Clinical Focus

  • Cardiovascular Disease

Academic Appointments

Professional Education

  • Fellowship:Stanford University (2005) CA
  • Medical Education:Mcgill University (1994) Canada
  • Board Certification: Cardiovascular Disease, American Board of Internal Medicine (2004)
  • Residency:McGill University Health Center (2000) Canada
  • PhD, McGill University, Epidemiology & Biostatistics (2008)
  • Board Certified, ABIM (training at Stanford University), Cardiovascular Medicine (2004)
  • MS, McGill University, Epidemiology & Biostatistics (2001)
  • Board Certified, ABIM (training at McGill University), Internal Medicine (1999)
  • MD, CM, McGill University, Medicine (1994)

Research & Scholarship

Current Research and Scholarly Interests

Genetic Epidemiology, Genetic Determinants of Complex Traits related to Cardiovasular Medicine, Pharmacoepidemiology of Cardiovascular Drugs & Outcomes, Cardiovascular Medicine related Pharmacogenomics, Biomarkers to predict major adverse cardiovascular events, Determinants of Insulin Mediated Glucose Uptake in South Asians

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


2013-14 Courses


Journal Articles

  • 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)


    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-β) 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 Web of Science ID 000322321100049

    View details for PubMedID 23874238

  • 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. K., Terzic, A., Waldman, S. A. 2013

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

    View details for PubMedID 24297835

  • 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., Koenig, 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., Lyytikainen, 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., Mueller-Nurasyid, M., Nikus, K., Peden, J. F., Rayner, N. W., Rasheed, A., Rosinger, S., Rubin, D., Rumpf, M. P., Schaefer, 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., Ferrieres, J., Gauguier, D., Go, A. S., Goodall, A. H., Gudnason, V., Hazen, S. L., Holm, H., Iribarren, C., Jang, Y., Kahonen, 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., Tregouet, D., Virtamo, J., Wallentin, L., Wareham, N., Zimmermann, M. E., Nieminen, M. S., Hengstenberg, C., Sandhu, M. S., Pastinen, T., Syvanen, A., Hovingh, G. K., Dedoussis, G., Franks, P. W., Lehtimaki, 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., Maerz, 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-U52


    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 Web of Science ID 000312838800009

    View details for PubMedID 23202125

  • 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
  • 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


    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

  • 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


    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

  • 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


    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

  • 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


    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

  • 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


    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

  • 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-?


    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

  • Clinical interpretation and implications of whole-genome sequencing. JAMA : the journal of the American Medical Association 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


    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 κ, 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 κ, 0.24; P < 001).In this exploratory study of 12 volunteer adults, the use of WGS was associated with incomplete coverage of inherited disease genes, low reproducibility of detection of genetic variation with the highest potential clinical effects, and uncertainty about clinically reportable findings. In certain cases, WGS will identify clinically actionable genetic variants warranting early medical intervention. These issues should be considered when determining the role of WGS in clinical medicine.

    View details for DOI 10.1001/jama.2014.1717

    View details for PubMedID 24618965

  • 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


    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


    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, β2-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


    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

  • 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


    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

  • Multiple Non-glycemic Genomic Loci Are Newly Associated with Blood Level of Glycated Hemoglobin in East Asians. Diabetes Chen, P., Takeuchi, F., Lee, J. Y., Li, H., Wu, J. Y., 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. C., Liu, J., Liao, J., Ye, X., Wang, Y., Lu, L., Young, T. L., Lee, J., Thai, A. C., Cheng, C. Y., van Dam, R. M., Friedlander, Y., Heng, C. K., Koh, W. P., Chen, C. H., Chang, L. C., Pan, W. H., 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., Huey-Herng Sheu, W., Rotter, J. I., Chen, Y. D., Hsu, C., Okada, Y., Kubo, M., Takahashi, A., Tanaka, T., van Rooij, F. J., Ganesh, S. K., Huang, J., Huang, T., Gross, M. D., Assimes, T. L., Miki, T., Shu, X. O., Qi, L., Chen, Y. T., Lin, X., Aung, T., Wong, T. Y., Teo, Y. Y., Kim, B. J., Kato, N., Tai, E. S. 2014


    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

  • 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


    . Unique identifier: NCT00000611.

    View details for DOI 10.1161/CIRCOUTCOMES.113.000373

    View details for PubMedID 24399330

  • 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


    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


    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 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

  • 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


    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


    Adiponectin is strongly inversely associated with insulin resistance and type 2 diabetes but its causal role remains controversial. We used a Mendelian randomisation 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 cases and 64,731 controls). In conventional regression analyses a 1 SD decrease in adiponectin levels was correlated with a 0.31 SD (95%CIs: 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 of 1.75 (95%CIs: 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, 0.11, N=29,771), nominal evidence of a causal relationship with lower insulin sensitivity (-0.20 SD; 95%CIs: -0.38, -0.02; N=1,860) and no evidence of a relationship with type 2 diabetes (odds ratio 0.94; 95%CIs: 0.75, 1.19; N= 2,777 cases and 13,011 controls). 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%CIs: -0.07, 0.01; N=2,969) or type 2 diabetes (odds ratio per weighted adiponectin lowering allele: 0.99; 95%CIs: 0.95, 1.04; 15,960 cases vs. 64,731 controls). 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

  • 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


    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

  • 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)


    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

  • 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


    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


    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, A., 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


    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

  • 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


    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

  • 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


    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


    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

  • Trans-Ethnic Fine-Mapping of Lipid Loci Identifies Population-Specific Signals and Allelic Heterogeneity That Increases the Trait Variance Explained PLOS GENETICS Wu, Y., Waite, L. L., Jackson, A. U., Sheu, W. H., Buyske, S., Absher, D., Arnett, D. K., Boerwinkle, E., Bonnycastle, L. L., Carty, C. L., Cheng, I., Cochran, B., Croteau-Chonka, D. C., Dumitrescu, L., Eaton, C. B., Franceschini, N., Guo, X., Henderson, B. E., Hindorff, L. A., Kim, E., Kinnunen, L., Komulainen, P., Lee, W., Le Marchand, L., Lin, Y., Lindstrom, J., Lingaas-Holmen, O., Mitchell, S. L., Narisu, N., Robinson, J. G., Schumacher, F., Stancakova, A., Sundvall, J., Sung, Y., Swift, A. J., Wang, W., Wilkens, L., Wilsgaard, T., Young, A. M., Adair, L. S., Ballantyne, C. M., Buzkova, P., Chakravarti, A., Collins, F. S., Duggan, D., Feranil, A. B., Ho, L., Hung, Y., Hunt, S. C., Hveem, K., Juang, J. J., Kesaniemi, A. Y., Kuusisto, J., Laakso, M., Lakka, T. A., Lee, I., Leppert, M. F., Matise, T. C., Moilanen, L., Njolstad, I., Peters, U., Quertermous, T., Rauramaa, R., Rotter, J. I., Saramies, J., Tuomilehto, J., Uusitupa, M., Wang, T., Boehnke, M., Haiman, C. A., Chen, Y. I., Kooperberg, C., Assimes, T. L., Crawford, D. C., Hsiung, C. A., North, K. E., Mohlke, K. L. 2013; 9 (3)


    Genome-wide association studies (GWAS) have identified ~100 loci associated with blood lipid levels, but much of the trait heritability remains unexplained, and at most loci the identities of the trait-influencing variants remain unknown. We conducted a trans-ethnic fine-mapping study at 18, 22, and 18 GWAS loci on the Metabochip for their association with triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C), respectively, in individuals of African American (n = 6,832), East Asian (n = 9,449), and European (n = 10,829) ancestry. We aimed to identify the variants with strongest association at each locus, identify additional and population-specific signals, refine association signals, and assess the relative significance of previously described functional variants. Among the 58 loci, 33 exhibited evidence of association at P<1 × 10(-4) in at least one ancestry group. Sequential conditional analyses revealed that ten, nine, and four loci in African Americans, Europeans, and East Asians, respectively, exhibited two or more signals. At these loci, accounting for all signals led to a 1.3- to 1.8-fold increase in the explained phenotypic variance compared to the strongest signals. Distinct signals across ancestry groups were identified at PCSK9 and APOA5. Trans-ethnic analyses narrowed the signals to smaller sets of variants at GCKR, PPP1R3B, ABO, LCAT, and ABCA1. Of 27 variants reported previously to have functional effects, 74% exhibited the strongest association at the respective signal. In conclusion, trans-ethnic high-density genotyping and analysis confirm the presence of allelic heterogeneity, allow the identification of population-specific variants, and limit the number of candidate SNPs for functional studies.

    View details for DOI 10.1371/journal.pgen.1003379

    View details for Web of Science ID 000316866700054

    View details for PubMedID 23555291

  • 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. F., 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. U., 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. 2013


    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

  • 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., Brent Richards, J. 2013


    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 PubMedID 23664276

  • 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. 2013


    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

  • 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)


    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-?


    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

  • 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


    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

  • 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


    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,

    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)


    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


    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

  • 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


    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

  • 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)


    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

  • 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


    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)


    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


    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


    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
  • 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)
  • 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


    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

  • 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


    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


    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

  • 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)


    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

  • 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


    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: Unique identifier: NCT00380185.

    View details for DOI 10.1177/1358863X10388345

    View details for Web of Science ID 000285574400002

    View details for PubMedID 21183651

  • 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


    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


    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


    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


    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

  • 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


    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

  • 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


    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

  • 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


    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)


    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

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


    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


    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

  • 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


    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

  • 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


    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


    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


    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

  • 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


    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


    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


    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


    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

  • 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


    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

  • 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


    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


    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


    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


    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

Conference Proceedings

  • 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
  • Detailed Physiologic Characterization Reveals Diverse Mechanisms for Novel Genetic Loci Regulating Glucose and Insulin Metabolism in Humans 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: 1266-1275


    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

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