Publications

Adipocytes


Assistant Professor of Medicine (Cardiovascular Medicine) at the Stanford University Medical Center

Publications

  • Predictive network modeling in human induced pluripotent stem cells identifies key driver genes for insulin responsiveness. PLoS computational biology Carcamo-Orive, I., Henrion, M. Y., Zhu, K., Beckmann, N. D., Cundiff, P., Moein, S., Zhang, Z., Alamprese, M., D'Souza, S. L., Wabitsch, M., Schadt, E. E., Quertermous, T., Knowles, J. W., Chang, R. 2020; 16 (12): e1008491

    Abstract

    Insulin resistance (IR) precedes the development of type 2 diabetes (T2D) and increases cardiovascular disease risk. Although genome wide association studies (GWAS) have uncovered new loci associated with T2D, their contribution to explain the mechanisms leading to decreased insulin sensitivity has been very limited. Thus, new approaches are necessary to explore the genetic architecture of insulin resistance. To that end, we generated an iPSC library across the spectrum of insulin sensitivity in humans. RNA-seq based analysis of 310 induced pluripotent stem cell (iPSC) clones derived from 100 individuals allowed us to identify differentially expressed genes between insulin resistant and sensitive iPSC lines. Analysis of the co-expression architecture uncovered several insulin sensitivity-relevant gene sub-networks, and predictive network modeling identified a set of key driver genes that regulate these co-expression modules. Functional validation in human adipocytes and skeletal muscle cells (SKMCs) confirmed the relevance of the key driver candidate genes for insulin responsiveness.

    View details for DOI 10.1371/journal.pcbi.1008491

    View details for PubMedID 33362275

  • Children with Heterozygous Familial Hypercholesterolemia in the United States: Data from the CASCADE FH Registry. The Journal of pediatrics de Ferranti, S. D., Shrader, P., Linton, M. F., Knowles, J. W., Hudgins, L. C., Benuck, I., Kindt, I., O'Brien, E. C., Peterson, A. L., Ahmad, Z. S., Clauss, S., Duell, P. B., Shapiro, M. D., Wilemon, K., Gidding, S. S., Neal, W. 2020

    Abstract

    OBJECTIVE: To describe enrollment characteristics of youth in the CAscade SCreening for Awareness and DEtection (CASCADE) Familial Hypercholesterolemia Registry.STUDY DESIGN: Cross-sectional analysis of 493 participants <18 years old with heterozygous FH recruited from US lipid clinics (n=20), between April 1, 2014 and January 12, 2018. At enrollment, some were new patients and some were in care. Clinical characteristics are described, including lipid levels and lipid lowering treatments (LLTs).RESULTS: Mean age at diagnosis was 9.4 (4.0) years; 47% female, 68% white and 12% Hispanic. Average (SD) highest LDL-C was 238 (61) mg/dL prior to treatment. Lipid lowering therapy (LLT) was used by 64% of participants; 56% were treated with statin. LDL-C declined 84 mg/dL (33%) among those treated with LLT; statins produced the greatest decline, 100 mg/dL (39% reduction). At enrollment, 39% had reached an LDL-C goal, either <130 mg/dL or ≥50% decrease from pre-treatment; 20% of those on LLT reached both goals.CONCLUSIONS: Among youth enrolled in CASCADE FH, diagnosis occurred relatively late, only 77% of children eligible for LLT were on treatment and 39% of those treated met LDL-C goals. Opportunities exist for earlier diagnosis, broader use of LLT, and greater LDL-C lowering.

    View details for DOI 10.1016/j.jpeds.2020.09.042

    View details for PubMedID 32976895

  • Discovery and quality analysis of a comprehensive set of structural variants and short tandem repeats. Nature communications Jakubosky, D., Smith, E. N., D'Antonio, M., Jan Bonder, M., Young Greenwald, W. W., D'Antonio-Chronowska, A., Matsui, H., i2QTL Consortium, Stegle, O., Montgomery, S. B., DeBoever, C., Frazer, K. A., Bonder, M. J., Cai, N., Carcamo-Orive, I., D'Antonio, M., Frazer, K. A., Young Greenwald, W. W., Jakubosky, D., Knowles, J. W., Matsui, H., McCarthy, D. J., Mirauta, B. A., Montgomery, S. B., Quertermous, T., Seaton, D. D., Smail, C., Smith, E. N., Stegle, O. 2020; 11 (1): 2928

    Abstract

    Structural variants (SVs) and short tandem repeats (STRs) are important sources of genetic diversity but are not routinely analyzed in genetic studies because they are difficult to accurately identify and genotype. Because SVs and STRs range in size and type, it is necessary to apply multiple algorithms that incorporate different types of evidence from sequencing data and employ complex filtering strategies to discover a comprehensive set of high-quality and reproducible variants. Here we assemble a set of 719 deep whole genome sequencing (WGS) samples (mean 42*) from 477 distinct individuals which we use to discover and genotype a wide spectrum of SV and STR variants using five algorithms. We use 177 unique pairs of genetic replicates to identify factors that affect variant call reproducibility and develop a systematic filtering strategy to create of one of the most complete and well characterized maps of SVs and STRs to date.

    View details for DOI 10.1038/s41467-020-16481-5

    View details for PubMedID 32522985

  • Properties of structural variants and short tandem repeats associated with gene expression and complex traits. Nature communications Jakubosky, D., D'Antonio, M., Bonder, M. J., Smail, C., Donovan, M. K., Young Greenwald, W. W., Matsui, H., i2QTL Consortium, D'Antonio-Chronowska, A., Stegle, O., Smith, E. N., Montgomery, S. B., DeBoever, C., Frazer, K. A., Bonder, M. J., Cai, N., Carcamo-Orive, I., D'Antonio, M., Frazer, K. A., Young Greenwald, W. W., Jakubosky, D., Knowles, J. W., Matsui, H., McCarthy, D. J., Mirauta, B. A., Montgomery, S. B., Quertermous, T., Seaton, D. D., Smail, C., Smith, E. N., Stegle, O. 2020; 11 (1): 2927

    Abstract

    Structural variants (SVs) and short tandem repeats (STRs) comprise a broad group of diverse DNA variants which vastly differ in their sizes and distributions across the genome. Here, we identify genomic features of SV classes and STRs that are associated with gene expression and complex traits, including their locations relative to eGenes, likelihood of being associated with multiple eGenes, associated eGene types (e.g., coding, noncoding, level of evolutionary constraint), effect sizes, linkage disequilibrium with tagging single nucleotide variants used in GWAS, and likelihood of being associated with GWAS traits. We identify a set of high-impact SVs/STRs associated with the expression of three or more eGenes via chromatin loops and show that they are highly enriched for being associated with GWAS traits. Our study provides insights into the genomic properties of structural variant classes and short tandem repeats that are associated with gene expression and human traits.

    View details for DOI 10.1038/s41467-020-16482-4

    View details for PubMedID 32522982

  • Insulin Resistance and Mitochondrial Dysfunction Mediated by Nat1 Deficiency Sangwung, P., Fathzadeh, M., Knowles, J. AMER DIABETES ASSOC. 2020
  • Gaps in Dyslipidemia Care Among Working-Aged Individuals With Employer-Sponsored Health Care. Journal of the American Heart Association Shiffman, D., Louie, J. Z., Devlin, J. J., Knowles, J. W., McPhaul, M. J. 2020: e015807

    Abstract

    Background The American Heart Association and American College of Cardiology guidelines defined patient-management groups that would benefit from lowering of low-density lipoprotein cholesterol (LDL-C). We assessed gaps in dyslipidemia care among employees and spouses with health benefits. Methods and Results We studied 17889 employees and spouses who were covered by an employer-sponsored health plan and participated in an annual health assessment. Using medical claims, laboratory tests, and risk assessment questionnaires, we found that 43% of participants were in one of 4 patient-management groups: secondary prevention, severe hypercholesterolemia (LDL-C ≥190mg/dL at least once in the preceding 5years), diabetes mellitus, or elevated 10-year risk of cardiovascular disease. To assess gaps in dyslipidemia care, we used LDL-C ≤70mg/dL as the goal for both the secondary prevention group and those in the elevated 10-year risk group with >20% risk; LDL-C ≤100mg/dL was used for the other groups. Among those in patient-management groups, 27.3% were in the secondary prevention group, 7.4% were in the severe hypercholesterolemia group, 29.9% were in the diabetes mellitus group, and 35.4% were in the elevated 10-year risk group. About 74% of those in patient-management groups had above-goal LDL-C levels, whereas only 31% had evidence of a lipid-lowering therapy in the past 6months: 45% in the secondary prevention group, 31% in the severe hypercholesterolemia group, 36% in the diabetes mellitus group, and 17% in the elevated 10-year risk group. Conclusions The substantial gaps in LDL-C treatment and goal attainment among members of an employer-sponsored medical plan who were mostly aware of their LDL-C levels indicate the need for gap-closure initiatives.

    View details for DOI 10.1161/JAHA.119.015807

    View details for PubMedID 32319337

  • Delisting STAP1: The Rise and Fall of a Putative Hypercholesterolemia Gene. Arteriosclerosis, thrombosis, and vascular biology Hegele, R. A., Knowles, J. W., Horton, J. D. 2020; 40 (4): 847–49

    View details for DOI 10.1161/ATVBAHA.120.314006

    View details for PubMedID 32208993

  • Association of insulin resistance, from mid-life to late-life, with aortic stiffness in late-life: the Atherosclerosis Risk in Communities Study. Cardiovascular diabetology Poon, A. K., Meyer, M. L., Tanaka, H., Selvin, E., Pankow, J., Zeng, D., Loehr, L., Knowles, J. W., Rosamond, W., Heiss, G. 2020; 19 (1): 11

    Abstract

    BACKGROUND: Insulin resistance may contribute to aortic stiffening that leads to end-organ damage. We examined the cross-sectional association and prospective association of insulin resistance and aortic stiffness in older adults without diabetes.METHODS: We analyzed 2571 men and women at Visit 5 (in 2011-2013), and 2350 men and women at repeat examinations from baseline at Visit 1 (in 1987-1989) to Visit 5 (in 2011-2013). Linear regression was used to estimate the difference in aortic stiffness per standard unit of HOMA-IR, TG/HDL-C, and TyG at Visit 5. Linear mixed effects were used to assess if high, as opposed to non-high, aortic stiffness (>75th percentile) was preceded by a faster annual rate of change in log-HOMA-IR, log-TG/HDL-C, and log-TyG from Visit 1 to Visit 5.RESULTS: The mean age of participants was 75years, 37% (n=957) were men, and 17% (n=433) were African American. At Visit 5, higher HOMA-IR, higher TG/HDL-C, and higher TyG were associated with higher aortic stiffness (16cm/s per SD (95% CI 6, 27), 29cm/s per SD (95% CI 18, 40), and 32cm/s per SD (95% CI 22, 42), respectively). From Visit 1 to Visit 5, high aortic stiffness, compared to non-high aortic stiffness, was not preceded by a faster annual rate of change in log-HOMA-IR from baseline to 9years (0.030 (95% CI 0.024, 0.035) vs. 0.025 (95% CI 0.021, 0.028); p=0.15) or 9years onward (0.011 (95% CI 0.007, 0.015) vs. 0.011 (95% CI 0.009, 0.013); p=0.31); in log-TG/HDL-C from baseline to 9years (0.019 (95% CI 0.015, 0.024) vs. 0.024 (95% CI 0.022, 0.026); p=0.06) or 9years onward (-0.007 (95% CI -0.010, -0.005) vs. -0.009 (95% CI -0.010, -0.007); p=0.08); or in log-TyG from baseline to 9years (0.002 (95% CI 0.002, 0.003) vs. 0.003 (95% CI 0.003, 0.003); p=0.03) or 9years onward (0 (95% CI 0, 0) vs. 0 (95% CI 0, 0); p=0.08).CONCLUSIONS: Among older adults without diabetes, insulin resistance was associated with aortic stiffness, but the putative role of insulin resistance in aortic stiffness over the life course requires further study.

    View details for DOI 10.1186/s12933-020-0986-y

    View details for PubMedID 31992297

  • Effect of Alirocumab on Lipoprotein(a) and Cardiovascular Risk After AcuteCoronary Syndrome. Journal of the American College of Cardiology Bittner, V. A., Szarek, M., Aylward, P. E., Bhatt, D. L., Diaz, R., Edelberg, J. M., Fras, Z., Goodman, S. G., Halvorsen, S., Hanotin, C., Harrington, R. A., Jukema, J. W., Loizeau, V., Moriarty, P. M., Moryusef, A., Pordy, R., Roe, M. T., Sinnaeve, P., Tsimikas, S., Vogel, R., White, H. D., Zahger, D., Zeiher, A. M., Steg, P. G., Schwartz, G. G., ODYSSEY OUTCOMES Committees and Investigators 2020; 75 (2): 133–44

    Abstract

    BACKGROUND: Lipoprotein(a) concentration is associated with cardiovascular events. Alirocumab, a proprotein convertase subtilisin/kexin type 9 inhibitor, lowers lipoprotein(a) and low-density lipoprotein cholesterol (LDL-C).OBJECTIVES: A pre-specified analysis of the placebo-controlled ODYSSEY Outcomes trial in patients with recent acute coronary syndrome (ACS) determined whether alirocumab-induced changes in lipoprotein(a) and LDL-C independently predicted major adverse cardiovascular events (MACE).METHODS: One to 12months after ACS, 18,924 patients on high-intensity statin therapy were randomized to alirocumab or placebo and followed for 2.8 years (median). Lipoprotein(a) was measured at randomization and 4 and 12months thereafter. The primary MACE outcome was coronary heart disease death, nonfatal myocardial infarction, ischemic stroke, or hospitalization for unstable angina.RESULTS: Baseline lipoprotein(a) levels (median: 21.2mg/dl; interquartile range [IQR]: 6.7 to 59.6mg/dl) and LDL-C [corrected for cholesterol content in lipoprotein(a)] predicted MACE. Alirocumab reduced lipoprotein(a) by 5.0mg/dl (IQR: 0 to 13.5mg/dl), corrected LDL-C by 51.1mg/dl (IQR: 33.7 to 67.2mg/dl), and reduced the risk of MACE (hazardratio [HR]: 0.85; 95% confidence interval [CI]: 0.78 to 0.93). Alirocumab-induced reductions of lipoprotein(a) and corrected LDL-C independently predicted lower risk of MACE, after adjustment for baseline concentrations of both lipoproteins and demographic and clinical characteristics. A 1-mg/dl reduction in lipoprotein(a) with alirocumab was associated with a HR of 0.994 (95%CI: 0.990 to 0.999; p=0.0081).CONCLUSIONS: Baseline lipoprotein(a) and corrected LDL-C levels and their reductions by alirocumab predicted the risk of MACE after recent ACS. Lipoprotein(a) lowering by alirocumab is an independent contributor to MACE reduction, which suggests that lipoprotein(a) should be an independent treatment target after ACS. (ODYSSEY Outcomes: Evaluationof Cardiovascular Outcomes After an Acute Coronary Syndrome During Treatment With Alirocumab; NCT01663402).

    View details for DOI 10.1016/j.jacc.2019.10.057

    View details for PubMedID 31948641

  • Cardiorespiratory Fitness, Body-Mass Index, and Markers of Insulin Resistance in Apparently Healthy Women and Men. The American journal of medicine Clarke, S. L., Reaven, G. M., Leonard, D., Barlow, C. E., Haskell, W. L., Willis, B. L., DeFina, L., Knowles, J. W., Maron, D. J. 2020

    Abstract

    BACKGROUND: Insulin resistance may be present in healthy adults and is associated poor health outcomes. Obesity is a risk factor for insulin resistance, but most obese adults do not have insulin resistance. Fitness may be protective, but the association between fitness, weight, and insulin resistance has not been studied in a large population of healthy adults.METHODS: A cross-sectional analysis of cardiorespiratory fitness, body-mass index, and markers of insulin resistance was performed. Study participants were enrolled at the Cooper Clinic (Dallas, Texas). The analysis included 19,263 women and 48,433 men with no history of diabetes or cardiovascular disease. Cardiorespiratory fitness was measured using exercise treadmill testing. Impaired fasting glucose (100-125 mg/dL) and elevated fasting triglycerides (≥150 mg/dL) were used as a markers of insulin resistance.RESULTS: Among normal weight individuals, poor fitness was associated with a 2.2 (1.4-3.6; p=0.001) fold higher odds of insulin resistance in women and a 2.8 (2.1-3.6; p<0.001) fold higher odds in men. The impact of fitness remained significant for overweight and obese individuals, with the highest risk group being the unfit obese. Among obese women, the odds ratio for insulin resistance was 11.0 (8.7-13.9; p<0.001) for fit and 20.3 (15.5-26.5; p<0.001) for unfit women. Among obese men, the odds ratio for insulin resistance was 7.4 (6.7-8.2; p<0.001) for fit and 12.9 (11.4-14.6; p<0.001) for unfit men.CONCLUSION: Independent of weight, poor fitness is associated with risk of insulin resistance. Obese individuals, particularly women, may benefit from the greatest absolute risk reduction by achieving moderate fitness.

    View details for DOI 10.1016/j.amjmed.2019.11.031

    View details for PubMedID 31926863

  • FAM13A affects body fat distribution and adipocyte function. Nature communications Fathzadeh, M., Li, J., Rao, A., Cook, N., Chennamsetty, I., Seldin, M., Zhou, X., Sangwung, P., Gloudemans, M. J., Keller, M., Attie, A., Yang, J., Wabitsch, M., Carcamo-Orive, I., Tada, Y., Lusis, A. J., Shin, M. K., Molony, C. M., McLaughlin, T., Reaven, G., Montgomery, S. B., Reilly, D., Quertermous, T., Ingelsson, E., Knowles, J. W. 2020; 11 (1): 1465

    Abstract

    Genetic variation in the FAM13A (Family with Sequence Similarity 13 Member A) locus has been associated with several glycemic and metabolic traits in genome-wide association studies (GWAS). Here, we demonstrate that in humans, FAM13A alleles are associated with increased FAM13A expression in subcutaneous adipose tissue (SAT) and an insulin resistance-related phenotype (e.g. higher waist-to-hip ratio and fasting insulin levels, but lower body fat). In human adipocyte models, knockdown of FAM13A in preadipocytes accelerates adipocyte differentiation. In mice, Fam13a knockout (KO) have a lower visceral to subcutaneous fat (VAT/SAT) ratio after high-fat diet challenge, in comparison to their wild-type counterparts. Subcutaneous adipocytes in KO mice show a size distribution shift toward an increased number of smaller adipocytes, along with an improved adipogenic potential. Our results indicate that GWAS-associated variants within the FAM13A locus alter adipose FAM13A expression, which in turn, regulates adipocyte differentiation and contribute to changes in body fat distribution.

    View details for DOI 10.1038/s41467-020-15291-z

    View details for PubMedID 32193374

  • Genomic integrity of human induced pluripotent stem cells across nine studies in the NHLBI NextGen program. Stem cell research Kanchan, K., Iyer, K., Yanek, L. R., Carcamo-Orive, I., Taub, M. A., Malley, C., Baldwin, K., Becker, L. C., Broeckel, U., Cheng, L., Cowan, C., D'Antonio, M., Frazer, K. A., Quertermous, T., Mostoslavsky, G., Murphy, G., Rabinovitch, M., Rader, D. J., Steinberg, M. H., Topol, E., Yang, W., Knowles, J. W., Jaquish, C. E., Ruczinski, I., Mathias, R. A. 2020; 46: 101803

    Abstract

    Human induced pluripotent stem cell (hiPSC) lines have previously been generated through the NHLBI sponsored NextGen program at nine individual study sites. Here, we examined the structural integrity of 506 hiPSC lines as determined by copy number variations (CNVs). We observed that 149 hiPSC lines acquired 258 CNVs relative to donor DNA. We identified six recurrent regions of CNVs on chromosomes 1, 2, 3, 16 and 20 that overlapped with cancer associated genes. Furthermore, the genes mapping to regions of acquired CNVs show an enrichment in cancer related biological processes (IL6 production) and signaling cascades (JNK cascade & NFκB cascade). The genomic region of instability on chr20 (chr20q11.2) includes transcriptomic signatures for cancer associated genes such as ID1, BCL2L1, TPX2, PDRG1 and HCK. Of these HCK shows statistically significant differential expression between carrier and non-carrier hiPSC lines. Overall, while a low level of genomic instability was observed in the NextGen generated hiPSC lines, the observation of structural instability in regions with known cancer associated genes substantiates the importance of systematic evaluation of genetic variations in hiPSCs before using them as disease/research models.

    View details for DOI 10.1016/j.scr.2020.101803

    View details for PubMedID 32442913

  • Women Living with Familial Hypercholesterolemia: Challenges and Considerations Surrounding Their Care. Current atherosclerosis reports Balla, S., Ekpo, E. P., Wilemon, K. A., Knowles, J. W., Rodriguez, F. 2020; 22 (10): 60

    Abstract

    To highlight the gender-based differences in presentation and disparities in care for women with familial hypercholesterolemia (FH).Women with FH experience specific barriers to care including underrepresentation in research, significant underappreciation of risk, and interrupted therapy during childbearing. National and international registry and clinical trial data show significant healthcare disparities for women with FH. Women with FH are less likely to be on guideline-recommended high-intensity statin medications and those placed on statins are more likely to discontinue them within their first year. Women with FH are also less likely to be on regimens including non-statin agents such as PCSK9 inhibitors. As a result, women with FH are less likely to achieve target low-density lipoprotein cholesterol (LDL-C) targets, even those with prior atherosclerotic cardiovascular disease (ASCVD). FH is common, under-diagnosed, and under-treated. Disparities of care are more pronounced in women than men. Additionally, FH weighs differently on women throughout the course of their lives starting from choosing contraceptives as young girls along with lipid-lowering therapy, timing pregnancy, choosing breastfeeding or resumption of therapy, and finally deciding goals of care during menopause. Early identification and appropriate treatment prior to interruptions of therapy for childbearing can lead to marked reduction in morbidity and mortality. Women access care differently than men and increasing awareness among all providers, especially cardio-obstetricians, may improve diagnostic rates. Understanding the unique challenges women with FH face is crucial to close the gaps in care they experience.

    View details for DOI 10.1007/s11883-020-00881-5

    View details for PubMedID 32816232

  • Mitochondrial dysfunction, insulin resistance and potential genetic implications. Endocrinology Sangwung, P., Petersen, K. F., Shulman, G. I., Knowles, J. W. 2020

    Abstract

    Insulin resistance, IR, is fundamental to the development type 2 diabetes (T2D) and is present in most prediabetic (preDM) individuals. IR has both heritable and environmental determinants centered on energy storage and metabolism. Recent insights from human genetic studies, coupled with comprehensive in vivo and ex vivo metabolic studies in humans and rodents have highlighted the critical role of reduced mitochondrial function as a predisposing condition for ectopic lipid deposition and IR. These studies support the hypothesis that reduced mitochondrial function, particularly in insulin responsive tissues such as skeletal muscle, white adipose tissue, and liver is inextricably linked to tissue and whole body IR through effects on cellular energy balance. Here we discuss these findings as well as address potential mechanisms that serve as the nexus between mitochondrial malfunction and IR.

    View details for DOI 10.1210/endocr/bqaa017

    View details for PubMedID 32060542

  • RNA Interference Targeting Apolipoprotein C-III Results in Deep and Prolonged Reductions in Plasma Triglycerides Schwabe, C., Scott, R., Sullivan, D. R., Baker, J., Clifton, P., Hamilton, J., Given, B., Melquist, S., Knowles, J., Hegele, R. A., Ballantyne, C. M. LIPPINCOTT WILLIAMS & WILKINS. 2019: E987
  • RNA Interference Targeting Hepatic Angiopoietin-Like Protein 3 Results in Prolonged Reductions in Plasma Triglycerides and LDL-C in Human Subjects Watts, G. F., Schwabe, C., Scott, R., Gladding, P., Sullivan, D. R., Baker, J., Clifton, P., Hamilton, J., Given, B., Melquist, S., Knowles, J., Hegele, R. A., Ballantyne, C. M. LIPPINCOTT WILLIAMS & WILKINS. 2019: E987–E988
  • Precision screening for familial hypercholesterolaemia: a machine learning study applied to electronic health encounter data LANCET DIGITAL HEALTH Myers, K. D., Knowles, J. W., Staszak, D., Shapiro, M. D., Howard, W., Yadava, M., Zuzick, D., Williamson, L., Shah, N. H., Banda, J. M., Leader, J., Cromwell, W. C., Trautman, E., Murray, M. F., Baum, S. J., Myers, S., Gidding, S. S., Wilemon, K., Rader, D. J. 2019; 1 (8): E393–E402
  • Alirocumab in Patients With Polyvascular Disease and Recent Acute Coronary Syndrome ODYSSEY OUTCOMES Trial JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY Jukema, J., Szarek, M., Zijlstra, L. E., de Silva, H., Bhatt, D. L., Bittner, V. A., Diaz, R., Edelberg, J. M., Goodman, S. G., Hanotin, C., Harrington, R. A., Karpov, Y., Moryusef, A., Pordy, R., Prieto, J. C., Roe, M. T., White, H. D., Zeiher, A. M., Schwartz, G. G., Steg, P., ODYSSEY OUTCOMES Comm Investigator 2019; 74 (9): 1167–76
  • Risk Categorization Using New American College of Cardiology/American Heart Association Guidelines for Cholesterol Management and Its Relation to Alirocumab Treatment Following Acute Coronary Syndromes. Circulation Roe, M. T., Li, Q. H., Bhatt, D. L., Bittner, V. A., Diaz, R., Goodman, S. G., Harrington, R. A., Jukema, J. W., Lopez-Jaramillo, P., Lopes, R. D., Louie, M. J., Moriarty, P. M., Szarek, M., Vogel, R., White, H. D., Zeiher, A. M., Baccara-Dinet, M. T., Steg, P. G., Schwartz, G. G., ODYSSEY OUTCOMES Investigators 2019

    View details for DOI 10.1161/CIRCULATIONAHA.119.042551

    View details for PubMedID 31475572

  • SPECIFICATION OF ACMG/AMP GUIDELINES FOR VARIANT INTERPRETATION IN FAMILIAL HYPERCHOLESTEROLEMIA Chora, J. R., Iacocca, M. A., Carrie, A., Leigh, S. E., Tichy, L., Kurtz, C. L., Freiberger, T., Sijbrands, E. J., Hegele, R. A., Knowles, J. W., Bourbon, M. ELSEVIER IRELAND LTD. 2019: E68
  • The role of insulin as a key regulator of seeding, proliferation, and mRNA transcription of human pluripotent stem cells. Stem cell research & therapy Shahbazi, M., Cundiff, P., Zhou, W., Lee, P., Patel, A., D'Souza, S. L., Abbasi, F., Quertermous, T., Knowles, J. W. 2019; 10 (1): 228

    Abstract

    BACKGROUND: Human-induced pluripotent stem cells (hiPSCs) show a great promise as a renewable source of cells with broad biomedical applications. Since insulin has been used in the maintenance of hiPSCs, in this study we explored the role of insulin in culture of these cells.METHODS: We report conditions for insulin starvation and stimulation of hiPSCs. Crystal violet staining was used to study the adhesion and proliferation of hiPSCs. Apoptosis and cell cycle assays were performed through flow cytometry. Protein arrays were used to confirm phosphorylation targets, and mRNA sequencing was used to evaluate the effect of transcriptome.RESULTS: Insulin improved the seeding and proliferation of hiPSCs. We also observed an altered cell cycle profile and increase in apoptosis in hiPSCs in the absence of insulin. Furthermore, we confirmed phosphorylation of key components of insulin signaling pathway in the presence of insulin and demonstrated the significant effect of insulin on regulation of the mRNA transcriptome of hiPSCs.CONCLUSION: Insulin is a major regulator of seeding, proliferation, phosphorylation and mRNA transcriptome in hiPSCs. Collectively, our work furthers our understanding of human pluripotency and paves the way for future studies that use hiPSCs for modeling genetic ailments affecting insulin signaling pathways.

    View details for DOI 10.1186/s13287-019-1319-5

    View details for PubMedID 31358052

  • Effects of alirocumab on cardiovascular and metabolic outcomes after acute coronary syndrome in patients with or without diabetes: a prespecified analysis of the ODYSSEY OUTCOMES randomised controlled trial. The lancet. Diabetes & endocrinology Ray, K. K., Colhoun, H. M., Szarek, M., Baccara-Dinet, M., Bhatt, D. L., Bittner, V. A., Budaj, A. J., Diaz, R., Goodman, S. G., Hanotin, C., Harrington, R. A., Jukema, J. W., Loizeau, V., Lopes, R. D., Moryusef, A., Murin, J., Pordy, R., Ristic, A. D., Roe, M. T., Tunon, J., White, H. D., Zeiher, A. M., Schwartz, G. G., Steg, P. G., ODYSSEY OUTCOMES Committees and Investigators, Schwartz, G. G., Steg, P. G., Bhatt, D. L., Bittner, V. A., Diaz, R., Goodman, S. G., Harrington, R. A., Jukema, J. W., Szarek, M., White, H. D., Zeiher, A. M., Tricoci, P., Roe, M. T., Mahaffey, K. W., Edelberg, J. M., Hanotin, C., Lecorps, G., Moryusef, A., Pordy, R., Sasiela, W. J., Tamby, J., Aylward, P. E., Drexel, H., Sinnaeve, P., Dilic, M., Lopes, R. 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M., Ushakov, O., Dzyak, G., Goloborodko, B., Rudenko, A., Zheleznyy, V., Trevelyan, J., Zaman, A., Lee, K., Moriarty, A., Aggarwal, R. K., Clifford, P., Wong, Y., Iqbal, S. M., Subkovas, E., Braganza, D., Sarkar, D., Storey, R., Griffiths, H., McClure, S., Muthusamy, R., Smith, S., Kurian, J., Levy, T., Barr, C., Kadr, H., Gerber, R., Simaitis, A., Soran, H., Mathur, A., Brodison, A., Ayaz, M., Cheema, M., Oliver, R., Thackray, S., Mudawi, T., Rahman, G., Sultan, A., Sharman, D., Sprigings, D., Butler, R., Wilkinson, P., Lip, G. Y., Halcox, J., Gallagher, S., Ossei-Gerning, N., Vardi, G., Baldari, D., Brabham, D., Treasure Ii, C., Dahl, C., Palmer, B., Wiseman, A., Khan, A., Puri, S., Mohart, A. E., Ince, C., Flores, E., Wright, S., Cheng, S., Rosenberg, M., Rogers, W. J., Kosinski, E., Forgosh, L., Waltman, J., Khan, M., Shoukfeh, M., Dagher, G., Cambier, P., Lieber, I., Kumar, P., East, C., Krichmar, P., Hasan, M., White, L., Knickelbine, T., Haldis, T., Gillespie, E., Amidon, T., Suh, D., Arif, I., Abdallah, M., Akhter, F., Carlson, E., D'Urso, M., El-Ahdab, F., Nelson, W., Moriarty, K., Harris, B., Cohen, S., Carter, L., Doty, D., Sabatino, K., Haddad, T., Malik, A., Rao, S., Mulkay, A., Jovin, I., Klancke, K., Malhotra, V., Devarapalli, S. K., Koren, M., Chandna, H., Dodds Iii, G., Goraya, T., Bengston, J., Janik, M., Moran, J., Sumner, A., Kobayashi, J., Davis, W., Yazdani, S., Pasquini, J., Thakkar, M., Vedere, A., Leimbach, W., Rider, J., Fenton, S., Singh, N., Shah, A. V., Janosik, D., Pepine, C., Berman, B., Gelormini, J., Daniels, C., Richard, K., Keating, F., Kondo, N. I., Shetty, S., Levite, H., Waider, W., Takata, T., Abu-Fadel, M., Shah, V., Aggarwal, R., Izzo, M., Kumar, A., Hattler, B., Do, R., Link, C., Bortnick, A., Kinzfogl Iii, G., Ghitis, A., Larry, J., Teufel, E., Kuhlman, P., Mclaurin, B., Zhang, W., Thew, S., Abbas, J., White, M., Islam, O., Subherwal, S., Ranadive, N., Vakili, B., Gring, C., Henderson, D., Schuchard, T., Farhat, N., Kline, G., Mahal, S., Whitaker, J., Speirs, S., Andersen, R., Daboul, N., Horwitz, P., Zahr, F., Ponce, G., Jafar, Z., Mcgarvey, J. J., Panchal, V., Voyce, S., Blok, T., Sheldon, W., Azizad, M. M., Schmalfuss, C., Picone, M., Pederson, R., Herzog, W. J., Friedman, K., Lindsey, J., Nowins, R., Timothy, E., Leonard, P., Lepor, N., El Shahawy, M., Weintraub, H., Irimpen, A., Alonso, A., May, W., Christopher, D., Galski, T., Chu, A., Mody, F., Ramin, E., Hodes, Z., Rossi, J., Rose, G., Fairlamb, J., Lambert, C. J., Raisinghani, A., Abbate, A., Vetrovec, G., King, M., Carey, C., Gerber, J., Younis, L., Park, H. T., Vidovich, M., Knutson, T., Friedman, D., Chaleff, F., Loussararian, A., Rozeman, P., Kimmelstiel, C., Kuvin, J., Silver, K., Foster, M., Tonnessen, G., Espinoza, A., Amlani, M., Wali, A., Malozzi, C., Jong, G. T., Massey, C., Wattanakit, K., O'Donnell, P. J., Singal, D., Jaffrani, N., Banuru, S., Fisher, D., Xenakis, M., Perlmutter, N., Bhagwat, R., Strader, J. J., Blonder, R., Akyea-Djamson, A., Labroo, A., Lee, K., Marais, H. J., Claxton, E. J., Weiss, R., Kathryn, R., Berk, M., Rossi, P., Joshi, P., Khera, A., Khaira, A. S., Kumkumian, G., Lupovitch, S., Purow, J., Welka, S., Hoffman, D., Fischer, S., Soroka, E., Eagerton, D., Pancholy, S., Ray, M., Erenrich, N., Farrar, M., Pollock, S., French, W. J., Diamantis, S., Guy, D., Gimple, L., Neustel, M., Schwartz, S., Pereira, E., Albert, S., Spriggs, D., Strain, J., Mittal, S., Vo, A., Chane, M., Hall, J., Vijay, N., Lotun, K., Lester, F. M., Nahhas, A., Pope, T., Nager, P., Vohra, R., Sharma, M., Bashir, R., Ahmed, H., Berlowitz, M., Fishberg, R., Barrucco, R., Yang, E., Radin, M., Sporn, D., Stapleton, D., Eisenberg, S., Landzberg, J., Mcgough, M., Turk, S., Schwartz, M., Sundram, P. S., Jain, D., Zainea, M., Bayron, C., Karlsberg, R., Dohad, S., Lui, H., Keen, W., Westerhausen, D. J., Khurana, S., Agarwal, H., Birchem, J., Penny, W. J., Chang, M., Murphy, S., Henry, J., Schifferdecker, B., Gilbert, J. M., Chalavarya, G., Eaton, C., Schmedtje, J. F., Christenson, S., Dotani, I., Denham, D., Macdonell, A., Gibson, P., Rahman, A., Al Joundi, T., Assi, N., Conrad, G., Kotha, P., Love, M., Giesler, G., Rubenstein, H., Gamil, D., Akright, L., Krawczyk, J., Cobler, J., Wells, T., Welker, J., Foster, R., Gilmore, R., Anderson, J., Jacoby, D., Harris, B., Gardner, G., Dandillaya, R., Vora, K., Kostis, J., Hunter, J., Laxson, D., Ball, E., Wells, T., Vora, K., Ball, E., Welker, J., Lopes, R., Egydio, F., Kawakami, A., Oliveira, J., Wozniak, J., Matthews, A., Ratky, C., Valiris, J., Berdan, L., Hepditch, A., Quintero, K., Rorick, T., Westbrook, M., Pascual, A., Rovito, C., Bezault, M., Drouet, E., Simon, T., White, H. D., Alsweiler, C., Luyten, A., Butters, J., Griffith, L., Shaw, M., Grunberg, L., Islam, S., Bregeault, M., Bougon, N., Faustino, D., Fontecave, S., Murphy, J., Verrier, M., Agnetti, V., Andersen, D., Badreddine, E., Bekkouche, M., Bouancheau, C., Brigui, I., Brocklehurst, M., Cianciarulo, J., Devaul, D., Domokos, S., Gache, C., Gobillot, C., Guillou, S., Healy, J., Heath, M., Jaiwal, G., Javierre, C., Labeirie, J., Monier, M., Morales, U., Mrabti, A., Mthombeni, B., Okan, B., Smith, L., Sheller, J., Sopena, S., Pellan, V., Benbernou, F., Bengrait, N., Lamoureux, M., Kralova, K., Scemama, M., Bejuit, R., Coulange, A., Berthou, C., Repincay, J., Lorenzato, C., Etienne, A., Gouet, V., Lecorps, G., Loizeau, V., Normand, M., Ourliac, A., Rondel, C., Adamo, A., Beltran, P., Barraud, P., Dubois-Gache, H., Halle, B., Metwally, L., Mourgues, M., Sotty, M., Vincendet, M., Cotruta, R., Chengyue, Z., Fournie-Lloret, D., Morrello, C., Perthuis, A., Picault, P., Zobouyan, I., Colhoun, H. M., Dempsey, M. A., McClanahan, M. A. 2019

    Abstract

    BACKGROUND: After acute coronary syndrome, diabetes conveys an excess risk of ischaemic cardiovascular events. A reduction in mean LDL cholesterol to 1·4-1·8 mmol/L with ezetimibe or statins reduces cardiovascular events in patients with an acute coronary syndrome and diabetes. However, the efficacy and safety of further reduction in LDL cholesterol with an inhibitor of proprotein convertase subtilisin/kexin type 9 (PCSK9) after acute coronary syndrome is unknown. We aimed to explore this issue in a prespecified analysis of the ODYSSEY OUTCOMES trial of the PCSK9 inhibitor alirocumab, assessing its effects on cardiovascular outcomes by baseline glycaemic status, while also assessing its effects on glycaemic measures including risk of new-onset diabetes.METHODS: ODYSSEY OUTCOMES was a randomised, double-blind, placebo-controlled trial, done at 1315 sites in 57 countries, that compared alirocumab with placebo in patients who had been admitted to hospital with an acute coronary syndrome (myocardial infarction or unstable angina) 1-12 months before randomisation and who had raised concentrations of atherogenic lipoproteins despite use of high-intensity statins. Patients were randomly assigned (1:1) to receive alirocumab or placebo every 2 weeks; randomisation was stratified by country and was done centrally with an interactive voice-response or web-response system. Alirocumab was titrated to target LDL cholesterol concentrations of 0·65-1·30 mmol/L. In this prespecified analysis, we investigated the effect of alirocumab on cardiovascular events by glycaemic status at baseline (diabetes, prediabetes, or normoglycaemia)-defined on the basis of patient history, review of medical records, or baseline HbA1c or fasting serum glucose-and risk of new-onset diabetes among those without diabetes at baseline. The primary endpoint was a composite of death from coronary heart disease, non-fatal myocardial infarction, fatal or non-fatal ischaemic stroke, or unstable angina requiring hospital admission. ODYSSEY OUTCOMES is registered with ClinicalTrials.gov, number NCT01663402.FINDINGS: At study baseline, 5444 patients (28·8%) had diabetes, 8246 (43·6%) had prediabetes, and 5234 (27·7%) had normoglycaemia. There were no significant differences across glycaemic categories in median LDL cholesterol at baseline (2·20-2·28 mmol/L), after 4 months' treatment with alirocumab (0·80 mmol/L), or after 4 months' treatment with placebo (2·25-2·28 mmol/L). In the placebo group, the incidence of the primary endpoint over a median of 2·8 years was greater in patients with diabetes (16·4%) than in those with prediabetes (9·2%) or normoglycaemia (8·5%); hazard ratio (HR) for diabetes versus normoglycaemia 2·09 (95% CI 1·78-2·46, p<0·0001) and for diabetes versus prediabetes 1·90 (1·65-2·17, p<0·0001). Alirocumab resulted in similar relative reductions in the incidence of the primary endpoint in each glycaemic category, but a greater absolute reduction in the incidence of the primary endpoint in patients with diabetes (2·3%, 95% CI 0·4 to 4·2) than in those with prediabetes (1·2%, 0·0 to 2·4) or normoglycaemia (1·2%, -0·3 to 2·7; absolute risk reduction pinteraction=0·0019). Among patients without diabetes at baseline, 676 (10·1%) developed diabetes in the placebo group, compared with 648 (9·6%) in the alirocumab group; alirocumab did not increase the risk of new-onset diabetes (HR 1·00, 95% CI 0·89-1·11). HRs were 0·97 (95% CI 0·87-1·09) for patients with prediabetes and 1·30 (95% CI 0·93-1·81) for those with normoglycaemia (pinteraction=0·11).INTERPRETATION: After a recent acute coronary syndrome, alirocumab treatment targeting an LDL cholesterol concentration of 0·65-1·30 mmol/L produced about twice the absolute reduction in cardiovascular events among patients with diabetes as in those without diabetes. Alirocumab treatment did not increase the risk of new-onset diabetes.FUNDING: Sanofi and Regeneron Pharmaceuticals.

    View details for DOI 10.1016/S2213-8587(19)30158-5

    View details for PubMedID 31272931

  • Polygenic risk scores in coronary artery disease CURRENT OPINION IN CARDIOLOGY Rao, A. S., Knowles, J. W. 2019; 34 (4): 435–40
  • Trends in overall, cardiovascular and cancer-related mortality among individuals with diabetes reported on death certificates in the United States between 2007 and 2017 DIABETOLOGIA Kim, D., Li, A. A., Cholankeril, G., Kim, S. H., Ingelsson, E., Knowles, J. W., Harrington, R. A., Ahmed, A. 2019; 62 (7): 1185–94
  • No evidence of a causal association of type 2 diabetes and glucose metabolism with atrial fibrillation DIABETOLOGIA Harati, H., Zanetti, D., Rao, A., Gustafsson, S., Perez, M., Ingelsson, E., Knowles, J. W. 2019; 62 (5): 800–804
  • Trends in overall, cardiovascular and cancer-related mortality among individuals with diabetes reported on death certificates in the United States between 2007 and 2017. Diabetologia Kim, D., Li, A. A., Cholankeril, G., Kim, S. H., Ingelsson, E., Knowles, J. W., Harrington, R. A., Ahmed, A. 2019

    Abstract

    AIMS/HYPOTHESIS: The determination of diabetes as underlying cause of death by using the death certificate may result in inaccurate estimation of national mortality attributed to diabetes, because individuals who die with diabetes generally have other conditions that may contribute to their death. We investigated the trends in age-standardised mortality due to diabetes as underlying or contributing cause of death and cause-specific mortality from cardiovascular disease (CVD), complications of diabetes and cancer among individuals with diabetes listed on death certificates in the USA from 2007 to 2017.METHODS: Using the US Census and national mortality database, we calculated age-standardised mortality due to diabetes as underlying or contributing cause of death and cause-specific mortality rates among adults over 20years with diabetes listed on death certificates. A total of 2,686,590 deaths where diabetes was underlying or contributing cause of death were analysed. We determined temporal mortality rate patterns by joinpoint regression analysis with estimates of annual percentage change (APC).RESULTS: Age-standardised diabetes mortality rates compared among underlying cause of death, contributing cause of death and all-cause mortality were 32.2 vs 75.7 vs 105.1 per 100,000 individuals during the study period. The age-standardised mortality rates due to diabetes as underlying or contributing cause of death declined from 112.2 per 100,000 individuals in 2007 to 104.3 per 100,000 individuals in 2017 with the most pronounced decline noted from 2007 to 2014 (APC -1.4%; 95% CI -1.9%, -1.0%) and stabilisation in decline from 2014 to 2017 (APC 1.1%; 95% CI -0.6%, 2.8%). In terms of cause-specific mortality among individuals with diabetes listed on death certificates, the age-standardised mortality rates for CVD declined at an annual rate of 1.2% with a marked decline of 2.3% between 2007 and 2014. Age-standardised diabetes-specific mortality rates as underlying cause of death decreased from 2007 to 2009 (APC -4.5%) and remained stable from 2009 to 2017. Age-standardised mortality rates for cancer steadily decreased with an average APC of -1.4% (95% CI -1.8%, -1.0%) during the 11-year period. Mortality in the subcategory of CVD demonstrated significant differences.CONCLUSIONS/INTERPRETATION: Current national estimates capture about 30% of all-cause mortality among individuals with diabetes listed as underlying or contributing cause of death on death certificates. The age-standardised mortality due to diabetes as underlying or contributing cause of death and cause-specific mortality from CVD in individuals with diabetes listed as underlying or contributing cause of death plateaued from 2014 onwards except for hypertensive heart disease and heart failure.

    View details for PubMedID 31011776

  • Body composition and atrial fibrillation: a Mendelian randomization study EUROPEAN HEART JOURNAL Tikkanen, E., Gustafsson, S., Knowles, J. W., Perez, M., Burgess, S., Ingelsson, E. 2019; 40 (16): 1277-+
  • Polygenic risk scores in coronary artery disease. Current opinion in cardiology Rao, A. S., Knowles, J. W. 2019

    Abstract

    PURPOSE OF REVIEW: Large genome-wide association studies (GWAS) have identified variants accounting for a substantial portion of the heritable risk for coronary artery disease (CAD). These studies have not only catalyzed drug discovery but also have opened the possibility of improved risk prediction and stratification. Here we review the current state-of-the art in polygenic risk scores (PRSs) and look to the future, as these scores move towards clinical application.RECENT FINDINGS: Over the last decade, multilocus PRSs for CAD have expanded to include millions of variants and demonstrated strong association with CAD outcomes, even when adjusted for traditional risk factors. Recently, PRSs have shown better prediction of CAD outcomes than any single traditional risk factor alone. Advances in statistical methods used to generate PRSs have improved their predictive ability and transferability between populations with varied ancestries. Initial clinical studies have also demonstrated the potential of genetic information to impact shared decision-making between patients and providers, leading to improved outcomes.SUMMARY: PRSs can improve risk stratification for CAD especially in white/European populations and have the potential to alter routine clinical care. However, unlocking this potential will require additional research in PRSs in nonwhite populations and substantial investment in clinical implementation studies.

    View details for PubMedID 30994529

  • Finding missed cases of familial hypercholesterolemia in health systems using machine learning NPJ DIGITAL MEDICINE Banda, J. M., Sarraju, A., Abbasi, F., Parizo, J., Pariani, M., Ison, H., Briskin, E., Wand, H., Dubois, S., Jung, K., Myers, S. A., Rader, D. J., Leader, J. B., Murray, M. F., Myers, K. D., Wilemon, K., Shah, N. H., Knowles, J. W. 2019; 2
  • Impact of race/ethnicity on insulin resistance and hypertriglyceridaemia DIABETES & VASCULAR DISEASE RESEARCH Raygor, V., Abbasi, F., Lazzeroni, L. C., Kim, S., Ingelsson, E., Reaven, G. M., Knowles, J. W. 2019; 16 (2): 153–59
  • Association of Statin Adherence With Mortality in Patients With Atherosclerotic Cardiovascular Disease JAMA CARDIOLOGY Rodriguez, F., Maron, D. J., Knowles, J. W., Virani, S. S., Lin, S., Heidenreich, P. A. 2019; 4 (3): 206–13
  • No evidence of a causal association of type 2 diabetes and glucose metabolism with atrial fibrillation. Diabetologia Harati, H., Zanetti, D., Rao, A., Gustafsson, S., Perez, M., Ingelsson, E., Knowles, J. W. 2019

    Abstract

    AIMS/HYPOTHESIS: Several epidemiological studies have shown an increased risk of atrial fibrillation in individuals with type 2 diabetes or milder forms of dysglycaemia. We aimed to assess whether this relation is causal using a Mendelian randomisation approach.METHODS: Two-sample Mendelian randomisation was used to obtain estimates of the influence of type 2 diabetes, fasting blood glucose (FBG), and HbA1c on the risk of atrial fibrillation. Instrumental variables were constructed using available summary statistics from meta-analyses of genome-wide association studies (GWAS) for type 2 diabetes and associated phenotypes. Pleiotropic SNPs were excluded from the analyses. The most recent GWAS meta-analysis summary statistics for atrial fibrillation, which included over 1 million individuals (approximately 60,000 individuals with atrial fibrillation) was used for outcome analysis.RESULTS: Neither type 2 diabetes (OR 1.01 [95% CI 0.98, 1.03]; p=0.37), nor FBG (OR 0.95 [95% CI 0.82, 1.09] per mmol/l; p=0.49) or HbA1c (OR 1.01 [95% CI, 0.85, 1.17] per mmol/mol [%]; p=0.88) were associated with atrial fibrillation in Mendelian randomisation analyses. We had >80% statistical power to detect ORs of 1.08, 1.06 and 1.09 or larger for type 2 diabetes, FBG and HbA1c, respectively, for associations with atrial fibrillation.CONCLUSIONS/INTERPRETATION: This Mendelian randomisation analysis does not support a causal role of clinical significance between genetically programmed type 2 diabetes, FBG or HbA1c and development of atrial fibrillation. These data suggest that drug treatment to reduce dysglycaemia is unlikely to be an effective strategy for atrial fibrillation prevention.DATA AVAILABILITY: The datasets analysed during the current study are available from the following repository: Nielsen JB, Thorolfsdottir RB, Fritsche LG, et al (2018) GWAS summary statistics for AF (N=60,620 AF cases and 970,216 controls). Center for Statistical Genetics: http://csg.sph.umich.edu/willer/public/afib2018/nielsen-thorolfsdottir-willer-NG2018-AFib-gwas-summary-statistics.tbl.gz.

    View details for PubMedID 30810766

  • Alirocumab Reduces Total Nonfatal Cardiovascular and Fatal Events The ODYSSEY OUTCOMES Trial JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY Szarek, M., White, H. D., Schwartz, G. G., Alings, M., Bhatt, D. L., Bittner, V. A., Chiang, C., Diaz, R., Edelberg, J. M., Goodman, S. G., Hanotin, C., Harrington, R. A., Jukema, J., Kimura, T., Kiss, R., Lecorps, G., Mahaffey, K. W., Moryusef, A., Pordy, R., Roe, M. T., Tricoci, P., Xavier, D., Zeiher, A. M., Steg, G., Schwartz, G. G., Steg, P., Bhatt, D. L., Bittner, V. A., Diaz, R., Goodman, S. G., Harrington, R. A., Jukema, J., Szarek, M., White, H. D., Zeiher, A. M., Tricoci, P., Roe, M. T., Mahaffey, K. W., Edelberg, J. M., Hanotin, C., Lecorps, G., Moryusef, A., Pordy, R., Sasiela, W. J., Tamby, J., Aylward, P. E., Drexel, H., Sinnaeve, P., Dilic, M., Gotcheva, N. N., Goodman, S. G., Prieto, J., Yong, H., Lopez-Jaramillo, P., Pecin, I., Reiner, Z., Ostadal, P., Poulsen, S., Viigimaa, M., Nieminen, M. S., Danchin, N., Chumburidze, V., Marx, N., Liberopoulos, E., Valdovinos, P., Tse, H., Kiss, R., Xavier, D., Zahger, D., Valgimigli, M., Kimura, T., Kim, H., Kim, S., Kedev, S., Erglis, A., Laucevicius, A., Yusoff, K., Lopez, R., Arturo, G., Alings, M., White, H. D., Halvorsen, S., Correa Flores, R. M., Sy, R. G., Budaj, A., Morais, J., Dorobantu, M., Karpov, Y., Ristic, A. D., Chua, T., Murin, J., Fras, Z., Dalby, A. J., Tunon, J., de Silva, H., Hagstrom, E., Muller, C., Chiang, C., Sritara, P., Guneri, S., Parkhomenko, A., Ray, K. K., Moriarty, P. M., Roe, M. T., Chaitman, B., Kelsey, S. F., Olsson, A. G., Rouleau, J., Simoons, M. L., Alexander, K., Meloni, C., Rosenson, R., Sijbrands, E. G., Alexander, J. H., Armaganijan, L., Bagai, A., Bahit, M., Brennan, J., Clifton, S., DeVore, A. D., Deloatch, S., Dickey, S., Dombrowski, K., Ducrocq, G., Eapen, Z., Endsley, P., Eppinger, A., Harrison, R. W., Hess, C., Hlatky, M. A., Jordan, J., Knowles, J. W., Kolls, B. J., Kong, D. F., Leonardi, S., Lillis, L., Maron, D. J., Marcus, J., Mathews, R., Mehta, R. H., Mentz, R. J., Moreira, H., Patel, C. B., Pereira, S., Perkins, L., Povsic, T. J., Puymirat, E., Jones, W., Shah, B. R., Sherwood, M. W., Stringfellow, K., Sujjavanich, D., Toma, M., Van Diepen, S. P., Wilson, M. D., Yan, A., Lopes, R. D., Trotter, C., Schiavi, L. B., Garrido, M., Alvarisqueta, A. F., Sassone, S. A., Bordonava, A. P., Alves De Lima, A. E., Schmidberg, J. M., Duronto, E. A., Caruso, O. C., Novaretto, L. P., Angel Hominal, M., Montana, O. R., Caccavo, A., Gomez Vilamajo, O. A., Lorenzatti, A. J., Cartasegna, L. R., Paterlini, G. A., Mackinnon, I. J., Caime, G. D., Amuchastegui, M., Salomone, R., Codutti, O. R., Jure, H. O., Bono, J. E., Hrabar, A. D., Vallejos, J. A., Ahuad Guerrero, R. A., Novoa, F., Patocchi, C. A., Zaidman, C. J., Giuliano, M. E., Dran, R. D., Vico, M. L., Carnero, G. S., Guzman, P. N., Medrano Allende, J. C., Garcia Brasca, D. F., Bustamante Labarta, M. H., Nani, S., Blumberg, E. S., Colombo, H. R., Liberman, A., Luciardi, H. L., Waisman, G. D., Berli, M. A., Duran, R., Cestari, H. G., Luquez, H. A., Giordano, J. A., Saavedra, S. S., Zapata, G., Costamagna, O., Llois, S., Waites, J. H., Collins, N., Soward, A., Aylward, P. E., Hii, C. S., Shaw, J., Arstall, M. A., Horowitz, J., Rogers, J. F., Colquhoun, D., Oqueli Flores, R. E., Roberts-Thomson, P., Raffel, O., Lehman, S. J., Aroney, C., Coverdale, S. M., Garrahy, P. J., Starmer, G., Sader, M., Carroll, P. A., Dick, R., Zweiker, R., Hoppe, U., Huber, K., Berger, R., Weidinger, F., Faes, D., Hermans, K., Pirenne, B., Leone, A., Hoffer, E., Vrolix, M. M., De Wolf, L., Wollaert, B., Castadot, M., Dujardin, K., Beauloye, C., Vervoort, G., Striekwold, H., Convens, C., Roosen, J., Barbato, E., Claeys, M., Cools, F., Terzic, I., Barakovic, F., Midzic, Z., Pojskic, B., Fazlibegovic, E., Durak-Nalbantic, A., Vulic, D., Muslibegovic, A., Goronja, B., Reis, G., Sousa, L., Nicolau, J. C., Giorgeto, F. E., Silva, R. P., Maia, L., Rech, R., Rossi, P. F., Cerqueira, M. G., Duda, N., Kalil, R., Kormann, A., Abrantes, J. M., Pimentel Filho, P., Soggia, A., de Santos, M. N., Neuenschwander, F., Bodanese, L. C., Michalaros, Y. L., Eliaschewitz, F. G., Vidotti, M. H., Leaes, P. E., Botelho, R. V., Kaiser, S., Fernandes Manenti, E. F., Precoma, D. B., Moura Jorge, J. C., Silva, P. B., Silveira, J. A., Saporito, W., Marin Neto, J. A., Feitosa, G. S., Ritt, L. F., de Souza, J. A., Costa, F., Souza, W. B., Reis, H. L., Machado, L., Aidar Ayoub, J., Todorov, G. V., Nikolov, F. P., Velcheva, E. S., Tzekova, M. L., Benov, H. O., Petranov, S. L., Tumbev, H. S., Shehova-Yankova, N. S., Markov, D. T., Raev, D. H., Mollov, M. N., Kichukov, K. N., Ilieva-Pandeva, K. A., Ivanova, R., Mincheva, V. M., Lazov, P. V., Dimov, B. I., Senaratne, M., Stone, J., Kornder, J., Pearce, S., Dion, D., Savard, D., Pesant, Y., Pandey, A., Robinson, S., Gosselin, G., Vizel, S., Hoag, G., Bourgeois, R., Morisset, A., Sabbah, E., Sussex, B., Kouz, S., MacDonald, P., Diaz, A., Michaud, N., Fell, D., Leung, R., Vuurmans, T., Lai, C., Nigro, F., Davies, R., Nogareda, G., Vijayaraghavan, R., Ducas, J., Lepage, S., Mehta, S., Cha, J., Dupuis, R., Fong, P., Rodes-Cabau, J., Fadlallah, H., Cleveland, D., Thao Huynh, Bata, I., Hameed, A., Pincetti, C., Potthoff, S., Prieto, J. C., Acevedo, M., Aguirre, A., Vejar, M., Yanez, M., Araneda, G., Fernandez, M., Perez, L., Varleta, P., Florenzano, F., Huidobro, L., Raffo, C. A., Olivares, C., Nahuelpan, L., Montecinos, H., Chen, J., Dong, Y., Huang, W., Wang, J., Huang, S., Yao, Z., Li, X., Cui, L., Lin, W., Sun, Y., Wang, J., Li, J., Zhang, X., Zhu, H., Chen, D., Huang, L., Dong, S., Su, G., Xu, B., Su, X., Cheng, X., Lin, J., Zong, W., Li, H., Feng, Y., Xu, D., Yang, X., Ke, Y., Lin, X., Zhang, Z., Zheng, Z., Luo, Z., Chen, Y., Ding, C., Zheng, Y., Li, X., Peng, D., Li, Y., Wei, M., Liu, S., Yu, Y., Qu, B., Jiang, W., Zhou, Y., Zhao, X., Yuan, Z., Guo, Y., Xu, X., Shi, X., Ge, J., Fu, G., Bai, F., Fang, W., Shou, X., Yang, X., Wang, J., Sun, Y., Lu, Q., Zhang, R., Zhu, J., Xu, Y., Fan, Z., Li, T., Wu, C., Jaramillo, N., Vallejo, G., Botia, D., Lopez, R., De Salazar, D., Bonfanti, A., Higuera, J., Silva, S., Lozada, H., Arroyo, J., Mendoza, J., Ruiz, R., Jatin, F., Herazo, A., Parada, J., Triana, M., Strozzi, M., Car, S., Milicic, D., Bencic, M., Pintaric, H., Prvulovic, D., Sikic, J., Persic, V., Mileta, D., Stambuk, K., Zdravko, B., Tomulic, V., Krstulovic, S., Starcevic, B., Spinar, J., Horak, D., Stasek, J., Alan, D., Machova, V., Linhart, A., Novotny, V., Kaucak, V., Rokyta, R., Naplava, R., Coufal, Z., Adamkova, V., Podpera, I., Zizka, J., Motovska, Z., Marusincova, I., Svab, P., Ostadal, P., Heinc, P., Kuchar, J., Povolny, P., Matuska, J., Raungaard, B., Clemmensen, P., Bang, L. E., May, O., Bottcher, M., Hove, J. D., Frost, L., Gislason, G., Larsen, J., Johansen, P., Hald, F., Jeppesen, J., Nielsen, T., Kristensen, K. S., Walichiewicz, P., Lomholdt, J. D., Klausen, I. C., Nielsen, P., Davidsen, F., Videbaek, L., Soots, M., Vahula, V., Hedman, A., Soopold, U., Martsin, K., Kristjan, A., Taskinen, M., Porthan, K., Airaksinen, J. K., Juonala, M., Kiviniemi, T., Vikman, S., Posio, P., Taurio, J., Huikuri, H., Kaikkonen, K., Coste, P., Ferrari, E., Morel, O., Montalescot, G., Barone-Rochette, G., Mansourati, J., Cottin, Y., Leclercq, F., Belhassane, A., Delarche, N., Boccara, F., Paganelli, F., Clerc, J., Schiele, F., Aboyans, V., Probst, V., Berland, J., Lefevre, T., Citron, B., Khintibidze, I., Shaburishvili, T., Pagava, Z., Ghlonti, R., Lominadze, Z., Khabeishvili, G., Hemetsberger, R., Rauch-Kroehnert, U., Stratmann, M., Appel, K., Schmidt, E., Omran, H., Stellbrink, C., Dorsel, T., Lianopoulos, E., Marx, R., Zirlik, A., Schellenberg, D., Heitzer, T., Laufs, U., Marx, N., Gielen, S., Winkelmann, B., Behrens, S., Sydow, K., Simonis, G., Muenzel, T., Werner, N., Leggewie, S., Boecker, D., Braun-Dullaeus, R., Toursarkissian, N., Jeserich, M., Weissbrodt, M., Schaeufele, T., Weil, J., Voeller, H., Waltenberger, J., Natour, M., Schmitt, S., Steiner, S., Heidenreich, L., Gremmler, U., Killat, H., Rieker, W., Patsilinakos, S., Kartalis, A., Manolis, A., Sionis, D., Liberopoulos, E., Skoumas, I., Athyros, V., Vardas, P., Parthenakis, F., Alexopoulos, D., Hahalis, G., Lekakis, J., Hatzitolios, A., Ovando, S., Valdovinos, P., Benecke, J., De Leon, E., Yan, B. Y., Siu, D. W., Turi, T., Merkely, B., Kiss, R., Ungi, I., Lupkovics, G., Nagy, L., Katona, A., Edes, I., Muller, G., Horvath, I., Kapin, T., Falukozy, J., Kumbla, M., Sandhu, M., Annam, S., Proddutur, N., Premchand, R. K., Mahajan, A., Abhyanakar, A. D., Kerkar, P., Govinda, R. A., Oomman, A., Sinha, D., Patil, S. N., Kahali, D., Sawhney, J., Joshi, A. B., Chaudhary, S., Harkut, P., Guha, S., Porwal, S., Jujjuru, S., Pothineni, R. B., Monteiro, M. R., Khan, A., Iyengar, S. S., Grewal, J., Chopda, M., Fulwani, M. C., Patange, A., Chopra, V. K., Goyal, N. K., Shinde, R., Manakshe, G. V., Patki, N., Sethi, S., Munusamy, V., Karna, S., Adhyapak, S., Pandurangi, U., Mathur, R., Kalashetti, S., Bhagwat, A., Raghuraman, B., Yerra, S., Bhansali, P., Borse, R., Das, S., Abdullakutty, J., Saathe, S., Palimkar, P., Abdullkutty, J., Sathe, S., Palimkar, P., Atar, S., Shechter, M., Mosseri, M., Arbel, Y., Lotan, C., Rosenschein, U., Katz, A., Henkin, Y., Francis, A., Klutstein, M., Nikolsky, E., Turgeman, Y., Halabi, M., Kornowski, R., Jonas, M., Amir, O., Rozenman, Y., Fuchs, S., Hussein, O., Gavish, D., Vered, Z., Caraco, Y., Elias, M., Tov, N., Lishner, M., Elias, N., Piovaccari, G., De Pellegrin, A., Guardigli, G., Licciardello, G., Auguadro, C., Cuccia, C., Salvioni, A., Musumeci, G., Calabro, P., Novo, S., Faggiano, P., De Cesare, N. B., Berti, S., Cavallini, C., Puccioni, E., Galvani, M., Tespili, M., Piatti, P., Palvarini, M., De Luca, G., Violini, R., De Leo, A., Filardi, P., Ferratini, M., Ricca, V., Dai, K., Kamiya, H., Ando, K., Takeda, Y., Morino, Y., Hata, Y., Kimura, K., Kishi, K., Michishita, I., Uehara, H., Higashikata, T., Hirayama, A., Hirooka, K., Sakagami, S., Taguchi, S., Koike, A., Fujinaga, H., Koba, S., Kozuma, K., Kawasaki, T., Ono, Y., Shimizu, M., Katsuda, Y., Wada, A., Shinke, T., Kimura, T., Ako, J., Fujii, K., Takahashi, T., Sakamoto, T., Furukawa, Y., Sugino, H., Mano, T., Utsu, N., Ito, K., Haraguchi, T., Ueda, Y., Nishibe, A., Fujimoto, K., Masutani, M., Fujimoto, K., Yoon, J., Kim, S., Park, H., Chae, I., Kim, M., Jeong, M., Rha, S., Kim, C., Kim, H., Hong, T., Tahk, S., Kim, Y., Busmane, A., Pontaga, N., Strelnieks, A., Mintale, I., Sime, I., Petrulioniene, Z., Kavaliauskiene, R., Jurgaitiene, R., Sakalyte, G., Slapikas, R., Norkiene, S., Misonis, N., Kibarskis, A., Kubilius, R., Bojovski, S., Kedev, S., Lozance, N., Kjovkaroski, A., Doncovska, S., Ong, T., Kasim, S., Maskon, O., Kandasamy, B., Yusoff, K., Liew, H. B., Mohamed, W., ODYSSEY OUTCOMES Comm Investigator 2019; 73 (4): 387–96
  • Body composition and atrial fibrillation: a Mendelian randomization study. European heart journal Tikkanen, E., Gustafsson, S., Knowles, J. W., Perez, M., Burgess, S., Ingelsson, E. 2019

    Abstract

    Aims: Increases in fat-free mass and fat mass have been associated with higher risk of atrial fibrillation (AF) in observational studies. It is not known whether these associations reflect independent causal processes. Our aim was to evaluate independent causal roles of fat-free mass and fat mass on AF.Methods and results: We conducted a large observational study to estimate the associations between fat-free mass and fat mass on incident AF in the UK Biobank (N=487404, N events=10365). Genome-wide association analysis was performed to obtain genetic instruments for Mendelian randomization (MR). We evaluated the causal effects of fat-free mass and fat mass on AF with two-sample method by using genetic associations from AFGen consortium as outcome. Finally, we evaluated independent causal effects of fat-free mass and fat mass with multivariate MR. Both fat-free mass and fat mass had observational associations with incident AF [hazard ratio (HR)=1.77, 95% confidence interval (CI) 1.72-1.83; HR=1.40, 95% CI 1.37-1.43 per standard deviation increase in fat-free and fat mass, respectively]. The causal effects using the inverse-variance weighted method were 1.55 (95% CI 1.38-1.75) for fat-free mass and 1.30 (95% CI 1.17-1.45) for fat mass. Weighted median, Egger regression, and penalized methods showed similar estimates. The multivariate MR analysis suggested that the causal effects of fat-free and fat mass were independent of each other (causal risk ratios: 1.37, 95% CI 1.06-1.75; 1.28, 95% CI 1.03-1.58).Conclusion: Genetically programmed increases in fat-free mass and fat mass independently cause an increased risk of AF.

    View details for PubMedID 30721963

  • Genetic Testing and Risk Scores: Impact on Familial Hypercholesterolemia FRONTIERS IN CARDIOVASCULAR MEDICINE Sarraju, A., Knowles, J. W. 2019; 6
  • Finding missed cases of familial hypercholesterolemia in health systems using machine learning. NPJ digital medicine Banda, J. M., Sarraju, A., Abbasi, F., Parizo, J., Pariani, M., Ison, H., Briskin, E., Wand, H., Dubois, S., Jung, K., Myers, S. A., Rader, D. J., Leader, J. B., Murray, M. F., Myers, K. D., Wilemon, K., Shah, N. H., Knowles, J. W. 2019; 2: 23

    Abstract

    Familial hypercholesterolemia (FH) is an underdiagnosed dominant genetic condition affecting approximately 0.4% of the population and has up to a 20-fold increased risk of coronary artery disease if untreated. Simple screening strategies have false positive rates greater than 95%. As part of the FH Foundation's FIND FH initiative, we developed a classifier to identify potential FH patients using electronic health record (EHR) data at Stanford Health Care. We trained a random forest classifier using data from known patients (n = 197) and matched non-cases (n = 6590). Our classifier obtained a positive predictive value (PPV) of 0.88 and sensitivity of 0.75 on a held-out test-set. We evaluated the accuracy of the classifier's predictions by chart review of 100 patients at risk of FH not included in the original dataset. The classifier correctly flagged 84% of patients at the highest probability threshold, with decreasing performance as the threshold lowers. In external validation on 466 FH patients (236 with genetically proven FH) and 5000 matched non-cases from the Geisinger Healthcare System our FH classifier achieved a PPV of 0.85. Our EHR-derived FH classifier is effective in finding candidate patients for further FH screening. Such machine learning guided strategies can lead to effective identification of the highest risk patients for enhanced management strategies.

    View details for DOI 10.1038/s41746-019-0101-5

    View details for PubMedID 31304370

    View details for PubMedCentralID PMC6550268

  • Safety and Efficacy of PCSK9 Inhibitors After Heart Transplantation CANADIAN JOURNAL OF CARDIOLOGY Moayedi, Y., Kozuszko, S., Knowles, J. W., Chih, S., Oro, G., Lee, R., Fearon, W. F., Ross, H. J., Teuteberg, J. J., Khush, K. K. 2019; 35 (1)
  • Longitudinal low density lipoprotein cholesterol goal achievement and cardiovascular outcomes among adult patients with familial hypercholesterolemia: The CASCADE FH registry. Atherosclerosis Duell, P. B., Gidding, S. S., Andersen, R. L., Knickelbine, T., Anderson, L., Gianos, E., Shrader, P., Kindt, I., O'Brien, E. C., McCann, D., Hemphill, L. C., Ahmed, C. D., Martin, S. S., Larry, J. A., Ahmad, Z. S., Kullo, I. J., Underberg, J. A., Guyton, J., Thompson, P., Wilemon, K., Roe, M. T., Rader, D. J., Cuchel, M., Linton, M. F., Shapiro, M. D., Moriarty, P. M., Knowles, J. W. 2019; 289: 85–93

    Abstract

    There are limited data from the US on outcomes of patients in specialty care for familial hypercholesterolemia (FH).CASCADE FH Registry data were analyzed to assess longitudinal changes in medication usage, in low density lipoprotein cholesterol (LDL-C) levels, and the rate of major adverse cardiovascular events (MACE (myocardial infarction, coronary revascularization, stroke or transient ischemic attack) in adults with FH followed in US specialty clinics.The cohort consisted of 1900 individuals (61% women, 87% Caucasian), with mean age of 56 ± 15 years, 37% prevalence of ASCVD at enrollment, mean pretreatment LDL-C 249 ± 68 mg/dl, mean enrollment LDL-C 145 mg/dl and 93% taking lipid lowering therapy. Over follow up of 20 ± 11 months, lipid lowering therapy use increased (mean decrease in LDL-C of 32 mg/dl (p < 0.001)). Only 48% of participants achieved LDL-C < 100 mg/dl and 22% achieved LDL-C < 70 mg/dl; ASCVD at enrollment was associated with greater likelihood of goal achievement. MACE event rates were almost 6 times higher among patients with prior ASCVD compared to those without (4.6 vs 0.8/100 patient years). Also associated with incident MACE were markers of FH severity and conventional ASCVD risk factors.With care in FH specialized clinics, LDL-C decreased, but LDL-C persisted >100 mg/dl in 52% of patients. High ASCVD event rates suggest that adults with FH warrant designation as having an ASCVD risk equivalent. Earlier and more aggressive therapy of FH is needed to prevent ASCVD events.

    View details for DOI 10.1016/j.atherosclerosis.2019.08.007

    View details for PubMedID 31487564

  • CRISPR-Cas9-mediated knockout of SPRY2 in human hepatocytes leads to increased glucose uptake and lipid droplet accumulation. BMC endocrine disorders Cook, N. L., Pjanic, M., Emmerich, A. G., Rao, A. S., Hetty, S., Knowles, J. W., Quertermous, T., Castillejo-López, C., Ingelsson, E. 2019; 19 (1): 115

    Abstract

    The prevalence of obesity and its comorbidities, including type 2 diabetes mellitus (T2DM), is dramatically increasing throughout the world; however, the underlying aetiology is incompletely understood. Genome-wide association studies (GWAS) have identified hundreds of genec susceptibility loci for obesity and T2DM, although the causal genes and mechanisms are largely unknown. SPRY2 is a candidate gene identified in GWAS of body fat percentage and T2DM, and has recently been linked to insulin production in pancreatic β-cells. In the present study, we aimed to further understand SPRY2 via functional characterisation in HepG2 cells, an in vitro model of human hepatocytes widely used to investigate T2DM and insulin resistance.CRISPR-Cas9 genome editing was used to target SPRY2 in HepG2 cells, and the functional consequences of SPRY2 knockout (KO) and overexpression subsequently assessed using glucose uptake and lipid droplet assays, measurement of protein kinase phosphorylation and RNA sequencing.The major functional consequence of SPRY2 KO was a significant increase in glucose uptake, along with elevated lipid droplet accumulation. These changes were attenuated, but not reversed, in cells overexpressing SPRY2. Phosphorylation of protein kinases across key signalling pathways (including Akt and mitogen activated protein kinases) was not altered after SPRY2 KO. Transcriptome profiling in SPRY2 KO and mock (control) cells revealed a number of differentially expressed genes related to cholesterol biosynthesis, cell cycle regulation and cellular signalling pathways. Phospholipase A2 group IIA (PLA2G2A) mRNA level was subsequently validated as significantly upregulated following SPRY2 KO, highlighting this as a potential mediator downstream of SPRY2.These findings suggest a role for SPRY2 in glucose and lipid metabolism in hepatocytes and contribute to clarifying the function of this gene in the context of metabolic diseases.

    View details for DOI 10.1186/s12902-019-0442-8

    View details for PubMedID 31664995

  • Precision screening for familial hypercholesterolaemia: a machine learning study applied to electronic health encounter data. The Lancet. Digital health Myers, K. D., Knowles, J. W., Staszak, D., Shapiro, M. D., Howard, W., Yadava, M., Zuzick, D., Williamson, L., Shah, N. H., Banda, J. M., Leader, J., Cromwell, W. C., Trautman, E., Murray, M. F., Baum, S. J., Myers, S., Gidding, S. S., Wilemon, K., Rader, D. J. 2019; 1 (8): e393–e402

    Abstract

    Cardiovascular outcomes for people with familial hypercholesterolaemia can be improved with diagnosis and medical management. However, 90% of individuals with familial hypercholesterolaemia remain undiagnosed in the USA. We aimed to accelerate early diagnosis and timely intervention for more than 1·3 million undiagnosed individuals with familial hypercholesterolaemia at high risk for early heart attacks and strokes by applying machine learning to large health-care encounter datasets.We trained the FIND FH machine learning model using deidentified health-care encounter data, including procedure and diagnostic codes, prescriptions, and laboratory findings, from 939 clinically diagnosed individuals with familial hypercholesterolaemia (395 of whom had a molecular diagnosis) and 83 136 individuals presumed free of familial hypercholesterolaemia, sampled from four US institutions. The model was then applied to a national health-care encounter database (170 million individuals) and an integrated health-care delivery system dataset (174 000 individuals). Individuals used in model training and those evaluated by the model were required to have at least one cardiovascular disease risk factor (eg, hypertension, hypercholesterolaemia, or hyperlipidemia). A Health Insurance Portability and Accountability Act of 1996-compliant programme was developed to allow providers to receive identification of individuals likely to have familial hypercholesterolaemia in their practice.Using a model with a measured precision (positive predictive value) of 0·85, recall (sensitivity) of 0·45, area under the precision-recall curve of 0·55, and area under the receiver operating characteristic curve of 0·89, we flagged 1 331 759 of 170 416 201 patients in the national database and 866 of 173 733 individuals in the health-care delivery system dataset as likely to have familial hypercholesterolaemia. Familial hypercholesterolaemia experts reviewed a sample of flagged individuals (45 from the national database and 103 from the health-care delivery system dataset) and applied clinical familial hypercholesterolaemia diagnostic criteria. Of those reviewed, 87% (95% Cl 73-100) in the national database and 77% (68-86) in the health-care delivery system dataset were categorised as having a high enough clinical suspicion of familial hypercholesterolaemia to warrant guideline-based clinical evaluation and treatment.The FIND FH model successfully scans large, diverse, and disparate health-care encounter databases to identify individuals with familial hypercholesterolaemia.The FH Foundation funded this study. Support was received from Amgen, Sanofi, and Regeneron.

    View details for DOI 10.1016/S2589-7500(19)30150-5

    View details for PubMedID 33323221

  • Genetic Testing and Risk Scores: Impact on Familial Hypercholesterolemia. Frontiers in cardiovascular medicine Sarraju, A., Knowles, J. W. 2019; 6: 5

    Abstract

    Familial Hypercholesterolemia (FH) is an inherited lipid disorder affecting 1 in 220 individuals resulting in highly elevated low-density lipoprotein levels and risk of premature coronary disease. Pathogenic variants causing FH typically involve the LDL receptor (LDLR), apolipoprotein B-100 (APOB), and proprotein convertase subtulisin/kexin type 9 genes (PCSK9) and if identified convey a risk of early onset coronary artery disease (ASCVD) of 3- to 10-fold vs. the general population depending on the severity of the mutation. Identification of monogenic FH within a family has implications for family-based testing (cascade screening), risk stratification, and potentially management, and it has now been recommended that such testing be offered to all potential FH patients. Recently, robust genome wide association studies (GWAS) have led to the recognition that the accumulation of common, small effect alleles affecting many LDL-c raising genes can result in a clinical phenotype largely indistinguishable from monogenic FH (i.e., a risk of early onset ASCVD of ~3-fold) in those at the extreme tail of the distribution for these alleles (i.e., the top 8% of the population for a polygenic risk score). The incorporation of these genetic risk scores into clinical practice for non-FH patients may improve risk stratification but is not yet widely performed due to a less robust evidence base for utility. Here, we review the current status of FH genetic testing, potential future applications as well as challenges and pitfalls.

    View details for PubMedID 30761309

  • Association of Statin Adherence With Mortality in Patients With Atherosclerotic Cardiovascular Disease. JAMA cardiology Rodriguez, F., Maron, D. J., Knowles, J. W., Virani, S. S., Lin, S., Heidenreich, P. A. 2019

    Abstract

    Statins decrease mortality in those with atherosclerotic cardiovascular disease (ASCVD), but statin adherence remains suboptimal.To determine the association between statin adherence and mortality in patients with ASCVD who have stable statin prescriptions.This retrospective cohort analysis included patients who were between ages 21 and 85 years and had 1 or more International Classification of Diseases, Ninth Revision, Clinical Modification codes for ASCVD on 2 or more dates in the previous 2 years without intensity changes to their statin prescription who were treated within the Veterans Affairs Health System between January 1, 2013, and April 2014.Statin adherence was defined by the medication possession ratio (MPR). Adherence levels were categorized as an MPR of less than 50%, 50% to 69%, 70% to 89%, and 90% or greater. For dichotomous analyses, adherence was defined as an MPR of 80% or greater.The primary outcome was death of all causes adjusted for demographic and clinical characteristics, as well as adherence to other cardiac medications.Of 347 104 eligible adults with ASCVD who had stable statin prescriptions, 5472 (1.6%) were women, 284 150 (81.9%) were white, 36 208 (10.4%) were African American, 16 323 (4.7%) were Hispanic, 4093 (1.2%) were Pacific Islander, 1293 (0.4%) were Native American, 1145 (0.3%) were Asian, and 1794 (0.5%) were other races. Patients taking moderate-intensity statin therapy were more adherent than patients taking high-intensity statin therapy (odds ratio [OR], 1.18; 95% CI, 1.16-1.20). Women were less adherent (OR, 0.89; 95% CI, 0.84-0.94), as were minority groups. Younger and older patients were less likely to be adherent compared with adults aged 65 to 74 years. During a mean (SD) of 2.9 (0.8) years of follow-up, there were 85 930 deaths (24.8%). Compared with the most adherent patients (MPR ≥ 90%), patients with an MPR of less than 50% had a hazard ratio (HR; adjusted for clinical characteristics and adherence to other cardiac medications) of 1.30 (95% CI, 1.27-1.34), those with an MPR of 50% to 69% had an HR of 1.21 (95% CI, 1.18-1.24), and those with an MPR of 70% to 89% had an HR of 1.08 (95% CI, 1.06-1.09).Using a national sample of Veterans Affairs patients with ASCVD, we found that a low adherence to statin therapy was associated with a greater risk of dying. Women, minorities, younger adults, and older adults were less likely to adhere to statins. Our findings underscore the importance of finding methods to improve adherence.

    View details for PubMedID 30758506

  • Impact of race/ethnicity on insulin resistance and hypertriglyceridaemia. Diabetes & vascular disease research Raygor, V., Abbasi, F., Lazzeroni, L. C., Kim, S., Ingelsson, E., Reaven, G. M., Knowles, J. W. 2019; 16 (2): 153–59

    Abstract

    Insulin sensitivity affects plasma triglyceride concentration and both differ by race/ethnicity. The purpose of this study was to provide a comprehensive assessment of the variation in insulin sensitivity and its relationship to hypertriglyceridaemia between five race/ethnic groups.In this cross-sectional study, clinical data for 1025 healthy non-Hispanic White, Hispanic White, East Asian, South Asian and African American individuals were analysed. Insulin-mediated glucose disposal (a direct measure of peripheral insulin sensitivity) was measured using the modified insulin suppression test. Statistical analysis was performed using analysis of co-variance.Of the study participants, 63% were non-Hispanic White, 9% were Hispanic White, 11% were East Asian, 11% were South Asian and 6% were African American. Overall, non-Hispanic Whites and African Americans displayed greater insulin sensitivity than East Asians and South Asians. Triglyceride concentration was positively associated with insulin resistance in all groups, including African Americans. Nevertheless, for any given level of insulin sensitivity, African Americans had the lowest triglyceride concentrations.Insulin sensitivity, as assessed by a direct measure of insulin-mediated glucose disposal, and its relationship to triglyceride concentration vary across five race/ethnic groups. Understanding these relationships is crucial for accurate cardiovascular risk stratification and prevention.

    View details for PubMedID 31014093

  • Increasing Mortality Among Patients With Diabetes and Chronic Liver Disease From 2007 Through 2017. Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association Kim, D., Cholankeril, G., Kim, S. H., Abbasi, F., Knowles, J. W., Ahmed, A. 2019

    View details for DOI 10.1016/j.cgh.2019.06.011

    View details for PubMedID 31220638

  • Effect of Alirocumab on Mortality After Acute Coronary Syndromes: An Analysis of the ODYSSEY OUTCOMES Randomized Clinical Trial. Circulation Steg, P. G., Szarek, M., Bhatt, D. L., Bittner, V. A., Brégeault, M. F., Dalby, A. J., Diaz, R., Edelberg, J. M., Goodman, S. G., Hanotin, C., Harrington, R. A., Jukema, J. W., Lecorps, G., Mahaffey, K. W., Moryusef, A., Ostadal, P., Parkhomenko, A., Pordy, R., Roe, M. T., Tricoci, P., Vogel, R., White, H. D., Zeiher, A. M., Schwartz, G. G. 2019

    Abstract

    Trials of proprotein convertase subtilisin-kexin type 9 (PCSK9) inhibitors demonstrated reductions in major adverse cardiovascular events, but not death. We assessed the effects of alirocumab on death after index acute coronary syndrome (ACS).ODYSSEY OUTCOMES was a double-blind, randomized comparison of alirocumab or placebo in 18 924 patients who had an ACS 1-12 months previously and elevated atherogenic lipoproteins despite intensive statin therapy. Alirocumab dose was blindly titrated to target achieved low-density lipoprotein cholesterol (LDL-C) between 25 and 50 mg/dL. We examined the effects of treatment on all-cause death and its components, cardiovascular and noncardiovascular death, with log-rank testing. Joint semiparametric models tested associations between nonfatal cardiovascular events and cardiovascular or noncardiovascular death.Median follow-up was 2.8 years. Death occurred in 334 (3.5%) and 392 (4.1%) patients, respectively, in the alirocumab and placebo groups (hazard ratio [HR], 0.85; 95% confidence interval [CI], 0.73 to 0.98; P=0.03, nominal P value). This resulted from nonsignificantly fewer cardiovascular (240 [2.5%] vs 271 [2.9%]; HR, 0.88; 95% CI, 0.74 to 1.05; P=0.15) and noncardiovascular (94 [1.0%] vs 121 [1.3%]; HR, 0.77; 95% CI, 0.59 to 1.01; P=0.06) deaths with alirocumab. In a prespecified analysis of 8242 patients eligible for ≥3 years' follow-up, alirocumab reduced death (HR, 0.78; 95% CI, 0.65 to 0.94; P=0.01). Patients with nonfatal cardiovascular events were at increased risk for cardiovascular and noncardiovascular deaths ( P<0.0001 for the associations). Alirocumab reduced total nonfatal cardiovascular events ( P<0.001) and thereby may have attenuated the number of noncardiovascular deaths. A post-hoc analysis found that, compared to patients with lower LDL-C, patients with baseline LDL-C ≥100 mg/dL (2.59 mmol/L) had a greater absolute risk of death and a larger mortality benefit from alirocumab (HR, 0.71; 95% CI, 0.56 to 0.90; Pinteraction=0.007). In the alirocumab group, all-cause death declined with achieved LDL-C at 4 months of treatment, to a level of approximately 30 mg/dL (adjusted P=0.017 for linear trend).Alirocumab added to intensive statin therapy has the potential to reduce death after ACS, particularly if treatment is maintained for ≥3 years, if baseline LDL-C is ≥100 mg/dL, or if achieved LDL-C is low.URL: https://www.clinicaltrials.gov. Unique Identifier: NCT01663402.

    View details for DOI 10.1161/CIRCULATIONAHA.118.038840

    View details for PubMedID 31117810

  • Effects of Alirocumab on Cardiovascular Events After Coronary Bypass Surgery. Journal of the American College of Cardiology Goodman, S. G., Aylward, P. E., Szarek, M., Chumburidze, V., Bhatt, D. L., Bittner, V. A., Diaz, R., Edelberg, J. M., Hanotin, C., Harrington, R. A., Jukema, J. W., Kedev, S., Letierce, A., Moryusef, A., Pordy, R., Ramos López, G. A., Roe, M. T., Viigimaa, M., White, H. D., Zeiher, A. M., Steg, P. G., Schwartz, G. G. 2019; 74 (9): 1177–86

    Abstract

    Patients with acute coronary syndrome (ACS) and history of coronary artery bypass grafting (CABG) are at high risk for recurrent cardiovascular events and death.This study sought to determine the clinical benefit of adding alirocumab to statins in ACS patients with prior CABG in a pre-specified analysis of ODYSSEY OUTCOMES (Evaluation of Cardiovascular Outcomes After an Acute Coronary Syndrome During Treatment With Alirocumab).Patients (n = 18,924) 1 to 12 months post-ACS with elevated atherogenic lipoprotein levels despite high-intensity statin therapy were randomized to alirocumab or placebo subcutaneously every 2 weeks. Median follow-up was 2.8 years. The primary composite endpoint of major adverse cardiovascular events (MACE) comprised coronary heart disease death, nonfatal myocardial infarction, ischemic stroke, or unstable angina requiring hospitalization. All-cause death was a secondary endpoint. Patients were categorized by CABG status: no CABG (n = 16,896); index CABG after qualifying ACS, but before randomization (n = 1,025); or CABG before the qualifying ACS (n = 1,003).In each CABG category, hazard ratios (95% confidence intervals) for MACE (no CABG 0.86 [0.78 to 0.95], index CABG 0.85 [0.54 to 1.35], prior CABG 0.77 [0.61 to 0.98]) and death (0.88 [0.75 to 1.03], 0.85 [0.46 to 1.59], 0.67 [0.44 to 1.01], respectively) were consistent with the overall trial results (0.85 [0.78 to 0.93] and 0.85 [0.73 to 0.98], respectively). Absolute risk reductions (95% confidence intervals) differed across CABG categories for MACE (no CABG 1.3% [0.5% to 2.2%], index CABG 0.9% [-2.3% to 4.0%], prior CABG 6.4% [0.9% to 12.0%]) and for death (0.4% [-0.1% to 1.0%], 0.5% [-1.9% to 2.9%], and 3.6% [0.0% to 7.2%]).Among patients with recent ACS and elevated atherogenic lipoproteins despite intensive statin therapy, alirocumab was associated with large absolute reductions in MACE and death in those with CABG preceding the ACS event. (ODYSSEY OUTCOMES: Evaluation of Cardiovascular Outcomes After an Acute Coronary Syndrome During Treatment With Alirocumab; NCT01663402).

    View details for DOI 10.1016/j.jacc.2019.07.015

    View details for PubMedID 31466614

  • Effects of alirocumab on types of myocardial infarction: insights from the ODYSSEY OUTCOMES trial. European heart journal White, H. D., Steg, P. G., Szarek, M., Bhatt, D. L., Bittner, V. A., Diaz, R., Edelberg, J. M., Erglis, A., Goodman, S. G., Hanotin, C., Harrington, R. A., Jukema, J. W., Lopes, R. D., Mahaffey, K. W., Moryusef, A., Pordy, R., Roe, M. T., Sritara, P., Tricoci, P., Zeiher, A. M., Schwartz, G. G. 2019

    Abstract

    The third Universal Definition of Myocardial Infarction (MI) Task Force classified MIs into five types: Type 1, spontaneous; Type 2, related to oxygen supply/demand imbalance; Type 3, fatal without ascertainment of cardiac biomarkers; Type 4, related to percutaneous coronary intervention; and Type 5, related to coronary artery bypass surgery. Low-density lipoprotein cholesterol (LDL-C) reduction with statins and proprotein convertase subtilisin-kexin Type 9 (PCSK9) inhibitors reduces risk of MI, but less is known about effects on types of MI. ODYSSEY OUTCOMES compared the PCSK9 inhibitor alirocumab with placebo in 18 924 patients with recent acute coronary syndrome (ACS) and elevated LDL-C (≥1.8 mmol/L) despite intensive statin therapy. In a pre-specified analysis, we assessed the effects of alirocumab on types of MI.Median follow-up was 2.8 years. Myocardial infarction types were prospectively adjudicated and classified. Of 1860 total MIs, 1223 (65.8%) were adjudicated as Type 1, 386 (20.8%) as Type 2, and 244 (13.1%) as Type 4. Few events were Type 3 (n = 2) or Type 5 (n = 5). Alirocumab reduced first MIs [hazard ratio (HR) 0.85, 95% confidence interval (CI) 0.77-0.95; P = 0.003], with reductions in both Type 1 (HR 0.87, 95% CI 0.77-0.99; P = 0.032) and Type 2 (0.77, 0.61-0.97; P = 0.025), but not Type 4 MI.After ACS, alirocumab added to intensive statin therapy favourably impacted on Type 1 and 2 MIs. The data indicate for the first time that a lipid-lowering therapy can attenuate the risk of Type 2 MI. Low-density lipoprotein cholesterol reduction below levels achievable with statins is an effective preventive strategy for both MI types.

    View details for DOI 10.1093/eurheartj/ehz299

    View details for PubMedID 31121022

  • Safety and Efficacy of PCSK9 Inhibitors After Heart Transplantation. The Canadian journal of cardiology Moayedi, Y., Kozuszko, S., Knowles, J. W., Chih, S., Oro, G., Lee, R., Fearon, W. F., Ross, H. J., Teuteberg, J. J., Khush, K. K. 2019; 35 (1)

    Abstract

    Dyslipidemia is common in patients undergoing heart transplantation and is associated with the progression of cardiac allograft vasculopathy. Two monoclonal antibodies directed against PCSK9i-evolocumab and alirocumab-are currently available. However, their use, safety and efficacy in the post-transplant setting have not been studied. We present our experience with 6 heart transplant recipients treated with a PCSK9i. A > 70% reduction in LDL-cholesterol was observed after evolocumab therapy. PCSK9 inhibitors are a potentially lipid-lowering therapeutic option for heart transplant patients with suboptimal LDL despite maximal tolerated statin doses.

    View details for PubMedID 30595172

  • Alirocumab and Cardiovascular Outcomes after Acute Coronary Syndrome NEW ENGLAND JOURNAL OF MEDICINE Schwartz, G. G., Steg, P. G., Szarek, M., Bhatt, D. L., Bittner, V. A., Diaz, R., Edelberg, J. M., Goodman, S. G., Hanotin, C., Harrington, R. A., Jukema, J. W., Lecorps, G., Mahaffey, K. W., Moryusef, A., Pordy, R., Quintero, K., Roe, M. T., Sasiela, W. J., Tamby, J., Tricoci, P., White, H. D., Zeiher, A. M., ODYSSEY OUTCOMES Comm Inv 2018; 379 (22): 2097–2107
  • Homozygous Familial Hypercholesterolemia in the United States: Data From the CASCADE-FH Registry Cuchel, M., Knowles, J. W., Kindt, I., Shrader, P., Hudgins, L. C., Duell, P. B., Shapiro, M. D., Rader, D. J., de Ferranti, S. D., Larry, J. A., Hemphill, L. C., Benuck, I., Andersen, R. L., Baum, S., Wilemon, K., Roe, M. T., Fishberg, R., Guyton, J., Kane, J., Ballantyne, C. M., Linton, M. F., Moriarty, P. M., Gidding, S. S. LIPPINCOTT WILLIAMS & WILKINS. 2018

Knowles Lab publications and collaborations