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Newly identified loci that influence lipid concentrations and risk of coronary artery disease

Nature Genetics volume 40, pages 161–169 (2008)Cite this article

Abstract

To identify genetic variants influencing plasma lipid concentrations, we first used genotype imputation and meta-analysis to combine three genome-wide scans totaling 8,816 individuals and comprising 6,068 individuals specific to our study (1,874 individuals from the FUSION study of type 2 diabetes and 4,184 individuals from the SardiNIA study of aging-associated variables) and 2,758 individuals from the Diabetes Genetics Initiative, reported in a companion study in this issue. We subsequently examined promising signals in 11,569 additional individuals. Overall, we identify strongly associated variants in eleven loci previously implicated in lipid metabolism (ABCA1, the APOA5-APOA4-APOC3-APOA1 and APOE-APOC clusters, APOB, CETP, GCKR, LDLR, LPL, LIPC, LIPG and PCSK9) and also in several newly identified loci (near MVK-MMAB and GALNT2, with variants primarily associated with high-density lipoprotein (HDL) cholesterol; near SORT1, with variants primarily associated with low-density lipoprotein (LDL) cholesterol; near TRIB1, MLXIPL and ANGPTL3, with variants primarily associated with triglycerides; and a locus encompassing several genes near NCAN, with variants strongly associated with both triglycerides and LDL cholesterol). Notably, the 11 independent variants associated with increased LDL cholesterol concentrations in our study also showed increased frequency in a sample of coronary artery disease cases versus controls.

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Figure 1: Summary of genome-wide association scans.

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References

  1. Mackay, J. & Mensah, G.A. The Atlas of Heart Disease and Stroke (World Health Organization, Geneva, 2004).

    Google Scholar 

  2. Law, M.R., Wald, N.J. & Rudnicka, A.R. Quantifying effect of statins on low density lipoprotein cholesterol, ischaemic heart disease, and stroke: systematic review and meta-analysis. Br. Med. J. 326, 1423 (2003).

    Article  CAS  Google Scholar 

  3. Kuulasmaa, K. et al. Estimation of contribution of changes in classic risk factors to trends in coronary-event rates across the WHO MONICA Project populations. Lancet 355, 675–687 (2000).

    Article  CAS  Google Scholar 

  4. Clarke, R. et al. Cholesterol fractions and apolipoproteins as risk factors for heart disease mortality in older men. Arch. Intern. Med. 167, 1373–1378 (2007).

    Article  CAS  Google Scholar 

  5. Grundy, S.M. et al. Implications of recent clinical trials for the National Cholesterol Education Program Adult Treatment Panel III guidelines. Circulation 110, 227–239 (2004).

    Article  Google Scholar 

  6. Gotto, A.M. Jr. & Brinton, E.A. Assessing low levels of high-density lipoprotein cholesterol as a risk factor in coronary heart disease: a working group report and update. J. Am. Coll. Cardiol. 43, 717–724 (2004).

    Article  CAS  Google Scholar 

  7. Prospective Studies Collaboration. Blood cholesterol and vascular mortality by age, sex and blood pressure: a meta-analysis of individual data from 61 prospective studies with 55,000 vascular deaths. Lancet 370, 1829–1839 (2007).

  8. Bansal, S. et al. Fasting compared with nonfasting triglycerides and risk of cardiovascular events in women. J. Am. Med. Assoc. 298, 309–316 (2007).

    Article  CAS  Google Scholar 

  9. Nordestgaard, B.G., Benn, M., Schnohr, P. & Tybjaerg-Hansen, A. Nonfasting triglycerides and risk of myocardial infarction, ischemic heart disease, and death in men and women. J. Am. Med. Assoc. 298, 299–308 (2007).

    Article  CAS  Google Scholar 

  10. Pilia, G. et al. Heritability of cardiovascular and personality traits in 6,148 Sardinians. PLoS Genet. 2, e132 (2006).

    Article  Google Scholar 

  11. Pollin, T.I. et al. A genome-wide scan of serum lipid levels in the Old Order Amish. Atherosclerosis 173, 89–96 (2004).

    Article  CAS  Google Scholar 

  12. Breslow, J.L. Genetics of lipoprotein abnormalities associated with coronary artery disease susceptibility. Annu. Rev. Genet. 34, 233–254 (2000).

    Article  CAS  Google Scholar 

  13. Scott, L.J. et al. A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants. Science 316, 1341–1345 (2007).

    Article  CAS  Google Scholar 

  14. Scuteri, A. et al. Genome-wide association scan shows genetic variants in the FTO gene are associated with obesity related traits. PLoS Genet. 3, e115 (2007).

    Article  Google Scholar 

  15. Saxena, R. et al. Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels. Science 316, 1331–1336 (2007).

    Article  CAS  Google Scholar 

  16. Kathiresan, S. et al. Six new loci associated with blood low-density lipoprotein cholesterol, high-density lipoprotein cholesterol or triglycerides in humans. Nat. Genet. advance online publication 13 January 2008; 10.1038/ng.75.

  17. Chen, W.M. & Abecasis, G.R. Family-based association tests for genome-wide association scans. Am. J. Hum. Genet. 81, 913–926 (2007).

    Article  CAS  Google Scholar 

  18. Burdick, J.T., Chen, W.M., Abecasis, G.R. & Cheung, V.G. In silico method for inferring genotypes in pedigrees. Nat. Genet. 38, 1002–1004 (2006).

    Article  CAS  Google Scholar 

  19. The International HapMap Consortium. The International HapMap Project. Nature 437, 1299–1320 (2005).

  20. George, V.T. & Elston, R.C. Testing of association between polymorphic markers and quantitative traits in pedigrees. Genet. Epidemiol. 4, 193–201 (1987).

    Article  CAS  Google Scholar 

  21. Abecasis, G.R., Cardon, L.R. & Cookson, W.O.C. A general test of association for quantitative traits in nuclear families. Am. J. Hum. Genet. 66, 279–292 (2000).

    Article  CAS  Google Scholar 

  22. Devlin, B. & Roeder, K. Genomic control for association studies. Biometrics 55, 997–1004 (1999).

    Article  CAS  Google Scholar 

  23. ISIS-3 Collaborative Group. ISIS-3: a randomised comparison of streptokinase vs tissue plasminogen activator vs anistreplase and of aspirin plus heparin vs aspirin alone among 41,299 cases of suspected acute myocardial infarction. ISIS-3 (Third International Study of Infarct Survival) Collaborative Group. Lancet 339, 753–770 (1992).

  24. Keavney, B. et al. Lipid-related genes and myocardial infarction in 4685 cases and 3460 controls: discrepancies between genotype, blood lipid concentrations, and coronary disease risk. Int. J. Epidemiol. 33, 1002–1013 (2004).

    Article  Google Scholar 

  25. Post, W. et al. Associations between genetic variants in the NOS1AP (CAPON) gene and cardiac repolarization in the old order Amish. Hum. Hered. 64, 214–219 (2007).

    Article  CAS  Google Scholar 

  26. Post, W. et al. Determinants of coronary artery and aortic calcification in the Old Order Amish. Circulation 115, 717–724 (2007).

    Article  Google Scholar 

  27. Hercberg, S. et al. The SU.VI.MAX Study: a randomized, placebo-controlled trial of the health effects of antioxidant vitamins and minerals. Arch. Intern. Med. 164, 2335–2342 (2004).

    Article  CAS  Google Scholar 

  28. Hercberg, S. et al. A primary prevention trial using nutritional doses of antioxidant vitamins and minerals in cardiovascular diseases and cancers in a general population: the SU.VI.MAX study–design, methods, and participant characteristics. SUpplementation en VItamines et Mineraux AntioXydants. Control. Clin. Trials 19, 336–351 (1998).

    Article  CAS  Google Scholar 

  29. The Caerphilly and Speedwell Collaborative Group. Caerphilly and Speedwell collaborative heart disease studies. J. Epidemiol. Community Health 38, 259–262 (1984).

  30. Bainton, D. et al. Plasma triglyceride and high density lipoprotein cholesterol as predictors of ischaemic heart disease in British men. The Caerphilly and Speedwell Collaborative Heart Disease Studies. Br. Heart J. 68, 60–66 (1992).

    Article  CAS  Google Scholar 

  31. Lawlor, D.A., Bedford, C., Taylor, M. & Ebrahim, S. Geographical variation in cardiovascular disease, risk factors, and their control in older women: British Women's Heart and Health Study. J. Epidemiol. Community Health 57, 134–140 (2003).

    Article  CAS  Google Scholar 

  32. Nielsen, M.S., Jacobsen, C., Olivecrona, G., Gliemann, J. & Petersen, C.M. Sortilin/neurotensin receptor-3 binds and mediates degradation of lipoprotein lipase. J. Biol. Chem. 274, 8832–8836 (1999).

    Article  CAS  Google Scholar 

  33. Samani, N.J. et al. Genomewide association analysis of coronary artery disease. N. Engl. J. Med. 357, 443–453 (2007).

    Article  CAS  Google Scholar 

  34. Koishi, R. et al. Angptl3 regulates lipid metabolism in mice. Nat. Genet. 30, 151–157 (2002).

    Article  CAS  Google Scholar 

  35. Romeo, S. et al. Population-based resequencing of ANGPTL4 uncovers variations that reduce triglycerides and increase HDL. Nat. Genet. 39, 513–516 (2007).

    Article  CAS  Google Scholar 

  36. Murphy, C., Murray, A.M., Meaney, S. & Gafvels, M. Regulation by SREBP-2 defines a potential link between isoprenoid and adenosylcobalamin metabolism. Biochem. Biophys. Res. Commun. 355, 359–364 (2007).

    Article  CAS  Google Scholar 

  37. Kiss-Toth, E. et al. Human tribbles, a protein family controlling mitogen-activated protein kinase cascades. J. Biol. Chem. 279, 42703–42708 (2004).

    Article  CAS  Google Scholar 

  38. Rauch, U., Feng, K. & Zhou, X.H. Neurocan: a brain chondroitin sulfate proteoglycan. Cell. Mol. Life Sci. 58, 1842–1856 (2001).

    Article  CAS  Google Scholar 

  39. Kuivenhoven, J.A. et al. The molecular pathology of lecithin:cholesterol acyltransferase (LCAT) deficiency syndromes. J. Lipid Res. 38, 191–205 (1997).

    CAS  PubMed  Google Scholar 

  40. Pare, G. et al. Genetic analysis of 103 candidate genes for coronary artery disease and associated phenotypes in a founder population reveals a new association between endothelin-1 and high-density lipoprotein cholesterol. Am. J. Hum. Genet. 80, 673–682 (2007).

    Article  CAS  Google Scholar 

  41. Magrane, J., Casaroli-Marano, R.P., Reina, M., Gafvels, M. & Vilaro, S. The role of O-linked sugars in determining the very low density lipoprotein receptor stability or release from the cell. FEBS Lett. 451, 56–62 (1999).

    Article  CAS  Google Scholar 

  42. The Welcome Trust Case Control Consortium. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 447, 661–678 (2007).

  43. Helgadottir, A. et al. A common variant on chromosome 9p21 affects the risk of myocardial infarction. Science 316, 1491–1493 (2007).

    Article  CAS  Google Scholar 

  44. McPherson, R. et al. A common allele on chromosome 9 associated with coronary heart disease. Science 316, 1488–1491 (2007).

    Article  CAS  Google Scholar 

  45. Barzilai, N. et al. Unique lipoprotein phenotype and genotype associated with exceptional longevity. J. Am. Med. Assoc. 290, 2030–2040 (2003).

    Article  CAS  Google Scholar 

  46. Baigent, C. et al. Efficacy and safety of cholesterol-lowering treatment: prospective meta-analysis of data from 90,056 participants in 14 randomised trials of statins. Lancet 366, 1267–1278 (2005).

    Article  CAS  Google Scholar 

  47. Cohen, J.C. et al. Multiple rare alleles contribute to low plasma levels of HDL cholesterol. Science 305, 869–872 (2004).

    Article  CAS  Google Scholar 

  48. Naoumova, R.P. et al. Severe hypercholesterolemia in four British families with the D374Y mutation in the PCSK9 gene: long-term follow-up and treatment response. Arterioscler. Thromb. Vasc. Biol. 25, 2654–2660 (2005).

    Article  CAS  Google Scholar 

  49. Lind, S. et al. Autosomal recessive hypercholesterolaemia: normalization of plasma LDL cholesterol by ezetimibe in combination with statin treatment. J. Intern. Med. 256, 406–412 (2004).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We are indebted to the many volunteers who generously participated in these studies. We thank our colleagues from the DGI for sharing prepublication data; M. Erdos, P. Chines, P. Deodhar, K. Kubalanza, A. Sprau and M. Tong of FUSION and E. Pugh, K. Doheny and Center for Inherited Disease Research (CIDR) investigators for expert technical work; N. Rosenberg for helpful discussions about population genetics; the SardiNIA Research Clinic staff; and the Amish Research Clinic staff. This study makes use of data generated by the Wellcome Trust Case Control Consortium. A full list of the investigators who contributed to the generation of the data are available from the WTCCC website. Funding for the WTCCC project was provided by the Wellcome Trust under award 076113. The Caerphilly study was funded by the Medical Research Council (UK). The Caerphilly study was undertaken by the former MRC Epidemiology Unit (South Wales) and was funded by the Medical Research Council of the United Kingdom. The data archive is maintained by the Department of Social Medicine, University of Bristol. This work was supported in part by the Intramural Research Program of the National Institute on Aging (NIA), by extramural grants from National Human Genome Research Institute (NHGRI), the National Diabetes and Digestive and Kidney Diseases (NIDDK) and the National Heart Lung and Blood Institute (NHLBI), by the American Diabetes Association, the Department of Veterans Affairs, the British Heart Foundation, the Medical Research Council of the United Kingdom and the French Ministry of Higher Education and Research. FUSION genome-wide genotyping was carried out by the Johns Hopkins University Genetic Resources Core Facility (GRCF) SNP Center at CIDR with support from CIDR NIH (contract N01-HG-65403) and the GRCF SNP Center. Additional support for the SardiNIA study was provided by the mayors, administration and residents of Lanusei, Ilbono, Arzana and Elini and the head of Public Health Unit ASL4 in Sardinia. C.J.W. is the recipient of a postdoctoral fellowship from the American Diabetes Association. G.R.A. and K.L.M. are Pew Scholars for the Biomedical Sciences.

Author information

Author notes

  1. Cristen J Willer and Serena Sanna: These authors contributed equally to the work.

Authors and Affiliations

  1. Department of Biostatistics, Center for Statistical Genetics, University of Michigan, 1420 Washington Heights, Ann Arbor, 48109, Michigan, USA

    Cristen J Willer, Serena Sanna, Anne U Jackson, Heather M Stringham, William L Duren, Wei-Min Chen, Yun Li, Laura J Scott, Paul A Scheet, Michael Boehnke & Gonçalo R Abecasis

  2. Istituto di Neurogenetica e Neurofarmacologia (INN), Consiglio Nazionale delle Ricerche, c/o Cittadella Universitaria di Monserrato, Monserrato, 09042, Cagliari, Italy

    Serena Sanna, Andrea Maschio, Fabio Busonero, Antonella Mulas, Giuseppe Albai, Manuela Uda & Antonio Cao

  3. Gerontology Research Center, National Institute on Aging, 5600 Nathan Shock Drive, Baltimore, 21224, Maryland, USA

    Angelo Scuteri, Samer S Najjar, James Strait, Ramaiah Nagaraja, Edward Lakatta & David Schlessinger

  4. Unitá Operativa Geriatria, Istituto per la Patologia Endocrina e Metabolica, Rome, Italy

    Angelo Scuteri

  5. Genome Technology Branch, National Human Genome Research Institute, Bethesda, 20892, Maryland, USA

    Lori L Bonnycastle, Amy J Swift, Mario A Morken, Narisu Narisu & Francis S Collins

  6. Clinical Trial Service Unit, University of Oxford, Richard Doll Building, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK

    Robert Clarke, Derrick Bennett, Sarah Parish & Rory Collins

  7. Centre National de Génotypage, Institut Génomique, Commissariat à l'Énergie Atomique, 2 rue Gaston Crémieux, CP 5721, Evry, 91057, Cedex, France

    Simon C Heath, Diana Zelenika & G Mark Lathrop

  8. Department of Social Medicine, University of Bristol, Canynge Hall, Whiteladies Road, Bristol, BS8 2PR, UK

    Nicholas J Timpson, Debbie A Lawlor, Yoav Ben-Shlomo & George Davey-Smith

  9. Division of Endocrinology, Diabetes and Nutrition, University of Maryland School of Medicine, Baltimore, 21201, Maryland, USA

    Haiqing Shen & Alan R Shuldiner

  10. U872 Institut National de la Santé et de la Recherche Médicale (INSERM) and Département de Santé Publique et d'Informatique Médicale, Faculté de Médecine René Descartes, 15 rue de l'Ecole de Médecine, Paris, 75270, France

    Pilar Galan

  11. U557 INSERM; U1125 Institut National de la Recherche Agronomique (INRA); Cnam; Paris 13 University; Centre de Recherche en Nutrition Humaine (CRNH) IdF,

    Pierre Meneton & Serge Hercberg

  12. U1125 Institut National de la Recherche Agronomique (INRA), 74 rue Marcel Cachin, Bobigny, 93017, Cedex, France

    Pierre Meneton & Serge Hercberg

  13. Department of Health and Functional Capacity, Laboratory of Analytical Biochemistry, National Public Health Institute, Helsinki, 00300, Finland

    Jouko Sundvall

  14. Department of Physiology and Biophysics, Keck School of Medicine, University of Southern California, Los Angeles, 90033, California, USA

    Richard M Watanabe & Richard N Bergman

  15. Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, 90089, California, USA

    Richard M Watanabe

  16. Department of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, Keppel St., London, WC1E 7HT, UK

    Shah Ebrahim

  17. Department of Health Promotion and Chronic Disease Prevention, Finland and Department of Public Health, Diabetes Unit, National Public Health Institute, 00300 Helsinki, University of Helsinki, Helsinki, 00014, Finland

    Jaakko Tuomilehto

  18. Department of Genetics, University of North Carolina, Chapel Hill, 27599, North Carolina, USA

    Karen L Mohlke

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  1. Cristen J Willer
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  2. Serena Sanna
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  43. Antonio Cao
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  44. Francis S Collins
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  47. Michael Boehnke
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  48. David Schlessinger
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  49. Karen L Mohlke
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  50. Gonçalo R Abecasis
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Corresponding authors

Correspondence to Karen L Mohlke or Gonçalo R Abecasis.

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Willer, C., Sanna, S., Jackson, A. et al. Newly identified loci that influence lipid concentrations and risk of coronary artery disease. Nat Genet 40, 161–169 (2008). https://doi.org/10.1038/ng.76

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