor-?/SMAD receptor complex. Many of these pathways had strengths of association comparable to those observed in lipid transport pathways. Network analysis of unique genes within the replicated pathways further revealed several interconnected functional and topologically interacting modules representing novel associations (eg, semaphoring-regulated axonal guidance pathway) besides confirming known processes (lipid metabolism). The connectivity in the observed networks was statistically significant compared with random networks (P<0.001). Network centrality analysis (degree and betweenness) further identified genes (eg, NCAM1, FYN, FURIN, etc.) likely to play critical roles in the maintenance and functioning of several of the replicated pathways.These findings provide novel insights into how genetic variation, interpreted in the context of biological processes and functional interactions among genes, may help define the genetic architecture of CAD.

    View details for DOI 10.1161/ATVBAHA.115.305513

    View details for Web of Science ID 000356867300021

    View details for PubMedID 25977570

  • Detecting clinically meaningful biomarkers with repeated measurements: An illustration with electronic health records BIOMETRICS Goldstein, B. A., Assimes, T., Winkelmayer, W. C., Hastie, T. 2015; 71 (2): 478-486

    Abstract

    Data sources with repeated measurements are an appealing resource to understand the relationship between changes in biological markers and risk of a clinical event. While longitudinal data present opportunities to observe changing risk over time, these analyses can be complicated if the measurement of clinical metrics is sparse and/or irregular, making typical statistical methods unsuitable. In this article, we use electronic health record (EHR) data as an example to present an analytic procedure to both create an analytic sample and analyze the data to detect clinically meaningful markers of acute myocardial infarction (MI). Using an EHR from a large national dialysis organization we abstracted the records of 64,318 individuals and identified 4769 people that had an MI during the study period. We describe a nested case-control design to sample appropriate controls and an analytic approach using regression splines. Fitting a mixed-model with truncated power splines we perform a series of goodness-of-fit tests to determine whether any of 11 regularly collected laboratory markers are useful clinical predictors. We test the clinical utility of each marker using an independent test set. The results suggest that EHR data can be easily used to detect markers of clinically acute events. Special software or analytic tools are not needed, even with irregular EHR data.

    View details for DOI 10.1111/biom.12283

    View details for Web of Science ID 000356810000024

    View details for PubMedID 25652566

  • Genetic analysis for a shared biological basis between migraine and coronary artery disease. Neurology. Genetics Winsvold, B. S., Nelson, C. P., Malik, R., Gormley, P., Anttila, V., Vander Heiden, J., Elliott, K. S., Jacobsen, L. M., Palta, P., Amin, N., de Vries, B., Hämäläinen, E., Freilinger, T., Ikram, M. A., Kessler, T., Koiranen, M., Ligthart, L., McMahon, G., Pedersen, L. M., Willenborg, C., Won, H., Olesen, J., Artto, V., Assimes, T. L., Blankenberg, S., Boomsma, D. I., Cherkas, L., Davey Smith, G., Epstein, S. E., Erdmann, J., Ferrari, M. D., Göbel, H., Hall, A. S., Jarvelin, M., Kallela, M., Kaprio, J., Kathiresan, S., Lehtimäki, T., McPherson, R., März, W., Nyholt, D. R., O'Donnell, C. J., Quaye, L., Rader, D. J., Raitakari, O., Roberts, R., Schunkert, H., Schürks, M., Stewart, A. F., Terwindt, G. M., Thorsteinsdottir, U., van den Maagdenberg, A. M., Van Duijn, C., Wessman, M., Kurth, T., Kubisch, C., Dichgans, M., Chasman, D. I., Cotsapas, C., Zwart, J., Samani, N. J., Palotie, A. 2015; 1 (1)

    Abstract

    To apply genetic analysis of genome-wide association data to study the extent and nature of a shared biological basis between migraine and coronary artery disease (CAD).Four separate methods for cross-phenotype genetic analysis were applied on data from 2 large-scale genome-wide association studies of migraine (19,981 cases, 56,667 controls) and CAD (21,076 cases, 63,014 controls). The first 2 methods quantified the extent of overlapping risk variants and assessed the load of CAD risk loci in migraineurs. Genomic regions of shared risk were then identified by analysis of covariance patterns between the 2 phenotypes and by querying known genome-wide significant loci.We found a significant overlap of genetic risk loci for migraine and CAD. When stratified by migraine subtype, this was limited to migraine without aura, and the overlap was protective in that patients with migraine had a lower load of CAD risk alleles than controls. Genes indicated by 16 shared risk loci point to mechanisms with potential roles in migraine pathogenesis and CAD, including endothelial dysfunction (PHACTR1) and insulin homeostasis (GIP).The results suggest that shared biological processes contribute to risk of migraine and CAD, but surprisingly this commonality is restricted to migraine without aura and the impact is in opposite directions. Understanding the mechanisms underlying these processes and their opposite relationship to migraine and CAD may improve our understanding of both disorders.

    View details for DOI 10.1212/NXG.0000000000000010

    View details for PubMedID 27066539

  • Characterization of TCF21 Downstream Target Regions Identifies a Transcriptional Network Linking Multiple Independent Coronary Artery Disease Loci. PLoS genetics Sazonova, O., Zhao, Y., Nürnberg, S., Miller, C., Pjanic, M., Castano, V. G., Kim, J. B., Salfati, E. L., Kundaje, A. B., Bejerano, G., Assimes, T., Yang, X., Quertermous, T. 2015; 11 (5)

    Abstract

    To functionally link coronary artery disease (CAD) causal genes identified by genome wide association studies (GWAS), and to investigate the cellular and molecular mechanisms of atherosclerosis, we have used chromatin immunoprecipitation sequencing (ChIP-Seq) with the CAD associated transcription factor TCF21 in human coronary artery smooth muscle cells (HCASMC). Analysis of identified TCF21 target genes for enrichment of molecular and cellular annotation terms identified processes relevant to CAD pathophysiology, including "growth factor binding," "matrix interaction," and "smooth muscle contraction." We characterized the canonical binding sequence for TCF21 as CAGCTG, identified AP-1 binding sites in TCF21 peaks, and by conducting ChIP-Seq for JUN and JUND in HCASMC confirmed that there is significant overlap between TCF21 and AP-1 binding loci in this cell type. Expression quantitative trait variation mapped to target genes of TCF21 was significantly enriched among variants with low P-values in the GWAS analyses, suggesting a possible functional interaction between TCF21 binding and causal variants in other CAD disease loci. Separate enrichment analyses found over-representation of TCF21 target genes among CAD associated genes, and linkage disequilibrium between TCF21 peak variation and that found in GWAS loci, consistent with the hypothesis that TCF21 may affect disease risk through interaction with other disease associated loci. Interestingly, enrichment for TCF21 target genes was also found among other genome wide association phenotypes, including height and inflammatory bowel disease, suggesting a functional profile important for basic cellular processes in non-vascular tissues. Thus, data and analyses presented here suggest that study of GWAS transcription factors may be a highly useful approach to identifying disease gene interactions and thus pathways that may be relevant to complex disease etiology.

    View details for DOI 10.1371/journal.pgen.1005202

    View details for PubMedID 26020271

  • Genetically Determined Height and Coronary Artery Disease NEW ENGLAND JOURNAL OF MEDICINE Nelson, C. P., Hamby, S. E., Saleheen, D., Hopewell, J. C., Zeng, L., Assimes, T. L., Kanoni, S., WILLENBORG, C., Burgess, S., Amouyel, P., Anand, S., Blankenberg, S., Boehm, B. O., Clarke, R. J., Collins, R., Dedoussis, G., Farrall, M., Franks, P. W., Groop, L., Hall, A. S., Hamsten, A., Hengstenberg, C., Hovingh, G. K., Ingelsson, E., Kathiresan, S., Kee, F., Koenig, I. R., Kooner, J., Lehtimaeki, T., Maerz, W., Mcpherson, R., Metspalu, A., NIEMINEN, M. S., O'Donnell, C. J., Palmer, C. N., Peters, A., Perola, M., Reilly, M. P., Ripatti, S., Roberts, R., Salomaa, V., Shah, S. H., Schreiber, S., Siegbahn, A., Thorsteinsdottir, U., Veronesi, G., Wareham, N., Willer, C. J., Zalloua, P. A., Erdmann, J., Deloukas, P., Watkins, H., Schunkert, H., Danesh, J., Thompson, J. R., Samani, N. J. 2015; 372 (17): 1608-1618

    Abstract

    The nature and underlying mechanisms of an inverse association between adult height and the risk of coronary artery disease (CAD) are unclear.We used a genetic approach to investigate the association between height and CAD, using 180 height-associated genetic variants. We tested the association between a change in genetically determined height of 1 SD (6.5 cm) with the risk of CAD in 65,066 cases and 128,383 controls. Using individual-level genotype data from 18,249 persons, we also examined the risk of CAD associated with the presence of various numbers of height-associated alleles. To identify putative mechanisms, we analyzed whether genetically determined height was associated with known cardiovascular risk factors and performed a pathway analysis of the height-associated genes.We observed a relative increase of 13.5% (95% confidence interval [CI], 5.4 to 22.1; P<0.001) in the risk of CAD per 1-SD decrease in genetically determined height. There was a graded relationship between the presence of an increased number of height-raising variants and a reduced risk of CAD (odds ratio for height quartile 4 versus quartile 1, 0.74; 95% CI, 0.68 to 0.84; P<0.001). Of the 12 risk factors that we studied, we observed significant associations only with levels of low-density lipoprotein cholesterol and triglycerides (accounting for approximately 30% of the association). We identified several overlapping pathways involving genes associated with both development and atherosclerosis.There is a primary association between a genetically determined shorter height and an increased risk of CAD, a link that is partly explained by the association between shorter height and an adverse lipid profile. Shared biologic processes that determine achieved height and the development of atherosclerosis may explain some of the association. (Funded by the British Heart Foundation and others.).

    View details for DOI 10.1056/NEJMoa1404881

    View details for Web of Science ID 000353294000006

    View details for PubMedID 25853659

  • Identification and validation of N-acetyltransferase 2 as an insulin sensitivity gene JOURNAL OF CLINICAL INVESTIGATION Knowles, J. W., Xie, W., Zhang, Z., Chennemsetty, I., Assimes, T. L., Paananen, J., Hansson, O., Pankow, J., Goodarzi, M. O., Carcamo-Orive, I., Morris, A. P., Chen, Y. I., Maekinen, V., Ganna, A., Mahajan, A., Guo, X., Abbasi, F., Greenawalt, D. M., Lum, P., Molony, C., Lind, L., Lindgren, C., Raffel, L. J., Tsao, P. S., Schadt, E. E., Rotter, J. I., Sinaiko, A., Reaven, G., Yang, X., Hsiung, C. A., Groop, L., Cordell, H. J., Laakso, M., Hao, K., Ingelsson, E., Frayling, T. M., Weedon, M. N., Walker, M., Quertermous, T. 2015; 125 (4): 1739-1751

    Abstract

    Decreased insulin sensitivity, also referred to as insulin resistance (IR), is a fundamental abnormality in patients with type 2 diabetes and a risk factor for cardiovascular disease. While IR predisposition is heritable, the genetic basis remains largely unknown. The GENEticS of Insulin Sensitivity consortium conducted a genome-wide association study (GWAS) for direct measures of insulin sensitivity, such as euglycemic clamp or insulin suppression test, in 2,764 European individuals, with replication in an additional 2,860 individuals. The presence of a nonsynonymous variant of N-acetyltransferase 2 (NAT2) [rs1208 (803A>G, K268R)] was strongly associated with decreased insulin sensitivity that was independent of BMI. The rs1208 "A" allele was nominally associated with IR-related traits, including increased fasting glucose, hemoglobin A1C, total and LDL cholesterol, triglycerides, and coronary artery disease. NAT2 acetylates arylamine and hydrazine drugs and carcinogens, but predicted acetylator NAT2 phenotypes were not associated with insulin sensitivity. In a murine adipocyte cell line, silencing of NAT2 ortholog Nat1 decreased insulin-mediated glucose uptake, increased basal and isoproterenol-stimulated lipolysis, and decreased adipocyte differentiation, while Nat1 overexpression produced opposite effects. Nat1-deficient mice had elevations in fasting blood glucose, insulin, and triglycerides and decreased insulin sensitivity, as measured by glucose and insulin tolerance tests, with intermediate effects in Nat1 heterozygote mice. Our results support a role for NAT2 in insulin sensitivity.

    View details for DOI 10.1172/JCI74592

    View details for Web of Science ID 000352248600037

    View details for PubMedID 25798622

  • Cardiometabolic effects of genetic upregulation of the interleukin 1 receptor antagonist: a Mendelian randomisation analysis LANCET DIABETES & ENDOCRINOLOGY Freitag, D. F., Butterworth, A. S., Willeit, P., Howson, J. M., Burgess, S., Kaptoge, S., Young, R., Ho, W. K., Wood, A. M., Sweeting, M., Spackman, S., Staley, J. R., Ramond, A., Harshfield, E., Nielsen, S. F., Grande, P., Lange, L. A., Bown, M. J., Jones, G. T., Scott, R. A., Bevan, S., Porcu, E., Thorleifsson, G., Zeng, L., Kessler, T., Nikpay, M., Do, R., Zhang, W., Hopewell, J. C., Kleber, M., Delgado, G. E., Nelson, C. P., Goel, A., Bis, J. C., Dehghan, A., Ligthart, S., Smith, A. V., Qu, L., van 't Hof, F. N., de Bakker, P. I., Baas, A. F., van Rij, A., Tromp, G., Kuivaniemi, H., Ritchie, M. D., Verma, S. S., Crawford, D. C., Malinowski, J., de Andrade, M., Kullo, I. J., Peissig, P. L., McCarty, C. A., Boettinger, E. P., Gottesman, O., Crosslin, D. R., Carrell, D. S., Rasmussen-Torvik, L. J., Pacheco, J. A., Huang, J., Timpson, N. J., Kettunen, J., Ala-Korpela, M., Mitchell, G. F., Parsa, A., Wilkinson, I. B., Gorski, M., Li, Y., Franceschini, N., Keller, M. F., Ganesh, S. K., Langefeld, C. D., Bruijn, L., Brown, M. A., Evans, D. M., Baltic, S., Ferreira, M. A., Baurecht, H., Weidinger, S., Franke, A., Lubitz, S. A., Mueller-Nurasyid, M., Felix, J. F., Smith, N. L., Sudman, M., Thompson, S. D., Zeggini, E., Panoutsopoulou, K., Nalls, M. A., Singleton, A., Polychronakos, C., Bradfield, J. P., Hakonarson, H., Easton, D. F., Thompson, D., Tomlinson, I. P., Dunlop, M., Hemminki, K., Morgan, G., Eisen, T., Goldschmidt, H., Allan, J. M., Henrion, M., Whiffin, N., Wang, Y., Chubb, D., Houlston, R. S., Iles, M. M., Bishop, D. T., Law, M. H., Hayward, N. K., Luo, Y., Nejentsev, S., Barbalic, M., Crossman, D., Sanna, S., Soranzo, N., Markus, H. S., Wareham, N. J., Rader, D. J., Reilly, M., Assimes, T., Harris, T. B., Hofman, A., Franco, O. H., Gudnason, V., Tracy, R., Psaty, B. M., Farrall, M., Watkins, H., Hall, A. S., Samani, N. J., Maerz, W., Clarke, R., Collins, R., Kooner, J. S., Chambers, J. C., Kathiresan, S., McPherson, R., Erdmann, J., Kastrati, A., Schunkert, H., Stefansson, K., Thorsteinsdottir, U., Walston, J. D., Tybjaerg-Hansen, A., Alam, D. S., Majumder, A. A., Di Angelantonio, E., Chowdhury, R., Nordestgaard, B. G., Saleheen, D., Thompson, S. G., Danesh, J. 2015; 3 (4): 243-253

    View details for DOI 10.1016/S2213-8587(15)00034-0

    View details for Web of Science ID 000353032600020

  • Dissecting the Roles of MicroRNAs in Coronary Heart Disease via Integrative Genomic Analyses ARTERIOSCLEROSIS THROMBOSIS AND VASCULAR BIOLOGY Huan, T., Rong, J., Tanriverdi, K., Meng, Q., Bhattacharya, A., McManus, D. D., Joehanes, R., Assimes, T. L., McPherson, R., Samani, N. J., Erdmann, J., Schunkert, H., Courchesne, P., Munson, P. J., Johnson, A. D., O'Donnell, C. J., Zhang, B., Larson, M. G., Freedman, J. E., Levy, D., Yang, X. 2015; 35 (4): 1011-1021

    Abstract

    The roles of microRNAs (miRNAs) in coronary heart disease (CHD) have not been well characterized. This study sought to systematically characterize the complex genomic architecture of CHD by integrating whole blood miRNA and mRNA expression with genetic variation in 186 CHD cases and 186 controls.At false discovery rate <0.2, 15 miRNAs were differentially expressed between CHD cases and controls. To explore regulatory mechanisms, we integrated miRNA and mRNA expression with genome-wide genotype data to investigate miRNA and mRNA associations and relationships of genetic variation with miRNAs. We identified a large number of correlated miRNA-mRNA pairs and genetic loci that seem to regulate miRNA levels. Subsequently, we explored the relationships of these complex molecular associations with CHD status. We identified a large difference in miRNA-mRNA associations between CHD cases and controls, as demonstrated by a significantly higher proportion of inversely correlated miRNA-mRNA pairs in cases versus controls (80% versus 30%; P<1×10(-16)), suggesting a genome-wide shift in the regulatory structure of the transcriptome in CHD. The differentially coexpressed miRNA-mRNA pairs showed enrichment for CHD risk genetic variants affecting both miRNA and mRNA expression levels, implicating a putatively causal role in CHD. Furthermore, 3 miRNAs (miR-1275, miR-365a-3p, and miR-150-5p) were associated with an mRNA coexpression module that was causally linked to CHD and reflected the dysregulation of B-cell centered immune function.Our results provide novel evidence that miRNAs are important regulators of biological processes involved in CHD via genetic control and via their tight coexpression with mRNAs.

    View details for DOI 10.1161/ATVBAHA.114.305176

    View details for Web of Science ID 000351709200034

    View details for PubMedID 25657313

  • New genetic loci link adipose and insulin biology to body fat distribution. Nature Shungin, D., Winkler, T. W., Croteau-Chonka, D. C., Ferreira, T., Locke, A. E., Mägi, R., Strawbridge, R. J., Pers, T. H., Fischer, K., Justice, A. E., Workalemahu, T., Wu, J. M., Buchkovich, M. L., Heard-Costa, N. L., Roman, T. S., Drong, A. W., Song, C., Gustafsson, S., Day, F. R., Esko, T., Fall, T., Kutalik, Z., Luan, J., Randall, J. C., Scherag, A., Vedantam, S., Wood, A. R., Chen, J., Fehrmann, R., Karjalainen, J., Kahali, B., Liu, C., Schmidt, E. M., Absher, D., Amin, N., Anderson, D., Beekman, M., Bragg-Gresham, J. L., Buyske, S., Demirkan, A., Ehret, G. B., Feitosa, M. F., Goel, A., Jackson, A. U., Johnson, T., Kleber, M. E., Kristiansson, K., Mangino, M., Mateo Leach, I., Medina-Gomez, C., Palmer, C. D., Pasko, D., Pechlivanis, S., Peters, M. J., Prokopenko, I., Stancáková, A., Ju Sung, Y., Tanaka, T., Teumer, A., van Vliet-Ostaptchouk, J. V., Yengo, L., Zhang, W., Albrecht, E., Ärnlöv, J., Arscott, G. M., Bandinelli, S., Barrett, A., Bellis, C., Bennett, A. J., Berne, C., Blüher, M., Böhringer, S., Bonnet, F., Böttcher, Y., Bruinenberg, M., Carba, D. B., Caspersen, I. H., Clarke, R., Daw, E. W., Deelen, J., Deelman, E., Delgado, G., Doney, A. S., Eklund, N., Erdos, M. R., Estrada, K., Eury, E., Friedrich, N., Garcia, M. E., Giedraitis, V., Gigante, B., Go, A. S., Golay, A., Grallert, H., Grammer, T. B., Gräßler, J., Grewal, J., Groves, C. J., Haller, T., Hallmans, G., Hartman, C. A., Hassinen, M., Hayward, C., Heikkilä, K., Herzig, K., Helmer, Q., Hillege, H. L., Holmen, O., Hunt, S. C., Isaacs, A., Ittermann, T., James, A. L., Johansson, I., Juliusdottir, T., Kalafati, I., Kinnunen, L., Koenig, W., Kooner, I. K., Kratzer, W., Lamina, C., Leander, K., Lee, N. R., Lichtner, P., Lind, L., Lindström, J., Lobbens, S., Lorentzon, M., Mach, F., Magnusson, P. K., Mahajan, A., McArdle, W. L., Menni, C., Merger, S., Mihailov, E., Milani, L., Mills, R., Moayyeri, A., Monda, K. L., Mooijaart, S. P., Mühleisen, T. W., Mulas, A., Müller, G., Müller-Nurasyid, M., Nagaraja, R., Nalls, M. A., Narisu, N., Glorioso, N., Nolte, I. M., Olden, M., Rayner, N. W., Renstrom, F., Ried, J. S., Robertson, N. R., Rose, L. M., Sanna, S., Scharnagl, H., Scholtens, S., Sennblad, B., Seufferlein, T., Sitlani, C. M., Vernon Smith, A., Stirrups, K., Stringham, H. M., Sundström, J., Swertz, M. A., Swift, A. J., Syvänen, A., Tayo, B. O., Thorand, B., Thorleifsson, G., Tomaschitz, A., Troffa, C., van Oort, F. V., Verweij, N., Vonk, J. M., Waite, L. L., Wennauer, R., Wilsgaard, T., Wojczynski, M. K., Wong, A., Zhang, Q., Hua Zhao, J., Brennan, E. P., Choi, M., Eriksson, P., Folkersen, L., Franco-Cereceda, A., Gharavi, A. G., Hedman, Å. K., Hivert, M., Huang, J., Kanoni, S., Karpe, F., Keildson, S., Kiryluk, K., Liang, L., Lifton, R. P., Ma, B., McKnight, A. J., McPherson, R., Metspalu, A., Min, J. L., Moffatt, M. F., Montgomery, G. W., Murabito, J. M., Nicholson, G., Nyholt, D. R., Olsson, C., Perry, J. R., Reinmaa, E., Salem, R. M., Sandholm, N., Schadt, E. E., Scott, R. A., Stolk, L., Vallejo, E. E., Westra, H., Zondervan, K. T., Amouyel, P., Arveiler, D., Bakker, S. J., Beilby, J., Bergman, R. N., Blangero, J., Brown, M. J., Burnier, M., Campbell, H., Chakravarti, A., Chines, P. S., Claudi-Boehm, S., Collins, F. S., Crawford, D. C., Danesh, J., de Faire, U., de Geus, E. J., Dörr, M., Erbel, R., Eriksson, J. G., Farrall, M., Ferrannini, E., Ferrières, J., Forouhi, N. G., Forrester, T., Franco, O. H., Gansevoort, R. T., Gieger, C., Gudnason, V., Haiman, C. A., Harris, T. B., Hattersley, A. T., Heliövaara, M., Hicks, A. A., Hingorani, A. D., Hoffmann, W., Hofman, A., Homuth, G., Humphries, S. E., Hyppönen, E., Illig, T., Jarvelin, M., Johansen, B., Jousilahti, P., Jula, A. M., Kaprio, J., Kee, F., Keinanen-Kiukaanniemi, S. M., Kooner, J. S., Kooperberg, C., Kovacs, P., Kraja, A. T., Kumari, M., Kuulasmaa, K., Kuusisto, J., Lakka, T. A., Langenberg, C., Le Marchand, L., Lehtimäki, T., Lyssenko, V., Männistö, S., Marette, A., Matise, T. C., McKenzie, C. A., McKnight, B., Musk, A. W., Möhlenkamp, S., Morris, A. D., Nelis, M., Ohlsson, C., Oldehinkel, A. J., Ong, K. K., Palmer, L. J., Penninx, B. W., Peters, A., Pramstaller, P. P., Raitakari, O. T., Rankinen, T., Rao, D. C., Rice, T. K., Ridker, P. M., Ritchie, M. D., Rudan, I., Salomaa, V., Samani, N. J., Saramies, J., Sarzynski, M. A., Schwarz, P. E., Shuldiner, A. R., Staessen, J. A., Steinthorsdottir, V., Stolk, R. P., Strauch, K., Tönjes, A., Tremblay, A., Tremoli, E., Vohl, M., Völker, U., Vollenweider, P., Wilson, J. F., Witteman, J. C., Adair, L. S., Bochud, M., Boehm, B. O., Bornstein, S. R., Bouchard, C., Cauchi, S., Caulfield, M. J., Chambers, J. C., Chasman, D. I., Cooper, R. S., Dedoussis, G., Ferrucci, L., Froguel, P., Grabe, H., Hamsten, A., Hui, J., Hveem, K., Jöckel, K., Kivimaki, M., Kuh, D., Laakso, M., Liu, Y., März, W., Munroe, P. B., Njølstad, I., Oostra, B. A., Palmer, C. N., Pedersen, N. L., Perola, M., Pérusse, L., Peters, U., Power, C., Quertermous, T., Rauramaa, R., Rivadeneira, F., Saaristo, T. E., Saleheen, D., Sinisalo, J., Slagboom, P. E., Snieder, H., Spector, T. D., Thorsteinsdottir, U., Stumvoll, M., Tuomilehto, J., Uitterlinden, A. G., Uusitupa, M., van der Harst, P., Veronesi, G., Walker, M., Wareham, N. J., Watkins, H., Wichmann, H., Abecasis, G. R., Assimes, T. L., Berndt, S. I., Boehnke, M., Borecki, I. B., Deloukas, P., Franke, L., Frayling, T. M., Groop, L. C., Hunter, D. J., Kaplan, R. C., O'Connell, J. R., Qi, L., Schlessinger, D., Strachan, D. P., Stefansson, K., van Duijn, C. M., Willer, C. J., Visscher, P. M., Yang, J., Hirschhorn, J. N., Zillikens, M. C., McCarthy, M. I., Speliotes, E. K., North, K. E., Fox, C. S., Barroso, I., Franks, P. W., Ingelsson, E., Heid, I. M., Loos, R. J., Cupples, L. A., Morris, A. P., Lindgren, C. M., Mohlke, K. L. 2015; 518 (7538): 187-196

    Abstract

    Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms.

    View details for DOI 10.1038/nature14132

    View details for PubMedID 25673412

    View details for PubMedCentralID PMC4338562

  • Genetic studies of body mass index yield new insights for obesity biology. Nature Locke, A. E., Kahali, B., Berndt, S. I., Justice, A. E., Pers, T. H., Day, F. R., Powell, C., Vedantam, S., Buchkovich, M. L., Yang, J., Croteau-Chonka, D. C., Esko, T., Fall, T., Ferreira, T., Gustafsson, S., Kutalik, Z., Luan, J., Mägi, R., Randall, J. C., Winkler, T. W., Wood, A. R., Workalemahu, T., Faul, J. D., Smith, J. A., Hua Zhao, J., Zhao, W., Chen, J., Fehrmann, R., Hedman, Å. K., Karjalainen, J., Schmidt, E. M., Absher, D., Amin, N., Anderson, D., Beekman, M., Bolton, J. L., Bragg-Gresham, J. L., Buyske, S., Demirkan, A., Deng, G., Ehret, G. B., Feenstra, B., Feitosa, M. F., Fischer, K., Goel, A., Gong, J., Jackson, A. U., Kanoni, S., Kleber, M. E., Kristiansson, K., Lim, U., Lotay, V., Mangino, M., Mateo Leach, I., Medina-Gomez, C., Medland, S. E., Nalls, M. A., Palmer, C. D., Pasko, D., Pechlivanis, S., Peters, M. J., Prokopenko, I., Shungin, D., Stancáková, A., Strawbridge, R. J., Ju Sung, Y., Tanaka, T., Teumer, A., Trompet, S., van der Laan, S. W., van Setten, J., van Vliet-Ostaptchouk, J. V., Wang, Z., Yengo, L., Zhang, W., Isaacs, A., Albrecht, E., Ärnlöv, J., Arscott, G. M., Attwood, A. P., Bandinelli, S., Barrett, A., Bas, I. N., Bellis, C., Bennett, A. J., Berne, C., Blagieva, R., Blüher, M., Böhringer, S., Bonnycastle, L. L., Böttcher, Y., Boyd, H. A., Bruinenberg, M., Caspersen, I. H., Ida Chen, Y., Clarke, R., Daw, E. W., de Craen, A. J., Delgado, G., Dimitriou, M., Doney, A. S., Eklund, N., Estrada, K., Eury, E., Folkersen, L., Fraser, R. M., Garcia, M. E., Geller, F., Giedraitis, V., Gigante, B., Go, A. S., Golay, A., Goodall, A. H., Gordon, S. D., Gorski, M., Grabe, H., Grallert, H., Grammer, T. B., Gräßler, J., Grönberg, H., Groves, C. J., Gusto, G., Haessler, J., Hall, P., Haller, T., Hallmans, G., Hartman, C. A., Hassinen, M., Hayward, C., Heard-Costa, N. L., Helmer, Q., Hengstenberg, C., Holmen, O., Hottenga, J., James, A. L., Jeff, J. M., Johansson, Å., Jolley, J., Juliusdottir, T., Kinnunen, L., Koenig, W., Koskenvuo, M., Kratzer, W., Laitinen, J., Lamina, C., Leander, K., Lee, N. R., Lichtner, P., Lind, L., Lindström, J., Sin Lo, K., Lobbens, S., Lorbeer, R., Lu, Y., Mach, F., Magnusson, P. K., Mahajan, A., McArdle, W. L., McLachlan, S., Menni, C., Merger, S., Mihailov, E., Milani, L., Moayyeri, A., Monda, K. L., Morken, M. A., Mulas, A., Müller, G., Müller-Nurasyid, M., Musk, A. W., Nagaraja, R., Nöthen, M. M., Nolte, I. M., Pilz, S., Rayner, N. W., Renstrom, F., Rettig, R., Ried, J. S., Ripke, S., Robertson, N. R., Rose, L. M., Sanna, S., Scharnagl, H., Scholtens, S., Schumacher, F. R., Scott, W. R., Seufferlein, T., Shi, J., Vernon Smith, A., Smolonska, J., Stanton, A. V., Steinthorsdottir, V., Stirrups, K., Stringham, H. M., Sundström, J., Swertz, M. A., Swift, A. J., Syvänen, A., Tan, S., Tayo, B. O., Thorand, B., Thorleifsson, G., Tyrer, J. P., Uh, H., Vandenput, L., Verhulst, F. C., Vermeulen, S. H., Verweij, N., Vonk, J. M., Waite, L. L., Warren, H. R., Waterworth, D., Weedon, M. N., Wilkens, L. R., Willenborg, C., Wilsgaard, T., Wojczynski, M. K., Wong, A., Wright, A. F., Zhang, Q., Brennan, E. P., Choi, M., Dastani, Z., Drong, A. W., Eriksson, P., Franco-Cereceda, A., Gådin, J. R., Gharavi, A. G., Goddard, M. E., Handsaker, R. E., Huang, J., Karpe, F., Kathiresan, S., Keildson, S., Kiryluk, K., Kubo, M., Lee, J., Liang, L., Lifton, R. P., Ma, B., McCarroll, S. A., McKnight, A. J., Min, J. L., Moffatt, M. F., Montgomery, G. W., Murabito, J. M., Nicholson, G., Nyholt, D. R., Okada, Y., Perry, J. R., Dorajoo, R., Reinmaa, E., Salem, R. M., Sandholm, N., Scott, R. A., Stolk, L., Takahashi, A., Tanaka, T., van't Hooft, F. M., Vinkhuyzen, A. A., Westra, H., Zheng, W., Zondervan, K. T., Heath, A. C., Arveiler, D., Bakker, S. J., Beilby, J., Bergman, R. N., Blangero, J., Bovet, P., Campbell, H., Caulfield, M. J., Cesana, G., Chakravarti, A., Chasman, D. I., Chines, P. S., Collins, F. S., Crawford, D. C., Cupples, L. A., Cusi, D., Danesh, J., de Faire, U., Den Ruijter, H. M., Dominiczak, A. F., Erbel, R., Erdmann, J., Eriksson, J. G., Farrall, M., Felix, S. B., Ferrannini, E., Ferrières, J., Ford, I., Forouhi, N. G., Forrester, T., Franco, O. H., Gansevoort, R. T., Gejman, P. V., Gieger, C., Gottesman, O., Gudnason, V., Gyllensten, U., Hall, A. S., Harris, T. B., Hattersley, A. T., Hicks, A. A., Hindorff, L. A., Hingorani, A. D., Hofman, A., Homuth, G., Hovingh, G. K., Humphries, S. E., Hunt, S. C., Hyppönen, E., Illig, T., Jacobs, K. B., Jarvelin, M., Jöckel, K., Johansen, B., Jousilahti, P., Jukema, J. W., Jula, A. M., Kaprio, J., Kastelein, J. J., Keinanen-Kiukaanniemi, S. M., Kiemeney, L. A., Knekt, P., Kooner, J. S., Kooperberg, C., Kovacs, P., Kraja, A. T., Kumari, M., Kuusisto, J., Lakka, T. A., Langenberg, C., Le Marchand, L., Lehtimäki, T., Lyssenko, V., Männistö, S., Marette, A., Matise, T. C., McKenzie, C. A., McKnight, B., Moll, F. L., Morris, A. D., Morris, A. P., Murray, J. C., Nelis, M., Ohlsson, C., Oldehinkel, A. J., Ong, K. K., Madden, P. A., Pasterkamp, G., Peden, J. F., Peters, A., Postma, D. S., Pramstaller, P. P., Price, J. F., Qi, L., Raitakari, O. T., Rankinen, T., Rao, D. C., Rice, T. K., Ridker, P. M., Rioux, J. D., Ritchie, M. D., Rudan, I., Salomaa, V., Samani, N. J., Saramies, J., Sarzynski, M. A., Schunkert, H., Schwarz, P. E., Sever, P., Shuldiner, A. R., Sinisalo, J., Stolk, R. P., Strauch, K., Tönjes, A., Trégouët, D., Tremblay, A., Tremoli, E., Virtamo, J., Vohl, M., Völker, U., Waeber, G., Willemsen, G., Witteman, J. C., Zillikens, M. C., Adair, L. S., Amouyel, P., Asselbergs, F. W., Assimes, T. L., Bochud, M., Boehm, B. O., Boerwinkle, E., Bornstein, S. R., Bottinger, E. P., Bouchard, C., Cauchi, S., Chambers, J. C., Chanock, S. J., Cooper, R. S., de Bakker, P. I., Dedoussis, G., Ferrucci, L., Franks, P. W., Froguel, P., Groop, L. C., Haiman, C. A., Hamsten, A., Hui, J., Hunter, D. J., Hveem, K., Kaplan, R. C., Kivimaki, M., Kuh, D., Laakso, M., Liu, Y., Martin, N. G., März, W., Melbye, M., Metspalu, A., Moebus, S., Munroe, P. B., Njølstad, I., Oostra, B. A., Palmer, C. N., Pedersen, N. L., Perola, M., Pérusse, L., Peters, U., Power, C., Quertermous, T., Rauramaa, R., Rivadeneira, F., Saaristo, T. E., Saleheen, D., Sattar, N., Schadt, E. E., Schlessinger, D., Slagboom, P. E., Snieder, H., Spector, T. D., Thorsteinsdottir, U., Stumvoll, M., Tuomilehto, J., Uitterlinden, A. G., Uusitupa, M., van der Harst, P., Walker, M., Wallaschofski, H., Wareham, N. J., Watkins, H., Weir, D. R., Wichmann, H., Wilson, J. F., Zanen, P., Borecki, I. B., Deloukas, P., Fox, C. S., Heid, I. M., O'Connell, J. R., Strachan, D. P., Stefansson, K., van Duijn, C. M., Abecasis, G. R., Franke, L., Frayling, T. M., McCarthy, M. I., Visscher, P. M., Scherag, A., Willer, C. J., Boehnke, M., Mohlke, K. L., Lindgren, C. M., Beckmann, J. S., Barroso, I., North, K. E., Ingelsson, E., Hirschhorn, J. N., Loos, R. J., Speliotes, E. K. 2015; 518 (7538): 197-206

    Abstract

    Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10(-8)), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ?2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.

    View details for DOI 10.1038/nature14177

    View details for PubMedID 25673413

    View details for PubMedCentralID PMC4382211

  • Exome sequencing identifies rare LDLR and APOA5 alleles conferring risk for myocardial infarction. Nature Do, R., Stitziel, N. O., Won, H., Jørgensen, A. B., Duga, S., Angelica Merlini, P., Kiezun, A., Farrall, M., Goel, A., Zuk, O., Guella, I., Asselta, R., Lange, L. A., Peloso, G. M., Auer, P. L., Girelli, D., Martinelli, N., Farlow, D. N., DePristo, M. A., Roberts, R., Stewart, A. F., Saleheen, D., Danesh, J., Epstein, S. E., Sivapalaratnam, S., Hovingh, G. K., Kastelein, J. J., Samani, N. J., Schunkert, H., Erdmann, J., Shah, S. H., Kraus, W. E., Davies, R., Nikpay, M., Johansen, C. T., Wang, J., Hegele, R. A., Hechter, E., Marz, W., Kleber, M. E., Huang, J., Johnson, A. D., Li, M., Burke, G. L., Gross, M., Liu, Y., Assimes, T. L., Heiss, G., Lange, E. M., Folsom, A. R., Taylor, H. A., Olivieri, O., Hamsten, A., Clarke, R., Reilly, D. F., Yin, W., Rivas, M. A., Donnelly, P., Rossouw, J. E., Psaty, B. M., Herrington, D. M., Wilson, J. G., Rich, S. S., Bamshad, M. J., Tracy, R. P., Cupples, L. A., Rader, D. J., Reilly, M. P., Spertus, J. A., Cresci, S., Hartiala, J., Tang, W. H., Hazen, S. L., Allayee, H., Reiner, A. P., Carlson, C. S., Kooperberg, C., Jackson, R. D., Boerwinkle, E., Lander, E. S., Schwartz, S. M., Siscovick, D. S., McPherson, R., Tybjaerg-Hansen, A., Abecasis, G. R., Watkins, H., Nickerson, D. A., Ardissino, D., Sunyaev, S. R., O'Donnell, C. J., Altshuler, D., Gabriel, S., Kathiresan, S. 2015; 518 (7537): 102-106

    Abstract

    Myocardial infarction (MI), a leading cause of death around the world, displays a complex pattern of inheritance. When MI occurs early in life, genetic inheritance is a major component to risk. Previously, rare mutations in low-density lipoprotein (LDL) genes have been shown to contribute to MI risk in individual families, whereas common variants at more than 45 loci have been associated with MI risk in the population. Here we evaluate how rare mutations contribute to early-onset MI risk in the population. We sequenced the protein-coding regions of 9,793 genomes from patients with MI at an early age (?50 years in males and ?60 years in females) along with MI-free controls. We identified two genes in which rare coding-sequence mutations were more frequent in MI cases versus controls at exome-wide significance. At low-density lipoprotein receptor (LDLR), carriers of rare non-synonymous mutations were at 4.2-fold increased risk for MI; carriers of null alleles at LDLR were at even higher risk (13-fold difference). Approximately 2% of early MI cases harbour a rare, damaging mutation in LDLR; this estimate is similar to one made more than 40 years ago using an analysis of total cholesterol. Among controls, about 1 in 217 carried an LDLR coding-sequence mutation and had plasma LDL cholesterol > 190 mg dl(-1). At apolipoprotein A-V (APOA5), carriers of rare non-synonymous mutations were at 2.2-fold increased risk for MI. When compared with non-carriers, LDLR mutation carriers had higher plasma LDL cholesterol, whereas APOA5 mutation carriers had higher plasma triglycerides. Recent evidence has connected MI risk with coding-sequence mutations at two genes functionally related to APOA5, namely lipoprotein lipase and apolipoprotein C-III (refs 18, 19). Combined, these observations suggest that, as well as LDL cholesterol, disordered metabolism of triglyceride-rich lipoproteins contributes to MI risk.

    View details for DOI 10.1038/nature13917

    View details for PubMedID 25487149

  • DNA methylation age of blood predicts future onset of lung cancer in the women's health initiative. Aging 2015

    Abstract

    Lung cancer is considered an age-associated disease, whose progression is in part due to accumulation of genomic instability as well as age-related decline in system integrity and function. Thus even among individuals exposed to high levels of genotoxic carcinogens, such as those found in cigarette smoke, lung cancer susceptibility may vary as a function of individual differences in the rate of biological aging. We recently developed a highly accurate candidate biomarker of aging based on DNA methylation (DNAm) levels, which may prove useful in assessing risk of aging-related diseases, such as lung cancer. Using data on 2,029 females from the Women's Health Initiative, we examined whether baseline measures of "intrinsic epigenetic age acceleration" (IEAA) predicted subsequent lung cancer incidence. We observed 43 lung cancer cases over the nearly twenty years of follow-up. Results showed that standardized measures of IEAA were significantly associated with lung cancer incidence (HR: 1.50, P=3.4x10-3). Furthermore, stratified Cox proportional hazard models suggested that the association may be even stronger among older individuals (70 years or above) or those who are current smokers. Overall, our results suggest that IEAA may be a useful biomarker for evaluating lung cancer susceptibility from a biological aging perspective.

    View details for PubMedID 26411804

  • Leveraging population admixture to characterize the heritability of complex traits. Nature genetics Zaitlen, N., Pasaniuc, B., Sankararaman, S., Bhatia, G., Zhang, J., Gusev, A., Young, T., Tandon, A., Pollack, S., Vilhjálmsson, B. J., Assimes, T. L., Berndt, S. I., Blot, W. J., Chanock, S., Franceschini, N., Goodman, P. G., He, J., Hennis, A. J., Hsing, A., Ingles, S. A., Isaacs, W., Kittles, R. A., Klein, E. A., Lange, L. A., Nemesure, B., Patterson, N., Reich, D., Rybicki, B. A., Stanford, J. L., Stevens, V. L., Strom, S. S., Whitsel, E. A., Witte, J. S., Xu, J., Haiman, C., Wilson, J. G., Kooperberg, C., Stram, D., Reiner, A. P., Tang, H., Price, A. L. 2014; 46 (12): 1356-1362

    Abstract

    Despite recent progress on estimating the heritability explained by genotyped SNPs (h(2)g), a large gap between h(2)g and estimates of total narrow-sense heritability (h(2)) remains. Explanations for this gap include rare variants or upward bias in family-based estimates of h(2) due to shared environment or epistasis. We estimate h(2) from unrelated individuals in admixed populations by first estimating the heritability explained by local ancestry (h(2)?). We show that h(2)? = 2FSTC?(1 - ?)h(2), where FSTC measures frequency differences between populations at causal loci and ? is the genome-wide ancestry proportion. Our approach is not susceptible to biases caused by epistasis or shared environment. We applied this approach to the analysis of 13 phenotypes in 21,497 African-American individuals from 3 cohorts. For height and body mass index (BMI), we obtained h(2) estimates of 0.55 ± 0.09 and 0.23 ± 0.06, respectively, which are larger than estimates of h(2)g in these and other data but smaller than family-based estimates of h(2).

    View details for DOI 10.1038/ng.3139

    View details for PubMedID 25383972

  • Inactivating mutations in NPC1L1 and protection from coronary heart disease. New England journal of medicine Stitziel, N. O., Won, H., Morrison, A. C., Peloso, G. M., Do, R., Lange, L. A., Fontanillas, P., Gupta, N., Duga, S., Goel, A., Farrall, M., Saleheen, D., Ferrario, P., König, I., Asselta, R., Merlini, P. A., Marziliano, N., Notarangelo, M. F., Schick, U., Auer, P., Assimes, T. L., Reilly, M., Wilensky, R., Rader, D. J., Hovingh, G. K., Meitinger, T., Kessler, T., Kastrati, A., Laugwitz, K., Siscovick, D., Rotter, J. I., Hazen, S. L., Tracy, R., Cresci, S., Spertus, J., Jackson, R., Schwartz, S. M., Natarajan, P., Crosby, J., Muzny, D., Ballantyne, C., Rich, S. S., O'Donnell, C. J., Abecasis, G., Sunyaev, S., Nickerson, D. A., Buring, J. E., Ridker, P. M., Chasman, D. I., Austin, E., Ye, Z., Kullo, I. J., Weeke, P. E., Shaffer, C. M., Bastarache, L. A., Denny, J. C., Roden, D. M., Palmer, C., Deloukas, P., Lin, D., Tang, Z., Erdmann, J., Schunkert, H., Danesh, J., Marrugat, J., Elosua, R., Ardissino, D., McPherson, R., Watkins, H., Reiner, A. P., Wilson, J. G., Altshuler, D., Gibbs, R. A., Lander, E. S., Boerwinkle, E., Gabriel, S., Kathiresan, S. 2014; 371 (22): 2072-2082

    Abstract

    Ezetimibe lowers plasma levels of low-density lipoprotein (LDL) cholesterol by inhibiting the activity of the Niemann-Pick C1-like 1 (NPC1L1) protein. However, whether such inhibition reduces the risk of coronary heart disease is not known. Human mutations that inactivate a gene encoding a drug target can mimic the action of an inhibitory drug and thus can be used to infer potential effects of that drug.We sequenced the exons of NPC1L1 in 7364 patients with coronary heart disease and in 14,728 controls without such disease who were of European, African, or South Asian ancestry. We identified carriers of inactivating mutations (nonsense, splice-site, or frameshift mutations). In addition, we genotyped a specific inactivating mutation (p.Arg406X) in 22,590 patients with coronary heart disease and in 68,412 controls. We tested the association between the presence of an inactivating mutation and both plasma lipid levels and the risk of coronary heart disease.With sequencing, we identified 15 distinct NPC1L1 inactivating mutations; approximately 1 in every 650 persons was a heterozygous carrier for 1 of these mutations. Heterozygous carriers of NPC1L1 inactivating mutations had a mean LDL cholesterol level that was 12 mg per deciliter (0.31 mmol per liter) lower than that in noncarriers (P=0.04). Carrier status was associated with a relative reduction of 53% in the risk of coronary heart disease (odds ratio for carriers, 0.47; 95% confidence interval, 0.25 to 0.87; P=0.008). In total, only 11 of 29,954 patients with coronary heart disease had an inactivating mutation (carrier frequency, 0.04%) in contrast to 71 of 83,140 controls (carrier frequency, 0.09%).Naturally occurring mutations that disrupt NPC1L1 function were found to be associated with reduced plasma LDL cholesterol levels and a reduced risk of coronary heart disease. (Funded by the National Institutes of Health and others.).

    View details for DOI 10.1056/NEJMoa1405386

    View details for PubMedID 25390462

  • Defining the role of common variation in the genomic and biological architecture of adult human height NATURE GENETICS Wood, A. R., Esko, T., Yang, J., Vedantam, S., Pers, T. H., Gustafsson, S., Chun, A. Y., Estrada, K., Luan, J., Kutalik, Z., Amin, N., Buchkovich, M. L., Croteau-Chonka, D. C., Day, F. R., Duan, Y., Fall, T., Fehrmann, R., Ferreira, T., Jackson, A. U., Karjalainen, J., Lo, K. S., Locke, A. E., Maegi, R., Mihailov, E., Porcu, E., Randall, J. C., Scherag, A., Vinkhuyzen, A. A., Westra, H., Winkler, T. W., Workalemahu, T., Zhao, J. H., Absher, D., Albrecht, E., Anderson, D., Baron, J., Beekman, M., Demirkan, A., Ehret, G. B., Feenstra, B., Feitosa, M. F., Fischer, K., Fraser, R. M., Goel, A., Gong, J., Justice, A. E., Kanoni, S., Kleber, M. E., Kristiansson, K., Lim, U., Lotay, V., Lui, J. C., Mangino, M., Leach, I. M., Medina-Gomez, C., Nalls, M. A., Nyholt, D. R., Palmer, C. D., Pasko, D., Pechlivanis, S., Prokopenko, I., Ried, J. S., Ripke, S., Shungin, D., Stancakova, A., Strawbridge, R. J., Sung, Y. J., Tanaka, T., Teumer, A., Trompet, S., van der Laan, S. W., van Setten, J., van Vliet-Ostaptchouk, J. V., Wang, Z., Yengo, L., Zhang, W., Afzal, U., Arnloev, J., Arscott, G. M., Bandinelli, S., Barrett, A., Bellis, C., Bennett, A. J., Berne, C., Blueher, M., Bolton, J. L., Boettcher, Y., Boyd, H. A., Bruinenberg, M., Buckley, B. M., Buyske, S., Caspersen, I. H., Chines, P. S., Clarke, R., Claudi-Boehm, S., Cooper, M., Daw, E. W., de Jong, P. A., Deelen, J., Delgado, G., Denny, J. C., Dhonukshe-Rutten, R., Dimitriou, M., Doney, A. S., Doerr, M., Eklund, N., Eury, E., Folkersen, L., Garcia, M. E., Geller, F., Giedraitis, V., Go, A. S., Grallert, H., Grammer, T. B., Graessler, J., Groenberg, H., de Groot, L. C., Groves, C. J., Haessler, J., Hall, P., Haller, T., Hallmans, G., Hannemann, A., Hartman, C. A., Hassinen, M., Hayward, C., Heard-Costa, N. L., Helmer, Q., Hemani, G., Henders, A. K., Hillege, H. L., Hlatky, M. A., Hoffmann, W., Hoffmann, P., Holmen, O., Houwing-Duistermaat, J. J., Illig, T., Isaacs, A., James, A. L., Jeff, J., Johansen, B., Johansson, A., Jolley, J., Juliusdottir, T., Junttila, J., Kho, A. N., Kinnunen, L., Klopp, N., Kocher, T., Kratzer, W., Lichtner, P., Lind, L., Lindstroem, J., Lobbens, S., Lorentzon, M., Lu, Y., Lyssenko, V., Magnusson, P. K., Mahajan, A., Maillard, M., McArdle, W. L., McKenzie, C. A., McLachlan, S., McLaren, P. J., Menni, C., Merger, S., Milani, L., Moayyeri, A., Monda, K. L., Morken, M. A., Mueller, G., Mueller-Nurasyid, M., Musk, A. W., Narisu, N., Nauck, M., Nolte, I. M., Noethen, M. M., Oozageer, L., Pilz, S., Rayner, N. W., Renstrom, F., Robertson, N. R., Rose, L. M., Roussel, R., Sanna, S., Scharnagl, H., Scholtens, S., Schumacher, F. R., Schunkert, H., Scott, R. A., Sehmi, J., Seufferlein, T., Shin, J., Silventoinen, K., Smit, J. H., Smith, A. V., Smolonska, J., Stanton, A. V., Stirrups, K., Stott, D. J., Stringham, H. M., Sundstrom, J., Swertz, M. A., Syvanen, A., Tayo, B. O., Thorleifsson, G., Tyrer, J. P., Van Dijk, S., van Schoor, N. M., van der Velde, N., van Heemst, D., van Oort, F. V., Vermeulen, S. H., Verweij, N., Vonk, J. M., Waite, L. L., Waldenberger, M., Wennauer, R., Wilkens, L. R., Willenborg, C., Wilsgaard, T., Wojczynski, M. K., Wong, A., Wright, A. F., Zhang, Q., Arveiler, D., Bakker, S. J., Beilby, J., Bergman, R. N., Bergmann, S., Biffar, R., Blangero, J., Boomsma, D. I., Bornstein, S. R., Bovet, P., Brambilla, P., Brown, M. J., Campbell, H., Caulfield, M. J., Chakravarti, A., Collins, R., Collins, F. S., Crawford, D. C., Cupples, L. A., Danesh, J., de Faire, U., Den Ruijter, H. M., Erbel, R., Erdmann, J., Eriksson, J. G., Farrall, M., Ferrannini, E., Ferrieres, J., Ford, I., Forouhi, N. G., Forrester, T., Gansevoort, R. T., Gejman, P. V., Gieger, C., Golay, A., Gottesman, O., Gudnason, V., Gyllensten, U., Haas, D. W., Hall, A. S., Harris, T. B., Hattersley, A. T., Heath, A. C., Hengstenberg, C., Hicks, A. A., Hindorff, L. A., Hingorani, A. D., Hofman, A., Hovingh, G. K., Humphries, S. E., Hunt, S. C., Hypponen, E., Jacobs, K. B., Jarvelin, M., Jousilahti, P., Jula, A. M., Kaprio, J., Kastelein, J. J., Kayser, M., Kee, F., Keinanen-Kiukaanniemi, S. M., Kiemeney, L. A., Kooner, J. S., Kooperberg, C., Koskinen, S., Kovacs, P., Kraja, A. T., Kumari, M., Kuusisto, J., Lakka, T. A., Langenberg, C., Le Marchand, L., Lehtimaki, T., Lupoli, S., Madden, P. A., Mannisto, S., Manunta, P., Marette, A., Matise, T. C., McKnight, B., Meitinger, T., Moll, F. L., Montgomery, G. W., Morris, A. D., Morris, A. P., Murray, J. C., Nelis, M., Ohlsson, C., Oldehinkel, A. J., Ong, K. K., Ouwehand, W. H., Pasterkamp, G., Peters, A., Pramstaller, P. P., Price, J. F., Qi, L., Raitakari, O. T., Rankinen, T., Rao, D. C., Rice, T. K., Ritchie, M., Rudan, I., Salomaa, V., Samani, N. J., Saramies, J., Sarzynski, M. A., Schwarz, P. E., Sebert, S., Sever, P., Shuldiner, A. R., Sinisalo, J., Steinthorsdottir, V., Stolk, R. P., Tardif, J., Toenjes, A., Tremblay, A., Tremoli, E., Virtamo, J., Vohl, M., Amouyel, P., Asselbergs, F. W., Assimes, T. L., Bochud, M., Boehm, B. O., Boerwinkle, E., Bottinger, E. P., Bouchard, C., Cauchi, S., Chambers, J. C., Chanock, S. J., Cooper, R. S., de Bakker, P. I., Dedoussis, G., Ferrucci, L., Franks, P. W., Froguel, P., Groop, L. C., Haiman, C. A., Hamsten, A., Hayes, M. G., Hui, J., Hunter, D. J., Hveem, K., Jukema, J. W., Kaplan, R. C., Kivimaki, M., Kuh, D., Laakso, M., Liu, Y., Martin, N. G., Maerz, W., Melbye, M., Moebus, S., Munroe, P. B., Njolstad, I., Oostra, B. A., Palmer, C. N., Pedersen, N. L., Perola, M., Perusse, L., Peters, U., Powell, J. E., Power, C., Quertermous, T., Rauramaa, R., Reinmaa, E., Ridker, P. M., Rivadeneira, F., Rotter, J. I., Saaristo, T. E., Saleheen, D., Schlessinger, D., Slagboom, P. E., Snieder, H., Spector, T. D., Strauch, K., Stumvoll, M., Tuomilehto, J., Uusitupa, M., van der Harst, P., Voelzke, H., Walker, M., Wareham, N. J., Watkins, H., Wichmann, H., Wilson, J. F., Zanen, P., Deloukas, P., Heid, I. M., Lindgren, C. M., Mohlke, K. L., Speliotes, E. K., Thorsteinsdottir, U., Barroso, I., Fox, C. S., North, K. E., Strachan, D. P., Beckmann, J. S., Berndt, S. I., Boehnke, M., Borecki, I. B., McCarthy, M. I., Metspalu, A., Stefansson, K., Uitterlinden, A. G., van Duijn, C. M., Franke, L., Willer, C. J., Price, A. L., Lettre, G., Loos, R. J., Weedon, M. N., Ingelsson, E., O'Connell, J. R., Abecasis, G. R., Chasman, D. I., Goddard, M. E., Visscher, P. M., Hirschhorn, J. N., Frayling, T. M. 2014; 46 (11): 1173-1186

    View details for DOI 10.1038/ng.3097

    View details for Web of Science ID 000344131900008

  • Meta-analysis of genome-wide association studies in East Asian-ancestry populations identifies four new loci for body mass index HUMAN MOLECULAR GENETICS Wen, W., Zheng, W., Okada, Y., Takeuchi, F., Tabara, Y., Hwang, J., Dorajoo, R., Li, H., Tsai, F., Yang, X., He, J., Wu, Y., He, M., Zhang, Y., Liang, J., Guo, X., Sheu, W. H., Delahanty, R., Guo, X., Kubo, M., Yamamoto, K., Ohkubo, T., Go, M. J., Liu, J. J., Gan, W., Chen, C., Gao, Y., Li, S., Lee, N. R., Wu, C., Zhou, X., Song, H., Yao, J., Lee, I., Long, J., Tsunoda, T., Akiyama, K., Takashima, N., Cho, Y. S., Ong, R. T., Lu, L., Chen, C., Tan, A., Rice, T. K., Adair, L. S., Gui, L., Allison, M., Lee, W., Cai, Q., Isomura, M., Umemura, S., Kim, Y. J., Seielstad, M., Hixson, J., Xiang, Y., Isono, M., Kim, B., Sim, X., Lu, W., Nabika, T., Lee, J., Lim, W., Gao, Y., Takayanagi, R., Kang, D., Wong, T. Y., Hsiung, C., Wu, I., Juang, J. J., Shi, J., Choi, B. Y., Aung, T., Hu, F., Kim, M. K., Lim, W., Wang, T., Shin, M., Lee, J., Ji, B., Lee, Y., Young, T. L., Shin, D. H., Chun, B., Cho, M., Han, B., Hwu, C., Assimes, T. L., Absher, D., Yan, X., Kim, E., Kuo, J. Z., Kwon, S., Taylor, K. D., Chen, Y. I., Rotter, J. I., Qi, L., Zhu, D., Wu, T., Mohlke, K. L., Gu, D., Mo, Z., Wu, J., Lin, X., Miki, T., Tai, E. S., Lee, J., Kato, N., Shu, X., Tanaka, T. 2014; 23 (20): 5492-5504

    View details for DOI 10.1093/hmg/ddu248

    View details for Web of Science ID 000343202400016

  • Study of exonic variation identifies incremental information regarding lipid-related and coronary heart disease genes. Circulation research Assimes, T. L., Quertermous, T. 2014; 115 (5): 478-480

    View details for DOI 10.1161/CIRCRESAHA.114.304693

    View details for PubMedID 25124323

  • Obesity, physical activity, and their interaction in incident atrial fibrillation in postmenopausal women. Journal of the American Heart Association Azarbal, F., Stefanick, M. L., Salmoirago-Blotcher, E., Manson, J. E., Albert, C. M., LaMonte, M. J., Larson, J. C., Li, W., Martin, L. W., Nassir, R., Garcia, L., Assimes, T. L., Tharp, K. M., Hlatky, M. A., Perez, M. V. 2014; 3 (4)

    Abstract

    Atrial fibrillation (AF) is the most common cardiac arrhythmia and is associated with increased risk of stroke and death. Obesity is an independent risk factor for AF, but modifiers of this risk are not well known. We studied the roles of obesity, physical activity, and their interaction in conferring risk of incident AF.The Women's Health Initiative (WHI) Observational Study was a prospective observational study of 93 676 postmenopausal women followed for an average of 11.5 years. Incident AF was identified using WHI-ascertained hospitalization records and diagnostic codes from Medicare claims. A multivariate Cox's hazard regression model adjusted for demographic and clinical risk factors was used to evaluate the interaction between obesity and physical activity and its association with incident AF. After exclusion of women with prevalent AF, incomplete data, or underweight body mass index (BMI), 9792 of the remaining 81 317 women developed AF. Women were, on average, 63.4 years old, 7.8% were African American, and 3.6% were Hispanic. Increased BMI (hazard ratio [HR], 1.12 per 5-kg/m(2) increase; 95% confidence interval [CI], 1.10 to 1.14) and reduced physical activity (>9 vs. 0 metabolic equivalent task hours per week; HR, 0.90; 95% CI, 0.85 to 0.96) were independently associated with higher rates of AF after multivariate adjustment. Higher levels of physical activity reduced the AF risk conferred by obesity (interaction P=0.033).Greater physical activity is associated with lower rates of incident AF and modifies the association between obesity and incident AF.

    View details for DOI 10.1161/JAHA.114.001127

    View details for PubMedID 25142057

  • Loss-of-Function Mutations in APOC3, Triglycerides, and Coronary Disease NEW ENGLAND JOURNAL OF MEDICINE Crosby, J., Peloso, G. M., Auer, P. L., Crosslin, D. R., Stitziel, N. O., Lange, L. A., Lu, Y., Tang, Z., Zhang, H., Hindy, G., Masca, N., Stirrups, K., Kanoni, S., Do, R., Jun, G., Hu, Y., Kang, H. M., Xue, C., Goel, A., Farrall, M., Duga, S., Merlini, P. A., Asselta, R., Girelli, D., Olivieri, O., Martinelli, N., Yin, W., Reilly, D., Speliotes, E., Fox, C. S., Hveem, K., Holmen, O. L., Nikpay, M., Farlow, D. N., Assimes, T. L., Franceschini, N., Robinson, J., North, K. E., Martin, L. W., DePristo, M., Gupta, N., Escher, S. A., Jansson, J., Van Zuydam, N., Palmer, C. N., Wareham, N., Koch, W., Meitinger, T., Peters, A., Lieb, W., Erbel, R., Konig, I. R., Kruppa, J., Degenhardt, F., Gottesman, O., Bottinger, E. P., O'Donnell, C. J., Psaty, B. M., Ballantyne, C. M., Abecasis, G., Ordovas, J. M., Melander, O., Watkins, H., Orho-Melander, M., Ardissino, D., Loos, R. J., McPherson, R., Willer, C. J., Erdmann, J., Hall, A. S., Samani, N. J., Deloukas, P., Schunkert, H., Wilson, J. G., Kooperberg, C., Rich, S. S., Tracy, R. P., Lin, D., Altshuler, D., Gabriel, S., Nickerson, D. A., Jarvik, G. P., Cupples, L. A., Reiner, A. P., Boerwinkle, E., Kathiresan, S. 2014; 371 (1): 22-31

    Abstract

    Background Plasma triglyceride levels are heritable and are correlated with the risk of coronary heart disease. Sequencing of the protein-coding regions of the human genome (the exome) has the potential to identify rare mutations that have a large effect on phenotype. Methods We sequenced the protein-coding regions of 18,666 genes in each of 3734 participants of European or African ancestry in the Exome Sequencing Project. We conducted tests to determine whether rare mutations in coding sequence, individually or in aggregate within a gene, were associated with plasma triglyceride levels. For mutations associated with triglyceride levels, we subsequently evaluated their association with the risk of coronary heart disease in 110,970 persons. Results An aggregate of rare mutations in the gene encoding apolipoprotein C3 (APOC3) was associated with lower plasma triglyceride levels. Among the four mutations that drove this result, three were loss-of-function mutations: a nonsense mutation (R19X) and two splice-site mutations (IVS2+1G?A and IVS3+1G?T). The fourth was a missense mutation (A43T). Approximately 1 in 150 persons in the study was a heterozygous carrier of at least one of these four mutations. Triglyceride levels in the carriers were 39% lower than levels in noncarriers (P<1×10(-20)), and circulating levels of APOC3 in carriers were 46% lower than levels in noncarriers (P=8×10(-10)). The risk of coronary heart disease among 498 carriers of any rare APOC3 mutation was 40% lower than the risk among 110,472 noncarriers (odds ratio, 0.60; 95% confidence interval, 0.47 to 0.75; P=4×10(-6)). Conclusions Rare mutations that disrupt APOC3 function were associated with lower levels of plasma triglycerides and APOC3. Carriers of these mutations were found to have a reduced risk of coronary heart disease. (Funded by the National Heart, Lung, and Blood Institute and others.).

    View details for DOI 10.1056/NEJMoa1307095

    View details for Web of Science ID 000338265700006

  • Integrative genomics reveals novel molecular pathways and gene networks for coronary artery disease. PLoS genetics Mäkinen, V., Civelek, M., Meng, Q., Zhang, B., Zhu, J., Levian, C., Huan, T., Segrè, A. V., Ghosh, S., Vivar, J., Nikpay, M., Stewart, A. F., Nelson, C. P., Willenborg, C., Erdmann, J., Blakenberg, S., O'Donnell, C. J., März, W., Laaksonen, R., Epstein, S. E., Kathiresan, S., Shah, S. H., Hazen, S. L., Reilly, M. P., Lusis, A. J., Samani, N. J., Schunkert, H., Quertermous, T., McPherson, R., Yang, X., Assimes, T. L. 2014; 10 (7)

    Abstract

    The majority of the heritability of coronary artery disease (CAD) remains unexplained, despite recent successes of genome-wide association studies (GWAS) in identifying novel susceptibility loci. Integrating functional genomic data from a variety of sources with a large-scale meta-analysis of CAD GWAS may facilitate the identification of novel biological processes and genes involved in CAD, as well as clarify the causal relationships of established processes. Towards this end, we integrated 14 GWAS from the CARDIoGRAM Consortium and two additional GWAS from the Ottawa Heart Institute (25,491 cases and 66,819 controls) with 1) genetics of gene expression studies of CAD-relevant tissues in humans, 2) metabolic and signaling pathways from public databases, and 3) data-driven, tissue-specific gene networks from a multitude of human and mouse experiments. We not only detected CAD-associated gene networks of lipid metabolism, coagulation, immunity, and additional networks with no clear functional annotation, but also revealed key driver genes for each CAD network based on the topology of the gene regulatory networks. In particular, we found a gene network involved in antigen processing to be strongly associated with CAD. The key driver genes of this network included glyoxalase I (GLO1) and peptidylprolyl isomerase I (PPIL1), which we verified as regulatory by siRNA experiments in human aortic endothelial cells. Our results suggest genetic influences on a diverse set of both known and novel biological processes that contribute to CAD risk. The key driver genes for these networks highlight potential novel targets for further mechanistic studies and therapeutic interventions.

    View details for DOI 10.1371/journal.pgen.1004502

    View details for PubMedID 25033284

  • Multiple nonglycemic genomic Loci are newly associated with blood level of glycated hemoglobin in East asians. Diabetes Chen, P., Takeuchi, F., Lee, J., Li, H., Wu, J., Liang, J., Long, J., Tabara, Y., Goodarzi, M. O., Pereira, M. A., Kim, Y. J., Go, M. J., Stram, D. O., Vithana, E., Khor, C., Liu, J., Liao, J., Ye, X., Wang, Y., Lu, L., Young, T. L., Lee, J., Thai, A. C., Cheng, C., van Dam, R. M., Friedlander, Y., Heng, C., Koh, W., Chen, C., Chang, L., Pan, W., Qi, Q., Isono, M., Zheng, W., Cai, Q., Gao, Y., Yamamoto, K., Ohnaka, K., Takayanagi, R., Kita, Y., Ueshima, H., Hsiung, C. A., Cui, J., Sheu, W. H., Rotter, J. I., Chen, Y. I., Hsu, C., Okada, Y., Kubo, M., Takahashi, A., Tanaka, T., van Rooij, F. J., Ganesh, S. K., Huang, J., Huang, T., Yuan, J., Hwang, J., Gross, M. D., Assimes, T. L., Miki, T., Shu, X., Qi, L., Chen, Y., Lin, X., Aung, T., Wong, T., Teo, Y., Kim, B., Kato, N., Tai, E. 2014; 63 (7): 2551-2562

    Abstract

    Glycated hemoglobin (HbA1C) is used as a measure of glycemic control and also as a diagnostic criterion for diabetes mellitus. To discover novel loci harbouring common variants associated with HbA1C in East Asians, we conducted a meta-analysis of 13 genome wide association studies (N=21,026). We replicated our findings in 3 additional studies comprising 11,576 individuals of East Asian ancestry. 10 variants showed associations that reached genome wide significance in the discovery dataset of which 9 [4 novel variants at TMEM79 (P-value 1.3 × 10(-23)), HBS1L/MYB (8.5 × 10(-15)), MYO9B (9.0 × 10(-12)) and CYBA (1.1 × 10(-8)) as well as 5 variants at loci that had been previously identified (CDKAL1, G6PC2/ABCB11, GCK, ANK1, and FN3K)] showed consistent evidence of association in replication datasets. These variants explained 1.76% of the variance in HbA1C. Several of these variants (TMEM79, HBS1L/MYB, CYBA, MYO9B, ANK1, and FN3K) showed no association with either blood glucose or type 2 diabetes. Amongst individuals with non-diabetic levels of fasting glucose (<7.0 mmol/l) but elevated (>=6.5%) HbA1c, 36.1% had HbA1C<6.5% after adjustment for these 6 variants. . Our East Asian GWAS meta-analysis has identified novel variants associated with HbA1C as well as demonstrating that the effects of known variants are largely transferable across ethnic groups. Variants affecting erythrocyte parameters rather than glucose metabolism may be relevant to the use of HbA1C for diagnosing diabetes in these populations.

    View details for DOI 10.2337/db13-1815

    View details for PubMedID 24647736

  • Impact of type 2 diabetes susceptibility variants on quantitative glycemic traits reveals mechanistic heterogeneity. Diabetes Dimas, A. S., Lagou, V., Barker, A., Knowles, J. W., Mägi, R., Hivert, M., Benazzo, A., Rybin, D., Jackson, A. U., Stringham, H. M., Song, C., Fischer-Rosinsky, A., Boesgaard, T. W., Grarup, N., Abbasi, F. A., Assimes, T. L., Hao, K., Yang, X., Lecoeur, C., Barroso, I., Bonnycastle, L. L., Böttcher, Y., Bumpstead, S., Chines, P. S., Erdos, M. R., Graessler, J., Kovacs, P., Morken, M. A., Narisu, N., Payne, F., Stancakova, A., Swift, A. J., Tönjes, A., Bornstein, S. R., Cauchi, S., Froguel, P., Meyre, D., Schwarz, P. E., Häring, H., Smith, U., Boehnke, M., Bergman, R. N., Collins, F. S., Mohlke, K. L., Tuomilehto, J., Quertemous, T., Lind, L., Hansen, T., Pedersen, O., Walker, M., Pfeiffer, A. F., Spranger, J., Stumvoll, M., Meigs, J. B., Wareham, N. J., Kuusisto, J., Laakso, M., Langenberg, C., Dupuis, J., Watanabe, R. M., Florez, J. C., Ingelsson, E., McCarthy, M. I., Prokopenko, I. 2014; 63 (6): 2158-2171

    Abstract

    Patients with established type 2 diabetes display both beta-cell dysfunction and insulin resistance. To define fundamental processes leading to the diabetic state, we examined the relationship between type 2 diabetes risk variants at 37 established susceptibility loci and indices of proinsulin processing, insulin secretion and insulin sensitivity. We included data from up to 58,614 non-diabetic subjects with basal measures, and 17,327 with dynamic measures. We employed additive genetic models with adjustment for sex, age and BMI, followed by fixed-effects inverse variance meta-analyses. Cluster analyses grouped risk loci into five major categories based on their relationship to these continuous glycemic phenotypes. The first cluster (PPARG, KLF14, IRS1, GCKR) was characterized by primary effects on insulin sensitivity. The second (MTNR1B, GCK) featured risk alleles associated with reduced insulin secretion and fasting hyperglycemia. ARAP1 constituted a third cluster characterized by defects in insulin processing. A fourth cluster (including TCF7L2, SLC30A8, HHEX/IDE, CDKAL1, CDKN2A/2B) was defined by loci influencing insulin processing and secretion without detectable change in fasting glucose. The final group contained twenty risk loci with no clear-cut associations to continuous glycemic traits. By assembling extensive data on continuous glycemic traits, we have exposed the diverse mechanisms whereby type 2 diabetes risk variants impact disease predisposition.

    View details for DOI 10.2337/db13-0949

    View details for PubMedID 24296717

  • Dissecting the causal genetic mechanisms of coronary heart disease. Current atherosclerosis reports Miller, C. L., Assimes, T. L., Montgomery, S. B., Quertermous, T. 2014; 16 (5): 406-?

    Abstract

    Large-scale genome-wide association studies (GWAS) have identified 46 loci that are associated with coronary heart disease (CHD). Additionally, 104 independent candidate variants (false discovery rate of 5 %) have been identified (Schunkert H, Konig IR, Kathiresan S, Reilly MP, Assimes TL, Holm H et al. Nat Genet 43:333-8, 2011; Deloukas P, Kanoni S, Willenborg C, Farrall M, Assimes TL, Thompson JR et al. Nat Genet 45:25-33, 2012; C4D Genetics Consortium. Nat Genet 43:339-44, 2011). The majority of the causal genes in these loci function independently of conventional risk factors. It is postulated that a number of the CHD-associated genes regulate basic processes in the vascular cells involved in atherosclerosis, and that study of the signaling pathways that are modulated in this cell type by causal regulatory variation will provide critical new insights for targeting the initiation and progression of disease. In this review, we will discuss the types of experimental approaches and data that are critical to understanding the molecular processes that underlie the disease risk at 9p21.3, TCF21, SORT1, and other CHD-associated loci.

    View details for DOI 10.1007/s11883-014-0406-4

    View details for PubMedID 24623178

  • Quantifying rare, deleterious variation in 12 human cytochrome P450 drug-metabolism genes in a large-scale exome dataset. Human molecular genetics Gordon, A. S., Tabor, H. K., Johnson, A. D., Snively, B. M., Assimes, T. L., Auer, P. L., Ioannidis, J. P., Peters, U., Robinson, J. G., Sucheston, L. E., Wang, D., Sotoodehnia, N., Rotter, J. I., Psaty, B. M., Jackson, R. D., Herrington, D. M., O'Donnell, C. J., Reiner, A. P., Rich, S. S., Rieder, M. J., Bamshad, M. J., Nickerson, D. A. 2014; 23 (8): 1957-1963

    Abstract

    The study of genetic influences on drug response and efficacy ('pharmacogenetics') has existed for over 50 years. Yet, we still lack a complete picture of how genetic variation, both common and rare, affects each individual's responses to medications. Exome sequencing is a promising alternative method for pharmacogenetic discovery as it provides information on both common and rare variation in large numbers of individuals. Using exome data from 2203 AA and 4300 Caucasian individuals through the NHLBI Exome Sequencing Project, we conducted a survey of coding variation within 12 Cytochrome P450 (CYP) genes that are collectively responsible for catalyzing nearly 75% of all known Phase I drug oxidation reactions. In addition to identifying many polymorphisms with known pharmacogenetic effects, we discovered over 730 novel nonsynonymous alleles across the 12 CYP genes of interest. These alleles include many with diverse functional effects such as premature stop codons, aberrant splicesites and mutations at conserved active site residues. Our analysis considering both novel, predicted functional alleles as well as known, actionable CYP alleles reveals that rare, deleterious variation contributes markedly to the overall burden of pharmacogenetic alleles within the populations considered, and that the contribution of rare variation to this burden is over three times greater in AA individuals as compared with Caucasians. While most of these impactful alleles are individually rare, 7.6-11.7% of individuals interrogated in the study carry at least one newly described potentially deleterious alleles in a major drug-metabolizing CYP.

    View details for DOI 10.1093/hmg/ddt588

    View details for PubMedID 24282029

  • Clinical interpretation and implications of whole-genome sequencing. JAMA Dewey, F. E., Grove, M. E., Pan, C., Goldstein, B. A., Bernstein, J. A., Chaib, H., Merker, J. D., Goldfeder, R. L., Enns, G. M., David, S. P., Pakdaman, N., Ormond, K. E., Caleshu, C., Kingham, K., Klein, T. E., Whirl-Carrillo, M., Sakamoto, K., Wheeler, M. T., Butte, A. J., Ford, J. M., Boxer, L., Ioannidis, J. P., Yeung, A. C., Altman, R. B., Assimes, T. L., Snyder, M., Ashley, E. A., Quertermous, T. 2014; 311 (10): 1035-1045

    Abstract

    Whole-genome sequencing (WGS) is increasingly applied in clinical medicine and is expected to uncover clinically significant findings regardless of sequencing indication.To examine coverage and concordance of clinically relevant genetic variation provided by WGS technologies; to quantitate inherited disease risk and pharmacogenomic findings in WGS data and resources required for their discovery and interpretation; and to evaluate clinical action prompted by WGS findings.An exploratory study of 12 adult participants recruited at Stanford University Medical Center who underwent WGS between November 2011 and March 2012. A multidisciplinary team reviewed all potentially reportable genetic findings. Five physicians proposed initial clinical follow-up based on the genetic findings.Genome coverage and sequencing platform concordance in different categories of genetic disease risk, person-hours spent curating candidate disease-risk variants, interpretation agreement between trained curators and disease genetics databases, burden of inherited disease risk and pharmacogenomic findings, and burden and interrater agreement of proposed clinical follow-up.Depending on sequencing platform, 10% to 19% of inherited disease genes were not covered to accepted standards for single nucleotide variant discovery. Genotype concordance was high for previously described single nucleotide genetic variants (99%-100%) but low for small insertion/deletion variants (53%-59%). Curation of 90 to 127 genetic variants in each participant required a median of 54 minutes (range, 5-223 minutes) per genetic variant, resulted in moderate classification agreement between professionals (Gross ?, 0.52; 95% CI, 0.40-0.64), and reclassified 69% of genetic variants cataloged as disease causing in mutation databases to variants of uncertain or lesser significance. Two to 6 personal disease-risk findings were discovered in each participant, including 1 frameshift deletion in the BRCA1 gene implicated in hereditary breast and ovarian cancer. Physician review of sequencing findings prompted consideration of a median of 1 to 3 initial diagnostic tests and referrals per participant, with fair interrater agreement about the suitability of WGS findings for clinical follow-up (Fleiss ?, 0.24; P?

    View details for DOI 10.1001/jama.2014.1717

    View details for PubMedID 24618965

    View details for PubMedCentralID PMC4119063

  • Coronary heart disease-associated variation in TCF21 disrupts a miR-224 binding site and miRNA-mediated regulation. PLoS genetics Miller, C. L., Haas, U., Diaz, R., Leeper, N. J., Kundu, R. K., Patlolla, B., Assimes, T. L., Kaiser, F. J., Perisic, L., Hedin, U., Maegdefessel, L., Schunkert, H., Erdmann, J., Quertermous, T., Sczakiel, G. 2014; 10 (3)

    Abstract

    Genome-wide association studies (GWAS) have identified chromosomal loci that affect risk of coronary heart disease (CHD) independent of classical risk factors. One such association signal has been identified at 6q23.2 in both Caucasians and East Asians. The lead CHD-associated polymorphism in this region, rs12190287, resides in the 3' untranslated region (3'-UTR) of TCF21, a basic-helix-loop-helix transcription factor, and is predicted to alter the seed binding sequence for miR-224. Allelic imbalance studies in circulating leukocytes and human coronary artery smooth muscle cells (HCASMC) showed significant imbalance of the TCF21 transcript that correlated with genotype at rs12190287, consistent with this variant contributing to allele-specific expression differences. 3' UTR reporter gene transfection studies in HCASMC showed that the disease-associated C allele has reduced expression compared to the protective G allele. Kinetic analyses in vitro revealed faster RNA-RNA complex formation and greater binding of miR-224 with the TCF21 C allelic transcript. In addition, in vitro probing with Pb2+ and RNase T1 revealed structural differences between the TCF21 variants in proximity of the rs12190287 variant, which are predicted to provide greater access to the C allele for miR-224 binding. miR-224 and TCF21 expression levels were anti-correlated in HCASMC, and miR-224 modulates the transcriptional response of TCF21 to transforming growth factor-? (TGF-?) and platelet derived growth factor (PDGF) signaling in an allele-specific manner. Lastly, miR-224 and TCF21 were localized in human coronary artery lesions and anti-correlated during atherosclerosis. Together, these data suggest that miR-224 interaction with the TCF21 transcript contributes to allelic imbalance of this gene, thus partly explaining the genetic risk for coronary heart disease associated at 6q23.2. These studies implicating rs12190287 in the miRNA-dependent regulation of TCF21, in conjunction with previous studies showing that this variant modulates transcriptional regulation through activator protein 1 (AP-1), suggests a unique bimodal level of complexity previously unreported for disease-associated variants.

    View details for DOI 10.1371/journal.pgen.1004263

    View details for PubMedID 24676100

    View details for PubMedCentralID PMC3967965

  • Whole-Exome Sequencing Identifies Rare and Low-Frequency Coding Variants Associated with LDL Cholesterol. American journal of human genetics Lange, L. A., Hu, Y., Zhang, H., Xue, C., Schmidt, E. M., Tang, Z., Bizon, C., Lange, E. M., Smith, J. D., Turner, E. H., Jun, G., Kang, H. M., Peloso, G., Auer, P., Li, K., Flannick, J., Zhang, J., Fuchsberger, C., Gaulton, K., Lindgren, C., Locke, A., Manning, A., Sim, X., Rivas, M. A., Holmen, O. L., Gottesman, O., Lu, Y., Ruderfer, D., Stahl, E. A., Duan, Q., Li, Y., Durda, P., Jiao, S., Isaacs, A., Hofman, A., Bis, J. C., Correa, A., Griswold, M. E., Jakobsdottir, J., Smith, A. V., Schreiner, P. J., Feitosa, M. F., Zhang, Q., Huffman, J. E., Crosby, J., Wassel, C. L., Do, R., Franceschini, N., Martin, L. W., Robinson, J. G., Assimes, T. L., Crosslin, D. R., Rosenthal, E. A., Tsai, M., Rieder, M. J., Farlow, D. N., Folsom, A. R., Lumley, T., Fox, E. R., Carlson, C. S., Peters, U., Jackson, R. D., van Duijn, C. M., Uitterlinden, A. G., Levy, D., Rotter, J. I., Taylor, H. A., Gudnason, V., Siscovick, D. S., Fornage, M., Borecki, I. B., Hayward, C., Rudan, I., Chen, Y. E., Bottinger, E. P., Loos, R. J., Sætrom, P., Hveem, K., Boehnke, M., Groop, L., McCarthy, M., Meitinger, T., Ballantyne, C. M., Gabriel, S. B., O'Donnell, C. J., Post, W. S., North, K. E., Reiner, A. P., Boerwinkle, E., Psaty, B. M., Altshuler, D., Kathiresan, S., Lin, D., Jarvik, G. P., Cupples, L. A., Kooperberg, C., Wilson, J. G., Nickerson, D. A., Abecasis, G. R., Rich, S. S., Tracy, R. P., Willer, C. J. 2014; 94 (2): 233-245

    Abstract

    Elevated low-density lipoprotein cholesterol (LDL-C) is a treatable, heritable risk factor for cardiovascular disease. Genome-wide association studies (GWASs) have identified 157 variants associated with lipid levels but are not well suited to assess the impact of rare and low-frequency variants. To determine whether rare or low-frequency coding variants are associated with LDL-C, we exome sequenced 2,005 individuals, including 554 individuals selected for extreme LDL-C (>98(th) or <2(nd) percentile). Follow-up analyses included sequencing of 1,302 additional individuals and genotype-based analysis of 52,221 individuals. We observed significant evidence of association between LDL-C and the burden of rare or low-frequency variants in PNPLA5, encoding a phospholipase-domain-containing protein, and both known and previously unidentified variants in PCSK9, LDLR and APOB, three known lipid-related genes. The effect sizes for the burden of rare variants for each associated gene were substantially higher than those observed for individual SNPs identified from GWASs. We replicated the PNPLA5 signal in an independent large-scale sequencing study of 2,084 individuals. In conclusion, this large whole-exome-sequencing study for LDL-C identified a gene not known to be implicated in LDL-C and provides unique insight into the design and analysis of similar experiments.

    View details for DOI 10.1016/j.ajhg.2014.01.010

    View details for PubMedID 24507775

  • The combination of 9p21.3 genotype and biomarker profile improves a peripheral artery disease risk prediction model. Vascular medicine Downing, K. P., Nead, K. T., Kojima, Y., Assimes, T., Maegdefessel, L., Quertermous, T., Cooke, J. P., Leeper, N. J. 2014; 19 (1): 3-8

    Abstract

    Peripheral artery disease (PAD) is a highly morbid condition affecting more than 8 million Americans. Frequently, PAD patients are unrecognized and therefore do not receive appropriate therapies. Therefore, new methods to identify PAD have been pursued, but have thus far had only modest success. Here we describe a new approach combining genomic and metabolic information to enhance the diagnosis of PAD. We measured the genotype of the chromosome 9p21 cardiovascular-risk polymorphism rs10757269 as well as the biomarkers C-reactive protein, cystatin C, ?2-microglobulin, and plasma glucose in a study population of 393 patients undergoing coronary angiography. The rs10757269 allele was associated with PAD status (ankle-brachial index < 0.9) independent of biomarkers and traditional cardiovascular risk factors (odds ratio=1.92; 95% confidence interval, 1.29-2.85). Importantly, compared to a previously validated risk factor-based PAD prediction model, the addition of biomarkers and rs10757269 significantly and incrementally improved PAD risk prediction as assessed by the net reclassification index (NRI=33.5%; p=0.001) and integrated discrimination improvement (IDI=0.016; p=0.017). In conclusion, a model including a panel of biomarkers, which includes both genomic information (which is reflective of heritable risk) and metabolic information (which integrates environmental exposures), predicts the presence or absence of PAD better than established risk models, suggesting clinical utility for the diagnosis of PAD.

    View details for DOI 10.1177/1358863X13514791

    View details for PubMedID 24323119

  • Near-Term Prediction of Sudden Cardiac Death in Older Hemodialysis Patients Using Electronic Health Records CLINICAL JOURNAL OF THE AMERICAN SOCIETY OF NEPHROLOGY Goldstein, B. A., Chang, T. I., Mitani, A. A., Assimes, T. L., Winkelmayer, W. C. 2014; 9 (1): 82-91

    Abstract

    Sudden cardiac death is the most common cause of death among individuals undergoing hemodialysis. The epidemiology of sudden cardiac death has been well studied, and efforts are shifting to risk assessment. This study aimed to test whether assessment of acute changes during hemodialysis that are captured in electronic health records improved risk assessment.Data were collected from all hemodialysis sessions of patients 66 years and older receiving hemodialysis from a large national dialysis provider between 2004 and 2008. The primary outcome of interest was sudden cardiac death the day of or day after a dialysis session. This study used data from 2004 to 2006 as the training set and data from 2007 to 2008 as the validation set. The machine learning algorithm, Random Forests, was used to derive the prediction model.In 22 million sessions, 898 people between 2004 and 2006 and 826 people between 2007 and 2008 died on the day of or day after a dialysis session that was serving as a training or test data session, respectively. A reasonably strong predictor was derived using just predialysis information (concordance statistic=0.782), which showed modest but significant improvement after inclusion of postdialysis information (concordance statistic=0.799, P<0.001). However, risk prediction decreased the farther out that it was forecasted (up to 1 year), and postdialytic information became less important.Subtle changes in the experience of hemodialysis aid in the assessment of sudden cardiac death and are captured by modern electronic health records. The collected data are better for the assessment of near-term risk as opposed to longer-term risk.

    View details for DOI 10.2215/CJN.03050313

    View details for Web of Science ID 000329364700013

    View details for PubMedID 24178968

  • Insulin resistance: regression and clustering. PloS one Yoon, S., Assimes, T. L., Quertermous, T., Hsiao, C., Chuang, L., Hwu, C., Rajaratnam, B., Olshen, R. A. 2014; 9 (6)

    Abstract

    In this paper we try to define insulin resistance (IR) precisely for a group of Chinese women. Our definition deliberately does not depend upon body mass index (BMI) or age, although in other studies, with particular random effects models quite different from models used here, BMI accounts for a large part of the variability in IR. We accomplish our goal through application of Gauss mixture vector quantization (GMVQ), a technique for clustering that was developed for application to lossy data compression. Defining data come from measurements that play major roles in medical practice. A precise statement of what the data are is in Section 1. Their family structures are described in detail. They concern levels of lipids and the results of an oral glucose tolerance test (OGTT). We apply GMVQ to residuals obtained from regressions of outcomes of an OGTT and lipids on functions of age and BMI that are inferred from the data. A bootstrap procedure developed for our family data supplemented by insights from other approaches leads us to believe that two clusters are appropriate for defining IR precisely. One cluster consists of women who are IR, and the other of women who seem not to be. Genes and other features are used to predict cluster membership. We argue that prediction with "main effects" is not satisfactory, but prediction that includes interactions may be.

    View details for DOI 10.1371/journal.pone.0094129

    View details for PubMedID 24887437

  • Use of Medicare Data to Identify Coronary Heart Disease Outcomes in the Women's Health Initiative. Circulation. Cardiovascular quality and outcomes Hlatky, M. A., Ray, R. M., Burwen, D. R., Margolis, K. L., Johnson, K. C., Kucharska-Newton, A., Manson, J. E., Robinson, J. G., Safford, M. M., Allison, M., Assimes, T. L., Bavry, A. A., Berger, J., Cooper-DeHoff, R. M., Heckbert, S. R., Li, W., Liu, S., Martin, L. W., Perez, M. V., Tindle, H. A., Winkelmayer, W. C., Stefanick, M. L. 2014; 7 (1): 157-162

    View details for DOI 10.1161/CIRCOUTCOMES.113.000373

    View details for PubMedID 24399330

  • Simple, standardized incorporation of genetic risk into non-genetic risk prediction tools for complex traits: coronary heart disease as an example. Frontiers in genetics Goldstein, B. A., Knowles, J. W., Salfati, E., Ioannidis, J. P., Assimes, T. L. 2014; 5: 254-?

    Abstract

    Genetic risk assessment is becoming an important component of clinical decision-making. Genetic Risk Scores (GRSs) allow the composite assessment of genetic risk in complex traits. A technically and clinically pertinent question is how to most easily and effectively combine a GRS with an assessment of clinical risk derived from established non-genetic risk factors as well as to clearly present this information to patient and health care providers.We illustrate a means to combine a GRS with an independent assessment of clinical risk using a log-link function. We apply the method to the prediction of coronary heart disease (CHD) in the Atherosclerosis Risk in Communities (ARIC) cohort. We evaluate different constructions based on metrics of effect change, discrimination, and calibration.The addition of a GRS to a clinical risk score (CRS) improves both discrimination and calibration for CHD in ARIC. RESULTS are similar regardless of whether external vs. internal coefficients are used for the CRS, risk factor single nucleotide polymorphisms (SNPs) are included in the GRS, or subjects with diabetes at baseline are excluded. We outline how to report the construction and the performance of a GRS using our method and illustrate a means to present genetic risk information to subjects and/or their health care provider.The proposed method facilitates the standardized incorporation of a GRS in risk assessment.

    View details for DOI 10.3389/fgene.2014.00254

    View details for PubMedID 25136350

  • Shared Genetic Susceptibility to Ischemic Stroke and Coronary Artery Disease A Genome-Wide Analysis of Common Variants STROKE Dichgans, M., Malik, R., Koenig, I. R., Rosand, J., Clarke, R., Gretarsdottir, S., Thorleifsson, G., Mitchell, B. D., Assimes, T. L., Levi, C., O'Donnell, C. J., Fornage, M., Thorsteinsdottir, U., Psaty, B. M., Hengstenberg, C., Seshadri, S., Erdmann, J., Bis, J. C., Peters, A., Boncoraglio, G. B., Maerz, W., Meschia, J. F., Kathiresan, S., Ikram, M. A., McPherson, R., Stefansson, K., Sudlow, C., Reilly, M. P., Thompson, J. R., Sharma, P., Hopewell, J. C., Chambers, J. C., Watkins, H., Rothwell, P. M., Roberts, R., Markus, H. S., Samani, N. J., Farrall, M., Schunkert, H. 2014; 45 (1): 24-36

    Abstract

    Ischemic stroke (IS) and coronary artery disease (CAD) share several risk factors and each has a substantial heritability. We conducted a genome-wide analysis to evaluate the extent of shared genetic determination of the two diseases.Genome-wide association data were obtained from the METASTROKE, Coronary Artery Disease Genome-wide Replication and Meta-analysis (CARDIoGRAM), and Coronary Artery Disease (C4D) Genetics consortia. We first analyzed common variants reaching a nominal threshold of significance (P<0.01) for CAD for their association with IS and vice versa. We then examined specific overlap across phenotypes for variants that reached a high threshold of significance. Finally, we conducted a joint meta-analysis on the combined phenotype of IS or CAD. Corresponding analyses were performed restricted to the 2167 individuals with the ischemic large artery stroke (LAS) subtype.Common variants associated with CAD at P<0.01 were associated with a significant excess risk for IS and for LAS and vice versa. Among the 42 known genome-wide significant loci for CAD, 3 and 5 loci were significantly associated with IS and LAS, respectively. In the joint meta-analyses, 15 loci passed genome-wide significance (P<5×10(-8)) for the combined phenotype of IS or CAD and 17 loci passed genome-wide significance for LAS or CAD. Because these loci had prior evidence for genome-wide significance for CAD, we specifically analyzed the respective signals for IS and LAS and found evidence for association at chr12q24/SH2B3 (PIS=1.62×10(-7)) and ABO (PIS=2.6×10(-4)), as well as at HDAC9 (PLAS=2.32×10(-12)), 9p21 (PLAS=3.70×10(-6)), RAI1-PEMT-RASD1 (PLAS=2.69×10(-5)), EDNRA (PLAS=7.29×10(-4)), and CYP17A1-CNNM2-NT5C2 (PLAS=4.9×10(-4)).Our results demonstrate substantial overlap in the genetic risk of IS and particularly the LAS subtype with CAD.

    View details for DOI 10.1161/STROKEAHA.113.002707

    View details for Web of Science ID 000328823400015

    View details for PubMedID 24262325

  • Genetics and Genomics for the Prevention and Treatment of Cardiovascular Disease: Update A Scientific Statement From the American Heart Association CIRCULATION Ganesh, S. K., Arnett, D. K., Assimes, T. L., Basson, C. T., Chakravarti, A., Ellinor, P. T., Engler, M. B., Goldmuntz, E., Herrington, D. M., Hershberger, R. E., Hong, Y., Johnson, J. A., Kittner, S. J., McDermott, D. A., Meschia, J. F., Mestroni, L., O'Donnell, C. J., Psaty, B. M., Vasan, R. S., Ruel, M., Shen, W., Terzic, A., Waldman, S. A. 2013; 128 (25): 2813-2851

    View details for DOI 10.1161/01.cir.0000437913.98912.1d

    View details for Web of Science ID 000330348100020

  • Trans-ethnic fine mapping identifies a novel independent locus at the 3 ' end of CDKAL1 and novel variants of several susceptibility loci for type 2 diabetes in a Han Chinese population DIABETOLOGIA Kuo, J. Z., Sheu, W. H., Assimes, T. L., Hung, Y., Absher, D., Chiu, Y., Mak, J., Wang, J., Kwon, S., Hsu, C., Goodarzi, M. O., Lee, I., Knowles, J. W., Miller, B. E., Lee, W., Juang, J. J., Wang, T., Guo, X., Taylor, K. D., Chuang, L., Hsiung, C. A., Quertermous, T., Rotter, J. I., Chen, Y. I. 2013; 56 (12): 2619-2628

    Abstract

    Candidate gene and genome-wide association studies have identified ?60 susceptibility loci for type 2 diabetes. A majority of these loci have been discovered and tested only in European populations. The aim of this study was to assess the presence and extent of trans-ethnic effects of these loci in an East Asian population.A total of 9,335 unrelated Chinese Han individuals, including 4,535 with type 2 diabetes and 4,800 non-diabetic ethnically matched controls, were genotyped using the Illumina 200K Metabochip. We tested 50 established loci for type 2 diabetes and related traits (fasting glucose, fasting insulin, 2 h glucose). Disease association with the additive model of inheritance was analysed with logistic regression.We found that 14 loci significantly transferred to the Chinese population, with two loci (p?=?5.7?×?10(-12) for KCNQ1; p?=?5.0?×?10(-8) for CDKN2A/B-CDKN2BAS) reaching independent genome-wide statistical significance. Five of these 14 loci had similar lead single-nucleotide polymorphisms (SNPs) as were found in the European studies while the other nine were different. Further stepwise conditional analysis identified a total of seven secondary signals and an independent novel locus at the 3' end of CDKAL1.These results suggest that many loci associated with type 2 diabetes are commonly shared between European and Chinese populations. Identification of population-specific SNPs may increase our understanding of the genetic architecture underlying type 2 diabetes in different ethnic populations.

    View details for DOI 10.1007/s00125-013-3047-1

    View details for Web of Science ID 000326599300010

    View details for PubMedID 24013783

  • Discovery and refinement of loci associated with lipid levels. Nature genetics Willer, C. J., Schmidt, E. M., Sengupta, S., Peloso, G. M., Gustafsson, S., Kanoni, S., Ganna, A., Chen, J., Buchkovich, M. L., Mora, S., Beckmann, J. S., Bragg-Gresham, J. L., Chang, H., Demirkan, A., den Hertog, H. M., Do, R., Donnelly, L. A., Ehret, G. B., Esko, T., Feitosa, M. F., Ferreira, T., Fischer, K., Fontanillas, P., Fraser, R. M., Freitag, D. F., Gurdasani, D., Heikkilä, K., Hyppönen, E., Isaacs, A., Jackson, A. U., Johansson, A., Johnson, T., Kaakinen, M., Kettunen, J., Kleber, M. E., Li, X., Luan, J., Lyytikäinen, L., Magnusson, P. K., Mangino, M., Mihailov, E., Montasser, M. E., Müller-Nurasyid, M., Nolte, I. M., O'Connell, J. R., Palmer, C. D., Perola, M., Petersen, A., Sanna, S., Saxena, R., Service, S. K., Shah, S., Shungin, D., Sidore, C., Song, C., Strawbridge, R. J., Surakka, I., Tanaka, T., Teslovich, T. M., Thorleifsson, G., van den Herik, E. G., Voight, B. F., Volcik, K. A., Waite, L. L., Wong, A., Wu, Y., Zhang, W., Absher, D., Asiki, G., Barroso, I., Been, L. F., Bolton, J. L., Bonnycastle, L. L., Brambilla, P., Burnett, M. S., Cesana, G., Dimitriou, M., Doney, A. S., Döring, A., Elliott, P., Epstein, S. E., Eyjolfsson, G. I., Gigante, B., Goodarzi, M. O., Grallert, H., Gravito, M. L., Groves, C. J., Hallmans, G., Hartikainen, A., Hayward, C., Hernandez, D., Hicks, A. A., Holm, H., Hung, Y., Illig, T., Jones, M. R., Kaleebu, P., Kastelein, J. J., Khaw, K., Kim, E., Klopp, N., Komulainen, P., Kumari, M., Langenberg, C., Lehtimäki, T., Lin, S., Lindström, J., Loos, R. J., Mach, F., McArdle, W. L., Meisinger, C., Mitchell, B. D., Müller, G., Nagaraja, R., Narisu, N., Nieminen, T. V., Nsubuga, R. N., Olafsson, I., Ong, K. K., Palotie, A., Papamarkou, T., Pomilla, C., Pouta, A., Rader, D. J., Reilly, M. P., Ridker, P. M., Rivadeneira, F., Rudan, I., Ruokonen, A., Samani, N., Scharnagl, H., Seeley, J., Silander, K., Stancáková, A., Stirrups, K., Swift, A. J., Tiret, L., Uitterlinden, A. G., van Pelt, L. J., Vedantam, S., Wainwright, N., Wijmenga, C., Wild, S. H., Willemsen, G., Wilsgaard, T., Wilson, J. F., Young, E. H., Zhao, J. H., Adair, L. S., Arveiler, D., Assimes, T. L., Bandinelli, S., Bennett, F., Bochud, M., Boehm, B. O., Boomsma, D. I., Borecki, I. B., Bornstein, S. R., Bovet, P., Burnier, M., Campbell, H., Chakravarti, A., Chambers, J. C., Chen, Y. I., Collins, F. S., Cooper, R. S., Danesh, J., Dedoussis, G., de Faire, U., Feranil, A. B., Ferrières, J., Ferrucci, L., Freimer, N. B., Gieger, C., Groop, L. C., Gudnason, V., Gyllensten, U., Hamsten, A., Harris, T. B., Hingorani, A., Hirschhorn, J. N., Hofman, A., Hovingh, G. K., Hsiung, C. A., Humphries, S. E., Hunt, S. C., Hveem, K., Iribarren, C., Järvelin, M., Jula, A., Kähönen, M., Kaprio, J., Kesäniemi, A., Kivimaki, M., Kooner, J. S., Koudstaal, P. J., Krauss, R. M., Kuh, D., Kuusisto, J., Kyvik, K. O., Laakso, M., Lakka, T. A., Lind, L., Lindgren, C. M., Martin, N. G., März, W., McCarthy, M. I., McKenzie, C. A., Meneton, P., Metspalu, A., Moilanen, L., Morris, A. D., Munroe, P. B., Njølstad, I., Pedersen, N. L., Power, C., Pramstaller, P. P., Price, J. F., Psaty, B. M., Quertermous, T., Rauramaa, R., Saleheen, D., Salomaa, V., Sanghera, D. K., Saramies, J., Schwarz, P. E., Sheu, W. H., Shuldiner, A. R., Siegbahn, A., Spector, T. D., Stefansson, K., Strachan, D. P., Tayo, B. O., Tremoli, E., Tuomilehto, J., Uusitupa, M., van Duijn, C. M., Vollenweider, P., Wallentin, L., Wareham, N. J., Whitfield, J. B., Wolffenbuttel, B. H., Ordovas, J. M., Boerwinkle, E., Palmer, C. N., Thorsteinsdottir, U., Chasman, D. I., Rotter, J. I., Franks, P. W., Ripatti, S., Cupples, L. A., Sandhu, M. S., Rich, S. S., Boehnke, M., Deloukas, P., Kathiresan, S., Mohlke, K. L., Ingelsson, E., Abecasis, G. R. 2013; 45 (11): 1274-1283

    Abstract

    Levels of low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides and total cholesterol are heritable, modifiable risk factors for coronary artery disease. To identify new loci and refine known loci influencing these lipids, we examined 188,577 individuals using genome-wide and custom genotyping arrays. We identify and annotate 157 loci associated with lipid levels at P < 5 × 10(-8), including 62 loci not previously associated with lipid levels in humans. Using dense genotyping in individuals of European, East Asian, South Asian and African ancestry, we narrow association signals in 12 loci. We find that loci associated with blood lipid levels are often associated with cardiovascular and metabolic traits, including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio and body mass index. Our results demonstrate the value of using genetic data from individuals of diverse ancestry and provide insights into the biological mechanisms regulating blood lipids to guide future genetic, biological and therapeutic research.

    View details for DOI 10.1038/ng.2797

    View details for PubMedID 24097068

  • Imputation of coding variants in African Americans: better performance using data from the exome sequencing project BIOINFORMATICS Duan, Q., Liu, E. Y., Auer, P. L., Zhang, G., Lange, E. M., Jun, G., Bizon, C., Jiao, S., Buyske, S., Franceschini, N., Carlson, C. S., Hsu, L., Reiner, A. P., Peters, U., Haessler, J., Curtis, K., Wassel, C. L., Robinson, J. G., Martin, L. W., Haiman, C. A., Le Marchand, L., Matise, T. C., Hindorff, L. A., Crawford, D. C., Assimes, T. L., Kang, H. M., Heiss, G., Jackson, R. D., Kooperberg, C., Wilson, J. G., Abecasis, G. R., North, K. E., Nickerson, D. A., Lange, L. A., Li, Y. 2013; 29 (21): 2744-2749

    Abstract

    Although the 1000 Genomes haplotypes are the most commonly used reference panel for imputation, medical sequencing projects are generating large alternate sets of sequenced samples. Imputation in African Americans using 3384 haplotypes from the Exome Sequencing Project, compared with 2184 haplotypes from 1000 Genomes Project, increased effective sample size by 8.3-11.4% for coding variants with minor allele frequency <1%. No loss of imputation quality was observed using a panel built from phenotypic extremes. We recommend using haplotypes from Exome Sequencing Project alone or concatenation of the two panels over quality score-based post-imputation selection or IMPUTE2's two-panel combination.yunli@med.unc.edu.Supplementary data are available at Bioinformatics online.

    View details for DOI 10.1093/bioinformatics/btt477

    View details for Web of Science ID 000325997500011

    View details for PubMedID 23956302

    View details for PubMedCentralID PMC3799474

  • Common variants associated with plasma triglycerides and risk for coronary artery disease. Nature genetics Do, R., Willer, C. J., Schmidt, E. M., Sengupta, S., Gao, C., Peloso, G. M., Gustafsson, S., Kanoni, S., Ganna, A., Chen, J., Buchkovich, M. L., Mora, S., Beckmann, J. S., Bragg-Gresham, J. L., Chang, H., Demirkan, A., den Hertog, H. M., Donnelly, L. A., Ehret, G. B., Esko, T., Feitosa, M. F., Ferreira, T., Fischer, K., Fontanillas, P., Fraser, R. M., Freitag, D. F., Gurdasani, D., Heikkilä, K., Hyppönen, E., Isaacs, A., Jackson, A. U., Johansson, A., Johnson, T., Kaakinen, M., Kettunen, J., Kleber, M. E., Li, X., Luan, J., Lyytikäinen, L., Magnusson, P. K., Mangino, M., Mihailov, E., Montasser, M. E., Müller-Nurasyid, M., Nolte, I. M., O'Connell, J. R., Palmer, C. D., Perola, M., Petersen, A., Sanna, S., Saxena, R., Service, S. K., Shah, S., Shungin, D., Sidore, C., Song, C., Strawbridge, R. J., Surakka, I., Tanaka, T., Teslovich, T. M., Thorleifsson, G., van den Herik, E. G., Voight, B. F., Volcik, K. A., Waite, L. L., Wong, A., Wu, Y., Zhang, W., Absher, D., Asiki, G., Barroso, I., Been, L. F., Bolton, J. L., Bonnycastle, L. L., Brambilla, P., Burnett, M. S., Cesana, G., Dimitriou, M., Doney, A. S., Döring, A., Elliott, P., Epstein, S. E., Eyjolfsson, G. I., Gigante, B., Goodarzi, M. O., Grallert, H., Gravito, M. L., Groves, C. J., Hallmans, G., Hartikainen, A., Hayward, C., Hernandez, D., Hicks, A. A., Holm, H., Hung, Y., Illig, T., Jones, M. R., Kaleebu, P., Kastelein, J. J., Khaw, K., Kim, E., Klopp, N., Komulainen, P., Kumari, M., Langenberg, C., Lehtimäki, T., Lin, S., Lindström, J., Loos, R. J., Mach, F., McArdle, W. L., Meisinger, C., Mitchell, B. D., Müller, G., Nagaraja, R., Narisu, N., Nieminen, T. V., Nsubuga, R. N., Olafsson, I., Ong, K. K., Palotie, A., Papamarkou, T., Pomilla, C., Pouta, A., Rader, D. J., Reilly, M. P., Ridker, P. M., Rivadeneira, F., Rudan, I., Ruokonen, A., Samani, N., Scharnagl, H., Seeley, J., Silander, K., Stancáková, A., Stirrups, K., Swift, A. J., Tiret, L., Uitterlinden, A. G., van Pelt, L. J., Vedantam, S., Wainwright, N., Wijmenga, C., Wild, S. H., Willemsen, G., Wilsgaard, T., Wilson, J. F., Young, E. H., Zhao, J. H., Adair, L. S., Arveiler, D., Assimes, T. L., Bandinelli, S., Bennett, F., Bochud, M., Boehm, B. O., Boomsma, D. I., Borecki, I. B., Bornstein, S. R., Bovet, P., Burnier, M., Campbell, H., Chakravarti, A., Chambers, J. C., Chen, Y. I., Collins, F. S., Cooper, R. S., Danesh, J., Dedoussis, G., de Faire, U., Feranil, A. B., Ferrières, J., Ferrucci, L., Freimer, N. B., Gieger, C., Groop, L. C., Gudnason, V., Gyllensten, U., Hamsten, A., Harris, T. B., Hingorani, A., Hirschhorn, J. N., Hofman, A., Hovingh, G. K., Hsiung, C. A., Humphries, S. E., Hunt, S. C., Hveem, K., Iribarren, C., Järvelin, M., Jula, A., Kähönen, M., Kaprio, J., Kesäniemi, A., Kivimaki, M., Kooner, J. S., Koudstaal, P. J., Krauss, R. M., Kuh, D., Kuusisto, J., Kyvik, K. O., Laakso, M., Lakka, T. A., Lind, L., Lindgren, C. M., Martin, N. G., März, W., McCarthy, M. I., McKenzie, C. A., Meneton, P., Metspalu, A., Moilanen, L., Morris, A. D., Munroe, P. B., Njølstad, I., Pedersen, N. L., Power, C., Pramstaller, P. P., Price, J. F., Psaty, B. M., Quertermous, T., Rauramaa, R., Saleheen, D., Salomaa, V., Sanghera, D. K., Saramies, J., Schwarz, P. E., Sheu, W. H., Shuldiner, A. R., Siegbahn, A., Spector, T. D., Stefansson, K., Strachan, D. P., Tayo, B. O., Tremoli, E., Tuomilehto, J., Uusitupa, M., van Duijn, C. M., Vollenweider, P., Wallentin, L., Wareham, N. J., Whitfield, J. B., Wolffenbuttel, B. H., Altshuler, D., Ordovas, J. M., Boerwinkle, E., Palmer, C. N., Thorsteinsdottir, U., Chasman, D. I., Rotter, J. I., Franks, P. W., Ripatti, S., Cupples, L. A., Sandhu, M. S., Rich, S. S., Boehnke, M., Deloukas, P., Mohlke, K. L., Ingelsson, E., Abecasis, G. R., Daly, M. J., Neale, B. M., Kathiresan, S. 2013; 45 (11): 1345-1352

    Abstract

    Triglycerides are transported in plasma by specific triglyceride-rich lipoproteins; in epidemiological studies, increased triglyceride levels correlate with higher risk for coronary artery disease (CAD). However, it is unclear whether this association reflects causal processes. We used 185 common variants recently mapped for plasma lipids (P < 5 × 10(-8) for each) to examine the role of triglycerides in risk for CAD. First, we highlight loci associated with both low-density lipoprotein cholesterol (LDL-C) and triglyceride levels, and we show that the direction and magnitude of the associations with both traits are factors in determining CAD risk. Second, we consider loci with only a strong association with triglycerides and show that these loci are also associated with CAD. Finally, in a model accounting for effects on LDL-C and/or high-density lipoprotein cholesterol (HDL-C) levels, the strength of a polymorphism's effect on triglyceride levels is correlated with the magnitude of its effect on CAD risk. These results suggest that triglyceride-rich lipoproteins causally influence risk for CAD.

    View details for DOI 10.1038/ng.2795

    View details for PubMedID 24097064

  • Mendelian randomization studies do not support a causal role for reduced circulating adiponectin levels in insulin resistance and type 2 diabetes. Diabetes Yaghootkar, H., Lamina, C., Scott, R. A., Dastani, Z., Hivert, M., Warren, L. L., Stancáková, A., Buxbaum, S. G., Lyytikäinen, L., Henneman, P., Wu, Y., Cheung, C. Y., Pankow, J. S., Jackson, A. U., Gustafsson, S., Zhao, J. H., Ballantyne, C. M., Xie, W., Bergman, R. N., Boehnke, M., El Bouazzaoui, F., Collins, F. S., Dunn, S. H., Dupuis, J., Forouhi, N. G., Gillson, C., Hattersley, A. T., Hong, J., Kähönen, M., Kuusisto, J., Kedenko, L., Kronenberg, F., Doria, A., Assimes, T. L., Ferrannini, E., Hansen, T., Hao, K., Häring, H., Knowles, J. W., Lindgren, C. M., Nolan, J. J., Paananen, J., Pedersen, O., Quertermous, T., Smith, U., Lehtimäki, T., Liu, C., Loos, R. J., McCarthy, M. I., Morris, A. D., Vasan, R. S., Spector, T. D., Teslovich, T. M., Tuomilehto, J., Van Dijk, K. W., Viikari, J. S., Zhu, N., Langenberg, C., Ingelsson, E., Semple, R. K., Sinaiko, A. R., Palmer, C. N., Walker, M., Lam, K. S., Paulweber, B., Mohlke, K. L., Van Duijn, C., Raitakari, O. T., Bidulescu, A., Wareham, N. J., Laakso, M., Waterworth, D. M., Lawlor, D. A., Meigs, J. B., Richards, J. B., Frayling, T. M. 2013; 62 (10): 3589-3598

    Abstract

    Adiponectin is strongly inversely associated with insulin resistance and type 2 diabetes, but its causal role remains controversial. We used a Mendelian randomization approach to test the hypothesis that adiponectin causally influences insulin resistance and type 2 diabetes. We used genetic variants at the ADIPOQ gene as instruments to calculate a regression slope between adiponectin levels and metabolic traits (up to 31,000 individuals) and a combination of instrumental variables and summary statistics-based genetic risk scores to test the associations with gold-standard measures of insulin sensitivity (2,969 individuals) and type 2 diabetes (15,960 case subjects and 64,731 control subjects). In conventional regression analyses, a 1-SD decrease in adiponectin levels was correlated with a 0.31-SD (95% CI 0.26-0.35) increase in fasting insulin, a 0.34-SD (0.30-0.38) decrease in insulin sensitivity, and a type 2 diabetes odds ratio (OR) of 1.75 (1.47-2.13). The instrumental variable analysis revealed no evidence of a causal association between genetically lower circulating adiponectin and higher fasting insulin (0.02 SD; 95% CI -0.07 to 0.11; N = 29,771), nominal evidence of a causal relationship with lower insulin sensitivity (-0.20 SD; 95% CI -0.38 to -0.02; N = 1,860), and no evidence of a relationship with type 2 diabetes (OR 0.94; 95% CI 0.75-1.19; N = 2,777 case subjects and 13,011 control subjects). Using the ADIPOQ summary statistics genetic risk scores, we found no evidence of an association between adiponectin-lowering alleles and insulin sensitivity (effect per weighted adiponectin-lowering allele: -0.03 SD; 95% CI -0.07 to 0.01; N = 2,969) or type 2 diabetes (OR per weighted adiponectin-lowering allele: 0.99; 95% CI 0.95-1.04; 15,960 case subjects vs. 64,731 control subjects). These results do not provide any consistent evidence that interventions aimed at increasing adiponectin levels will improve insulin sensitivity or risk of type 2 diabetes.

    View details for DOI 10.2337/db13-0128

    View details for PubMedID 23835345

    View details for PubMedCentralID PMC3781444

  • Disease-Related Growth Factor and Embryonic Signaling Pathways Modulate an Enhancer of TCF21 Expression at the 6q23.2 Coronary Heart Disease Locus PLOS GENETICS Miller, C. L., Anderson, D. R., Kundu, R. K., Raiesdana, A., Nuernberg, S. T., Diaz, R., Cheng, K., Leeper, N. J., Chen, C., Chang, I., Schadt, E. E., Hsiung, C. A., Assimes, T. L., Quertermous, T. 2013; 9 (7)

    View details for DOI 10.1371/journal.pgen.1003652

    View details for Web of Science ID 000322321100049

    View details for PubMedID 23874238

  • The shared allelic architecture of adiponectin levels and coronary artery disease. Atherosclerosis Dastani, Z., Johnson, T., Kronenberg, F., Nelson, C. P., Assimes, T. L., März, W., Richards, J. B. 2013; 229 (1): 145-148

    Abstract

    OBJECTIVE: A large body of epidemiologic data strongly suggests an association between excess adiposity and coronary artery disease (CAD). Low adiponectin levels, a hormone secreted only from adipocytes, have been associated with an increased risk of CAD in observational studies. However, these associations cannot clarify whether this relationship is causal or due to a shared set of causal factors or even confounding. Genome-wide association studies have identified common variants that influence adiponectin levels, providing valuable tools to examine the genetic relationship between adiponectin and CAD. METHODS: Using 145 genome wide significant SNPs for adiponectin from the ADIPOGen consortium (n = 49,891), we tested whether adiponectin-decreasing alleles influenced risk of CAD in the CARDIoGRAM consortium (n = 85,274). RESULTS: In single-SNP analysis, 5 variants among 145 SNPs were associated with increased risk of CAD after correcting for multiple testing (P < 4.4 × 10(-4)). Using a multi-SNP genotypic risk score to test whether adiponectin levels and CAD have a shared genetic etiology, we found that adiponectin-decreasing alleles increased risk of CAD (P = 5.4 × 10(-7)). CONCLUSION: These findings demonstrate that adiponectin levels and CAD have a shared allelic architecture and provide rationale to undertake a Mendelian randomization studies to understand if this relationship is causal.

    View details for DOI 10.1016/j.atherosclerosis.2013.03.034

    View details for PubMedID 23664276

  • Identification of heart rate-associated loci and their effects on cardiac conduction and rhythm disorders. Nature genetics Den Hoed, M., Eijgelsheim, M., Esko, T., Brundel, B. J., Peal, D. S., Evans, D. M., Nolte, I. M., Segrè, A. V., Holm, H., Handsaker, R. E., Westra, H., Johnson, T., Isaacs, A., Yang, J., Lundby, A., Zhao, J. H., Kim, Y. J., Go, M. J., Almgren, P., Bochud, M., Boucher, G., Cornelis, M. C., Gudbjartsson, D., Hadley, D., van der Harst, P., Hayward, C., den Heijer, M., Igl, W., Jackson, A. U., Kutalik, Z., Luan, J., Kemp, J. P., Kristiansson, K., Ladenvall, C., Lorentzon, M., Montasser, M. E., Njajou, O. T., O'Reilly, P. F., Padmanabhan, S., St Pourcain, B., Rankinen, T., Salo, P., Tanaka, T., Timpson, N. J., Vitart, V., Waite, L., Wheeler, W., Zhang, W., Draisma, H. H., Feitosa, M. F., Kerr, K. F., Lind, P. A., Mihailov, E., Onland-Moret, N. C., Song, C., Weedon, M. N., Xie, W., Yengo, L., Absher, D., Albert, C. M., Alonso, A., Arking, D. E., de Bakker, P. I., Balkau, B., Barlassina, C., Benaglio, P., Bis, J. C., Bouatia-Naji, N., Brage, S., Chanock, S. J., Chines, P. S., Chung, M., Darbar, D., Dina, C., Dörr, M., Elliott, P., Felix, S. B., Fischer, K., Fuchsberger, C., de Geus, E. J., Goyette, P., Gudnason, V., Harris, T. B., Hartikainen, A., Havulinna, A. S., Heckbert, S. R., Hicks, A. A., Hofman, A., Holewijn, S., Hoogstra-Berends, F., Hottenga, J., Jensen, M. K., Johansson, A., Junttila, J., Kääb, S., Kanon, B., Ketkar, S., Khaw, K., Knowles, J. W., Kooner, A. S., Kors, J. A., Kumari, M., Milani, L., Laiho, P., Lakatta, E. G., Langenberg, C., Leusink, M., Liu, Y., Luben, R. N., Lunetta, K. L., Lynch, S. N., Markus, M. R., Marques-Vidal, P., Mateo Leach, I., McArdle, W. L., McCarroll, S. A., Medland, S. E., Miller, K. A., Montgomery, G. W., Morrison, A. C., Müller-Nurasyid, M., Navarro, P., Nelis, M., O'Connell, J. R., O'Donnell, C. J., Ong, K. K., Newman, A. B., Peters, A., Polasek, O., Pouta, A., Pramstaller, P. P., Psaty, B. M., Rao, D. C., Ring, S. M., Rossin, E. J., Rudan, D., Sanna, S., Scott, R. A., Sehmi, J. S., Sharp, S., Shin, J. T., Singleton, A. B., Smith, A. V., Soranzo, N., Spector, T. D., Stewart, C., Stringham, H. M., Tarasov, K. V., Uitterlinden, A. G., Vandenput, L., Hwang, S., Whitfield, J. B., Wijmenga, C., Wild, S. H., Willemsen, G., Wilson, J. F., Witteman, J. C., Wong, A., Wong, Q., Jamshidi, Y., Zitting, P., Boer, J. M., Boomsma, D. I., Borecki, I. B., van Duijn, C. M., Ekelund, U., Forouhi, N. G., Froguel, P., Hingorani, A., Ingelsson, E., Kivimaki, M., Kronmal, R. A., Kuh, D., Lind, L., Martin, N. G., Oostra, B. A., Pedersen, N. L., Quertermous, T., Rotter, J. I., van der Schouw, Y. T., Verschuren, W. M., Walker, M., Albanes, D., Arnar, D. O., Assimes, T. L., Bandinelli, S., Boehnke, M., de Boer, R. A., Bouchard, C., Caulfield, W. L., Chambers, J. C., Curhan, G., Cusi, D., Eriksson, J., Ferrucci, L., van Gilst, W. H., Glorioso, N., de Graaf, J., Groop, L., Gyllensten, U., Hsueh, W., Hu, F. B., Huikuri, H. V., Hunter, D. J., Iribarren, C., Isomaa, B., Jarvelin, M., Jula, A., Kähönen, M., Kiemeney, L. A., van der Klauw, M. M., Kooner, J. S., Kraft, P., Iacoviello, L., Lehtimäki, T., Lokki, M. L., Mitchell, B. D., Navis, G., Nieminen, M. S., Ohlsson, C., Poulter, N. R., Qi, L., Raitakari, O. T., Rimm, E. B., Rioux, J. D., Rizzi, F., Rudan, I., Salomaa, V., Sever, P. S., Shields, D. C., Shuldiner, A. R., Sinisalo, J., Stanton, A. V., Stolk, R. P., Strachan, D. P., Tardif, J., Thorsteinsdottir, U., Tuomilehto, J., van Veldhuisen, D. J., Virtamo, J., Viikari, J., Vollenweider, P., Waeber, G., Widen, E., Cho, Y. S., Olsen, J. V., Visscher, P. M., Willer, C., Franke, L., Erdmann, J., Thompson, J. R., Pfeufer, A., Sotoodehnia, N., Newton-Cheh, C., Ellinor, P. T., Stricker, B. H., Metspalu, A., Perola, M., Beckmann, J. S., Smith, G. D., Stefansson, K., Wareham, N. J., Munroe, P. B., Sibon, O. C., Milan, D. J., Snieder, H., Samani, N. J., Loos, R. J. 2013; 45 (6): 621-631

    Abstract

    Elevated resting heart rate is associated with greater risk of cardiovascular disease and mortality. In a 2-stage meta-analysis of genome-wide association studies in up to 181,171 individuals, we identified 14 new loci associated with heart rate and confirmed associations with all 7 previously established loci. Experimental downregulation of gene expression in Drosophila melanogaster and Danio rerio identified 20 genes at 11 loci that are relevant for heart rate regulation and highlight a role for genes involved in signal transmission, embryonic cardiac development and the pathophysiology of dilated cardiomyopathy, congenital heart failure and/or sudden cardiac death. In addition, genetic susceptibility to increased heart rate is associated with altered cardiac conduction and reduced risk of sick sinus syndrome, and both heart rate-increasing and heart rate-decreasing variants associate with risk of atrial fibrillation. Our findings provide fresh insights into the mechanisms regulating heart rate and identify new therapeutic targets.

    View details for DOI 10.1038/ng.2610

    View details for PubMedID 23583979

  • Sex-stratified genome-wide association studies including 270,000 individuals show sexual dimorphism in genetic loci for anthropometric traits. PLoS genetics Randall, J. C., Winkler, T. W., Kutalik, Z., Berndt, S. I., Jackson, A. U., Monda, K. L., Kilpeläinen, T. O., Esko, T., Mägi, R., Li, S., Workalemahu, T., Feitosa, M. F., Croteau-Chonka, D. C., Day, F. R., Fall, T., Ferreira, T., Gustafsson, S., Locke, A. E., Mathieson, I., Scherag, A., Vedantam, S., Wood, A. R., Liang, L., Steinthorsdottir, V., Thorleifsson, G., Dermitzakis, E. T., Dimas, A. S., Karpe, F., Min, J. L., Nicholson, G., Clegg, D. J., Person, T., Krohn, J. P., Bauer, S., Buechler, C., Eisinger, K., Bonnefond, A., Froguel, P., Hottenga, J., Prokopenko, I., Waite, L. L., Harris, T. B., Smith, A. V., Shuldiner, A. R., McArdle, W. L., Caulfield, M. J., Munroe, P. B., Grönberg, H., Chen, Y. I., Li, G., Beckmann, J. S., Johnson, T., Thorsteinsdottir, U., Teder-Laving, M., Khaw, K., Wareham, N. J., Zhao, J. H., Amin, N., Oostra, B. A., Kraja, A. T., Province, M. A., Cupples, L. A., Heard-Costa, N. L., Kaprio, J., Ripatti, S., Surakka, I., Collins, F. S., Saramies, J., Tuomilehto, J., Jula, A., Salomaa, V., Erdmann, J., Hengstenberg, C., Loley, C., Schunkert, H., Lamina, C., Wichmann, H. E., Albrecht, E., Gieger, C., Hicks, A. A., Johansson, A., Pramstaller, P. P., Kathiresan, S., Speliotes, E. K., Penninx, B., Hartikainen, A., Jarvelin, M., Gyllensten, U., Boomsma, D. I., Campbell, H., Wilson, J. F., Chanock, S. J., Farrall, M., Goel, A., Medina-Gomez, C., Rivadeneira, F., Estrada, K., Uitterlinden, A. G., Hofman, A., Zillikens, M. C., den Heijer, M., Kiemeney, L. A., Maschio, A., Hall, P., Tyrer, J., Teumer, A., Völzke, H., Kovacs, P., Tönjes, A., Mangino, M., Spector, T. D., Hayward, C., Rudan, I., Hall, A. S., Samani, N. J., Attwood, A. P., Sambrook, J. G., Hung, J., Palmer, L. J., Lokki, M., Sinisalo, J., Boucher, G., Huikuri, H., Lorentzon, M., Ohlsson, C., Eklund, N., Eriksson, J. G., Barlassina, C., Rivolta, C., Nolte, I. M., Snieder, H., van der Klauw, M. M., van Vliet-Ostaptchouk, J. V., Gejman, P. V., Shi, J., Jacobs, K. B., Wang, Z., Bakker, S. J., Mateo Leach, I., Navis, G., van der Harst, P., Martin, N. G., Medland, S. E., Montgomery, G. W., Yang, J., Chasman, D. I., Ridker, P. M., Rose, L. M., Lehtimäki, T., Raitakari, O., Absher, D., Iribarren, C., Basart, H., Hovingh, K. G., Hyppönen, E., Power, C., Anderson, D., Beilby, J. P., Hui, J., Jolley, J., Sager, H., Bornstein, S. R., Schwarz, P. E., Kristiansson, K., Perola, M., Lindström, J., Swift, A. J., Uusitupa, M., Atalay, M., Lakka, T. A., Rauramaa, R., Bolton, J. L., Fowkes, G., Fraser, R. M., Price, J. F., Fischer, K., Krjutå Kov, K., Metspalu, A., Mihailov, E., Langenberg, C., Luan, J., Ong, K. K., Chines, P. S., Keinanen-Kiukaanniemi, S. M., Saaristo, T. E., Edkins, S., Franks, P. W., Hallmans, G., Shungin, D., Morris, A. D., Palmer, C. N., Erbel, R., Moebus, S., Nöthen, M. M., Pechlivanis, S., Hveem, K., Narisu, N., Hamsten, A., Humphries, S. E., Strawbridge, R. J., Tremoli, E., Grallert, H., Thorand, B., Illig, T., Koenig, W., Müller-Nurasyid, M., Peters, A., Boehm, B. O., Kleber, M. E., März, W., Winkelmann, B. R., Kuusisto, J., Laakso, M., Arveiler, D., Cesana, G., Kuulasmaa, K., Virtamo, J., Yarnell, J. W., Kuh, D., Wong, A., Lind, L., de Faire, U., Gigante, B., Magnusson, P. K., Pedersen, N. L., Dedoussis, G., Dimitriou, M., Kolovou, G., Kanoni, S., Stirrups, K., Bonnycastle, L. L., Njølstad, I., Wilsgaard, T., Ganna, A., Rehnberg, E., Hingorani, A., Kivimaki, M., Kumari, M., Assimes, T. L., Barroso, I., Boehnke, M., Borecki, I. B., Deloukas, P., Fox, C. S., Frayling, T., Groop, L. C., Haritunians, T., Hunter, D., Ingelsson, E., Kaplan, R., Mohlke, K. L., O'Connell, J. R., Schlessinger, D., Strachan, D. P., Stefansson, K., van Duijn, C. M., Abecasis, G. R., McCarthy, M. I., Hirschhorn, J. N., Qi, L., Loos, R. J., Lindgren, C. M., North, K. E., Heid, I. M. 2013; 9 (6)

    Abstract

    Given the anthropometric differences between men and women and previous evidence of sex-difference in genetic effects, we conducted a genome-wide search for sexually dimorphic associations with height, weight, body mass index, waist circumference, hip circumference, and waist-to-hip-ratio (133,723 individuals) and took forward 348 SNPs into follow-up (additional 137,052 individuals) in a total of 94 studies. Seven loci displayed significant sex-difference (FDR<5%), including four previously established (near GRB14/COBLL1, LYPLAL1/SLC30A10, VEGFA, ADAMTS9) and three novel anthropometric trait loci (near MAP3K1, HSD17B4, PPARG), all of which were genome-wide significant in women (P<5×10(-8)), but not in men. Sex-differences were apparent only for waist phenotypes, not for height, weight, BMI, or hip circumference. Moreover, we found no evidence for genetic effects with opposite directions in men versus women. The PPARG locus is of specific interest due to its role in diabetes genetics and therapy. Our results demonstrate the value of sex-specific GWAS to unravel the sexually dimorphic genetic underpinning of complex traits.

    View details for DOI 10.1371/journal.pgen.1003500

    View details for PubMedID 23754948

    View details for PubMedCentralID PMC3674993

  • A systems biology framework identifies molecular underpinnings of coronary heart disease. Arteriosclerosis, thrombosis, and vascular biology Huan, T., Zhang, B., Wang, Z., Joehanes, R., Zhu, J., Johnson, A. D., Ying, S., Munson, P. J., Raghavachari, N., Wang, R., Liu, P., Courchesne, P., Hwang, S., Assimes, T. L., McPherson, R., Samani, N. J., Schunkert, H., Meng, Q., Suver, C., O'Donnell, C. J., Derry, J., Yang, X., Levy, D. 2013; 33 (6): 1427-1434

    Abstract

    Genetic approaches have identified numerous loci associated with coronary heart disease (CHD). The molecular mechanisms underlying CHD gene-disease associations, however, remain unclear. We hypothesized that genetic variants with both strong and subtle effects drive gene subnetworks that in turn affect CHD. APPROACH AND RESULTS: We surveyed CHD-associated molecular interactions by constructing coexpression networks using whole blood gene expression profiles from 188 CHD cases and 188 age- and sex-matched controls. Twenty-four coexpression modules were identified, including 1 case-specific and 1 control-specific differential module (DM). The DMs were enriched for genes involved in B-cell activation, immune response, and ion transport. By integrating the DMs with gene expression-associated single-nucleotide polymorphisms and with results of genome-wide association studies of CHD and its risk factors, the control-specific DM was implicated as CHD causal based on its significant enrichment for both CHD and lipid expression-associated single-nucleotide polymorphisms. This causal DM was further integrated with tissue-specific Bayesian networks and protein-protein interaction networks to identify regulatory key driver genes. Multitissue key drivers (SPIB and TNFRSF13C) and tissue-specific key drivers (eg, EBF1) were identified.Our network-driven integrative analysis not only identified CHD-related genes, but also defined network structure that sheds light on the molecular interactions of genes associated with CHD risk.

    View details for DOI 10.1161/ATVBAHA.112.300112

    View details for PubMedID 23539213

  • Genetic variants associated with glycine metabolism and their role in insulin sensitivity and type 2 diabetes. Diabetes Xie, W., Wood, A. R., Lyssenko, V., Weedon, M. N., Knowles, J. W., Alkayyali, S., Assimes, T. L., Quertermous, T., Abbasi, F., Paananen, J., Häring, H., Hansen, T., Pedersen, O., Smith, U., Laakso, M., Dekker, J. M., Nolan, J. J., Groop, L., Ferrannini, E., Adam, K., Gall, W. E., Frayling, T. M., Walker, M. 2013; 62 (6): 2141-2150

    Abstract

    Circulating metabolites associated with insulin sensitivity may represent useful biomarkers, but their causal role in insulin sensitivity and diabetes is less certain. We previously identified novel metabolites correlated with insulin sensitivity measured by the hyperinsulinemic-euglycemic clamp. The top-ranking metabolites were in the glutathione and glycine biosynthesis pathways. We aimed to identify common genetic variants associated with metabolites in these pathways and test their role in insulin sensitivity and type 2 diabetes. With 1,004 nondiabetic individuals from the RISC study, we performed a genome-wide association study (GWAS) of 14 insulin sensitivity-related metabolites and one metabolite ratio. We replicated our results in the Botnia study (n = 342). We assessed the association of these variants with diabetes-related traits in GWAS meta-analyses (GENESIS [including RISC, EUGENE2, and Stanford], MAGIC, and DIAGRAM). We identified four associations with three metabolites-glycine (rs715 at CPS1), serine (rs478093 at PHGDH), and betaine (rs499368 at SLC6A12; rs17823642 at BHMT)-and one association signal with glycine-to-serine ratio (rs1107366 at ALDH1L1). There was no robust evidence for association between these variants and insulin resistance or diabetes. Genetic variants associated with genes in the glycine biosynthesis pathways do not provide consistent evidence for a role of glycine in diabetes-related traits.

    View details for DOI 10.2337/db12-0876

    View details for PubMedID 23378610

  • Genetic predisposition to higher blood pressure increases coronary artery disease risk. Hypertension Lieb, W., Jansen, H., Loley, C., Pencina, M. J., Nelson, C. P., Newton-Cheh, C., Boerwinkle, E., Hall, A. S., Hengstenberg, C., Laaksonen, R., Thorsteinsdottir, U., Ziegler, A., Peters, A., Thompson, J. R., Vasan, R. S., Assimes, T. L., Deloukas, P., Erdmann, J., Holm, H., Kathiresan, S., König, I. R., McPherson, R., Reilly, M. P., Roberts, R., Samani, N. J., Schunkert, H., Stewart, A. F. 2013; 61 (5): 995-1001

    Abstract

    Hypertension is a risk factor for coronary artery disease. Recent genome-wide association studies have identified 30 genetic variants associated with higher blood pressure at genome-wide significance (P<5 × 10(-8)). If elevated blood pressure is a causative factor for coronary artery disease, these variants should also increase coronary artery disease risk. Analyzing genome-wide association data from 22 233 coronary artery disease cases and 64 762 controls, we observed in the Coronary ARtery DIsease Genome-Wide Replication And Meta-Analysis (CARDIoGRAM) consortium that 88% of these blood pressure-associated polymorphisms were likewise positively associated with coronary artery disease, that is, they had an odds ratio >1 for coronary artery disease, a proportion much higher than expected by chance (P=4 × 10(-5)). The average relative coronary artery disease risk increase per each of the multiple blood pressure-raising alleles observed in the consortium was 3.0% for systolic blood pressure-associated polymorphisms (95% confidence interval, 1.8%-4.3%) and 2.9% for diastolic blood pressure-associated polymorphisms (95% confidence interval, 1.7%-4.1%). In substudies, individuals carrying most systolic blood pressure- and diastolic blood pressure-related risk alleles (top quintile of a genetic risk score distribution) had 70% (95% confidence interval, 50%-94%) and 59% (95% confidence interval, 40%-81%) higher odds of having coronary artery disease, respectively, as compared with individuals in the bottom quintile. In conclusion, most blood pressure-associated polymorphisms also confer an increased risk for coronary artery disease. These findings are consistent with a causal relationship of increasing blood pressure to coronary artery disease. Genetic variants primarily affecting blood pressure contribute to the genetic basis of coronary artery disease.

    View details for DOI 10.1161/HYPERTENSIONAHA.111.00275

    View details for PubMedID 23478099

  • Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture. Nature genetics Berndt, S. I., Gustafsson, S., Mägi, R., Ganna, A., Wheeler, E., Feitosa, M. F., Justice, A. E., Monda, K. L., Croteau-Chonka, D. C., Day, F. R., Esko, T., Fall, T., Ferreira, T., Gentilini, D., Jackson, A. U., Luan, J., Randall, J. C., Vedantam, S., Willer, C. J., Winkler, T. W., Wood, A. R., Workalemahu, T., Hu, Y., Lee, S. H., Liang, L., Lin, D., Min, J. L., Neale, B. M., Thorleifsson, G., Yang, J., Albrecht, E., Amin, N., Bragg-Gresham, J. L., Cadby, G., den Heijer, M., Eklund, N., Fischer, K., Goel, A., Hottenga, J., Huffman, J. E., Jarick, I., Johansson, Å., Johnson, T., Kanoni, S., Kleber, M. E., König, I. R., Kristiansson, K., Kutalik, Z., Lamina, C., Lecoeur, C., Li, G., Mangino, M., McArdle, W. L., Medina-Gomez, C., Müller-Nurasyid, M., Ngwa, J. S., Nolte, I. M., Paternoster, L., Pechlivanis, S., Perola, M., Peters, M. J., Preuss, M., Rose, L. M., Shi, J., Shungin, D., Smith, A. V., Strawbridge, R. J., Surakka, I., Teumer, A., Trip, M. D., Tyrer, J., van Vliet-Ostaptchouk, J. V., Vandenput, L., Waite, L. L., Zhao, J. H., Absher, D., Asselbergs, F. W., Atalay, M., Attwood, A. P., Balmforth, A. J., Basart, H., Beilby, J., Bonnycastle, L. L., Brambilla, P., Bruinenberg, M., Campbell, H., Chasman, D. I., Chines, P. S., Collins, F. S., Connell, J. M., Cookson, W. O., de Faire, U., de Vegt, F., Dei, M., Dimitriou, M., Edkins, S., Estrada, K., Evans, D. M., Farrall, M., Ferrario, M. M., Ferrières, J., Franke, L., Frau, F., Gejman, P. V., Grallert, H., Grönberg, H., Gudnason, V., Hall, A. S., Hall, P., Hartikainen, A., Hayward, C., Heard-Costa, N. L., Heath, A. C., Hebebrand, J., Homuth, G., Hu, F. B., Hunt, S. E., Hyppönen, E., Iribarren, C., Jacobs, K. B., Jansson, J., Jula, A., Kähönen, M., Kathiresan, S., Kee, F., Khaw, K., Kivimäki, M., Koenig, W., Kraja, A. T., Kumari, M., Kuulasmaa, K., Kuusisto, J., Laitinen, J. H., Lakka, T. A., Langenberg, C., Launer, L. J., Lind, L., Lindström, J., Liu, J., Liuzzi, A., Lokki, M., Lorentzon, M., Madden, P. A., Magnusson, P. K., Manunta, P., Marek, D., März, W., Mateo Leach, I., McKnight, B., Medland, S. E., Mihailov, E., Milani, L., Montgomery, G. W., Mooser, V., Mühleisen, T. W., Munroe, P. B., Musk, A. W., Narisu, N., Navis, G., Nicholson, G., Nohr, E. A., Ong, K. K., Oostra, B. A., Palmer, C. N., Palotie, A., Peden, J. F., Pedersen, N., Peters, A., Polasek, O., Pouta, A., Pramstaller, P. P., Prokopenko, I., Pütter, C., Radhakrishnan, A., Raitakari, O., Rendon, A., Rivadeneira, F., Rudan, I., Saaristo, T. E., Sambrook, J. G., Sanders, A. R., Sanna, S., Saramies, J., Schipf, S., Schreiber, S., Schunkert, H., Shin, S., Signorini, S., Sinisalo, J., Skrobek, B., Soranzo, N., Stancáková, A., Stark, K., Stephens, J. C., Stirrups, K., Stolk, R. P., Stumvoll, M., Swift, A. J., Theodoraki, E. V., Thorand, B., Tregouet, D., Tremoli, E., van der Klauw, M. M., van Meurs, J. B., Vermeulen, S. H., Viikari, J., Virtamo, J., Vitart, V., Waeber, G., Wang, Z., Widén, E., Wild, S. H., Willemsen, G., Winkelmann, B. R., Witteman, J. C., Wolffenbuttel, B. H., Wong, A., Wright, A. F., Zillikens, M. C., Amouyel, P., Boehm, B. O., Boerwinkle, E., Boomsma, D. I., Caulfield, M. J., Chanock, S. J., Cupples, L. A., Cusi, D., Dedoussis, G. V., Erdmann, J., Eriksson, J. G., Franks, P. W., Froguel, P., Gieger, C., Gyllensten, U., Hamsten, A., Harris, T. B., Hengstenberg, C., Hicks, A. A., Hingorani, A., Hinney, A., Hofman, A., Hovingh, K. G., Hveem, K., Illig, T., Jarvelin, M., Jöckel, K., Keinanen-Kiukaanniemi, S. M., Kiemeney, L. A., Kuh, D., Laakso, M., Lehtimäki, T., Levinson, D. F., Martin, N. G., Metspalu, A., Morris, A. D., Nieminen, M. S., Njølstad, I., Ohlsson, C., Oldehinkel, A. J., Ouwehand, W. H., Palmer, L. J., Penninx, B., Power, C., Province, M. A., Psaty, B. M., Qi, L., Rauramaa, R., Ridker, P. M., Ripatti, S., Salomaa, V., Samani, N. J., Snieder, H., Sørensen, T. I., Spector, T. D., Stefansson, K., Tönjes, A., Tuomilehto, J., Uitterlinden, A. G., Uusitupa, M., van der Harst, P., Vollenweider, P., Wallaschofski, H., Wareham, N. J., Watkins, H., Wichmann, H., Wilson, J. F., Abecasis, G. R., Assimes, T. L., Barroso, I., Boehnke, M., Borecki, I. B., Deloukas, P., Fox, C. S., Frayling, T., Groop, L. C., Haritunian, T., Heid, I. M., Hunter, D., Kaplan, R. C., Karpe, F., Moffatt, M. F., Mohlke, K. L., O'Connell, J. R., Pawitan, Y., Schadt, E. E., Schlessinger, D., Steinthorsdottir, V., Strachan, D. P., Thorsteinsdottir, U., van Duijn, C. M., Visscher, P. M., Di Blasio, A. M., Hirschhorn, J. N., Lindgren, C. M., Morris, A. P., Meyre, D., Scherag, A., McCarthy, M. I., Speliotes, E. K., North, K. E., Loos, R. J., Ingelsson, E. 2013; 45 (5): 501-512

    Abstract

    Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups.

    View details for DOI 10.1038/ng.2606

    View details for PubMedID 23563607

    View details for PubMedCentralID PMC3973018

  • Measurement of insulin-mediated glucose uptake: direct comparison of the modified insulin suppression test and the euglycemic, hyperinsulinemic clamp. Metabolism Knowles, J. W., Assimes, T. L., Tsao, P. S., Natali, A., Mari, A., Quertermous, T., Reaven, G. M., Abbasi, F. 2013; 62 (4): 548-553

    Abstract

    Two direct measurements of peripheral insulin sensitivity are the M value derived from the euglycemic, hyperinsulinemic clamp (EC) and the steady-state plasma glucose (SSPG) concentration derived from the insulin suppression test (IST). Prior work suggests that these measures are highly correlated, but the agreement between them is unknown. To determine the agreement between SSPG and M and to develop transformation equations to convert SSPG to M and vice versa, we directly compared these two measurements in the same individuals.A total of 15 nondiabetic subjects (9 women and 6 men) underwent both an EC and a modified version of the IST within a median interval of 5days. We performed standard correlation metrics of the two measures and developed transformation regression equations for the two measures.The mean±SD age of the subjects was 57±7years and body mass index, 27.7±3.9kg/m(2). The median (interquartile range) SSPG concentration was 6.7 (5.1, 9.8) mmol/L and M value, 49.6 (28.9, 64.2) ?mol/min/kg-LBM. There was a highly significant correlation between SSPG and M (r=-0.87, P <0.001). The relationship was best fit by regression models with exponential/logarithmic functions (R(2)=0.85). Bland-Altman plots demonstrated an excellent agreement between these measures of insulin action.The SSPG and M are highly related measures of insulin sensitivity and the results provide the means to directly compare the two measurements.

    View details for DOI 10.1016/j.metabol.2012.10.002

    View details for PubMedID 23151437

  • Association Between the Chromosome 9p21 Locus and Angiographic Coronary Artery Disease Burden A Collaborative Meta-Analysis JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY Chan, K., Patel, R. S., Newcombe, P., Nelson, C. P., Qasim, A., Epstein, S. E., Burnett, S., Vaccarino, V. L., Zafari, A. M., Shah, S. H., Anderson, J. L., Carlquist, J. F., Hartiala, J., Allayee, H., Hinohara, K., Lee, B., Erl, A., Ellis, K. L., Goel, A., Schaefer, A. S., El Mokhtari, N. E., Goldstein, B. A., Hlatky, M. A., Go, A. S., Shen, G., Gong, Y., Pepine, C., Laxton, R. C., Whittaker, J. C., Tang, W. H., Johnson, J. A., Wang, Q. K., Assimes, T. L., Noethlings, U., Farrall, M., Watkins, H., Richards, A. M., Cameron, V. A., Muendlein, A., Drexel, H., Koch, W., Park, J. E., Kimura, A., Shen, W., Simpson, I. A., Hazen, S. L., Horne, B. D., Hauser, E. R., Quyyumi, A. A., Reilly, M. P., Samani, N. J., Ye, S. 2013; 61 (9): 957-970

    Abstract

    This study sought to ascertain the relationship of 9p21 locus with: 1) angiographic coronary artery disease (CAD) burden; and 2) myocardial infarction (MI) in individuals with underlying CAD.Chromosome 9p21 variants have been robustly associated with coronary heart disease, but questions remain on the mechanism of risk, specifically whether the locus contributes to coronary atheroma burden or plaque instability.We established a collaboration of 21 studies consisting of 33,673 subjects with information on both CAD (clinical or angiographic) and MI status along with 9p21 genotype. Tabular data are provided for each cohort on the presence and burden of angiographic CAD, MI cases with underlying CAD, and the diabetic status of all subjects.We first confirmed an association between 9p21 and CAD with angiographically defined cases and control subjects (pooled odds ratio [OR]: 1.31, 95% confidence interval [CI]: 1.20 to 1.43). Among subjects with angiographic CAD (n = 20,987), random-effects model identified an association with multivessel CAD, compared with those with single-vessel disease (OR: 1.10, 95% CI: 1.04 to 1.17)/copy of risk allele). Genotypic models showed an OR of 1.15, 95% CI: 1.04 to 1.26 for heterozygous carrier and OR: 1.23, 95% CI: 1.08 to 1.39 for homozygous carrier. Finally, there was no significant association between 9p21 and prevalent MI when both cases (n = 17,791) and control subjects (n = 15,882) had underlying CAD (OR: 0.99, 95% CI: 0.95 to 1.03)/risk allele.The 9p21 locus shows convincing association with greater burden of CAD but not with MI in the presence of underlying CAD. This adds further weight to the hypothesis that 9p21 locus primarily mediates an atherosclerotic phenotype.

    View details for DOI 10.1016/j.jacc.2012.10.051

    View details for Web of Science ID 000315294100012

    View details for PubMedID 23352782

    View details for PubMedCentralID PMC3653306

  • Large-scale association analysis identifies new risk loci for coronary artery disease. Nature genetics Deloukas, P., Kanoni, S., Willenborg, C., Farrall, M., Assimes, T. L., Thompson, J. R., Ingelsson, E., Saleheen, D., Erdmann, J., Goldstein, B. A., Stirrups, K., König, I. R., Cazier, J., Johansson, A., Hall, A. S., Lee, J., Willer, C. J., Chambers, J. C., Esko, T., Folkersen, L., Goel, A., Grundberg, E., Havulinna, A. S., Ho, W. K., Hopewell, J. C., Eriksson, N., Kleber, M. E., Kristiansson, K., Lundmark, P., Lyytikäinen, L., Rafelt, S., Shungin, D., Strawbridge, R. J., Thorleifsson, G., Tikkanen, E., Van Zuydam, N., Voight, B. F., Waite, L. L., Zhang, W., Ziegler, A., Absher, D., Altshuler, D., Balmforth, A. J., Barroso, I., Braund, P. S., Burgdorf, C., Claudi-Boehm, S., Cox, D., Dimitriou, M., Do, R., Doney, A. S., El Mokhtari, N., Eriksson, P., Fischer, K., Fontanillas, P., Franco-Cereceda, A., Gigante, B., Groop, L., Gustafsson, S., Hager, J., Hallmans, G., Han, B., Hunt, S. E., Kang, H. M., Illig, T., Kessler, T., Knowles, J. W., Kolovou, G., Kuusisto, J., Langenberg, C., Langford, C., Leander, K., Lokki, M., Lundmark, A., McCarthy, M. I., Meisinger, C., Melander, O., Mihailov, E., Maouche, S., Morris, A. D., Müller-Nurasyid, M., Nikus, K., Peden, J. F., Rayner, N. W., Rasheed, A., Rosinger, S., Rubin, D., Rumpf, M. P., Schäfer, A., Sivananthan, M., Song, C., Stewart, A. F., Tan, S., Thorgeirsson, G., van der Schoot, C. E., Wagner, P. J., Wells, G. A., Wild, P. S., Yang, T., Amouyel, P., Arveiler, D., Basart, H., Boehnke, M., Boerwinkle, E., Brambilla, P., Cambien, F., Cupples, A. L., de Faire, U., Dehghan, A., Diemert, P., Epstein, S. E., Evans, A., Ferrario, M. M., Ferrières, J., Gauguier, D., Go, A. S., Goodall, A. H., Gudnason, V., Hazen, S. L., Holm, H., Iribarren, C., Jang, Y., Kähönen, M., Kee, F., Kim, H., Klopp, N., Koenig, W., Kratzer, W., Kuulasmaa, K., Laakso, M., Laaksonen, R., Lee, J., Lind, L., Ouwehand, W. H., Parish, S., Park, J. E., Pedersen, N. L., Peters, A., Quertermous, T., Rader, D. J., Salomaa, V., Schadt, E., Shah, S. H., Sinisalo, J., Stark, K., Stefansson, K., Trégouët, D., Virtamo, J., Wallentin, L., Wareham, N., Zimmermann, M. E., Nieminen, M. S., Hengstenberg, C., Sandhu, M. S., Pastinen, T., Syvänen, A., Hovingh, G. K., Dedoussis, G., Franks, P. W., Lehtimäki, T., Metspalu, A., Zalloua, P. A., Siegbahn, A., Schreiber, S., Ripatti, S., Blankenberg, S. S., Perola, M., Clarke, R., Boehm, B. O., O'Donnell, C., Reilly, M. P., März, W., Collins, R., Kathiresan, S., Hamsten, A., Kooner, J. S., Thorsteinsdottir, U., Danesh, J., Palmer, C. N., Roberts, R., Watkins, H., Schunkert, H., Samani, N. J. 2013; 45 (1): 25-33

    Abstract

    Coronary artery disease (CAD) is the commonest cause of death. Here, we report an association analysis in 63,746 CAD cases and 130,681 controls identifying 15 loci reaching genome-wide significance, taking the number of susceptibility loci for CAD to 46, and a further 104 independent variants (r(2) < 0.2) strongly associated with CAD at a 5% false discovery rate (FDR). Together, these variants explain approximately 10.6% of CAD heritability. Of the 46 genome-wide significant lead SNPs, 12 show a significant association with a lipid trait, and 5 show a significant association with blood pressure, but none is significantly associated with diabetes. Network analysis with 233 candidate genes (loci at 10% FDR) generated 5 interaction networks comprising 85% of these putative genes involved in CAD. The four most significant pathways mapping to these networks are linked to lipid metabolism and inflammation, underscoring the causal role of these activities in the genetic etiology of CAD. Our study provides insights into the genetic basis of CAD and identifies key biological pathways.

    View details for DOI 10.1038/ng.2480

    View details for PubMedID 23202125

  • Disease-related growth factor and embryonic signaling pathways modulate an enhancer of TCF21 expression at the 6q23.2 coronary heart disease locus. PLoS genetics Miller, C. L., Anderson, D. R., Kundu, R. K., Raiesdana, A., Nürnberg, S. T., Diaz, R., Cheng, K., Leeper, N. J., Chen, C., Chang, I., Schadt, E. E., Hsiung, C. A., Assimes, T. L., Quertermous, T. 2013; 9 (7)

    Abstract

    Coronary heart disease (CHD) is the leading cause of mortality in both developed and developing countries worldwide. Genome-wide association studies (GWAS) have now identified 46 independent susceptibility loci for CHD, however, the biological and disease-relevant mechanisms for these associations remain elusive. The large-scale meta-analysis of GWAS recently identified in Caucasians a CHD-associated locus at chromosome 6q23.2, a region containing the transcription factor TCF21 gene. TCF21 (Capsulin/Pod1/Epicardin) is a member of the basic-helix-loop-helix (bHLH) transcription factor family, and regulates cell fate decisions and differentiation in the developing coronary vasculature. Herein, we characterize a cis-regulatory mechanism by which the lead polymorphism rs12190287 disrupts an atypical activator protein 1 (AP-1) element, as demonstrated by allele-specific transcriptional regulation, transcription factor binding, and chromatin organization, leading to altered TCF21 expression. Further, this element is shown to mediate signaling through platelet-derived growth factor receptor beta (PDGFR-?) and Wilms tumor 1 (WT1) pathways. A second disease allele identified in East Asians also appears to disrupt an AP-1-like element. Thus, both disease-related growth factor and embryonic signaling pathways may regulate CHD risk through two independent alleles at TCF21.

    View details for DOI 10.1371/journal.pgen.1003652

    View details for PubMedID 23874238

  • Long-Term Use of Angiotensin Receptor Blockers and the Risk of Cancer PLOS ONE Azoulay, L., Assimes, T. L., Yin, H., Bartels, D. B., Schiffrin, E. L., Suissa, S. 2012; 7 (12)

    Abstract

    The association between angiotensin receptor blockers (ARBs) and cancer is controversial with meta-analyses of randomized controlled trials and observational studies reporting conflicting results. Thus, the objective of this study was to determine whether ARBs are associated with an overall increased risk of the four most common cancers, namely, lung, colorectal, breast and prostate cancers, and to explore these effects separately for each cancer type. We conducted a retrospective cohort study using a nested case-control analysis within the United Kingdom (UK) General Practice Research Database. We assembled a cohort of patients prescribed antihypertensive agents between 1995, the year the first ARB (losartan) entered the UK market, and 2008, with follow-up until December 31, 2010. Cases were patients newly-diagnosed with lung, colorectal, breast and prostate cancer during follow-up. We used conditional logistic regression to estimate adjusted rate ratios (RRs) and 95% confidence intervals (CIs) of cancer incidence, comparing ever use of ARBs with ever use of diuretics and/or beta-blockers. The cohort included 1,165,781 patients, during which 41,059 patients were diagnosed with one of the cancers under study (rate 554/100,000 person-years). When compared to diuretics and/or beta-blockers, ever use of ARBs was not associated with an increased rate of cancer overall (RR: 1.00; 95% CI: 0.96-1.03) or with each cancer site separately. The use of angiotensin-converting enzyme inhibitors and calcium channel blockers was associated with an increased rate of lung cancer (RR: 1.13; 95% CI: 1.06-1.20 and RR: 1.19; 95% CI: 1.12-1.27, respectively). This study provides additional evidence that the use of ARBs does not increase the risk of cancer overall or any of the four major cancer sites. Additional research is needed to further investigate a potentially increased risk of lung cancer with angiotensin-converting enzyme inhibitors and calcium channel blockers.

    View details for DOI 10.1371/journal.pone.0050893

    View details for Web of Science ID 000313236200045

    View details for PubMedID 23251399

  • FTO genotype is associated with phenotypic variability of body mass index NATURE Yang, J., Loos, R. J., Powell, J. E., Medland, S. E., Speliotes, E. K., Chasman, D. I., Rose, L. M., Thorleifsson, G., Steinthorsdottir, V., Maegi, R., Waite, L., Smith, A. V., Yerges-Armstrong, L. M., Monda, K. L., Hadley, D., Mahajan, A., Li, G., Kapur, K., Vitart, V., Huffman, J. E., Wang, S. R., Palmer, C., Esko, T., Fischer, K., Zhao, J. H., Demirkan, A., Isaacs, A., Feitosa, M. F., Luan, J., Heard-Costa, N. L., White, C., Jackson, A. U., Preuss, M., Ziegler, A., Eriksson, J., Kutalik, Z., Frau, F., Nolte, I. M., van Vliet-Ostaptchouk, J. V., Hottenga, J., Jacobs, K. B., Verweij, N., Goel, A., Medina-Gomez, C., Estrada, K., Bragg-Gresham, J. L., Sanna, S., Sidore, C., Tyrer, J., Teumer, A., Prokopenko, I., Mangino, M., Lindgren, C. M., Assimes, T. L., Shuldiner, A. R., Hui, J., Beilby, J. P., McArdle, W. L., Hall, P., Haritunians, T., Zgaga, L., Kolcic, I., Polasek, O., Zemunik, T., Oostra, B. A., Junttila, M. J., Groenberg, H., Schreiber, S., Peters, A., Hicks, A. A., Stephens, J., Foad, N. S., Laitinen, J., Pouta, A., Kaakinen, M., Willemsen, G., Vink, J. M., Wild, S. H., Navis, G., Asselbergs, F. W., Homuth, G., John, U., Iribarren, C., Harris, T., Launer, L., Gudnason, V., O'Connell, J. R., Boerwinkle, E., Cadby, G., Palmer, L. J., James, A. L., Musk, A. W., Ingelsson, E., Psaty, B. M., Beckmann, J. S., Waeber, G., Vollenweider, P., Hayward, C., Wright, A. F., Rudan, I., Groop, L. C., Metspalu, A., Khaw, K. T., van Duijn, C. M., Borecki, I. B., Province, M. A., Wareham, N. J., Tardif, J., Huikuri, H. V., Cupples, L. A., Atwood, L. D., Fox, C. S., Boehnke, M., Collins, F. S., Mohlke, K. L., Erdmann, J., Schunkert, H., Hengstenberg, C., Stark, K., Lorentzon, M., Ohlsson, C., Cusi, D., Staessen, J. A., van der Klauw, M. M., Pramstaller, P. P., Kathiresan, S., Jolley, J. D., Ripatti, S., Jarvelin, M., de Geus, E. J., Boomsma, D. I., Penninx, B., Wilson, J. F., Campbell, H., Chanock, S. J., van der Harst, P., Hamsten, A., Watkins, H., Hofman, A., Witteman, J. C., Zillikens, M. C., Uitterlinden, A. G., Rivadeneira, F., Zillikens, M. C., Kiemeney, L. A., Vermeulen, S. H., Abecasis, G. R., Schlessinger, D., Schipf, S., Stumvoll, M., Toenjes, A., Spector, T. D., North, K. E., Lettre, G., McCarthy, M. I., Berndt, S. I., Heath, A. C., Madden, P. A., Nyholt, D. R., Montgomery, G. W., Martin, N. G., McKnight, B., Strachan, D. P., Hill, W. G., Snieder, H., Ridker, P. M., Thorsteinsdottir, U., Stefansson, K., Frayling, T. M., Hirschhorn, J. N., Goddard, M. E., Visscher, P. M. 2012; 490 (7419): 267-?

    Abstract

    There is evidence across several species for genetic control of phenotypic variation of complex traits, such that the variance among phenotypes is genotype dependent. Understanding genetic control of variability is important in evolutionary biology, agricultural selection programmes and human medicine, yet for complex traits, no individual genetic variants associated with variance, as opposed to the mean, have been identified. Here we perform a meta-analysis of genome-wide association studies of phenotypic variation using ?170,000 samples on height and body mass index (BMI) in human populations. We report evidence that the single nucleotide polymorphism (SNP) rs7202116 at the FTO gene locus, which is known to be associated with obesity (as measured by mean BMI for each rs7202116 genotype), is also associated with phenotypic variability. We show that the results are not due to scale effects or other artefacts, and find no other experiment-wise significant evidence for effects on variability, either at loci other than FTO for BMI or at any locus for height. The difference in variance for BMI among individuals with opposite homozygous genotypes at the FTO locus is approximately 7%, corresponding to a difference of ?0.5?kilograms in the standard deviation of weight. Our results indicate that genetic variants can be discovered that are associated with variability, and that between-person variability in obesity can partly be explained by the genotype at the FTO locus. The results are consistent with reported FTO by environment interactions for BMI, possibly mediated by DNA methylation. Our BMI results for other SNPs and our height results for all SNPs suggest that most genetic variants, including those that influence mean height or mean BMI, are not associated with phenotypic variance, or that their effects on variability are too small to detect even with samples sizes greater than 100,000.

    View details for DOI 10.1038/nature11401

    View details for Web of Science ID 000309733300051

    View details for PubMedID 22982992

    View details for PubMedCentralID PMC3564953

  • Randomized Trial of Personal Genomics for Preventive Cardiology Design and Challenges CIRCULATION-CARDIOVASCULAR GENETICS Knowles, J. W., Assimes, T. L., Kiernan, M., Pavlovic, A., Goldstein, B. A., Yank, V., McConnell, M. V., Absher, D., Bustamante, C., Ashley, E. A., Ioannidis, J. P. 2012; 5 (3): 368-376

    View details for DOI 10.1161/CIRCGENETICS.112.962746

    View details for Web of Science ID 000309884900017

    View details for PubMedID 22715281

  • Genetic determinants of the ankle-brachial index: A meta-analysis of a cardiovascular candidate gene 50K SNP panel in the candidate gene association resource (CARe) consortium ATHEROSCLEROSIS Wassel, C. L., Lamina, C., Nambi, V., Coassin, S., Mukamal, K. J., Ganesh, S. K., Jacobs, D. R., Franceschini, N., Papanicolaou, G. J., Gibson, Q., Yanek, L. R., van der Harst, P., Ferguson, J. F., Crawford, D. C., Waite, L. L., Allison, M. A., Criqui, M. H., McDermott, M. M., Mehra, R., Cupples, L. A., Hwang, S., Redline, S., Kaplan, R. C., Heiss, G., Rotter, J. I., Boerwinkle, E., Taylor, H. A., Eraso, L. H., Haun, M., Li, M., Meisinger, C., O'Connell, J. R., Shuldineri, A. R., Tybjaerg-Hansen, A., Frikke-Schmidt, R., Kollerits, B., Rantner, B., Dieplinger, B., Stadler, M., Mueller, T., Haltmayer, M., Klein-Weigel, P., Summerer, M., Wichmann, H., Asselbergs, F. W., Navis, G., Leach, I. M., Brown-Gentry, K., Goodloe, R., Assimes, T. L., Becker, D. M., Cooke, J. P., Absher, D. M., Olin, J. W., Mitchell, B. D., Reilly, M. P., Mohler, E. R., North, K. E., Reiner, A. P., Kronenberg, F., Murabito, J. M. 2012; 222 (1): 138-147

    Abstract

    Candidate gene association studies for peripheral artery disease (PAD), including subclinical disease assessed with the ankle-brachial index (ABI), have been limited by the modest number of genes examined. We conducted a two stage meta-analysis of ?50,000 SNPs across ?2100 candidate genes to identify genetic variants for ABI.We studied subjects of European ancestry from 8 studies (n=21,547, 55% women, mean age 44-73 years) and African American ancestry from 5 studies (n=7267, 60% women, mean age 41-73 years) involved in the candidate gene association resource (CARe) consortium. In each ethnic group, additive genetic models were used (with each additional copy of the minor allele corresponding to the given beta) to test each SNP for association with continuous ABI (excluding ABI>1.40) and PAD (defined as ABI<0.90) using linear or logistic regression with adjustment for known PAD risk factors and population stratification. We then conducted a fixed-effects inverse-variance weighted meta-analyses considering a p<2×10(-6) to denote statistical significance.In the European ancestry discovery meta-analyses, rs2171209 in SYTL3 (?=-0.007, p=6.02×10(-7)) and rs290481 in TCF7L2 (?=-0.008, p=7.01×10(-7)) were significantly associated with ABI. None of the SNP associations for PAD were significant, though a SNP in CYP2B6 (p=4.99×10(-5)) was among the strongest associations. These 3 genes are linked to key PAD risk factors (lipoprotein(a), type 2 diabetes, and smoking behavior, respectively). We sought replication in 6 population-based and 3 clinical samples (n=15,440) for rs290481 and rs2171209. However, in the replication stage (rs2171209, p=0.75; rs290481, p=0.19) and in the combined discovery and replication analysis the SNP-ABI associations were no longer significant (rs2171209, p=1.14×10(-3); rs290481, p=8.88×10(-5)). In African Americans, none of the SNP associations for ABI or PAD achieved an experiment-wide level of significance.Genetic determinants of ABI and PAD remain elusive. Follow-up of these preliminary findings may uncover important biology given the known gene-risk factor associations. New and more powerful approaches to PAD gene discovery are warranted.

    View details for DOI 10.1016/j.atherosclerosis.2012.01.039

    View details for Web of Science ID 000302960600022

    View details for PubMedID 22361517

    View details for PubMedCentralID PMC3596171

  • PREDICTING ACUTE SUDDEN CARDIAC DEATH 49th Congress of the European-Renal-Association/European-Dialysis-and-Transplant-Association (ERA-EDTA) Goldstein, B., Winkelmayer, W., Assimes, T. OXFORD UNIV PRESS. 2012: 59?59

    View details for Web of Science ID 000311494700134

  • Central obesity is important but not essential component of the metabolic syndrome for predicting diabetes mellitus in a hypertensive family-based cohort. Results from the Stanford Asia-pacific program for hypertension and insulin resistance (SAPPHIRe) Taiwan follow-up study CARDIOVASCULAR DIABETOLOGY Lee, I., Chiu, Y., Hwu, C., He, C., Chiang, F., Lin, Y., Assimes, T., Curb, J. D., Sheu, W. H. 2012; 11

    Abstract

    Metabolic abnormalities have a cumulative effect on development of diabetes, but only central obesity has been defined as the essential criterion of metabolic syndrome (MetS) by the International Diabetes Federation. We hypothesized that central obesity contributes to a higher risk of new-onset diabetes than other metabolic abnormalities in the hypertensive families.Non-diabetic Chinese were enrolled and MetS components were assessed to establish baseline data in a hypertensive family-based cohort study. Based on medical records and glucose tolerance test (OGTT), the cumulative incidence of diabetes was analyzed in this five-year study by Cox regression models. Contribution of central obesity to development of new-onset diabetes was assessed in subjects with the same number of positive MetS components.Among the total of 595 subjects who completed the assessment, 125 (21.0%) developed diabetes. Incidence of diabetes increased in direct proportion to the number of positive MetS components (P???0.001). Although subjects with central obesity had a higher incidence of diabetes than those without (55.7 vs. 30.0 events/1000 person-years, P???0.001), the difference became non-significant after adjusting of the number of positive MetS components (hazard ratio?=?0.72, 95%CI: 0.45-1.13). Furthermore, in all participants with three positive MetS components, there was no difference in the incidence of diabetes between subjects with and without central obesity (hazard ratio?=?1.04, 95%CI: 0.50-2.16).In Chinese hypertensive families, the incidence of diabetes in subjects without central obesity was similar to that in subjects with central obesity when they also had the same number of positive MetS components. We suggest that central obesity is very important, but not the essential component of the metabolic syndrome for predicting of new-onset diabetes. (Trial registration: NCT00260910, ClinicalTrials.gov).

    View details for DOI 10.1186/1475-2840-11-43

    View details for Web of Science ID 000308428000001

    View details for PubMedID 22537054

  • Evaluation of the Metabochip Genotyping Array in African Americans and Implications for Fine Mapping of GWAS-Identified Loci: The PAGE Study PLOS ONE Buyske, S., Wu, Y., Carty, C. L., Cheng, I., Assimes, T. L., Dumitrescu, L., Hindorff, L. A., Mitchell, S., Ambite, J. L., Boerwinkle, E., Buzkova, P., Carlson, C. S., Cochran, B., Duggan, D., Eaton, C. B., Fesinmeyer, M. D., Franceschini, N., Haessler, J., Jenny, N., Kang, H. M., Kooperberg, C., Lin, Y., Le Marchand, L., Matise, T. C., Robinson, J. G., Rodriguez, C., Schumacher, F. R., Voight, B. F., Young, A., Manolio, T. A., Mohlke, K. L., Haiman, C. A., Peters, U., Crawford, D. C., North, K. E. 2012; 7 (4)

    Abstract

    The Metabochip is a custom genotyping array designed for replication and fine mapping of metabolic, cardiovascular, and anthropometric trait loci and includes low frequency variation content identified from the 1000 Genomes Project. It has 196,725 SNPs concentrated in 257 genomic regions. We evaluated the Metabochip in 5,863 African Americans; 89% of all SNPs passed rigorous quality control with a call rate of 99.9%. Two examples illustrate the value of fine mapping with the Metabochip in African-ancestry populations. At CELSR2/PSRC1/SORT1, we found the strongest associated SNP for LDL-C to be rs12740374 (p = 3.5 × 10(-11)), a SNP indistinguishable from multiple SNPs in European ancestry samples due to high correlation. Its distinct signal supports functional studies elsewhere suggesting a causal role in LDL-C. At CETP we found rs17231520, with risk allele frequency 0.07 in African Americans, to be associated with HDL-C (p = 7.2 × 10(-36)). This variant is very rare in Europeans and not tagged in common GWAS arrays, but was identified as associated with HDL-C in African Americans in a single-gene study. Our results, one narrowing the risk interval and the other revealing an associated variant not found in Europeans, demonstrate the advantages of high-density genotyping of common and rare variation for fine mapping of trait loci in African American samples.

    View details for DOI 10.1371/journal.pone.0035651

    View details for Web of Science ID 000305341000054

    View details for PubMedID 22539988

  • Interleukin-6 receptor pathways in coronary heart disease: a collaborative meta-analysis of 82 studies LANCET Sarwar, N., Butterworth, A. S., Freitag, D. F., Gregson, J., Willeit, P., Gorman, D. N., Gao, P., Saleheen, D., Rendon, A., Nelson, C. P., Braund, P. S., Hall, A. S., Chasman, D. I., Tybjaerg-Hansen, A., Chambers, J. C., Benjamin, E. J., Franks, P. W., Clarke, R., Wilde, A. A., Trip, M. D., Steri, M., Witteman, J. C., Qi, L., van der Schoot, C. E., de Faire, U., Erdmann, J., Stringham, H. M., Koenig, W., Rader, D. J., Melzer, D., Reich, D., Psaty, B. M., Kleber, M. E., Panagiotakos, D. B., Willeit, J., Wennberg, P., Woodward, M., Adamovic, S., Rimm, E. B., Meade, T. W., Gillum, R. F., Shaffer, J. A., Hofman, A., Onat, A., Sundstrom, J., Wassertheil-Smoller, S., Mellstrom, D., Gallacher, J., Cushman, M., Tracy, R. P., Kauhanen, J., Karlsson, M., Salonen, J. T., Wilhelmsen, L., Amouyel, P., Cantin, B., Best, L. G., Ben-Shlomo, Y., Manson, J. E., Davey-Smith, G., de Bakker, P. I., O'Donnell, C. J., Wilson, J. F., Wilson, A. G., Assimes, T. L., Jansson, J., Ohlsson, C., Tivesten, A., Ljunggren, O., Reilly, M. P., Hamsten, A., Ingelsson, E., Cambien, F., Hung, J., Thomas, G. N., Boehnke, M., Schunkert, H., Asselbergs, F. W., Kastelein, J. J., Gudnason, V., Salomaa, V., Harris, T. B., Kooner, J. S., Allin, K. H., Nordestgaard, B. G., Hopewell, J. C., Goodall, A. H., Ridker, P. M., Holm, H., Watkins, H., Ouwehand, W. H., Samani, N. J., Kaptoge, S., Di Angelantonio, E., Harari, O., Danesh, J. 2012; 379 (9822): 1205-1213

    Abstract

    Persistent inflammation has been proposed to contribute to various stages in the pathogenesis of cardiovascular disease. Interleukin-6 receptor (IL6R) signalling propagates downstream inflammation cascades. To assess whether this pathway is causally relevant to coronary heart disease, we studied a functional genetic variant known to affect IL6R signalling.In a collaborative meta-analysis, we studied Asp358Ala (rs2228145) in IL6R in relation to a panel of conventional risk factors and inflammation biomarkers in 125,222 participants. We also compared the frequency of Asp358Ala in 51,441 patients with coronary heart disease and in 136,226 controls. To gain insight into possible mechanisms, we assessed Asp358Ala in relation to localised gene expression and to postlipopolysaccharide stimulation of interleukin 6.The minor allele frequency of Asp358Ala was 39%. Asp358Ala was not associated with lipid concentrations, blood pressure, adiposity, dysglycaemia, or smoking (p value for association per minor allele ?0·04 for each). By contrast, for every copy of 358Ala inherited, mean concentration of IL6R increased by 34·3% (95% CI 30·4-38·2) and of interleukin 6 by 14·6% (10·7-18·4), and mean concentration of C-reactive protein was reduced by 7·5% (5·9-9·1) and of fibrinogen by 1·0% (0·7-1·3). For every copy of 358Ala inherited, risk of coronary heart disease was reduced by 3·4% (1·8-5·0). Asp358Ala was not related to IL6R mRNA levels or interleukin-6 production in monocytes.Large-scale human genetic and biomarker data are consistent with a causal association between IL6R-related pathways and coronary heart disease.British Heart Foundation; UK Medical Research Council; UK National Institute of Health Research, Cambridge Biomedical Research Centre; BUPA Foundation.

    View details for DOI 10.1016/S0140-6736(11)61931-4

    View details for Web of Science ID 000302230400033

    View details for PubMedID 22421339

  • A LARGE-SCALE MULTI ETHNIC STUDY OF A DIRECT MEASURE OF INSULIN SENSITIVITY DEMONSTRATES THAT SOUTH ASIANS ARE THE MOST INSULIN RESISTANT ETHNIC GROUP IN THE US 61st Annual Scientific Session and Expo of the American-College-of-Cardiology (ACC)/Conference on ACC-i2 with TCT Divakaruni, M. S., Abbasi, F., Desai, M., Lamendola, C., Palaniappan, L., Reaven, G., Assimes, T. ELSEVIER SCIENCE INC. 2012: E1792?E1792

    View details for Web of Science ID 000302326702003

  • Age-Related Somatic Structural Changes in the Nuclear Genome of Human Blood Cells AMERICAN JOURNAL OF HUMAN GENETICS Forsberg, L. A., Rasi, C., Razzaghian, H. R., Pakalapati, G., Waite, L., Thilbeault, K. S., Ronowicz, A., Wineinger, N. E., Tiwari, H. K., Boomsma, D., Westerman, M. P., Harris, J. R., Lyle, R., Essand, M., Eriksson, F., Assimes, T. L., Iribarren, C., Strachan, E., O'Hanlon, T. P., Rider, L. G., Miller, F. W., Giedraitis, V., Lannfelt, L., Ingelsson, M., Piotrowski, A., Pedersen, N. L., Absher, D., Dumanski, J. P. 2012; 90 (2): 217-228

    Abstract

    Structural variations are among the most frequent interindividual genetic differences in the human genome. The frequency and distribution of de novo somatic structural variants in normal cells is, however, poorly explored. Using age-stratified cohorts of 318 monozygotic (MZ) twins and 296 single-born subjects, we describe age-related accumulation of copy-number variation in the nuclear genomes in vivo and frequency changes for both megabase- and kilobase-range variants. Megabase-range aberrations were found in 3.4% (9 of 264) of subjects ?60 years old; these subjects included 78 MZ twin pairs and 108 single-born individuals. No such findings were observed in 81 MZ pairs or 180 single-born subjects who were ?55 years old. Recurrent region- and gene-specific mutations, mostly deletions, were observed. Longitudinal analyses of 43 subjects whose data were collected 7-19 years apart suggest considerable variation in the rate of accumulation of clones carrying structural changes. Furthermore, the longitudinal analysis of individuals with structural aberrations suggests that there is a natural self-removal of aberrant cell clones from peripheral blood. In three healthy subjects, we detected somatic aberrations characteristic of patients with myelodysplastic syndrome. The recurrent rearrangements uncovered here are candidates for common age-related defects in human blood cells. We anticipate that extension of these results will allow determination of the genetic age of different somatic-cell lineages and estimation of possible individual differences between genetic and chronological age. Our work might also help to explain the cause of an age-related reduction in the number of cell clones in the blood; such a reduction is one of the hallmarks of immunosenescence.

    View details for DOI 10.1016/j.ajhg.2011.12.009

    View details for Web of Science ID 000300742200003

    View details for PubMedID 22305530

    View details for PubMedCentralID PMC3276669

  • Homocysteine and Coronary Heart Disease: Meta-analysis of MTHFR Case-Control Studies, Avoiding Publication Bias PLOS MEDICINE Clarke, R., Bennett, D. A., Parish, S., Verhoef, P., Dotsch-Klerk, M., Lathrop, M., Xu, P., Nordestgaard, B. G., Holm, H., Hopewell, J. C., Saleheen, D., Tanaka, T., Anand, S. S., Chambers, J. C., Kleber, M. E., Ouwehand, W. H., Yamada, Y., Elbers, C., Peters, B., Stewart, A. F., Reilly, M. M., Thorand, B., Yusuf, S., Engert, J. C., Assimes, T. L., Kooner, J., Danesh, J., Watkins, H., Samani, N. J., Collins, R., Peto, R. 2012; 9 (2)

    Abstract

    Moderately elevated blood levels of homocysteine are weakly correlated with coronary heart disease (CHD) risk, but causality remains uncertain. When folate levels are low, the TT genotype of the common C677T polymorphism (rs1801133) of the methylene tetrahydrofolate reductase gene (MTHFR) appreciably increases homocysteine levels, so "Mendelian randomization" studies using this variant as an instrumental variable could help test causality.Nineteen unpublished datasets were obtained (total 48,175 CHD cases and 67,961 controls) in which multiple genetic variants had been measured, including MTHFR C677T. These datasets did not include measurements of blood homocysteine, but homocysteine levels would be expected to be about 20% higher with TT than with CC genotype in the populations studied. In meta-analyses of these unpublished datasets, the case-control CHD odds ratio (OR) and 95% CI comparing TT versus CC homozygotes was 1.02 (0.98-1.07; p?=?0.28) overall, and 1.01 (0.95-1.07) in unsupplemented low-folate populations. By contrast, in a slightly updated meta-analysis of the 86 published studies (28,617 CHD cases and 41,857 controls), the OR was 1.15 (1.09-1.21), significantly discrepant (p?=?0.001) with the OR in the unpublished datasets. Within the meta-analysis of published studies, the OR was 1.12 (1.04-1.21) in the 14 larger studies (those with variance of log OR<0.05; total 13,119 cases) and 1.18 (1.09-1.28) in the 72 smaller ones (total 15,498 cases).The CI for the overall result from large unpublished datasets shows lifelong moderate homocysteine elevation has little or no effect on CHD. The discrepant overall result from previously published studies reflects publication bias or methodological problems.

    View details for DOI 10.1371/journal.pmed.1001177

    View details for Web of Science ID 000301222600009

    View details for PubMedID 22363213

    View details for PubMedCentralID PMC3283559

  • Association Between Chromosome 9p21 Variants and the Ankle-Brachial Index Identified by a Meta-Analysis of 21 Genome-Wide Association Studies CIRCULATION-CARDIOVASCULAR GENETICS Murabito, J. M., White, C. C., Kavousi, M., Sun, Y. V., Feitosa, M. F., Nambi, V., Lamina, C., Schillert, A., Coassin, S., Bis, J. C., Broer, L., Crawford, D. C., Franceschini, N., Frikke-Schmidt, R., Haun, M., Holewijn, S., Huffman, J. E., Hwang, S., Kiechl, S., Kollerits, B., Montasser, M. E., Nolte, I. M., Rudock, M. E., Senft, A., Teumer, A., van der Harst, P., Vitart, V., Waite, L. L., Wood, A. R., Wassel, C. L., Absher, D. M., Allison, M. A., Amin, N., Arnold, A., Asselbergs, F. W., Aulchenko, Y., Bandinelli, S., Barbalic, M., Boban, M., Brown-Gentry, K., Couper, D. J., Criqui, M. H., Dehghan, A., den Heijer, M., Dieplinger, B., Ding, J., Doerr, M., Espinola-Klein, C., Felix, S. B., Ferrucci, L., Folsom, A. R., Fraedrich, G., Gibson, Q., Goodloe, R., Gunjaca, G., Haltmayer, M., Heiss, G., Hofman, A., Kieback, A., Kiemeney, L. A., Kolcic, I., Kullo, I. J., Kritchevsky, S. B., Lackner, K. J., Li, X., Lieb, W., Lohman, K., Meisinger, C., Melzer, D., Mohler, E. R., Mudnic, I., Mueller, T., Navis, G., Oberhollenzer, F., Olin, J. W., O'Connell, J., O'Donnell, C. J., Palmas, W., Penninx, B. W., Petersmann, A., Polasek, O., Psaty, B. M., Rantner, B., Rice, K., Rivadeneira, F., Rotter, J. I., Seldenrijk, A., Stadler, M., Summerer, M., Tanaka, T., Tybjaerg-Hansen, A., Uitterlinden, A. G., van Gilst, W. H., Vermeulen, S. H., Wild, S. H., Wild, P. S., Willeit, J., Zeller, T., Zemunik, T., Zgaga, L., Assimes, T. L., Blankenberg, S., Boerwinkle, E., Campbell, H., Cooke, J. P., de Graaf, J., Herrington, D., Kardia, S. L., Mitchell, B. D., Murray, A., Muenzel, T., Newman, A. B., Oostra, B. A., Rudan, I., Shuldiner, A. R., Snieder, H., van Duijn, C. M., Voelker, U., Wright, A. F., Wichmann, H., Wilson, J. F., Witteman, J. C., Liu, Y., Hayward, C., Borecki, I. B., Ziegler, A., North, K. E., Cupples, L. A., Kronenberg, F. 2012; 5 (1): 100-112

    Abstract

    Genetic determinants of peripheral arterial disease (PAD) remain largely unknown. To identify genetic variants associated with the ankle-brachial index (ABI), a noninvasive measure of PAD, we conducted a meta-analysis of genome-wide association study data from 21 population-based cohorts.Continuous ABI and PAD (ABI ?0.9) phenotypes adjusted for age and sex were examined. Each study conducted genotyping and imputed data to the ?2.5 million single nucleotide polymorphisms (SNPs) in HapMap. Linear and logistic regression models were used to test each SNP for association with ABI and PAD using additive genetic models. Study-specific data were combined using fixed effects inverse variance weighted meta-analyses. There were a total of 41 692 participants of European ancestry (?60% women, mean ABI 1.02 to 1.19), including 3409 participants with PAD and with genome-wide association study data available. In the discovery meta-analysis, rs10757269 on chromosome 9 near CDKN2B had the strongest association with ABI (?=-0.006, P=2.46×10(-8)). We sought replication of the 6 strongest SNP associations in 5 population-based studies and 3 clinical samples (n=16 717). The association for rs10757269 strengthened in the combined discovery and replication analysis (P=2.65×10(-9)). No other SNP associations for ABI or PAD achieved genome-wide significance. However, 2 previously reported candidate genes for PAD and 1 SNP associated with coronary artery disease were associated with ABI: DAB21P (rs13290547, P=3.6×10(-5)), CYBA (rs3794624, P=6.3×10(-5)), and rs1122608 (LDLR, P=0.0026).Genome-wide association studies in more than 40 000 individuals identified 1 genome wide significant association on chromosome 9p21 with ABI. Two candidate genes for PAD and 1 SNP for coronary artery disease are associated with ABI.

    View details for DOI 10.1161/CIRCGENETICS.111.961292

    View details for Web of Science ID 000309884100017

    View details for PubMedID 22199011

  • Novel loci for adiponectin levels and their influence on type 2 diabetes and metabolic traits: a multi-ethnic meta-analysis of 45,891 individuals. PLoS genetics Dastani, Z., Hivert, M., Timpson, N., Perry, J. R., Yuan, X., Scott, R. A., Henneman, P., Heid, I. M., Kizer, J. R., Lyytikäinen, L., Fuchsberger, C., Tanaka, T., Morris, A. P., Small, K., Isaacs, A., Beekman, M., Coassin, S., Lohman, K., Qi, L., Kanoni, S., Pankow, J. S., Uh, H., Wu, Y., Bidulescu, A., Rasmussen-Torvik, L. J., Greenwood, C. M., Ladouceur, M., Grimsby, J., Manning, A. K., Liu, C., Kooner, J., Mooser, V. E., Vollenweider, P., Kapur, K. A., Chambers, J., Wareham, N. J., Langenberg, C., Frants, R., Willems-Vandijk, K., Oostra, B. A., Willems, S. M., Lamina, C., Winkler, T. W., Psaty, B. M., Tracy, R. P., Brody, J., Chen, I., Viikari, J., Kähönen, M., Pramstaller, P. P., Evans, D. M., St Pourcain, B., Sattar, N., Wood, A. R., Bandinelli, S., Carlson, O. D., Egan, J. M., Böhringer, S., van Heemst, D., Kedenko, L., Kristiansson, K., Nuotio, M., Loo, B., Harris, T., Garcia, M., Kanaya, A., Haun, M., Klopp, N., Wichmann, H., Deloukas, P., Katsareli, E., Couper, D. J., Duncan, B. B., Kloppenburg, M., Adair, L. S., Borja, J. B., Wilson, J. G., Musani, S., Guo, X., Johnson, T., Semple, R., Teslovich, T. M., Allison, M. A., Redline, S., Buxbaum, S. G., Mohlke, K. L., Meulenbelt, I., Ballantyne, C. M., Dedoussis, G. V., Hu, F. B., Liu, Y., Paulweber, B., Spector, T. D., Slagboom, P. E., Ferrucci, L., Jula, A., Perola, M., Raitakari, O., Florez, J. C., Salomaa, V., Eriksson, J. G., Frayling, T. M., Hicks, A. A., Lehtimäki, T., Smith, G. D., Siscovick, D. S., Kronenberg, F., Van Duijn, C., Loos, R. J., Waterworth, D. M., Meigs, J. B., Dupuis, J., Richards, J. B., Voight, B. F., Scott, L. J., Steinthorsdottir, V., Dina, C., Welch, R. P., Zeggini, E., Huth, C., Aulchenko, Y. S., Thorleifsson, G., McCulloch, L. J., Ferreira, T., Grallert, H., Amin, N., Wu, G., Willer, C. J., Raychaudhuri, S., McCarroll, S. A., Hofmann, O. M., Segrè, A. V., van Hoek, M., Navarro, P., Ardlie, K., Balkau, B., Benediktsson, R., Bennett, A. J., Blagieva, R., Boerwinkle, E., Bonnycastle, L. L., Boström, K. B., Bravenboer, B., Bumpstead, S., Burtt, N. P., Charpentier, G., Chines, P. S., Cornelis, M., Crawford, G., Doney, A. S., Elliott, K. S., Elliott, A. L., Erdos, M. R., Fox, C. S., Franklin, C. S., Ganser, M., Gieger, C., Grarup, N., Green, T., Griffin, S., Groves, C. J., Guiducci, C., Hadjadj, S., Hassanali, N., Herder, C., Isomaa, B., Jackson, A. U., Johnson, P. R., Jørgensen, T., Kao, W. H., Kong, A., Kraft, P., Kuusisto, J., Lauritzen, T., Li, M., Lieverse, A., Lindgren, C. M., Lyssenko, V., Marre, M., Meitinger, T., Midthjell, K., Morken, M. A., Narisu, N., Nilsson, P., Owen, K. R., Payne, F., Petersen, A., Platou, C., Proença, C., Prokopenko, I., Rathmann, W., Rayner, N. W., Robertson, N. R., Rocheleau, G., Roden, M., Sampson, M. J., Saxena, R., Shields, B. M., Shrader, P., Sigurdsson, G., Sparsø, T., Strassburger, K., Stringham, H. M., Sun, Q., Swift, A. J., Thorand, B., Tichet, J., Tuomi, T., van Dam, R. M., Van Haeften, T. W., van Herpt, T., van Vliet-Ostaptchouk, J. V., Walters, G. B., Weedon, M. N., Wijmenga, C., Witteman, J., Bergman, R. N., Cauchi, S., Collins, F. S., Gloyn, A. L., Gyllensten, U., Hansen, T., Hide, W. A., Hitman, G. A., Hofman, A., Hunter, D. J., Hveem, K., Laakso, M., Morris, A. D., Palmer, C. N., Rudan, I., Sijbrands, E., Stein, L. D., Tuomilehto, J., Uitterlinden, A., Walker, M., Watanabe, R. M., Abecasis, G. R., Boehm, B. O., Campbell, H., Daly, M. J., Hattersley, A. T., Pedersen, O., Barroso, I., Groop, L., Sladek, R., Thorsteinsdottir, U., Wilson, J. F., Illig, T., Froguel, P., van Duijn, C. M., Stefansson, K., Altshuler, D., Boehnke, M., McCarthy, M. I., Soranzo, N., Wheeler, E., Glazer, N. L., Bouatia-Naji, N., Mägi, R., Randall, J., Elliott, P., Rybin, D., Dehghan, A., Hottenga, J. J., Song, K., Goel, A., Lajunen, T., Doney, A., Cavalcanti-Proença, C., Kumari, M., Timpson, N. J., Zabena, C., Ingelsson, E., An, P., O'Connell, J., Luan, J., Elliott, A., McCarroll, S. A., Roccasecca, R. M., Pattou, F., Sethupathy, P., Ariyurek, Y., Barter, P., Beilby, J. P., Ben-Shlomo, Y., Bergmann, S., Bochud, M., Bonnefond, A., Borch-Johnsen, K., Böttcher, Y., Brunner, E., Bumpstead, S. J., Chen, Y. I., Chines, P., Clarke, R., Coin, L. J., Cooper, M. N., Crisponi, L., Day, I. N., de Geus, E. J., Delplanque, J., Fedson, A. C., Fischer-Rosinsky, A., Forouhi, N. G., Franzosi, M. G., Galan, P., Goodarzi, M. O., Graessler, J., Grundy, S., Gwilliam, R., Hallmans, G., Hammond, N., Han, X., Hartikainen, A., Hayward, C., Heath, S. C., Hercberg, S., Hillman, D. R., Hingorani, A. D., Hui, J., Hung, J., Kaakinen, M., Kaprio, J., Kesaniemi, Y. A., Kivimaki, M., Knight, B., Koskinen, S., Kovacs, P., Kyvik, K. O., Lathrop, G. M., Lawlor, D. A., Le Bacquer, O., Lecoeur, C., Li, Y., Mahley, R., Mangino, M., Martínez-Larrad, M. T., McAteer, J. B., McPherson, R., Meisinger, C., Melzer, D., Meyre, D., Mitchell, B. D., Mukherjee, S., Naitza, S., Neville, M. J., Orrù, M., Pakyz, R., Paolisso, G., Pattaro, C., Pearson, D., Peden, J. F., Pedersen, N. L., Pfeiffer, A. F., Pichler, I., Polasek, O., Posthuma, D., Potter, S. C., Pouta, A., Province, M. A., Rayner, N. W., Rice, K., Ripatti, S., Rivadeneira, F., Rolandsson, O., Sandbaek, A., Sandhu, M., Sanna, S., Sayer, A. A., Scheet, P., Seedorf, U., Sharp, S. J., Shields, B., Sigurðsson, G., Sijbrands, E. J., Silveira, A., Simpson, L., Singleton, A., Smith, N. L., Sovio, U., Swift, A., Syddall, H., Syvänen, A., Tönjes, A., Uitterlinden, A. G., Van Dijk, K. W., Varma, D., Visvikis-Siest, S., Vitart, V., Vogelzangs, N., Waeber, G., Wagner, P. J., Walley, A., Ward, K. L., Watkins, H., Wild, S. H., Willemsen, G., Witteman, J. C., Yarnell, J. W., Zelenika, D., Zethelius, B., Zhai, G., Zhao, J. H., Zillikens, M. C., Borecki, I. B., Meneton, P., Magnusson, P. K., Nathan, D. M., Williams, G. H., Silander, K., Bornstein, S. R., Schwarz, P., Spranger, J., Karpe, F., Shuldiner, A. R., Cooper, C., Serrano-Ríos, M., Lind, L., Palmer, L. J., Hu, F. B., Franks, P. W., Ebrahim, S., Marmot, M., Kao, W. H., Pramstaller, P. P., Wright, A. F., Stumvoll, M., Hamsten, A., Buchanan, T. A., Valle, T. T., Rotter, J. I., Penninx, B. W., Boomsma, D. I., Cao, A., Scuteri, A., Schlessinger, D., Uda, M., Ruokonen, A., Jarvelin, M., Peltonen, L., Mooser, V., Sladek, R., Musunuru, K., Smith, A. V., Edmondson, A. C., Stylianou, I. M., Koseki, M., Pirruccello, J. P., Chasman, D. I., Johansen, C. T., Fouchier, S. W., Peloso, G. M., Barbalic, M., Ricketts, S. L., Bis, J. C., Feitosa, M. F., Orho-Melander, M., Melander, O., Li, X., Li, M., Cho, Y. S., Go, M. J., Kim, Y. J., Lee, J., Park, T., Kim, K., Sim, X., Ong, R. T., Croteau-Chonka, D. C., Lange, L. A., Smith, J. D., Ziegler, A., Zhang, W., Zee, R. Y., Whitfield, J. B., Thompson, J. R., Surakka, I., Spector, T. D., Smit, J. H., Sinisalo, J., Scott, J., Saharinen, J., Sabatti, C., Rose, L. M., Roberts, R., Rieder, M., Parker, A. N., Pare, G., O'Donnell, C. J., Nieminen, M. S., Nickerson, D. A., Montgomery, G. W., McArdle, W., Masson, D., Martin, N. G., Marroni, F., Lucas, G., Luben, R., Lokki, M., Lettre, G., Launer, L. J., Lakatta, E. G., Laaksonen, R., Kyvik, K. O., König, I. R., Khaw, K., Kaplan, L. M., Johansson, Å., Janssens, A. C., Igl, W., Hovingh, G. K., Hengstenberg, C., Havulinna, A. S., Hastie, N. D., Harris, T. B., Haritunians, T., Hall, A. S., Groop, L. C., Gonzalez, E., Freimer, N. B., Erdmann, J., Ejebe, K. G., Döring, A., Dominiczak, A. F., Demissie, S., Deloukas, P., de Faire, U., Crawford, G., Chen, Y. I., Caulfield, M. J., Boekholdt, S. M., Assimes, T. L., Quertermous, T., Seielstad, M., Wong, T. Y., Tai, E., Feranil, A. B., Kuzawa, C. W., Taylor, H. A., Gabriel, S. B., Holm, H., Gudnason, V., Krauss, R. M., Ordovas, J. M., Munroe, P. B., Kooner, J. S., Tall, A. R., Hegele, R. A., Kastelein, J. J., Schadt, E. E., Strachan, D. P., Reilly, M. P., Samani, N. J., Schunkert, H., Cupples, L. A., Sandhu, M. S., Ridker, P. M., Rader, D. J., Kathiresan, S. 2012; 8 (3)

    Abstract

    Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P?=?4.5×10(-8)-1.2×10(-43)). Using a novel method to combine data across ethnicities (N?=?4,232 African Americans, N?=?1,776 Asians, and N?=?29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p<3×10(-4)). We next developed a multi-SNP genotypic risk score to test the association of adiponectin decreasing risk alleles on metabolic traits and diseases using consortia-level meta-analytic data. This risk score was associated with increased risk of T2D (p?=?4.3×10(-3), n?=?22,044), increased triglycerides (p?=?2.6×10(-14), n?=?93,440), increased waist-to-hip ratio (p?=?1.8×10(-5), n?=?77,167), increased glucose two hours post oral glucose tolerance testing (p?=?4.4×10(-3), n?=?15,234), increased fasting insulin (p?=?0.015, n?=?48,238), but with lower in HDL-cholesterol concentrations (p?=?4.5×10(-13), n?=?96,748) and decreased BMI (p?=?1.4×10(-4), n?=?121,335). These findings identify novel genetic determinants of adiponectin levels, which, taken together, influence risk of T2D and markers of insulin resistance.

    View details for DOI 10.1371/journal.pgen.1002607

    View details for PubMedID 22479202

  • Abdominal Aortic Aneurysm Is Associated with a Variant in Low-Density Lipoprotein Receptor-Related Protein 1 AMERICAN JOURNAL OF HUMAN GENETICS Bown, M. J., Jones, G. T., Harrison, S. C., Wright, B. J., Bumpstead, S., Baas, A. F., Gretarsdottir, S., Badger, S. A., Bradley, D. T., Burnand, K., Child, A. H., Clough, R. E., Cockerill, G., Hafez, H., Scott, D. J., Futers, S., Johnson, A., Sohrabi, S., Smith, A., Thompson, M. M., van Bockxmeer, F. M., Waltham, M., Matthiasson, S. E., Thorleifsson, G., Thorsteinsdottir, U., Blankensteijn, J. D., Teijink, J. A., Wijmenga, C., de Graaf, J., Kiemeney, L. A., Assimes, T. L., McPherson, R., Folkersen, L., Franco-Cereceda, A., Palmen, J., Smith, A. J., Sylvius, N., Wild, J. B., Refstrup, M., Edkins, S., Gwilliam, R., Hunt, S. E., Potter, S., Lindholt, J. S., Frikke-Schmidt, R., Tybjaerg-Hansen, A., Hughes, A. E., Golledge, J., Norman, P. E., van Rij, A., Powel, J. T., Eriksson, P., Stefansson, K., Thompson, J. R., Humphries, S. E., Sayers, R. D., Deloukas, P., Samani, N. J. 2011; 89 (5): 619-627

    Abstract

    Abdominal aortic aneurysm (AAA) is a common cause of morbidity and mortality and has a significant heritability. We carried out a genome-wide association discovery study of 1866 patients with AAA and 5435 controls and replication of promising signals (lead SNP with a p value < 1 × 10(-5)) in 2871 additional cases and 32,687 controls and performed further follow-up in 1491 AAA and 11,060 controls. In the discovery study, nine loci demonstrated association with AAA (p < 1 × 10(-5)). In the replication sample, the lead SNP at one of these loci, rs1466535, located within intron 1 of low-density-lipoprotein receptor-related protein 1 (LRP1) demonstrated significant association (p = 0.0042). We confirmed the association of rs1466535 and AAA in our follow-up study (p = 0.035). In a combined analysis (6228 AAA and 49182 controls), rs1466535 had a consistent effect size and direction in all sample sets (combined p = 4.52 × 10(-10), odds ratio 1.15 [1.10-1.21]). No associations were seen for either rs1466535 or the 12q13.3 locus in independent association studies of coronary artery disease, blood pressure, diabetes, or hyperlipidaemia, suggesting that this locus is specific to AAA. Gene-expression studies demonstrated a trend toward increased LRP1 expression for the rs1466535 CC genotype in arterial tissues; there was a significant (p = 0.029) 1.19-fold (1.04-1.36) increase in LRP1 expression in CC homozygotes compared to TT homozygotes in aortic adventitia. Functional studies demonstrated that rs1466535 might alter a SREBP-1 binding site and influence enhancer activity at the locus. In conclusion, this study has identified a biologically plausible genetic variant associated specifically with AAA, and we suggest that this variant has a possible functional role in LRP1 expression.

    View details for DOI 10.1016/j.ajhg.2011.10.002

    View details for Web of Science ID 000297090100003

    View details for PubMedID 22055160

  • Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk NATURE Ehret, G. B., Munroe, P. B., Rice, K. M., Bochud, M., Johnson, A. D., Chasman, D. I., Smith, A. V., Tobin, M. D., Verwoert, G. C., Hwang, S., Pihur, V., Vollenweider, P., O'Reilly, P. F., Amin, N., Bragg-Gresham, J. L., Teumer, A., Glazer, N. L., Launer, L., Zhao, J. H., Aulchenko, Y., Heath, S., Sober, S., Parsa, A., Luan, J., Arora, P., Dehghan, A., Zhang, F., Lucas, G., Hicks, A. A., Jackson, A. U., Peden, J. F., Tanaka, T., Wild, S. H., Rudan, I., Igl, W., Milaneschi, Y., Parker, A. N., Fava, C., Chambers, J. C., Fox, E. R., Kumari, M., Go, M. J., van der Harst, P., Kao, W. H., Sjogren, M., Vinay, D. G., Alexander, M., Tabara, Y., Shaw-Hawkins, S., Whincup, P. H., Liu, Y., Shi, G., Kuusisto, J., Tayo, B., Seielstad, M., Sim, X., Khanh-Dung Hoang Nguyen, K. D., Lehtimaki, T., Matullo, G., Wu, Y., Gaunt, T. R., Onland-Moret, N. C., Cooper, M. N., Platou, C. G., Org, E., Hardy, R., Dahgam, S., Palmen, J., Vitart, V., Braund, P. S., Kuznetsova, T., Uiterwaal, C. S., Adeyemo, A., Palmas, W., Campbell, H., Ludwig, B., Tomaszewski, M., Tzoulaki, I., Palmer, N. D., Aspelund, T., Garcia, M., Chang, Y. C., O'Connell, J. R., Steinle, N. I., Grobbee, D. E., Arking, D. E., Kardia, S. L., Morrison, A. C., Hernandez, D., Najjar, S., McArdle, W. L., Hadley, D., Brown, M. J., Connell, J. M., Hingorani, A. D., Day, I. N., Lawlor, D. A., Beilby, J. P., Lawrence, R. W., Clarke, R., Hopewell, J. C., Ongen, H., Dreisbach, A. W., Li, Y., Young, J. H., Bis, J. C., Kahonen, M., Viikari, J., Adair, L. S., Lee, N. R., Chen, M., Olden, M., Pattaro, C., Bolton, J. A., Koettgen, A., Bergmann, S., Mooser, V., Chaturvedi, N., Frayling, T. M., Islam, M., Jafar, T. H., Erdmann, J., Kulkarni, S. R., Bornstein, S. R., Graessler, J., Groop, L., Voight, B. F., Kettunen, J., Howard, P., Taylor, A., Guarrera, S., Ricceri, F., Emilsson, V., Plump, A., Barroso, I. S., Khaw, K., Weder, A. B., Hunt, S. C., Sun, Y. V., Bergman, R. N., Collins, F. S., Bonnycastle, L. L., Scott, L. J., Stringham, H. M., Peltonen, L., Perola, M., Vartiainen, E., Brand, S., Staessen, J. A., Wang, T. J., Burton, P. R., Artigas, M. S., Dong, Y., Snieder, H., Wang, X., Zhu, H., Lohman, K. K., Rudock, M. E., Heckbert, S. R., Smith, N. L., Wiggins, K. L., Doumatey, A., Shriner, D., Veldre, G., Viigimaa, M., Kinra, S., Prabhakaran, D., Tripathy, V., Langefeld, C. D., Rosengren, A., Thelle, D. S., Corsi, A. M., Singleton, A., Forrester, T., Hilton, G., McKenzie, C. A., Salako, T., Iwai, N., Kita, Y., Ogihara, T., Ohkubo, T., Okamura, T., Ueshima, H., Umemura, S., Eyheramendy, S., Meitinger, T., Wichmann, H., Cho, Y. S., Kim, H., Lee, J., Scott, J., Sehmi, J. S., Zhang, W., Hedblad, B., Nilsson, P., Smith, G. D., Wong, A., Narisu, N., Stancakova, A., Raffel, L. J., Yao, J., Kathiresan, S., O'Donnell, C. J., Schwartz, S. M., Ikram, M. A., Longstreth, W. T., Mosley, T. H., Seshadri, S., Shrine, N. R., Wain, L. V., Morken, M. A., Swift, A. J., Laitinen, J., Prokopenko, I., Zitting, P., Cooper, J. A., Humphries, S. E., Danesh, J., Rasheed, A., Goel, A., Hamsten, A., Watkins, H., Bakker, S. J., van Gilst, W. H., Janipalli, C. s., Mani, K. R., Yajnik, C. S., Hofman, A., Mattace-Raso, F. U., Oostra, B. A., Demirkan, A., Isaacs, A., Rivadeneira, F., Lakatta, E. G., Orru, M., Scuteri, A., Ala-Korpela, M., Kangas, A. J., Lyytikainen, L., Soininen, P., Tukiainen, T., Wurtz, P., Ong, R. T., Doerr, M., Kroemer, H. K., Voelker, U., Voelzke, H., Galan, P., Hercberg, S., Lathrop, M., Zelenika, D., Deloukas, P., Mangino, M., Spector, T. D., Zhai, G., Meschia, J. F., Nalls, M. A., Sharma, P., Terzic, J., Kumar, M. V., Denniff, M., Zukowska-Szczechowska, E., Wagenknecht, L. E., Fowkes, F. G., Charchar, F. J., Schwarz, P. E., Hayward, C., Guo, X., Rotimi, C., Bots, M. L., Brand, E., Samani, N. J., Polasek, O., Talmud, P. J., Nyberg, F., Kuh, D., Laan, M., Hveem, K., Palmer, L. J., van der Schouw, Y. T., Casas, J. P., Mohlke, K. L., Vineis, P., Raitakari, O., Ganesh, S. K., Wong, T. Y., Tai, E. S., Cooper, R. S., Laakso, M., Rao, D. C., Harris, T. B., Morris, R. W., Dominiczak, A. F., Kivimaki, M., Marmot, M. G., Miki, T., Saleheen, D., Chandak, G. R., Coresh, J., Navis, G., Salomaa, V., Han, B., Zhu, X., Kooner, J. S., Melander, O., Ridker, P. M., Bandinelli, S., Gyllensten, U. B., Wright, A. F., Wilson, J. F., Ferrucci, L., Farrall, M., Tuomilehto, J., Pramstaller, P. P., Elosua, R., Soranzo, N., Sijbrands, E. J., Altshuler, D., Loos, R. J., Shuldiner, A. R., Gieger, C., Meneton, P., Uitterlinden, A. G., Wareham, N. J., Gudnason, V., Rotter, J. I., Rettig, R., Uda, M., Strachan, D. P., Witteman, J. C., Hartikainen, A., Beckmann, J. S., Boerwinkle, E., Vasan, R. S., Boehnke, M., Larson, M. G., Jarvelin, M., Psaty, B. M., Abecasis, G. R., Chakravarti, A., Elliott, P., van Duijn, C. M., Newton-Cheh, C., Levy, D., Caulfield, M. J., Johnson, T. 2011; 478 (7367): 103-109

    Abstract

    Blood pressure is a heritable trait influenced by several biological pathways and responsive to environmental stimuli. Over one billion people worldwide have hypertension (?140?mm?Hg systolic blood pressure or? ?90?mm?Hg diastolic blood pressure). Even small increments in blood pressure are associated with an increased risk of cardiovascular events. This genome-wide association study of systolic and diastolic blood pressure, which used a multi-stage design in 200,000 individuals of European descent, identified sixteen novel loci: six of these loci contain genes previously known or suspected to regulate blood pressure (GUCY1A3-GUCY1B3, NPR3-C5orf23, ADM, FURIN-FES, GOSR2, GNAS-EDN3); the other ten provide new clues to blood pressure physiology. A genetic risk score based on 29 genome-wide significant variants was associated with hypertension, left ventricular wall thickness, stroke and coronary artery disease, but not kidney disease or kidney function. We also observed associations with blood pressure in East Asian, South Asian and African ancestry individuals. Our findings provide new insights into the genetics and biology of blood pressure, and suggest potential novel therapeutic pathways for cardiovascular disease prevention.

    View details for DOI 10.1038/nature10405

    View details for Web of Science ID 000295575400043

    View details for PubMedID 21909115

  • Immortal Person Time Bias in Pharmacoepidemiological Studies of Antihypertensive Drugs AMERICAN JOURNAL OF CARDIOLOGY Assimes, T. L., Suissa, S. 2011; 108 (6): 902-903

    View details for DOI 10.1016/j.amjcard.2011.06.031

    View details for Web of Science ID 000295352700029

    View details for PubMedID 21884882

  • Human metabolic individuality in biomedical and pharmaceutical research NATURE Suhre, K., Shin, S., Petersen, A., Mohney, R. P., Meredith, D., Waegele, B., Altmaier, E., Deloukas, P., Erdmann, J., Grundberg, E., Hammond, C. J., Hrabe de Angelis, M., Kastenmueller, G., Koettgen, A., Kronenberg, F., Mangino, M., Meisinger, C., Meitinger, T., Mewes, H., Milburn, M. V., Prehn, C., Raffler, J., Ried, J. S., Roemisch-Margl, W., Samani, N. J., Small, K. S., Wichmann, H., Zhai, G., Illig, T., Spector, T. D., Adamski, J., Soranzo, N., Gieger, C. 2011; 477 (7362): 54-U60

    Abstract

    Genome-wide association studies (GWAS) have identified many risk loci for complex diseases, but effect sizes are typically small and information on the underlying biological processes is often lacking. Associations with metabolic traits as functional intermediates can overcome these problems and potentially inform individualized therapy. Here we report a comprehensive analysis of genotype-dependent metabolic phenotypes using a GWAS with non-targeted metabolomics. We identified 37 genetic loci associated with blood metabolite concentrations, of which 25 show effect sizes that are unusually high for GWAS and account for 10-60% differences in metabolite levels per allele copy. Our associations provide new functional insights for many disease-related associations that have been reported in previous studies, including those for cardiovascular and kidney disorders, type 2 diabetes, cancer, gout, venous thromboembolism and Crohn's disease. The study advances our knowledge of the genetic basis of metabolic individuality in humans and generates many new hypotheses for biomedical and pharmaceutical research.

    View details for DOI 10.1038/nature10354

    View details for Web of Science ID 000294404300029

    View details for PubMedID 21886157

  • Large-Scale Gene-Centric Analysis Identifies Novel Variants for Coronary Artery Disease PLOS GENETICS Butterworth, A. S., Braund, P. S., Farrall, M., Hardwick, R. J., Saleheen, D., Peden, J. F., Soranzo, N., Chambers, J. C., Sivapalaratnam, S., Kleber, M. E., Keating, B., Qasim, A., Klopp, N., Erdmann, J., Assimes, T. L., Ball, S. G., Balmforth, A. J., Barnes, T. A., Basart, H., Baumert, J., Bezzina, C. R., Boerwinkle, E., Boehm, B. O., Brocheton, J., Bugert, P., Cambien, F., Clarke, R., Codd, V., Collins, R., Couper, D., Cupples, L. A., De Jong, J. S., Diemert, P., Ejebe, K., Elbers, C. C., Elliott, P., Fornage, M., Franzosi, M., Frossard, P., Garner, S., Goel, A., Goodall, A. H., Hengstenberg, C., Hunt, S. E., Kastelein, J. J., Klungel, O. H., Klueter, H., Koch, K., Koenig, I. R., Kooner, A. S., Laaksonen, R., Lathrop, M., Li, M., Liu, K., McPherson, R., Musameh, M. D., Musani, S., Nelson, C. P., O'Donnell, C. J., Ongen, H., Papanicolaou, G., Peters, A., Peters, B. J., Potter, S., Psaty, B. M., Qu, L., Rader, D. J., Rasheed, A., Rice, C., Scott, J., Seedorf, U., Sehmi, J. S., Sotoodehnia, N., Stark, K., Stephens, J., van der Schoot, C. E., van der Schouw, Y. T., Thorsteinsdottir, U., Tomaszewski, M., van der Harst, P., Vasan, R. S., Wilde, A. A., Willenborg, C., Winkelmann, B. R., Zaidi, M., Zhang, W., Ziegler, A., de Bakker, P. I., Koenig, W., Maerz, W., Trip, M. D., Reilly, M. P., Kathiresan, S., Schunkert, H., Hamsten, A., Hall, A. S., Kooner, J. S., Thompson, S. G., Thompson, J. R., Deloukas, P., Ouwehand, W. H., Watkins, H., Danesh, J., Samani, N. J. 2011; 7 (9)

    View details for DOI 10.1371/journal.pgen.1002260

    View details for Web of Science ID 000295419100015

  • Low lifetime recreational activity is a risk factor for peripheral arterial disease JOURNAL OF VASCULAR SURGERY Wilson, A. M., Sadrzadeh-Rafie, A. H., Myers, J., Assimes, T., Nead, K. T., Higgins, M., Gabriel, A., Olin, J., Cooke, J. P. 2011; 54 (2): 427-432

    Abstract

    The relationship between lifetime physical activity and the risk of developing peripheral arterial disease (PAD) is not known.We studied 1381 patients referred for elective coronary angiography in a point prevalence analysis. PAD was defined as ankle-brachial index (ABI) <0.9 at the time or a history of revascularization of the lower extremities regardless of ABI measure. We used a validated physical activity questionnaire to retrospectively measure each patient's lifetime recreational activity (LRA). Multivariate and logistic regression analyses were used to assess the independent association of LRA to ABI and the presence of PAD.PAD was present in 19% (n = 258) of all subjects. Subjects reporting no regular LRA had greater diastolic blood pressure and were more likely to be female. They had lower average ABI, and a higher proportion had PAD (25.6%). In a regression model, including traditional risk factors and LRA, multivariate analysis showed that age (P < .001), female gender (P < .001), systolic blood pressure (P = .014), fasting glucose (P < .001), serum triglycerides (P = .02), and cumulative pack years (P < .001) were independent negative predictors of ABI, and LRA was a positive predictor of ABI (P < .001). History of sedentary lifestyle independently increased the odds ratio for PAD (odds ratio, 0.46; 95% confidence interval, 1.01-2.10) when assessed by logistic regression. Intriguingly, there is a correlation between physical activity and gender, such that women with low LRA are at greatest risk.Recalled LRA is positively correlated to ABI and associated with PAD. Whereas the mechanism for this effect is not clear, LRA may be a useful clinical screening tool for PAD risk, and strategies to increase adult recreational activity may reduce the burden of PAD later in life.

    View details for DOI 10.1016/j.jvs.2011.02.052

    View details for Web of Science ID 000293814400025

    View details for PubMedID 21664093

  • A Bivariate Genome-Wide Approach to Metabolic Syndrome STAMPEED Consortium DIABETES Kraja, A. T., Vaidya, D., Pankow, J. S., Goodarzi, M. O., Assimes, T. L., Kullo, I. J., Sovio, U., Mathias, R. A., Sun, Y. V., Franceschini, N., Absher, D., Li, G., Zhang, Q., Feitosa, M. F., Glazer, N. L., Haritunians, T., Hartikainen, A., Knowles, J. W., North, K. E., Iribarren, C., Kral, B., Yanek, L., O'Reilly, P. F., McCarthy, M. I., Jaquish, C., Couper, D. J., Chakravarti, A., Psaty, B. M., Becker, L. C., Province, M. A., Boerwinkle, E., Quertermous, T., Palotie, L., Jarvelin, M., Becker, D. M., Kardia, S. L., Rotter, J. I., Chen, Y. I., Borecki, I. B. 2011; 60 (4): 1329-1339

    Abstract

    OBJECTIVE The metabolic syndrome (MetS) is defined as concomitant disorders of lipid and glucose metabolism, central obesity, and high blood pressure, with an increased risk of type 2 diabetes and cardiovascular disease. This study tests whether common genetic variants with pleiotropic effects account for some of the correlated architecture among five metabolic phenotypes that define MetS. RESEARCH DESIGN AND METHODS Seven studies of the STAMPEED consortium, comprising 22,161 participants of European ancestry, underwent genome-wide association analyses of metabolic traits using a panel of ?2.5 million imputed single nucleotide polymorphisms (SNPs). Phenotypes were defined by the National Cholesterol Education Program (NCEP) criteria for MetS in pairwise combinations. Individuals exceeding the NCEP thresholds for both traits of a pair were considered affected. RESULTS Twenty-nine common variants were associated with MetS or a pair of traits. Variants in the genes LPL, CETP, APOA5 (and its cluster), GCKR (and its cluster), LIPC, TRIB1, LOC100128354/MTNR1B, ABCB11, and LOC100129150 were further tested for their association with individual qualitative and quantitative traits. None of the 16 top SNPs (one per gene) associated simultaneously with more than two individual traits. Of them 11 variants showed nominal associations with MetS per se. The effects of 16 top SNPs on the quantitative traits were relatively small, together explaining from ?9% of the variance in triglycerides, 5.8% of high-density lipoprotein cholesterol, 3.6% of fasting glucose, and 1.4% of systolic blood pressure. CONCLUSIONS Qualitative and quantitative pleiotropic tests on pairs of traits indicate that a small portion of the covariation in these traits can be explained by the reported common genetic variants.

    View details for DOI 10.2337/db10-1011

    View details for Web of Science ID 000289496100029

    View details for PubMedID 21386085

    View details for PubMedCentralID PMC3064107

  • Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease NATURE GENETICS Schunkert, H., Koenig, I. R., Kathiresan, S., Reilly, M. P., Assimes, T. L., Holm, H., Preuss, M., Stewart, A. F., Barbalic, M., Gieger, C., Absher, D., Aherrahrou, Z., Allayee, H., Altshuler, D., Anand, S. S., Andersen, K., Anderson, J. L., Ardissino, D., Ball, S. G., Balmforth, A. J., Barnes, T. A., Becker, D. M., Becker, L. C., Berger, K., Bis, J. C., Boekholdt, S. M., Boerwinkle, E., Braund, P. S., Brown, M. J., Burnett, M. S., Buysschaert, I., Carlquist, J. F., Chen, L., Cichon, S., Codd, V., Davies, R. W., Dedoussis, G., Dehghan, A., Demissie, S., Devaney, J. M., Diemert, P., Do, R., Doering, A., Eifert, S., El Mokhtari, N. E., Ellis, S. G., Elosua, R., Engert, J. C., Epstein, S. E., de Faire, U., Fischer, M., Folsom, A. R., Freyer, J., Gigante, B., Girelli, D., Gretarsdottir, S., Gudnason, V., Gulcher, J. R., Halperin, E., Hammond, N., Hazen, S. L., Hofman, A., Horne, B. D., Illig, T., Iribarren, C., Jones, G. T., Jukema, J. W., Kaiser, M. A., Kaplan, L. M., Kastelein, J. J., Khaw, K., Knowles, J. W., Kolovou, G., Kong, A., Laaksonen, R., Lambrechts, D., Leander, K., Lettre, G., Li, M., Lieb, W., Loley, C., Lotery, A. J., Mannucci, P. M., Maouche, S., Martinelli, N., McKeown, P. P., Meisinger, C., Meitinger, T., Melander, O., Merlini, P. A., Mooser, V., Morgan, T., Muehleisen, T. W., Muhlestein, J. B., Muenzel, T., Musunuru, K., Nahrstaedt, J., Nelson, C. P., Noethen, M. M., Olivieri, O., Patel, R. S., Patterson, C. C., Peters, A., Peyvandi, F., Qu, L., Quyyumi, A. A., Rader, D. J., Rallidis, L. S., Rice, C., Rosendaal, F. R., Rubin, D., Salomaa, V., Sampietro, M. L., Sandhu, M. S., Schadt, E., Schaefer, A., Schillert, A., Schreiber, S., Schrezenmeir, J., Schwartz, S. M., Siscovick, D. S., Sivananthan, M., Sivapalaratnam, S., Smith, A., Smith, T. B., Snoep, J. D., Soranzo, N., Spertus, J. A., Stark, K., Stirrups, K., Stoll, M., Tang, W. H., Tennstedt, S., Thorgeirsson, G., Thorleifsson, G., Tomaszewski, M., Uitterlinden, A. G., van Rij, A. M., Voight, B. F., Wareham, N. J., Wells, G. A., Wichmann, H., Wild, P. S., Willenborg, C., Witteman, J. C., Wright, B. J., Ye, S., Zeller, T., Ziegler, A., Cambien, F., Goodall, A. H., Cupples, L. A., Quertermous, T., Maerz, W., Hengstenberg, C., Blankenberg, S., Ouwehand, W. H., Hall, A. S., Deloukas, P., Thompson, J. R., Stefansson, K., Roberts, R., Thorsteinsdottir, U., O'Donnell, C. J., McPherson, R., Erdmann, J., Samani, N. J. 2011; 43 (4): 333-U153

    Abstract

    We performed a meta-analysis of 14 genome-wide association studies of coronary artery disease (CAD) comprising 22,233 individuals with CAD (cases) and 64,762 controls of European descent followed by genotyping of top association signals in 56,682 additional individuals. This analysis identified 13 loci newly associated with CAD at P < 5 × 10?? and confirmed the association of 10 of 12 previously reported CAD loci. The 13 new loci showed risk allele frequencies ranging from 0.13 to 0.91 and were associated with a 6% to 17% increase in the risk of CAD per allele. Notably, only three of the new loci showed significant association with traditional CAD risk factors and the majority lie in gene regions not previously implicated in the pathogenesis of CAD. Finally, five of the new CAD risk loci appear to have pleiotropic effects, showing strong association with various other human diseases or traits.

    View details for DOI 10.1038/ng.784

    View details for Web of Science ID 000288903700013

    View details for PubMedID 21378990

    View details for PubMedCentralID PMC3119261

  • Genome-Wide Association Analysis Identifies Variants Associated with Nonalcoholic Fatty Liver Disease That Have Distinct Effects on Metabolic Traits PLOS GENETICS Speliotes, E. K., Yerges-Armstrong, L. M., Wu, J., Hernaez, R., Kim, L. J., Palmer, C. D., Gudnason, V., Eiriksdottir, G., Garcia, M. E., Launer, L. J., Nalls, M. A., Clark, J. M., Mitchell, B. D., Shuldiner, A. R., Butler, J. L., Tomas, M., Hoffmann, U., Hwang, S., Massaro, J. M., O'Donnell, C. J., Sahani, D. V., Salomaa, V., Schadt, E. E., Schwartz, S. M., Siscovick, D. S., Voight, B. F., Carr, J. J., Feitosa, M. F., Harris, T. B., Fox, C. S., Smith, A. V., Kao, W. H., Hirschhorn, J. N., Borecki, I. B. 2011; 7 (3)

    Abstract

    Nonalcoholic fatty liver disease (NAFLD) clusters in families, but the only known common genetic variants influencing risk are near PNPLA3. We sought to identify additional genetic variants influencing NAFLD using genome-wide association (GWA) analysis of computed tomography (CT) measured hepatic steatosis, a non-invasive measure of NAFLD, in large population based samples. Using variance components methods, we show that CT hepatic steatosis is heritable (?26%-27%) in family-based Amish, Family Heart, and Framingham Heart Studies (n?=?880 to 3,070). By carrying out a fixed-effects meta-analysis of genome-wide association (GWA) results between CT hepatic steatosis and ?2.4 million imputed or genotyped SNPs in 7,176 individuals from the Old Order Amish, Age, Gene/Environment Susceptibility-Reykjavik study (AGES), Family Heart, and Framingham Heart Studies, we identify variants associated at genome-wide significant levels (p<5×10(-8)) in or near PNPLA3, NCAN, and PPP1R3B. We genotype these and 42 other top CT hepatic steatosis-associated SNPs in 592 subjects with biopsy-proven NAFLD from the NASH Clinical Research Network (NASH CRN). In comparisons with 1,405 healthy controls from the Myocardial Genetics Consortium (MIGen), we observe significant associations with histologic NAFLD at variants in or near NCAN, GCKR, LYPLAL1, and PNPLA3, but not PPP1R3B. Variants at these five loci exhibit distinct patterns of association with serum lipids, as well as glycemic and anthropometric traits. We identify common genetic variants influencing CT-assessed steatosis and risk of NAFLD. Hepatic steatosis associated variants are not uniformly associated with NASH/fibrosis or result in abnormalities in serum lipids or glycemic and anthropometric traits, suggesting genetic heterogeneity in the pathways influencing these traits.

    View details for DOI 10.1371/journal.pgen.1001324

    View details for Web of Science ID 000288996600006

    View details for PubMedID 21423719

  • Family History of Heart Disease The Re-Emergence of a Traditional Risk Factor JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY Assimes, T. L. 2011; 57 (5): 628-629

    View details for DOI 10.1016/j.jacc.2010.09.036

    View details for Web of Science ID 000286622400015

    View details for PubMedID 21272755

  • Identification of ADAMTS7 as a novel locus for coronary atherosclerosis and association of ABO with myocardial infarction in the presence of coronary atherosclerosis: two genome-wide association studies LANCET Reilly, M. P., Li, M., He, J., Ferguson, J. F., Stylianou, I. M., Mehta, N. N., Burnett, M. S., Devaney, J. M., Knouff, C. W., Thompson, J. R., Horne, B. D., Stewart, A. F., Assimes, T. L., Wild, P. S., Allayee, H., Nitschke, P. L., Patel, R. S., Martinelli, N., Girelli, D., Quyyumi, A. A., Anderson, J. L., Erdmann, J., Hall, A. S., Schunkert, H., Quertermous, T., Blankenberg, S., Hazen, S. L., Roberts, R., Kathiresan, S., Samani, N. J., Epstein, S. E., Rader, D. J. 2011; 377 (9763): 383-392

    Abstract

    We tested whether genetic factors distinctly contribute to either development of coronary atherosclerosis or, specifically, to myocardial infarction in existing coronary atherosclerosis.We did two genome-wide association studies (GWAS) with coronary angiographic phenotyping in participants of European ancestry. To identify loci that predispose to angiographic coronary artery disease (CAD), we compared individuals who had this disorder (n=12,393) with those who did not (controls, n=7383). To identify loci that predispose to myocardial infarction, we compared patients who had angiographic CAD and myocardial infarction (n=5783) with those who had angiographic CAD but no myocardial infarction (n=3644).In the comparison of patients with angiographic CAD versus controls, we identified a novel locus, ADAMTS7 (p=4·98×10(-13)). In the comparison of patients with angiographic CAD who had myocardial infarction versus those with angiographic CAD but no myocardial infarction, we identified a novel association at the ABO locus (p=7·62×10(-9)). The ABO association was attributable to the glycotransferase-deficient enzyme that encodes the ABO blood group O phenotype previously proposed to protect against myocardial infarction.Our findings indicate that specific genetic predispositions promote the development of coronary atherosclerosis whereas others lead to myocardial infarction in the presence of coronary atherosclerosis. The relation to specific CAD phenotypes might modify how novel loci are applied in personalised risk assessment and used in the development of novel therapies for CAD.The PennCath and MedStar studies were supported by the Cardiovascular Institute of the University of Pennsylvania, by the MedStar Health Research Institute at Washington Hospital Center and by a research grant from GlaxoSmithKline. The funding and support for the other cohorts contributing to the paper are described in the webappendix.

    View details for DOI 10.1016/S0140-6736(10)61996-4

    View details for Web of Science ID 000287337000028

    View details for PubMedID 21239051

  • Sex differences in the prevalence of peripheral artery disease in patients undergoing coronary catheterization VASCULAR MEDICINE Rafie, A. H., Stefanick, M. L., Sims, S. T., Phan, T., Higgins, M., Gabriel, A., Assimes, T., Narasimhan, B., Nead, K. T., Myers, J., Olin, J., Cooke, J. P. 2010; 15 (6): 443-450

    Abstract

    To determine whether there are sex differences in the prevalence of peripheral artery disease, we performed an observational study of 1014 men and 547 women, aged ? 40 years, referred for elective coronary angiography. Women were slightly older, more obese, had higher low-density lipoprotein cholesterol (LDL-C) levels and systolic blood pressure (BP), and were more likely to be African American. Women had higher high-density lipoprotein cholesterol (HDL-C) levels, lower diastolic BP, and were less likely to smoke or to have a history of cardiovascular disease. Women had less prevalent (62% vs 81%) and less severe coronary artery disease (CAD) (p < 0.001 for both) by coronary angiography, but more prevalent peripheral artery disease (PAD) as determined by the ankle-brachial index (ABI) than men (23.6% versus 17.2%). Independent predictors of lower ABI were female sex, black race, older age, tobacco use, CAD, diabetes, and triglyceride level. In a full multivariable logistic regression model, women had a risk-adjusted odds ratio for PAD of 1.78 (95% CI 1.25-2.54) relative to men. Among patients referred for coronary angiography, women have less prevalent and less severe CAD, but more prevalent PAD, a sex difference that is not explained by traditional cardiovascular disease risk factors or CAD severity. Clinical Trial Registration-URL: http://clinicaltrials.gov. Unique identifier: NCT00380185.

    View details for DOI 10.1177/1358863X10388345

    View details for Web of Science ID 000285574400002

    View details for PubMedID 21183651

  • Genetics of Coronary Atherosclerotic Plaque Rupture and Myocardial Infarction Ferguson, J. F., Li, M., He, J., Qasim, A. N., Burnett, M. S., Devaney, J. M., DerOhannessian, S. L., Knouff, C. W., Thompson, J. R., Stewart, A. F., Assimes, T. L., Barnard, J., Wild, P. S., Allayee, H., Braund, P. S., Absher, D., Chen, L., Hall, A. S., Quertermous, T., Blankenberg, S., Hazen, S. L., Roberts, R., McPherson, R., Kathiresan, S., Mooser, V., Hakonarson, H., Samani, N. J., Epstein, S. E., Rader, D. J., Reilly, M. P. LIPPINCOTT WILLIAMS & WILKINS. 2010

    View details for Web of Science ID 000208231601546

  • Lack of Association Between the Trp719Arg Polymorphism in Kinesin-Like Protein-6 and Coronary Artery Disease in 19 Case-Control Studies JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY Assimes, T. L., Holm, H., Kathiresan, S., Reilly, M. P., Thorleifsson, G., Voight, B. F., Erdmann, J., Willenborg, C., Vaidya, D., Xie, C., Patterson, C. C., Morgan, T. M., Burnett, M. S., Li, M., Hlatky, M. A., Knowles, J. W., Thompson, J. R., Absher, D., Iribarren, C., Go, A., Fortmann, S. P., Sidney, S., Risch, N., Tang, H., Myers, R. M., Berger, K., Stoll, M., Shah, S. H., Thorgeirsson, G., Andersen, K., Havulinna, A. S., Herrera, J. E., Faraday, N., Kim, Y., Kral, B. G., Mathias, R. A., Ruczinski, I., Suktitipat, B., Wilson, A. F., Yanek, L. R., Becker, L. C., Linsel-Nitschke, P., Lieb, W., Koenig, I. R., Hengstenberg, C., Fischer, M., Stark, K., Reinhard, W., Winogradow, J., Grassl, M., Grosshennig, A., Preuss, M., Schreiber, S., Wichmann, H., Meisinger, C., Yee, J., Friedlander, Y., Do, R., Meigs, J. B., Williams, G., Nathan, D. M., MacRae, C. A., Qu, L., Wilensky, R. L., Matthai, W. H., Qasim, A. N., Hakonarson, H., Pichard, A. D., Kent, K. M., Satler, L., Lindsay, J. M., Waksman, R., Knouff, C. W., Waterworth, D. M., Walker, M. C., Mooser, V. E., Marrugat, J., Lucas, G., Subirana, I., Sala, J., Ramos, R., Martinelli, N., Olivieri, O., Trabetti, E., Malerba, G., Pignatti, P. F., Guiducci, C., Mirel, D., Parkin, M., Hirschhorn, J. N., Asselta, R., Duga, S., Musunuru, K., Daly, M. J., Purcell, S., Eifert, S., Braund, P. S., Wright, B. J., Balmforth, A. J., Ball, S. G., Ouwehand, W. H., Deloukas, P., Scholz, M., Cambien, F., Huge, A., Scheffold, T., Salomaa, V., Girelli, D., Granger, C. B., Peltonen, L., McKeown, P. P., Altshuler, D., Melander, O., Devaney, J. M., Epstein, S. E., Rader, D. J., Elosua, R., Engert, J. C., Anand, S. S., Hall, A. S., Ziegler, A., O'Donnell, C. J., Spertus, J. A., Siscovick, D., Schwartz, S. M., Becker, D., Thorsteinsdottir, U., Stefansson, K., Schunkert, H., Samani, N. J., Quertermous, T. 2010; 56 (19): 1552-1563

    Abstract

    We sought to replicate the association between the kinesin-like protein 6 (KIF6) Trp719Arg polymorphism (rs20455), and clinical coronary artery disease (CAD).Recent prospective studies suggest that carriers of the 719Arg allele in KIF6 are at increased risk of clinical CAD compared with noncarriers.The KIF6 Trp719Arg polymorphism (rs20455) was genotyped in 19 case-control studies of nonfatal CAD either as part of a genome-wide association study or in a formal attempt to replicate the initial positive reports.A total of 17,000 cases and 39,369 controls of European descent as well as a modest number of South Asians, African Americans, Hispanics, East Asians, and admixed cases and controls were successfully genotyped. None of the 19 studies demonstrated an increased risk of CAD in carriers of the 719Arg allele compared with noncarriers. Regression analyses and fixed-effects meta-analyses ruled out with high degree of confidence an increase of ?2% in the risk of CAD among European 719Arg carriers. We also observed no increase in the risk of CAD among 719Arg carriers in the subset of Europeans with early-onset disease (younger than 50 years of age for men and younger than 60 years of age for women) compared with similarly aged controls as well as all non-European subgroups.The KIF6 Trp719Arg polymorphism was not associated with the risk of clinical CAD in this large replication study.

    View details for DOI 10.1016/j.jacc.2010.06.022

    View details for Web of Science ID 000283538000005

    View details for PubMedID 20933357

    View details for PubMedCentralID PMC3084526

  • Meta-analysis identifies 13 new loci associated with waist-hip ratio and reveals sexual dimorphism in the genetic basis of fat distribution NATURE GENETICS Heid, I. M., Jackson, A. U., Randall, J. C., Winkler, T. W., Qi, L., Steinthorsdottir, V., Thorleifsson, G., Zillikens, M. C., Speliotes, E. K., Maegi, R., Workalemahu, T., White, C. C., Bouatia-Naji, N., Harris, T. B., Berndt, S. I., Ingelsson, E., Willer, C. J., Weedon, M. N., Luan, J., Vedantam, S., Esko, T., Kilpelaeinen, T. O., Kutalik, Z., Li, S., Monda, K. L., Dixon, A. L., Holmes, C. C., Kaplan, L. M., Liang, L., Min, J. L., Moffatt, M. F., Molony, C., Nicholson, G., Schadt, E. E., Zondervan, K. T., Feitosa, M. F., Ferreira, T., Allen, H. L., Weyant, R. J., Wheeler, E., Wood, A. R., Estrada, K., Goddard, M. E., Lettre, G., Mangino, M., Nyholt, D. R., Purcell, S., Smith, A. V., Visscher, P. M., Yang, J., McCarroll, S. A., Nemesh, J., Voight, B. F., Absher, D., Amin, N., Aspelund, T., Coin, L., Glazer, N. L., Hayward, C., Heard-Costa, N. L., Hottenga, J., Johansson, A., Johnson, T., Kaakinen, M., Kapur, K., Ketkar, S., Knowles, J. W., Kraft, P., Kraja, A. T., Lamina, C., Leitzmann, M. F., McKnight, B., Morris, A. P., Ong, K. K., Perry, J. R., Peters, M. J., Polasek, O., Prokopenko, I., Rayner, N. W., Ripatti, S., Rivadeneira, F., Robertson, N. R., Sanna, S., Sovio, U., Surakka, I., Teumer, A., van Wingerden, S., Vitart, V., Zhao, J. H., Cavalcanti-Proenca, C., Chines, P. S., Fisher, E., Kulzer, J. R., Lecoeur, C., Narisu, N., Sandholt, C., Scott, L. J., Silander, K., Stark, K., Tammesoo, M., Teslovich, T. M., Timpson, N. J., Watanabe, R. M., Welch, R., Chasman, D. I., Cooper, M. N., Jansson, J., Kettunen, J., Lawrence, R. W., Pellikka, N., Perola, M., Vandenput, L., Alavere, H., Almgren, P., Atwood, L. D., Bennett, A. J., Biffar, R., Bonnycastle, L. L., Bornstein, S. R., Buchanan, T. A., Campbell, H., Day, I. N., Dei, M., Doerr, M., Elliott, P., Erdos, M. R., Eriksson, J. G., Freimer, N. B., Fu, M., Gaget, S., Geus, E. J., Gjesing, A. P., Grallert, H., Graessler, J., Groves, C. J., Guiducci, C., Hartikainen, A., Hassanali, N., Havulinna, A. S., Herzig, K., Hicks, A. A., Hui, J., Igl, W., Jousilahti, P., Jula, A., Kajantie, E., Kinnunen, L., Kolcic, I., Koskinen, S., Kovacs, P., Kroemer, H. K., Krzelj, V., Kuusisto, J., Kvaloy, K., Laitinen, J., Lantieri, O., Lathrop, G. M., Lokki, M., Luben, R. N., Ludwig, B., McArdle, W. L., McCarthy, A., Morken, M. A., Nelis, M., Neville, M. J., Pare, G., Parker, A. N., Peden, J. F., Pichler, I., Pietilainen, K. H., Platou, C. G., Pouta, A., Ridderstrale, M., Samani, N. J., Saramies, J., Sinisalo, J., Smit, J. H., Strawbridge, R. J., Stringham, H. M., Swift, A. J., Teder-Laving, M., Thomson, B., Usala, G., van Meurs, J. B., van Ommen, G., Vatin, V., Volpato, C. B., Wallaschofski, H., Walters, G. B., Widen, E., Wild, S. H., Willemsen, G., Witte, D. R., Zgaga, L., Zitting, P., Beilby, J. P., James, A. L., Kahonen, M., Lehtimaki, T., Nieminen, M. S., Ohlsson, C., Palmer, L. J., Raitakari, O., Ridker, P. M., Stumvoll, M., Toenjes, A., Viikari, J., Balkau, B., Ben-Shlomo, Y., Bergman, R. N., Boeing, H., Smith, G. D., Ebrahim, S., Froguel, P., Hansen, T., Hengstenberg, C., Hveem, K., Isomaa, B., Jorgensen, T., Karpe, F., Khaw, K., Laakso, M., Lawlor, D. A., Marre, M., Meitinger, T., Metspalu, A., Midthjell, K., Pedersen, O., Salomaa, V., Schwarz, P. E., Tuomi, T., Tuomilehto, J., Valle, T. T., Wareham, N. J., Arnold, A. M., Beckmann, J. S., Bergmann, S., Boerwinkle, E., Boomsma, D. I., Caulfield, M. J., Collins, F. S., Eiriksdottir, G., Gudnason, V., Gyllensten, U., Hamsten, A., Hattersley, A. T., Hofman, A., Hu, F. B., Illig, T., Iribarren, C., Jarvelin, M., Kao, W. H., Kaprio, J., Launer, L. J., Munroe, P. B., Oostra, B., Penninx, B. W., Pramstaller, P. P., Psaty, B. M., Quertermous, T., Rissanen, A., Rudan, I., Shuldiner, A. R., Soranzo, N., Spector, T. D., Syvanen, A., Uda, M., Uitterlinden, A., Voelzke, H., Vollenweider, P., Wilson, J. F., Witteman, J. C., Wright, A. F., Abecasis, G. R., Boehnke, M., Borecki, I. B., Deloukas, P., Frayling, T. M., Groop, L. C., Haritunians, T., Hunter, D. J., Kaplan, R. C., North, K. E., O'Connell, J. R., Peltonen, L., Schlessinger, D., Strachan, D. P., Hirschhorn, J. N., Assimes, T. L., Wichmann, H., Thorsteinsdottir, U., van Duijn, C. M., Stefansson, K., Cupples, L. A., Loos, R. J., Barroso, I., McCarthy, M. I., Fox, C. S., Mohlke, K. L., Lindgren, C. M. 2010; 42 (11): 949-U160

    Abstract

    Waist-hip ratio (WHR) is a measure of body fat distribution and a predictor of metabolic consequences independent of overall adiposity. WHR is heritable, but few genetic variants influencing this trait have been identified. We conducted a meta-analysis of 32 genome-wide association studies for WHR adjusted for body mass index (comprising up to 77,167 participants), following up 16 loci in an additional 29 studies (comprising up to 113,636 subjects). We identified 13 new loci in or near RSPO3, VEGFA, TBX15-WARS2, NFE2L3, GRB14, DNM3-PIGC, ITPR2-SSPN, LY86, HOXC13, ADAMTS9, ZNRF3-KREMEN1, NISCH-STAB1 and CPEB4 (P = 1.9 × 10?? to P = 1.8 × 10???) and the known signal at LYPLAL1. Seven of these loci exhibited marked sexual dimorphism, all with a stronger effect on WHR in women than men (P for sex difference = 1.9 × 10?³ to P = 1.2 × 10?¹³). These findings provide evidence for multiple loci that modulate body fat distribution independent of overall adiposity and reveal strong gene-by-sex interactions.

    View details for DOI 10.1038/ng.685

    View details for Web of Science ID 000283540500011

    View details for PubMedID 20935629

  • Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index NATURE GENETICS Speliotes, E. K., Willer, C. J., Berndt, S. I., Monda, K. L., Thorleifsson, G., Jackson, A. U., Allen, H. L., Lindgren, C. M., Luan, J., Maegi, R., Randall, J. C., Vedantam, S., Winkler, T. W., Qi, L., Workalemahu, T., Heid, I. M., Steinthorsdottir, V., Stringham, H. M., Weedon, M. N., Wheeler, E., Wood, A. R., Ferreira, T., Weyant, R. J., Segre, A. V., Estrada, K., Liang, L., Nemesh, J., Park, J., Gustafsson, S., Kilpelaenen, T. O., Yang, J., Bouatia-Naji, N., Esko, T., Feitosa, M. F., Kutalik, Z., Mangino, M., Raychaudhuri, S., Scherag, A., Smith, A. V., Welch, R., Zhao, J. H., Aben, K. K., Absher, D. M., Amin, N., Dixon, A. L., Fisher, E., Glazer, N. L., Goddard, M. E., Heard-Costa, N. L., Hoesel, V., Hottenga, J., Johansson, A., Johnson, T., Ketkar, S., Lamina, C., Li, S., Moffatt, M. F., Myers, R. H., Narisu, N., Perry, J. R., Peters, M. J., Preuss, M., Ripatti, S., Rivadeneira, F., Sandholt, C., Scott, L. J., Timpson, N. J., Tyrer, J. P., van Wingerden, S., Watanabe, R. M., White, C. C., Wiklund, F., Barlassina, C., Chasman, D. I., Cooper, M. N., Jansson, J., Lawrence, R. W., Pellikka, N., Prokopenko, I., Shi, J., Thiering, E., Alavere, H., Alibrandi, M. T., Almgren, P., Arnold, A. M., Aspelund, T., Atwood, L. D., Balkau, B., Balmforth, A. J., Bennett, A. J., Ben-Shlomo, Y., Bergman, R. N., Bergmann, S., Biebermann, H., Blakemore, A. I., Boes, T., Bonnycastle, L. L., Bornstein, S. R., Brown, M. J., Buchanan, T. A., Busonero, F., Campbell, H., Cappuccio, F. P., Cavalcanti-Proenca, C., Chen, Y. I., Chen, C., Chines, P. S., Clarke, R., Coin, L., Connell, J., Day, I. N., den Heijer, M., Duan, J., Ebrahim, S., Elliott, P., Elosua, R., Eiriksdottir, G., Erdos, M. R., Eriksson, J. G., Facheris, M. F., Felix, S. B., Fischer-Posovszky, P., Folsom, A. R., Friedrich, N., Freimer, N. B., Fu, M., Gaget, S., Gejman, P. V., Geus, E. J., Gieger, C., Gjesing, A. P., Goel, A., Goyette, P., Grallert, H., Graessler, J., Greenawalt, D. M., Groves, C. J., Gudnason, V., Guiducci, C., Hartikainen, A., Hassanali, N., Hall, A. S., Havulinna, A. S., Hayward, C., Heath, A. C., Hengstenberg, C., Hicks, A. A., Hinney, A., Hofman, A., Homuth, G., Hui, J., Igl, W., Iribarren, C., Isomaa, B., Jacobs, K. B., Jarick, I., Jewell, E., John, U., Jorgensen, T., Jousilahti, P., Jula, A., Kaakinen, M., Kajantie, E., Kaplan, L. M., Kathiresan, S., Kettunen, J., Kinnunen, L., Knowles, J. W., Kolcic, I., Koenig, I. R., Koskinen, S., Kovacs, P., Kuusisto, J., Kraft, P., Kvaloy, K., Laitinen, J., Lantieri, O., Lanzani, C., Launer, L. J., Lecoeur, C., Lehtimaeki, T., Lettre, G., Liu, J., Lokki, M., Lorentzon, M., Luben, R. N., Ludwig, B., Manunta, P., Marek, D., Marre, M., Martin, N. G., McArdle, W. L., McCarthy, A., McKnight, B., Meitinger, T., Melander, O., Meyre, D., Midthjell, K., Montgomery, G. W., Morken, M. A., Morris, A. P., Mulic, R., Ngwa, J. S., Nelis, M., Neville, M. J., Nyholt, D. R., O'Donnell, C. J., O'Rahilly, S., Ong, K. K., Oostra, B., Pare, G., Parker, A. N., Perola, M., Pichler, I., Pietilaeinen, K. H., Platou, C. G., Polasek, O., Pouta, A., Rafelt, S., Raitakari, O., Rayner, N. W., Ridderstrale, M., Rief, W., Ruokonen, A., Robertson, N. R., Rzehak, P., Salomaa, V., Sanders, A. R., Sandhu, M. S., Sanna, S., Saramies, J., Savolainen, M. J., Scherag, S., Schipf, S., Schreiber, S., Schunkert, H., Silander, K., Sinisalo, J., Siscovick, D. S., Smit, J. H., Soranzo, N., Sovio, U., Stephens, J., Surakka, I., Swift, A. J., Tammesoo, M., Tardif, J., Teder-Laving, M., Teslovich, T. M., Thompson, J. R., Thomson, B., Toenjes, A., Tuomi, T., van Meurs, J. B., van Ommen, G., Vatin, V., Viikari, J., Visvikis-Siest, S., Vitart, V., Vogel, C. I., Voight, B. F., Waite, L. L., Wallaschofski, H., Walters, G. B., Widen, E., Wiegand, S., Wild, S. H., Willemsen, G., Witte, D. R., Witteman, J. C., Xu, J., Zhang, Q., Zgaga, L., Ziegler, A., Zitting, P., Beilby, J. P., Farooqi, I. S., Hebebrand, J., Huikuri, H. V., James, A. L., Kaehoenen, M., Levinson, D. F., Macciardi, F., Nieminen, M. S., Ohlsson, C., Palmer, L. J., Ridker, P. M., Stumvoll, M., Beckmann, J. S., Boeing, H., Boerwinkle, E., Boomsma, D. I., Caulfield, M. J., Chanock, S. J., Collins, F. S., Cupples, L. A., Smith, G. D., Erdmann, J., Froguel, P., Greonberg, H., Gyllensten, U., Hall, P., Hansen, T., Harris, T. B., Hattersley, A. T., Hayes, R. B., Heinrich, J., Hu, F. B., Hveem, K., Illig, T., Jarvelin, M., Kaprio, J., Karpe, F., Khaw, K., Kiemeney, L. A., Krude, H., Laakso, M., Lawlor, D. A., Metspalu, A., Munroe, P. B., Ouwehand, W. H., Pedersen, O., Penninx, B. W., Peters, A., Pramstaller, P. P., Quertermous, T., Reinehr, T., Rissanen, A., Rudan, I., Samani, N. J., Schwarz, P. E., Shuldiner, A. R., Spector, T. D., Tuomilehto, J., Uda, M., Uitterlinden, A., Valle, T. T., Wabitsch, M., Waeber, G., Wareham, N. J., Watkins, H., Wilson, J. F., Wright, A. F., Zillikens, M. C., Chatterjee, N., McCarroll, S. A., Purcell, S., Schadt, E. E., Visscher, P. M., Assimes, T. L., Borecki, I. B., Deloukas, P., Fox, C. S., Groop, L. C., Haritunians, T., Hunter, D. J., Kaplan, R. C., Mohlke, K. L., O'Connell, J. R., Peltonen, L., Schlessinger, D., Strachan, D. P., van Duijn, C. M., Wichmann, H., Frayling, T. M., Thorsteinsdottir, U., Abecasis, G. R., Barroso, I., Boehnke, M., Stefansson, K., North, K. E., McCarthy, M. I., Hirschhorn, J. N., Ingelsson, E., Loos, R. J. 2010; 42 (11): 937-U53

    Abstract

    Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and ? 2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 × 10??), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation.

    View details for DOI 10.1038/ng.686

    View details for Web of Science ID 000283540500010

    View details for PubMedID 20935630

  • Hundreds of variants clustered in genomic loci and biological pathways affect human height NATURE Allen, H. L., Estrada, K., Lettre, G., Berndt, S. I., Weedon, M. N., Rivadeneira, F., Willer, C. J., Jackson, A. U., Vedantam, S., Raychaudhuri, S., Ferreira, T., Wood, A. R., Weyant, R. J., Segre, A. V., Speliotes, E. K., Wheeler, E., Soranzo, N., Park, J., Yang, J., Gudbjartsson, D., Heard-Costa, N. L., Randall, J. C., Qi, L., Smith, A. V., Maegi, R., Pastinen, T., Liang, L., Heid, I. M., Luan, J., Thorleifsson, G., Winkler, T. W., Goddard, M. E., Lo, K. S., Palmer, C., Workalemahu, T., Aulchenko, Y. S., Johansson, A., Zillikens, M. C., Feitosa, M. F., Esko, T., Johnson, T., Ketkar, S., Kraft, P., Mangino, M., Prokopenko, I., Absher, D., Albrecht, E., Ernst, F., Glazer, N. L., Hayward, C., Hottenga, J., Jacobs, K. B., Knowles, J. W., Kutalik, Z., Monda, K. L., Polasek, O., Preuss, M., Rayner, N. W., Robertson, N. R., Steinthorsdottir, V., Tyrer, J. P., Voight, B. F., Wiklund, F., Xu, J., Zhao, J. H., Nyholt, D. R., Pellikka, N., Perola, M., Perry, J. R., Surakka, I., Tammesoo, M., Altmaier, E. L., Amin, N., Aspelund, T., Bhangale, T., Boucher, G., Chasman, D. I., Chen, C., Coin, L., Cooper, M. N., Dixon, A. L., Gibson, Q., Grundberg, E., Hao, K., Junttila, M. J., Kaplan, L. M., Kettunen, J., Koenig, I. R., Kwan, T., Lawrence, R. W., Levinson, D. F., Lorentzon, M., McKnight, B., Morris, A. P., Mueller, M., Ngwa, J. S., Purcell, S., Rafelt, S., Salem, R. M., Salvi, E., Sanna, S., Shi, J., Sovio, U., Thompson, J. R., Turchin, M. C., Vandenput, L., Verlaan, D. J., Vitart, V., White, C. C., Ziegler, A., Almgren, P., Balmforth, A. J., Campbell, H., Citterio, L., de Grandi, A., Dominiczak, A., Duan, J., Elliott, P., Elosua, R., Eriksson, J. G., Freimer, N. B., Geus, E. J., Glorioso, N., Haiqing, S., Hartikainen, A., Havulinna, A. S., Hicks, A. A., Hui, J., Igl, W., Illig, T., Jula, A., Kajantie, E., Kilpelaeinen, T. O., Koiranen, M., Kolcic, I., Koskinen, S., Kovacs, P., Laitinen, J., Liu, J., Lokki, M., Marusic, A., Maschio, A., Meitinger, T., Mulas, A., Pare, G., Parker, A. N., Peden, J. F., Petersmann, A., Pichler, I., Pietilainen, K. H., Pouta, A., Riddertrale, M., Rotter, J. I., Sambrook, J. G., Sanders, A. R., Schmidt, C. O., Sinisalo, J., Smit, J. H., Stringham, H. M., Walters, G. B., Widen, E., Wild, S. H., Willemsen, G., Zagato, L., Zgaga, L., Zitting, P., Alavere, H., Farrall, M., McArdle, W. L., Nelis, M., Peters, M. J., Ripatti, S., vVan Meurs, J. B., Aben, K. K., Ardlie, K. G., Beckmann, J. S., Beilby, J. P., Bergman, R. N., Bergmann, S., Collins, F. S., Cusi, D., den Heijer, M., Eiriksdottir, G., Gejman, P. V., Hall, A. S., Hamsten, A., Huikuri, H. V., Iribarren, C., Kahonen, M., Kaprio, J., Kathiresan, S., Kiemeney, L., Kocher, T., Launer, L. J., Lehtimaki, T., Melander, O., Mosley, T. H., Musk, A. W., Nieminen, M. S., O'Donnell, C. J., Ohlsson, C., Oostra, B., Palmer, L. J., Raitakari, O., Ridker, P. M., Rioux, J. D., Rissanen, A., Rivolta, C., Schunkert, H., Shuldiner, A. R., Siscovick, D. S., Stumvoll, M., Toenjes, A., Tuomilehto, J., van Ommen, G., Viikari, J., Heath, A. C., Martin, N. G., Montgomery, G. W., Province, M. A., Kayser, M., Arnold, A. M., Atwood, L. D., Boerwinkle, E., Chanock, S. J., Deloukas, P., Gieger, C., Gronberg, H., Hall, P., Hattersley, A. T., Hengstenberg, C., Hoffman, W., Lathrop, G. M., Salomaa, V., Schreiber, S., Uda, M., Waterworth, D., Wright, A. F., Assimes, T. L., Barroso, I., Hofman, A., Mohlke, K. L., Boomsma, D. I., Caulfield, M. J., Cupples, L. A., Erdmann, J., Fox, C. S., Gudnason, V., Gyllensten, U., Harris, T. B., Hayes, R. B., Jarvelin, M., Mooser, V., Munroe, P. B., Ouwehand, W. H., Penninx, B. W., Pramstaller, P. P., Quertermous, T., Rudan, I., Samani, N. J., Spector, T. D., Voelzke, H., Watkins, H., Wilson, J. F., Groop, L. C., Haritunians, T., Hu, F. B., Kaplan, R. C., Metspalu, A., North, K. E., Schlessinger, D., Wareham, N. J., Hunter, D. J., O'Connell, J. R., Strachan, D. P., Schadt, H., Thorsteinsdottir, U., Peltonen, L., Uitterlinden, A. G., Visscher, P. M., Chatterjee, N., Loos, R. J., Boehnke, M., McCarthy, M. I., Ingelsson, E., Lindgren, C. M., Abecasis, G. R., Stefansson, K., Frayling, T. M., Hirschhorn, J. N. 2010; 467 (7317): 832-838

    Abstract

    Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P?

    View details for DOI 10.1038/nature09410

    View details for Web of Science ID 000282898700065

    View details for PubMedID 20881960

  • Design of the Coronary ARtery DIsease Genome-Wide Replication And Meta-Analysis (CARDIoGRAM) Study A Genome-Wide Association Meta-analysis Involving More Than 22 000 Cases and 60 000 Controls CIRCULATION-CARDIOVASCULAR GENETICS Preuss, M., Koenig, I. R., Thompson, J. R., Erdmann, J., Absher, D., Assimes, T. L., Blankenberg, S., Boerwinkle, E., Chen, L., Cupples, L. A., Hall, A. S., Halperin, E., Hengstenberg, C., Holm, H., Laaksonen, R., Li, M., Maerz, W., McPherson, R., Musunuru, K., Nelson, C. P., Burnett, M. S., Epstein, S. E., O'Donnell, C. J., Quertermous, T., Rader, D. J., Roberts, R., Schillert, A., Stefansson, K., Stewart, A. F., Thorleifsson, G., Voight, B. F., Wells, G. A., Ziegler, A., Kathiresan, S., Reilly, M. P., Samani, N. J., Schunkert, H. 2010; 3 (5): 475-U186

    Abstract

    Recent genome-wide association studies (GWAS) of myocardial infarction (MI) and other forms of coronary artery disease (CAD) have led to the discovery of at least 13 genetic loci. In addition to the effect size, power to detect associations is largely driven by sample size. Therefore, to maximize the chance of finding novel susceptibility loci for CAD and MI, the Coronary ARtery DIsease Genome-wide Replication And Meta-analysis (CARDIoGRAM) consortium was formed.CARDIoGRAM combines data from all published and several unpublished GWAS in individuals with European ancestry; includes >22 000 cases with CAD, MI, or both and >60 000 controls; and unifies samples from the Atherosclerotic Disease VAscular functioN and genetiC Epidemiology study, CADomics, Cohorts for Heart and Aging Research in Genomic Epidemiology, deCODE, the German Myocardial Infarction Family Studies I, II, and III, Ludwigshafen Risk and Cardiovascular Heath Study/AtheroRemo, MedStar, Myocardial Infarction Genetics Consortium, Ottawa Heart Genomics Study, PennCath, and the Wellcome Trust Case Control Consortium. Genotyping was carried out on Affymetrix or Illumina platforms followed by imputation of genotypes in most studies. On average, 2.2 million single nucleotide polymorphisms were generated per study. The results from each study are combined using meta-analysis. As proof of principle, we meta-analyzed risk variants at 9p21 and found that rs1333049 confers a 29% increase in risk for MI per copy (P=2×10?²?).CARDIoGRAM is poised to contribute to our understanding of the role of common genetic variation on risk for CAD and MI.

    View details for DOI 10.1161/CIRCGENETICS.109.899443

    View details for Web of Science ID 000283163100012

    View details for PubMedID 20923989

  • Call to Action: Cardiovascular Disease in Asian Americans A Science Advisory From the American Heart Association CIRCULATION Palaniappan, L. P., Araneta, M. R., Assimes, T. L., Barrett-Connor, E. L., Carnethon, M. R., Criqui, M. H., Fung, G. L., Narayan, K. M., Patel, H., Taylor-Piliae, R. E., Wilson, P. W., Wong, N. D. 2010; 122 (12): 1242-1252

    View details for DOI 10.1161/CIR.0b013e3181f22af4

    View details for Web of Science ID 000282042100014

    View details for PubMedID 20733105

  • Biological, clinical and population relevance of 95 loci for blood lipids NATURE Teslovich, T. M., Musunuru, K., Smith, A. V., Edmondson, A. C., Stylianou, I. M., Koseki, M., Pirruccello, J. P., Ripatti, S., Chasman, D. I., Willer, C. J., Johansen, C. T., Fouchier, S. W., Isaacs, A., Peloso, G. M., Barbalic, M., Ricketts, S. L., Bis, J. C., Aulchenko, Y. S., Thorleifsson, G., Feitosa, M. F., Chambers, J., Orho-Melander, M., Melander, O., Johnson, T., Li, X., Guo, X., Li, M., Cho, Y. S., Go, M. J., Kim, Y. J., Lee, J., Park, T., Kim, K., Sim, X., Ong, R. T., Croteau-Chonka, D. C., Lange, L. A., Smith, J. D., Song, K., Zhao, J. H., Yuan, X., Luan, J., Lamina, C., Ziegler, A., Zhang, W., Zee, R. Y., Wright, A. F., Witteman, J. C., Wilson, J. F., Willemsen, G., Wichmann, H., Whitfield, J. B., Waterworth, D. M., Wareham, N. J., Waeber, G., Vollenweider, P., Voight, B. F., Vitart, V., Uitterlinden, A. G., Uda, M., Tuomilehto, J., Thompson, J. R., Tanaka, T., Surakka, I., Stringham, H. M., Spector, T. D., Soranzo, N., Smit, J. H., Sinisalo, J., Silander, K., Sijbrands, E. J., Scuteri, A., Scott, J., Schlessinger, D., Sanna, S., Salomaa, V., Saharinen, J., Sabatti, C., Ruokonen, A., Rudan, I., Rose, L. M., Roberts, R., Rieder, M., Psaty, B. M., Pramstaller, P. P., Pichler, I., Perola, M., Penninx, B. W., Pedersen, N. L., Pattaro, C., Parker, A. N., Pare, G., Oostra, B. A., O'Donnell, C. J., Nieminen, M. S., Nickerson, D. A., Montgomery, G. W., Meitinger, T., McPherson, R., McCarthy, M. I., McArdle, W., Masson, D., Martin, N. G., Marroni, F., Mangino, M., Magnusson, P. K., Lucas, G., Luben, R., Loos, R. J., Lokki, M., Lettre, G., Langenberg, C., Launer, L. J., Lakatta, E. G., Laaksonen, R., Kyvik, K. O., Kronenberg, F., Koenig, I. R., Khaw, K., Kaprio, J., Kaplan, L. M., Johansson, A., Jarvelin, M., Janssens, A. C., Ingelsson, E., Igi, W., Hovingh, G. K., Hottenga, J., Hofman, A., Hicks, A. A., Hengstenberg, C., Heid, I. M., Hayward, C., Havulinna, A. S., Hastie, N. D., Harris, T. B., Haritunians, T., Hall, A. S., Gyllensten, U., Guiducci, C., Groop, L. C., Gonzalez, E., Gieger, C., Freimer, N. B., Ferrucci, L., Erdmann, J., Elliott, P., Ejebe, K. G., Doering, A., Dominiczak, A. F., Demissie, S., Deloukas, P., de Geus, E. J., de Faire, U., Crawford, G., Collins, F. S., Chen, Y. I., Caulfield, M. J., Campbell, H., Burtt, N. P., Bonnycastle, L. L., Boomsma, D. I., Boekholdt, S. M., Bergman, R. N., Barroso, I., Bandinelli, S., Ballantyne, C. M., Assimes, T. L., Quertermous, T., Altshuler, D., Seielstad, M., Wong, T. Y., Tai, E., Feranil, A. B., Kuzawa, C. W., Adair, L. S., Taylor, H. A., Borecki, I. B., Gabriel, S. B., Wilson, J. G., Holm, H., Thorsteinsdottir, U., Gudnason, V., Krauss, R. M., Mohlke, K. L., Ordovas, J. M., Munroe, P. B., Kooner, J. S., Tall, A. R., Hegele, R. A., Kastelein, J. J., Schadt, E. E., Rotter, J. I., Boerwinkle, E., Strachan, D. P., Mooser, V., Stefansson, K., Reilly, M. P., Samani, N. J., Schunkert, H., Cupples, L. A., Sandhu, M. S., Ridker, P. M., Rader, D. J., van Duijn, C. M., Peltonen, L., Abecasis, G. R., Boehnke, M., Kathiresan, S. 2010; 466 (7307): 707-713

    Abstract

    Plasma concentrations of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides are among the most important risk factors for coronary artery disease (CAD) and are targets for therapeutic intervention. We screened the genome for common variants associated with plasma lipids in >100,000 individuals of European ancestry. Here we report 95 significantly associated loci (P < 5 x 10(-8)), with 59 showing genome-wide significant association with lipid traits for the first time. The newly reported associations include single nucleotide polymorphisms (SNPs) near known lipid regulators (for example, CYP7A1, NPC1L1 and SCARB1) as well as in scores of loci not previously implicated in lipoprotein metabolism. The 95 loci contribute not only to normal variation in lipid traits but also to extreme lipid phenotypes and have an impact on lipid traits in three non-European populations (East Asians, South Asians and African Americans). Our results identify several novel loci associated with plasma lipids that are also associated with CAD. Finally, we validated three of the novel genes-GALNT2, PPP1R3B and TTC39B-with experiments in mouse models. Taken together, our findings provide the foundation to develop a broader biological understanding of lipoprotein metabolism and to identify new therapeutic opportunities for the prevention of CAD.

    View details for DOI 10.1038/nature09270

    View details for Web of Science ID 000280562500029

    View details for PubMedID 20686565

  • An "Almost Exhaustive" Search-Based Sequential Permutation Method for Detecting Epistasis in Disease Association Studies GENETIC EPIDEMIOLOGY Ma, L., Assimes, T. L., Asadi, N. B., Iribarren, C., Quertermous, T., Wong, W. H. 2010; 34 (5): 434-443

    Abstract

    Due to the complex nature of common diseases, their etiology is likely to involve "uncommon but strong" (UBS) interactive effects--i.e. allelic combinations that are each present in only a small fraction of the patients but associated with high disease risk. However, the identification of such effects using standard methods for testing association can be difficult. In this work, we introduce a method for testing interactions that is particularly powerful in detecting UBS effects. The method consists of two modules--one is a pattern counting algorithm designed for efficiently evaluating the risk significance of each marker combination, and the other is a sequential permutation scheme for multiple testing correction. We demonstrate the work of our method using a candidate gene data set for cardiovascular and coronary diseases with an injected UBS three-locus interaction. In addition, we investigate the power and false rejection properties of our method using data sets simulated from a joint dominance three-locus model that gives rise to UBS interactive effects. The results show that our method can be much more powerful than standard approaches such as trend test and multifactor dimensionality reduction for detecting UBS interactions.

    View details for DOI 10.1002/gepi.20496

    View details for Web of Science ID 000280349600007

    View details for PubMedID 20583286

  • Detailed Physiologic Characterization Reveals Diverse Mechanisms for Novel Genetic Loci Regulating Glucose and Insulin Metabolism in Humans 59th Annual Meeting of the American-Society-of-Human-Genetics Ingelsson, E., Langenberg, C., Hivert, M., Prokopenko, I., Lyssenko, V., Dupuis, J., Maegi, R., Sharp, S., Jackson, A. U., Assimes, T. L., Shrader, P., Knowles, J. W., Zethelius, B., Abbasi, F. A., Bergman, R. N., Bergmann, A., Berne, C., Boehnke, M., Bonnycastle, L. L., Bornstein, S. R., Buchanan, T. A., Bumpstead, S. J., Boettcher, Y., Chines, P., Collins, F. S., Cooper, C. C., Dennison, E. M., Erdos, M. R., Ferrannini, E., Fox, C. S., Graessler, J., Hao, K., Isomaa, B., Jameson, K. A., Kovacs, P., Kuusisto, J., Laakso, M., Ladenval, C., Mohlke, K. L., Morken, M. A., Narisu, N., Nathan, D. M., Pascoe, L., Payne, F., Petrie, J. R., Sayer, A. A., Schwarz, P. E., Scott, L. J., Stringham, H. M., Stumvoll, M., Swift, A. J., Syvanen, A., Tuomi, T., Tuomilehto, J., Tonjes, A., Valle, T. T., Williams, G. H., Lind, L., Barroso, I., Quertermous, T., Walker, M., Wareham, N. J., Meigs, J. B., McCarthy, M. I., Groop, L., Watanabe, R. M., Florez, J. C. AMER DIABETES ASSOC. 2010: 1266?75

    Abstract

    OBJECTIVE Recent genome-wide association studies have revealed loci associated with glucose and insulin-related traits. We aimed to characterize 19 such loci using detailed measures of insulin processing, secretion, and sensitivity to help elucidate their role in regulation of glucose control, insulin secretion and/or action. RESEARCH DESIGN AND METHODS We investigated associations of loci identified by the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC) with circulating proinsulin, measures of insulin secretion and sensitivity from oral glucose tolerance tests (OGTTs), euglycemic clamps, insulin suppression tests, or frequently sampled intravenous glucose tolerance tests in nondiabetic humans (n = 29,084). RESULTS The glucose-raising allele in MADD was associated with abnormal insulin processing (a dramatic effect on higher proinsulin levels, but no association with insulinogenic index) at extremely persuasive levels of statistical significance (P = 2.1 x 10(-71)). Defects in insulin processing and insulin secretion were seen in glucose-raising allele carriers at TCF7L2, SCL30A8, GIPR, and C2CD4B. Abnormalities in early insulin secretion were suggested in glucose-raising allele carriers at MTNR1B, GCK, FADS1, DGKB, and PROX1 (lower insulinogenic index; no association with proinsulin or insulin sensitivity). Two loci previously associated with fasting insulin (GCKR and IGF1) were associated with OGTT-derived insulin sensitivity indices in a consistent direction. CONCLUSIONS Genetic loci identified through their effect on hyperglycemia and/or hyperinsulinemia demonstrate considerable heterogeneity in associations with measures of insulin processing, secretion, and sensitivity. Our findings emphasize the importance of detailed physiological characterization of such loci for improved understanding of pathways associated with alterations in glucose homeostasis and eventually type 2 diabetes.

    View details for DOI 10.2337/DB09-1568

    View details for Web of Science ID 000277554700019

    View details for PubMedID 20185807

  • Genome-wide meta-analyses identify multiple loci associated with smoking behavior NATURE GENETICS Furberg, H., Kim, Y., Dackor, J., Boerwinkle, E., Franceschini, N., Ardissino, D., Bernardinelli, L., Mannucci, P. M., Mauri, F., Merlini, P. A., Absher, D., Assimes, T. L., Fortmann, S. P., Iribarren, C., Knowles, J. W., Quertermous, T., Ferrucci, L., Tanaka, T., Bis, J. C., Furberg, C. D., Haritunians, T., McKnight, B., Psaty, B. M., Taylor, K. D., Thacker, E. L., Almgren, P., Groop, L., Ladenvall, C., Boehnke, M., Jackson, A. U., Mohlke, K. L., Stringham, H. M., Tuomilehto, J., Benjamin, E. J., Hwang, S., Levy, D., Preis, S. R., Vasan, R. S., Duan, J., Gejman, P. V., Levinson, D. F., Sanders, A. R., Shi, J., Lips, E. H., McKay, J. D., Agudo, A., Barzan, L., Bencko, V., Benhamou, S., Castellsague, X., Canova, C., Conway, D. I., Fabianova, E., Foretova, L., Janout, V., Healy, C. M., Holcatova, I., Kjaerheim, K., Lagiou, P., Lissowska, J., Lowry, R., Macfarlane, T. V., Mates, D., Richiardi, L., Rudnai, P., Szeszenia-Dabrowska, N., Zaridze, D., Znaor, A., Lathrop, M., Brennan, P., Bandinelli, S., Frayling, T. M., Guralnik, J. M., Milaneschi, Y., Perry, J. R., Altshuler, D., Elosua, R., Kathiresan, S., Lucas, G., Melander, O., O'Donnell, C. J., Salomaa, V., Schwartz, S. M., Voight, B. F., Penninx, B. W., Smit, J. H., Vogelzangs, N., Boomsma, D. I., de Geus, E. J., Vink, J. M., Willemsen, G., Chanock, S. J., Gu, F., Hankinson, S. E., Hunter, D. J., Hofman, A., Tiemeier, H., Uitterlinden, A. G., van Duijn, C. M., Walter, S., Chasman, D. I., Everett, B. M., Pare, G., Ridker, P. M., Li, M. D., Maes, H. H., Audrain-McGovern, J., Posthuma, D., Thornton, L. M., Lerman, C., Kaprio, J., Rose, J. E., Ioannidis, J. P., Kraft, P., Lin, D., Sullivan, P. F. 2010; 42 (5): 441-U134

    Abstract

    Consistent but indirect evidence has implicated genetic factors in smoking behavior. We report meta-analyses of several smoking phenotypes within cohorts of the Tobacco and Genetics Consortium (n = 74,053). We also partnered with the European Network of Genetic and Genomic Epidemiology (ENGAGE) and Oxford-GlaxoSmithKline (Ox-GSK) consortia to follow up the 15 most significant regions (n > 140,000). We identified three loci associated with number of cigarettes smoked per day. The strongest association was a synonymous 15q25 SNP in the nicotinic receptor gene CHRNA3 (rs1051730[A], beta = 1.03, standard error (s.e.) = 0.053, P = 2.8 x 10(-73)). Two 10q25 SNPs (rs1329650[G], beta = 0.367, s.e. = 0.059, P = 5.7 x 10(-10); and rs1028936[A], beta = 0.446, s.e. = 0.074, P = 1.3 x 10(-9)) and one 9q13 SNP in EGLN2 (rs3733829[G], beta = 0.333, s.e. = 0.058, P = 1.0 x 10(-8)) also exceeded genome-wide significance for cigarettes per day. For smoking initiation, eight SNPs exceeded genome-wide significance, with the strongest association at a nonsynonymous SNP in BDNF on chromosome 11 (rs6265[C], odds ratio (OR) = 1.06, 95% confidence interval (Cl) 1.04-1.08, P = 1.8 x 10(-8)). One SNP located near DBH on chromosome 9 (rs3025343[G], OR = 1.12, 95% Cl 1.08-1.18, P = 3.6 x 10(-8)) was significantly associated with smoking cessation.

    View details for DOI 10.1038/ng.571

    View details for Web of Science ID 000277179500017

    View details for PubMedID 20418890

    View details for PubMedCentralID PMC2914600

  • Use of venlafaxine compared with other antidepressants and the risk of sudden cardiac death or near death: a nested case-control study BRITISH MEDICAL JOURNAL Martinez, C., Assimes, T. L., Mines, D., Dell'Aniello, S., Suissa, S. 2010; 340

    Abstract

    To assess whether use of the antidepressant venlafaxine is associated with an increased risk of sudden cardiac death or near death compared with other commonly used antidepressants.Population based observational study.We did a nested case-control analysis within a new user cohort formed using the United Kingdom General Practice Research Database.New users of venlafaxine, fluoxetine, citalopram, or dosulepin on or after 1 January 1995, aged 18 to 89 years, with a diagnosis of depression or anxiety. Participants were followed-up until February 2005, or the occurrence of sudden cardiac death or near death, identified from medical records indicating non-fatal acute ventricular tachyarrhythmia, sudden death due to cardiac causes, or out of hospital deaths from acute ischaemic cardiac events. For each case, 30 controls were selected matched for age, sex, calendar time, and indication. We used conditional logistic regression to calculate the adjusted odds ratio of sudden cardiac death or near death associated with current use of venlafaxine compared with current use of fluoxetine, citalopram or dosulepin.207 384 participants were followed-up for an average of 3.3 years. There were 568 cases of sudden cardiac death or near death, which were matched to 14 812 controls. The adjusted odds ratio of sudden cardiac death or near death associated with venlafaxine use was 0.66 (95% confidence interval 0.38 to 1.14) relative to fluoxetine use, whereas compared with citalopram it was 0.89 (0.50 to 1.60) and with dosulepin 0.83 (0.46 to 1.52).In this large, population based study, the use of venlafaxine was not associated with an excess risk of sudden cardiac death or near death compared with fluoxetine, dosulepin, or citalopram, in patients with depression or anxiety.

    View details for DOI 10.1136/bmj.c249

    View details for Web of Science ID 000274343700003

    View details for PubMedID 20139216

  • Age at incident treatment of hypertension and risk of cancer: a population study CANCER CAUSES & CONTROL Assimes, T. L., Suissa, S. 2009; 20 (10): 1811-1820

    Abstract

    To determine the effect of treated hypertension on the risk of cancer.Population based external comparison study using the Saskatchewan Health databases.A total of 42,270 subjects were followed for a median of 17.9 years after initiating antihypertensives for hypertension. The effect of hypertension on the risk of cancer varied significantly by age (interaction p < 0.001). Compared with the general population, subjects under 60 years at the time of initiation of antihypertensives had a significantly increased risk of cancer (RR 1.34, 95% CI 1.18?1.52 adjusted for age, sex, and calendar year) while subjects over 60 had a significantly decreased risk (RR 0.88, 95% CI 0.78?0.98). Similar results were obtained for cancer death outcomes. In each subgroup, relative risks across most cancer sites were similar in magnitude and direction. Results were essentially unchanged when analyses were restricted to cancers diagnosed after the first 10 years of follow-up.The effect of treated hypertension on cancer risk varies by the age at incident treatment of hypertension.These findings are not a result of reverse causality or detection bias. However, they may in part be a consequence of residual confounding and/or reflect the type of hypertension being treated.

    View details for DOI 10.1007/s10552-009-9374-3

    View details for Web of Science ID 000271809000003

    View details for PubMedID 19533392

  • Characterizing the admixed African ancestry of African Americans GENOME BIOLOGY Zakharia, F., Basu, A., Absher, D., Assimes, T. L., Go, A. S., Hlatky, M. A., Iribarren, C., Knowles, J. W., Li, J., Narasimhan, B., Sidney, S., Southwick, A., Myers, R. M., Quertermous, T., Risch, N., Tang, H. 2009; 10 (12)

    Abstract

    Accurate, high-throughput genotyping allows the fine characterization of genetic ancestry. Here we applied recently developed statistical and computational techniques to the question of African ancestry in African Americans by using data on more than 450,000 single-nucleotide polymorphisms (SNPs) genotyped in 94 Africans of diverse geographic origins included in the HGDP, as well as 136 African Americans and 38 European Americans participating in the Atherosclerotic Disease Vascular Function and Genetic Epidemiology (ADVANCE) study. To focus on African ancestry, we reduced the data to include only those genotypes in each African American determined statistically to be African in origin.From cluster analysis, we found that all the African Americans are admixed in their African components of ancestry, with the majority contributions being from West and West-Central Africa, and only modest variation in these African-ancestry proportions among individuals. Furthermore, by principal components analysis, we found little evidence of genetic structure within the African component of ancestry in African Americans.These results are consistent with historic mating patterns among African Americans that are largely uncorrelated to African ancestral origins, and they cast doubt on the general utility of mtDNA or Y-chromosome markers alone to delineate the full African ancestry of African Americans. Our results also indicate that the genetic architecture of African Americans is distinct from that of Africans, and that the greatest source of potential genetic stratification bias in case-control studies of African Americans derives from the proportion of European ancestry.

    View details for DOI 10.1186/gb-2009-10-12-r141

    View details for Web of Science ID 000274289000011

    View details for PubMedID 20025784

    View details for PubMedCentralID PMC2812948

  • Digital ischemia JOURNAL OF CARDIOVASCULAR MEDICINE Kapoor, J. R., Kapoor, R., Assimes, T. L. 2008; 9 (12): 1285-1286

    Abstract

    In this report, we describe the case of a 43-year-old mechanic who presented with very painful, numb, and cold left middle and fourth fingers. The diagnosis of the hypothenar hammer syndrome was made by history, physical examination, and characteristic findings on diagnostic imaging. This syndrome often goes unrecognized by physicians yet rapid recognition and treatment are crucial to avoid permanent injury. As the differential diagnosis for isolated digital ischemia is broad, physicians need to remain aware of this rare acquired vascular disorder, especially in susceptible patients.

    View details for DOI 10.2459/JCM.0b013e3283168d50

    View details for Web of Science ID 000261209200017

    View details for PubMedID 19001942

  • Long-term use of antihypertensive drugs and risk of cancer PHARMACOEPIDEMIOLOGY AND DRUG SAFETY Assimes, T. L., Elstein, E., Langleben, A., Suissa, S. 2008; 17 (11): 1039-1049

    Abstract

    Determine the relative risk of cancer users of commonly prescribed antihypertensive drugs with a focus on documenting risk in long-term users (>7.5 years).We conducted a nested case-control study using the Saskatchewan Health databases. Cancer risks in users of beta-blockers, calcium channel blockers (CCBs), and rennin-angiotensin system inhibitors (RASIs), respectively, were compared to risks in users of thiazide diuretics.A total of 11,697 first cases of cancer and the subset of 6918 subjects who died from cancer were each matched to 10 controls. The mean total duration of use of the four classes of antihypertensive drugs (estimated by dispensation of prescriptions) ranged from 3.6 to 5.7 years. A subgroup of cases was exposed long term (mean total duration of use: 9.7-11.4 years, range: 7.5-23.1 years). Modest differences in risk between users of the four classes were detected for colon, head & neck, lung, and hematological cancers but none of these associations demonstrated a clear dose response relationship for both first cancer and fatal cancer. Otherwise, for cancer at all sites combined and for the four most common cancers, we were able to rule out, with reasonable confidence, small to modest differences in the risk of cancer among users of any duration (upper 95% confidence intervals (CIs): 1.45) and modest to large differences in risk among long-term users (upper 95%CI: 3.06).The long-term use of commonly prescribed classes of antihypertensive drugs does not appear to promote or initiate cancer.

    View details for DOI 10.1002/pds.1656

    View details for Web of Science ID 000261011600001

    View details for PubMedID 18780400

  • Sax Differences In Peripheral Arterial Disease 81st Annual Scientific Session of the American-Heart-Association Rafie, A. H., Sims, T., Edwards, K. A., Phan, T., Stefanick, M. L., Assimes, T., Trammel, J. A., Olin, J., Cooke, J. P. LIPPINCOTT WILLIAMS & WILKINS. 2008: S811?S811

    View details for Web of Science ID 000262104502719

  • Susceptibility locus for clinical and subclinical coronary artery disease at chromosome 9p21 in the multi-ethnic ADVANCE study HUMAN MOLECULAR GENETICS Assimes, T. L., Knowles, J. W., Basu, A., Iribarren, C., Southwick, A., Tang, H., Absher, D., Li, J., Fair, J. M., Rubin, G. D., Sidney, S., Fortmann, S. P., Go, A. S., Hlatky, M. A., Myers, R. M., Risch, N., Quertermous, T. 2008; 17 (15): 2320-2328

    Abstract

    A susceptibility locus for coronary artery disease (CAD) at chromosome 9p21 has recently been reported, which may influence the age of onset of CAD. We sought to replicate these findings among white subjects and to examine whether these results are consistent with other racial/ethnic groups by genotyping three single nucleotide polymorphisms (SNPs) in the risk interval in the Atherosclerotic Disease, Vascular Function, and Genetic Epidemiology (ADVANCE) study. One or more of these SNPs was associated with clinical CAD in whites, U.S. Hispanics and U.S. East Asians. None of the SNPs were associated with CAD in African Americans although the power to detect an odds ratio (OR) in this group equivalent to that seen in whites was only 24-30%. ORs were higher in Hispanics and East Asians and lower in African Americans, but in all groups the 95% confidence intervals overlapped with ORs observed in whites. High-risk alleles were also associated with increased coronary artery calcification in controls and the magnitude of these associations by racial/ethnic group closely mirrored the magnitude observed for clinical CAD. Unexpectedly, we noted significant genotype frequency differences between male and female cases (P = 0.003-0.05). Consequently, men tended towards a recessive and women tended towards a dominant mode of inheritance. Finally, an effect of genotype on the age of onset of CAD was detected but only in men carrying two versus one or no copy of the high-risk allele and presenting with CAD at age >50 years. Further investigations in other populations are needed to confirm or refute our findings.

    View details for DOI 10.1093/hmg/ddn132

    View details for Web of Science ID 000257788300007

    View details for PubMedID 18443000

    View details for PubMedCentralID PMC2733811

  • A near null variant of 12/15-LOX encoded by a novel SNP in ALOX15 and the risk of coronary artery disease ATHEROSCLEROSIS Assimes, T. L., Knowles, J. W., Priest, J. R., Basu, A., Borchert, A., Volcik, K. A., Grove, M. L., Tabor, H. K., Southwick, A., Tabibiazar, R., Sidney, S., Boerwinkle, E., Go, A. S., Iribarren, C., Hlatky, M. A., Fortmann, S. P., Myers, R. M., Kuhn, H., Riseh, N., Quertermous, T. 2008; 198 (1): 136-144

    Abstract

    Murine genetic models suggest that function of the 12/15-LOX enzyme promotes atherosclerosis. We tested the hypothesis that exonic and/or promoter single nucleotide polymorphisms (SNPs) in the human 12/15-LOX gene (ALOX15) alter the risk of symptomatic coronary artery disease (CAD).We resequenced ALOX15 and then genotyped a common promoter and a less common novel coding SNP (T560M) in 1809 subjects with CAD and 1734 controls from Kaiser Permanente including a subset of participants of the Coronary Artery Risk Development in Young Adults study. We found no association between the promoter SNP and the risk of CAD. However, heterozygote carriers of the 560M allele had an increased risk of CAD (adjusted OR, 1.62; P=0.02) compared to non-carriers. In vitro studies demonstrated a 20-fold reduction in the catalytic activity of 560M when compared to 560T. We then genotyped T560M in 12,974 participants of the Atherosclerosis Risk in Communities study and similarly found that heterozygote carriers had an increased risk of CAD compared to non-carriers (adjusted HR, 1.31; P=0.06). In both population studies, homozygote carriers were rare and associated with a non-significant decreased risk of CAD compared to non-carriers (adjusted OR, 0.55; P=0.63 and HR, 0.93; P=0.9).A coding SNP in ALOX15 (T560M) results in a near null variant of human 12/15-LOX. Assuming a co-dominant mode of inheritance, this variant does not protect against CAD. Assuming a recessive mode of inheritance, the effect of this mutation remains unclear, but is unlikely to provide a protective effect to the degree suggested by mouse knockout studies.

    View details for DOI 10.1016/j.atheroscierosis.2007.09.003

    View details for Web of Science ID 000255491800016

    View details for PubMedID 17959182

  • Common polymorphisms of ALOX5 and ALOX5AP and risk of coronary artery disease HUMAN GENETICS Assimes, T. L., Knowles, J. W., Priest, J. R., Basu, A., Volcik, K. A., Southwick, A., Tabor, H. K., Hartiala, J., Allayee, H., Grove, M. L., Tabibiazar, R., Sidney, S., Fortmann, S. P., Go, A., Hlatky, M., Iribarren, C., Boerwinkle, E., Myers, R., Risch, N., Quertermous, T. 2008; 123 (4): 399-408

    Abstract

    Recent human genetic studies suggest that allelic variants of leukotriene pathway genes influence the risk of clinical and subclinical atherosclerosis. We sequenced the promoter, exonic, and splice site regions of ALOX5 and ALOX5AP and then genotyped 7 SNPs in ALOX5 and 6 SNPs in ALOX5AP in 1,552 cases with clinically significant coronary artery disease (CAD) and 1,583 controls from Kaiser Permanente including a subset of participants of the coronary artery risk development in young adults study. A nominally significant association was detected between a promoter SNP in ALOX5 (rs12762303) and CAD in our subset of white/European subjects (adjusted odds ratio per minor allele, log-additive model, 1.32; P = 0.002). In this race/ethnic group, rs12762303 has a minor allele frequency of 15% and is tightly linked to variation at the SP1 variable tandem repeat promoter polymorphism. However, the association between CAD and rs12762303 could not be reproduced in the atherosclerosis risk in communities study (hazard rate ratio per minor allele; 1.08, P = 0.1). Assuming a recessive mode of inheritance, the association was not significant in either population study but our power to detect modest effects was limited. No significant associations were observed between all other SNPs and the risk of CAD. Overall, our findings do not support a link between common allelic variation in or near ALOX5 or ALOX5AP and the risk of CAD. However, additional studies are needed to exclude modest effects of promoter variation in ALOX5 on the risk of CAD assuming a recessive mode of inheritance.

    View details for DOI 10.1007/s00439-008-0489-5

    View details for Web of Science ID 000254959600008

    View details for PubMedID 18369664

  • Failure to replicate an association of SNPs in the oxidized LDL receptor gene (OLRI) with CAD BMC MEDICAL GENETICS Knowles, J. W., Assimes, T. L., Boerwinkle, E., Fortmann, S. P., Go, A., Grove, M. L., Hlatky, M., Iribarren, C., Li, J., Myers, R., Risch, N., Sidney, S., Southwick, A., Volcik, K. A., Quertermous, T. 2008; 9

    Abstract

    The lectin-like oxidized LDL receptor LOX-1 (encoded by OLR1) is believed to play a key role in atherogenesis and some reports suggest an association of OLR1 polymorphisms with myocardial infarction (MI). We tested whether single nucleotide polymorphisms (SNPs) in OLR1 are associated with clinically significant CAD in the Atherosclerotic Disease, VAscular FuNction, & Geneti C Epidemiology (ADVANCE) study.ADVANCE is a population-based case-control study of subjects receiving care within Kaiser Permanente of Northern California including a subset of participants of the Coronary Artery Risk Development in Young Adults (CARDIA) study. We first resequenced the promoter, exonic, and splice site regions of OLR1 and then genotyped four single nucleotide polymorphisms (SNPs), including a non-synonymous SNP (rs11053646, Lys167Asn) as well as an intronic SNP (rs3736232) previously associated with CAD.In 1,809 cases with clinical CAD and 1,734 controls, the minor allele of the coding SNP was nominally associated with a lower odds ratio (OR) of CAD across all ethnic groups studied (minimally adjusted OR 0.8, P = 0.007; fully adjusted OR 0.8, P = 0.01). The intronic SNP was nominally associated with an increased risk of CAD (minimally adjusted OR 1.12, p = 0.03; fully adjusted OR 1.13, P = 0.03). However, these associations were not replicated in over 13,200 individuals (including 1,470 cases) in the Atherosclerosis Risk in Communities (ARIC) study.Our results do not support the presence of an association between selected common SNPs in OLR1 and the risk of clinical CAD.

    View details for DOI 10.1186/1471-2350-9-23

    View details for Web of Science ID 000255652400001

    View details for PubMedID 18384690

    View details for PubMedCentralID PMC2322963

  • Associations Among Multiple Markers and Complex Disease: Models, Algorithms, and Applications GENETIC DISSECTION OF COMPLEX TRAITS, 2ND EDITION Assimes, T. L., Olshen, A. B., Narasimhan, B., Olshen, R. A. 2008; 60: 437-464

    Abstract

    This chapter is a report on collaborations among its authors and others over many years. It devolves from our goal of understanding genes, their main and epistatic effects combined with interactions involving demographic and environmental features also, as together they predict genetically complex diseases. Thus, our goal is "association." Particular phenotypes of interest to us are hypertension, insulin resistance, angina, and myocardial infarction. Prediction of complex disease is notoriously difficult, though it would be made easier were we given strand-specific information on genotype. Unfortunately, with current technology, genotypic information comes to us "unphased." While obviously we have strand-specific information when genotype is homozygous, we do not have such information when genotype is heterozygous. To summarize, the ultimate goals of approaches we provide is to predict phenotype, typically untoward or not, within a specific window of time. Our approach is neither through linkage nor from finding haplotype frequencies per se.

    View details for DOI 10.1016/S0065-2660(07)00416-6

    View details for Web of Science ID 000280575900018

    View details for PubMedID 18358329

  • Polymorphisms in hypoxia inducible factor 1 and the initial clinical presentation of coronary disease AMERICAN HEART JOURNAL Hlatky, M. A., Quertermous, T., Boothroyd, D. B., Priest, J. R., Glassford, A. J., Myers, R. M., Fortmann, S. P., Iribarren, C., Tabor, H. K., Assimes, T. L., Tibshirani, R. J., Go, A. S. 2007; 154 (6): 1035-1042

    Abstract

    Only some patients with coronary artery disease (CAD) develop acute myocardial infarction (MI), and emerging evidence suggests vulnerability to MI varies systematically among patients and may have a genetic component. The goal of this study was to assess whether polymorphisms in genes encoding elements of pathways mediating the response to ischemia affect vulnerability to MI among patients with underlying CAD.We prospectively identified patients at the time of their initial clinical presentation of CAD who had either an acute MI or stable exertional angina. We collected clinical data and genotyped 34 polymorphisms in 6 genes (ANGPT1, HIF1A, THBS1, VEGFA, VEGFC, VEGFR2).The 909 patients with acute MI were significantly more likely than the 466 patients with stable angina to be male, current smokers, and hypertensive, and less likely to be taking beta-blockers or statins. Three polymorphisms in HIF1A (Pro582Ser, rs11549465; rs1087314; and Thr418Ile, rs41508050) were significantly more common in patients who presented with stable exertional angina rather than acute MI, even after statistical adjustment for cardiac risk factors and medications. The HIF-mediated transcriptional activity was significantly lower when HIF1A null fibroblasts were transfected with variant HIF1A alleles than with wild-type HIF1A alleles.Polymorphisms in HIF1A were associated with development of stable exertional angina rather than acute MI as the initial clinical presentation of CAD.

    View details for DOI 10.1016/j.ahj.2007.07.042

    View details for Web of Science ID 000251396200006

    View details for PubMedID 18035072

  • Circulating chemokines accurately identify individuals with clinically significant atherosclerotic heart disease PHYSIOLOGICAL GENOMICS Ardigo, D., Assimes, T. L., Fortmann, S. P., Go, A. S., Hlatky, M., Hytopoulos, E., Iribarren, C., Tsao, P. S., Tabibiazar, R., Quertermous, T. 2007; 31 (3): 402-409

    Abstract

    Serum inflammatory markers correlate with outcome and response to therapy in subjects with cardiovascular disease. However, current individual markers lack specificity for the diagnosis of coronary artery disease (CAD). We hypothesize that a multimarker proteomic approach measuring serum levels of vascular derived inflammatory biomarkers could reveal a "signature of disease" that can serve as a highly accurate method to assess for the presence of coronary atherosclerosis. We simultaneously measured serum levels of seven chemokines [CXCL10 (IP-10), CCL11 (eotaxin), CCL3 (MIP1 alpha), CCL2 (MCP1), CCL8 (MCP2), CCL7 (MCP3), and CCL13 (MCP4)] in 48 subjects with clinically significant CAD ("cases") and 44 controls from the ADVANCE Study. We applied three classification algorithms to identify the combination of variables that would best predict case-control status and assessed the diagnostic performance of these models with receiver operating characteristic (ROC) curves. The serum levels of six chemokines were significantly higher in cases compared with controls (P < 0.05). All three classification algorithms entered three chemokines in their final model, and only logistic regression selected clinical variables. Logistic regression produced the highest ROC of the three algorithms (AUC = 0.95; SE = 0.03), which was markedly better than the AUC for the logistic regression model of traditional risk factors of CAD without (AUC = 0.67; SE = 0.06) or with CRP (AUC = 0.68; SE = 0.06). A combination of serum levels of multiple chemokines identifies subjects with clinically significant atherosclerotic heart disease with a very high degree of accuracy. These results need to be replicated in larger cross-sectional studies and their prognostic value explored.

    View details for DOI 10.1152/physiolgenomics.00104.2007

    View details for Web of Science ID 000251780600005

    View details for PubMedID 17698927

  • Genetic susceptibility to peripheral arterial disease: A dark corner in vascular biology ARTERIOSCLEROSIS THROMBOSIS AND VASCULAR BIOLOGY Knowles, J. W., Assimes, T. L., Li, J., Quertermous, T., Cooke, J. P. 2007; 27 (10): 2068-2078

    Abstract

    Peripheral arterial disease (PAD) is characterized by reduced blood flow to the limbs, usually as a consequence of atherosclerosis, and affects approximately 12 million Americans. It is a common cause of cardiovascular morbidity and an independent predictor of cardiovascular mortality. Similar to other atherosclerotic diseases, such as coronary artery disease, PAD is the result of the complex interplay between injurious environmental stimuli and genetic predisposing factors of the host. Genetic susceptibility to PAD is likely contributed by sequence variants in multiple genes, each with modest effects. Although many of these variants probably alter susceptibility both to PAD and to coronary artery disease, it is likely that there exists a set of variants specifically to alter susceptibility to PAD. Despite the prevalence of PAD and its high societal burden, relatively little is known about such genetic variants. This review summarizes our limited present knowledge and gives an overview of recent, more powerful approaches to elucidating the genetic basis of PAD. We discuss the advantages and limitations of genetic studies and highlight the need for collaborative networks of PAD investigators for shedding light on this dark corner of vascular biology.

    View details for DOI 10.1161/01.ATV.0000282199.66398.8c

    View details for Web of Science ID 000249587000002

    View details for PubMedID 17656669

    View details for PubMedCentralID PMC4321902

  • Heritability of left ventricular mass in Japanese families living in Hawaii: the SAPPHIRe Study JOURNAL OF HYPERTENSION Assimes, T. L., Narasimhan, B., Seto, T. B., Yoon, S., Curb, J. D., Olshen, R. A., Quertermous, T. 2007; 25 (5): 985-992

    Abstract

    Established determinants of left ventricular (LV) mass explain only a modest fraction of its variability. Family studies to date suggest that a proportion of the unexplained variability can be accounted for by additive polygenic effects. An estimate of this proportion has not been reported previously in an East Asian population. The objective of this study was to estimate the heritability of LV mass in Japanese families living in Hawaii.We analyzed data by components of variance in a sample of 169 hypertensive families (n = 476 subjects) and, separately, in a population-based sample of 256 families (n = 501 subjects) participating in the Honolulu Heart Program.In multivariate models, established predictors of LV mass explained about half the total variance of LV mass. Using SOLAR, our estimates of the narrow sense heritability of LV mass ranged from 42.5% (SE 9.8, P < 0.0001) in our sample of hypertensive families to 60.6% (SE 11.7, P < 0.0001) in our population-based sample of families. Parametric bootstrap analyses confirmed that the inference for each sample was appropriate.Assuming the absence of shared familial environmental effects, close to half of the unexplained variance of LV mass in Japanese subjects living in Hawaii is genetic in nature. This estimate was observed in two independent samples. Therefore, the pursuit of novel genetic determinants of LV mass through either whole genome or candidate gene association studies of this population may be worthwhile. Such studies are certainly feasible.

    View details for Web of Science ID 000245741200015

    View details for PubMedID 17414662

  • Does left ventricular mass differ between apparently normal adults of different ethnicities? The family blood pressure program 47th Annual Conference on Cardiovascular Disease Epidemiology and Prevention Devereux, R. B., Cooper, R., Weder, A., Seto, T., Hanis, C., Mosley, T., Assimes, T., Rao, D. C., Arnett, D. K. LIPPINCOTT WILLIAMS & WILKINS. 2007: E288?E288

    View details for Web of Science ID 000244482200370

  • Plasma asymmetric dimethylarginine is an independent marker of peripheral artery disease but not coronary artery disease: A novel marker of atherosclerosis with topographical specificity 79th Annual Scientific Session of the American-Heart-Association Ng, M. K., Assimes, T., Wang, B., McGee, S., Harada, R. K., Yeung, A. C., Narasimhan, B., Olin, J. W., Cooke, J. P. LIPPINCOTT WILLIAMS & WILKINS. 2006: 775?76

    View details for Web of Science ID 000241792805111

  • Plasma asymmetric dimethylarginine is an independent marker for the presence and severity of peripheral artery disease 55th Annual Scientific Session of the American-College-of-Cardiology Ng, M. K., Assimes, T., Wang, B. Y., McGee, S., Harada, R. K., Yeung, A. C., Narasimhan, B., Olin, J. W., Cooke, J. P. ELSEVIER SCIENCE INC. 2006: 294A?294A

    View details for Web of Science ID 000235530402070

  • Cardiac outcomes occurred more frequently with PCI than CABG or medical therapy in coronary artery disease. ACP journal club Assimes, T., Hlatky, M. A. 2004; 141 (3): 57-?

    View details for PubMedID 15518441

  • Inhaled corticosteroid use in asthma and the prevention of myocardial infarction AMERICAN JOURNAL OF MEDICINE Suissa, S., Assimes, T., Brassard, P., Ernst, P. 2003; 115 (5): 377-381

    Abstract

    Asthma patients may be at increased risk of cardiovascular outcomes due to hypoxemia from asthma exacerbations and bronchodilator-induced tachycardia. We investigated whether inhaled corticosteroids, which are known to improve asthma control and reduce exacerbations, are associated with a lower rate of myocardial infarction.We used the Saskatchewan Health databases to form a population-based cohort of subjects aged 5 to 44 years who were using antiasthma drugs between 1975 and 1991. Subjects were followed until 1997, the age of 55 years, or death. A nested case-control approach was used where each subject with a first myocardial infarction was matched on calendar time, age, and sex with up to 10 controls randomly selected from the cohort.The cohort consisted of 30,569 subjects, including 105 patients with myocardial infarction who were matched with 933 controls. The adjusted rate ratio of myocardial infarction for inhaled corticosteroid use during the year before the index date was 0.56 (95% confidence interval [CI]: 0.32 to 0.99) as compared with no use. Myocardial infarction decreased by 12% (95% CI: 0% to 23%) with each additional canister used during this 1-year period. The rate ratio of myocardial infarction for inhaled corticosteroid use was 0.78 (95% CI: 0.41 to 1.51) among patients with milder asthma and 0.19 (95% CI: 0.04 to 0.97) among those with more severe asthma.Inhaled corticosteroid use may reduce the risk of myocardial infarction in asthma patients, particularly those with more severe disease.

    View details for DOI 10.1016/S0002-9343(03)00393-0

    View details for Web of Science ID 000185776400006

    View details for PubMedID 14553873

  • Inhaled short acting beta agonist use in COPD and the risk of acute myocardial infarction THORAX Suissa, S., Assimes, T., Ernst, P. 2003; 58 (1): 43-46

    Abstract

    A recent study found that short acting beta agonists used in the treatment of asthma and chronic obstructive pulmonary disease (COPD) may increase the risk of acute myocardial infarction. We investigated this hypothesis in patients with COPD already at high risk of cardiac disease.The Saskatchewan Health Services databases were used to form a population based cohort of all patients newly diagnosed with COPD over the age of 55 years identified between 1980 and 1997. All subjects were followed up until 1999, death, or the first occurrence of acute myocardial infarction. Those with a first acute myocardial infarction, fatal or non-fatal, were matched on calendar time and age with cohort members.The cohort consisted of 12 090 subjects including 1127 cases with fatal or non-fatal acute myocardial infarction. The adjusted rate ratio for current use of inhaled beta agonists was 1.12 (95% confidence interval (CI) 0.95 to 1.33), and for first time use it was 1.02 (95% CI 0.52 to 2.00). There was also no significant increase in risk when the analysis was restricted to subjects with cardiac risk factors such as hypertension and diabetes, or to subjects not having been prescribed beta blocker medications.Short acting inhaled beta agonist use among patients with COPD does not appear to increase the risk of fatal or non-fatal acute myocardial infarction.

    View details for Web of Science ID 000180487700008

    View details for PubMedID 12511719

  • The use of perioperative corticosteroids in craniomaxillofacial surgery PLASTIC AND RECONSTRUCTIVE SURGERY Assimes, T. L., Lessard, M. L. 1999; 103 (1): 313-321

    Abstract

    A literature search could not identify a study on the prevalence of the use of perioperative corticosteroids by surgeons performing craniomaxillofacial surgery. To gather this information, we conducted a survey of North American members of the American Society of Maxillofacial Surgeons classified as "active" in the society's roster. The first 90 members in forward and reverse alphabetical order who were capable of receiving a fax transmission were faxed our survey. Sixty surgeons responded, for a response rate of 66.7 percent. Twenty-eight (46.7 percent) reported using short-term, high-dose, perioperative corticosteroids to control postsurgical inflammation. Surgeons performing facial aesthetic surgery alone or in addition to craniomaxillofacial surgery were more likely to be using steroids (Fisher's exact test, p = 0.038). A variety of steroid drugs and regimens were cited by steroid users. The most common reason for using steroids was to decrease edema. Thirty-two (53.3 percent) responders reported that they were not using steroids. The most common reason for not using them was a lack of literature to support their effectiveness. All responders were asked to report any complications encountered with the use of steroids. The majority (78.3 percent) reported no complications. The most common complication encountered was euphoria (13.3 percent). No one reported the occurrence of avascular necrosis of the hip or humerus with the use of steroids. Based on a literature review, an analysis of the steroid regimens and complications reported revealed that steroid use was generally safe. Nevertheless, in addition to the traditional steroid contraindications, consideration should be given to withholding steroids in patients with any of the known risk factors for avascular necrosis, in patients who are or recently have been on nonsteroidal anti-inflammatory drugs, and in aspirin-sensitive asthmatics. These patients may be at increased risk for serious adverse effects with the use of steroids. More research is required to objectively measure the effect of steroids on edema and, if beneficial, to determine the optimal drug regimen.

    View details for Web of Science ID 000077707200050

    View details for PubMedID 9915196

  • Torsade de pointes with sotalol overdose treated successfully with lidocaine CANADIAN JOURNAL OF CARDIOLOGY Assimes, T. L., Malcolm, I. 1998; 14 (5): 753-756

    Abstract

    Torsade de pointes is a polymorphic ventricular tachyarrhythmia associated with a long QT interval. The prognosis is excellent if torsade is recognized early. In the acquired long QT syndrome, measures should be taken quickly to identify and correct all predisposing conditions and to treat or prevent torsade. Established treatments of acquired torsade are magnesium bolus, electrolyte replacement, isoproterenol infusion and cardiac pacing. Sotalol overdose causing torsade is reported in which lidocaine appears to have suppressed an episode of torsade as well as prevented further episodes. Current understanding of the electrophysiological mechanisms of torsade and lidocaine, a review of the literature and the author's experience indicate that lidocaine is a potentially useful therapy in torsade.

    View details for Web of Science ID 000074005600021

    View details for PubMedID 9627533

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