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The novel genetic variant predisposing to coronary artery disease in the region of the PSRC1 and CELSR2 genes on chromosome 1 associates with serum cholesterol

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Abstract

Through genome-wide association studies, we have recently identified seven novel loci that confer a substantial increase in risk for coronary artery disease (CAD). Elucidating the mechanisms by which these loci affect CAD risk could have important clinical utility. Here, we investigated whether these loci act through mechanisms involving traditional cardiovascular risk factors. We genotyped 2,037 adult individuals from 520 nuclear families characterised for body mass index, waist-hip ratio, 24-h ambulatory blood pressure, total cholesterol, high-density lipoprotein cholesterol and glucose for the lead single nucleotide polymorphisms (SNPs) in the seven CAD-associated loci. SNP rs599839, representing the locus in the vicinity of the PSRC1 and CELSR2 genes on chromosome 1p13.3, showed a strong association with total cholesterol. The CAD-associated risk allele A of rs599839 (allele frequency 0.78) was associated with a 0.17-mmol/l (95% CI 0.10 to 0.24 mmol/l) higher serum cholesterol level per allele copy (P = 3.84 × 10−6). The association of the A allele with higher total cholesterol was confirmed in an independent cohort (n = 847) of healthy adults (P = 1.0 × 10−4) and related to an effect on low-density lipoprotein (LDL) cholesterol (P = 8.56 × 10−5). An association of rs599839 with LDL cholesterol was also shown in 1,090 cases with myocardial infarction (P = 0.0026). None of the other variants showed a strong association with the measured cardiovascular risk factors, suggesting that these loci act through other mechanisms. However, the novel CAD-associated locus in the vicinity of the PSRC1 and CELSR2 genes on chromosome 1 probably enhances CAD risk through an effect on plasma LDL cholesterol. The findings support further investigation of the role of these genes in cholesterol metabolism and coronary risk.

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References

  1. Rosamond W, Flegal K, Friday G, Furie K, Go A, Greenlund K, Haase N, Ho M, Howard V, Kissela B, Kittner S, Lloyd-Jones D, McDermott M, Meigs J, Moy C, Nichol G, O'Donnell CJ, Roger V, Rumsfeld J, Sorlie P, Steinberger J, Thom T, Wasserthiel-Smoller S, Hong Y, American Heart Association Statistics Committee and Stroke Statistics Subcommittee (2007) Heart disease and stroke statistics—2007 update: a report from the American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Circulation 115:e69–e171

    Article  PubMed  Google Scholar 

  2. Marenberg ME, Risch N, Berkman LF, Floderus B, de Faire U (1994) Genetic susceptibility to death from coronary heart disease in a study of twins. N Engl J Med 330:1041–1046

    Article  PubMed  CAS  Google Scholar 

  3. Watkins H, Farrall M (2006) Genetic susceptibility to coronary artery disease: from promise to progress. Nat Rev Genet 7:163–173

    Article  PubMed  CAS  Google Scholar 

  4. Burton PR, Tobin MD, Hopper JL (2005) Key concepts in genetic epidemiology. Lancet 366:941–951

    Article  PubMed  Google Scholar 

  5. Samani NJ, Erdmann J, Hall AS, Hengstenberg C, Mangino M, Mayer B, Dixon RJ, Meitinger T, Braund P, Wichmann HE, Barrett JH, König IR, Stevens SE, Szymczak S, Tregouet DA, Iles MM, Pahlke F, Pollard H, Lieb W, Cambien F, Fischer M, Ouwehand W, Blankenberg S, Balmforth AJ, Baessler A, Ball SG, Strom TM, Braenne I, Gieger C, Deloukas P, Tobin MD, Ziegler A, Thompson JR, Schunkert H, WTCCC and the Cardiogenics Consortium (2007) Genomewide association analysis of coronary artery disease. N Engl J Med 357:443–453

    Article  PubMed  CAS  Google Scholar 

  6. McPherson R, Pertsemlidis A, Kavaslar N, Stewart A, Roberts R, Cox DR, Hinds DA, Pennacchio LA, Tybjaerg-Hansen A, Folsom AR, Boerwinkle E, Hobbs HH, Cohen JC (2007) A common allele on chromosome 9 associated with coronary heart disease. Science 316:1488–1491

    Article  PubMed  CAS  Google Scholar 

  7. Helgadottir A, Thorleifsson G, Manolescu A, Gretarsdottir S, Blondal T, Jonasdottir A, Jonasdottir A, Sigurdsson A, Baker A, Palsson A, Masson G, Gudbjartsson DF, Magnusson KP, Andersen K, Levey AI, Backman VM, Matthiasdottir S, Jonsdottir T, Palsson S, Einarsdottir H, Gunnarsdottir S, Gylfason A, Vaccarino V, Hooper WC, Reilly MP, Granger CB, Austin H, Rader DJ, Shah SH, Quyyumi AA, Gulcher JR, Thorgeirsson G, Thorsteinsdottir U, Kong A, Stefansson K (2007) A common variant on chromosome 9p21 affects the risk of myocardial infarction. Science 316:1491–1493

    Article  PubMed  CAS  Google Scholar 

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

    Article  Google Scholar 

  9. Tobin MD, Tomaszewski M, Braund PS, Hajat C, Raleigh SM, Palmer TM, Caulfield M, Burton PR, Samani NJ (2008) Common variation in genes underlying monogenic forms of hypertension and hypotension and ambulatory blood pressure in the general population. Hypertension 51:1658–1664

    Article  PubMed  CAS  Google Scholar 

  10. Levy D, DeStefano AL, Larson MG, O'Donnell CJ, Lifton RP, Gavras H, Cupples LA, Myers RH (2000) Evidence for a gene influencing blood pressure on chromosome 17. Genome scan linkage results for longitudinal blood pressure phenotypes in subjects from the Framingham Heart Study. Hypertension 36:477–483

    PubMed  CAS  Google Scholar 

  11. Tobin MD, Sheehan NA, Scurrah K, Burton PR (2005) Adjusting for treatment effects in studies of quantitative traits: antihypertensive therapy and systolic blood pressure. Stats Med 24:2911–2935

    Article  Google Scholar 

  12. Sedlacek K, Neureuther K, Mueller JC, Stark K, Fischer M, Baessler A, Reinhard W, Broeckel U, Lieb W, Erdmann J, Schunkert H, Riegger G, Illig T, Meitinger T, Hengstenberg C (2007) Lymphotoxin-alpha and galectin-2 SNPs are not associated with myocardial infarction in two different German populations. J Mol Med 85:997–1004

    Article  PubMed  CAS  Google Scholar 

  13. Holmer SR, Hengstenberg C, Mayer B, Döring A, Löwel H, Engel S, Hense HW, Wolf M, Klein G, Riegger GA, Schunkert H (2000) Lipoprotein lipase gene polymorphism, cholesterol subfractions and myocardial infarction in large samples of the general population. Cardiovasc Res 47:806–812

    Article  PubMed  CAS  Google Scholar 

  14. Burton P, Gurrin L, Sly P (1998) Extending the simple linear regression model to account for correlated responses: an introduction to generalized estimating equations and multi-level mixed modelling. Stat Med 17:1261–1291

    Article  PubMed  CAS  Google Scholar 

  15. Royston P, Sauerbrei W (2004) A new approach to modelling interactions between treatment and continuous covariates in clinical trials by using fractional polynomials. Stat Med 23:2509–2525

    Article  PubMed  Google Scholar 

  16. Nyholt DR (2006) ssSNPer: identifying statistically similar SNPs to aid interpretation of genetic association studies. Bioinformatics 22:2960–2966

    Article  PubMed  CAS  Google Scholar 

  17. Wang P, Dai M, Xuan W, McEachin RC, Jackson AU, Scott LJ, Athey B, Watson SJ, Meng F (2006) SNP Function Portal: a web database for exploring the function implication of SNP alleles. Bioinformatics 22:e523–e529

    Article  PubMed  CAS  Google Scholar 

  18. Xu H, Gregory SG, Hauser ER, Stenger JE, Pericak-Vance MA, Vance JM, Züchner S, Hauser MA (2005) SNPselector: a web tool for selecting SNPs for genetic association studies. Bioinformatics 21:4181–4617

    Article  PubMed  CAS  Google Scholar 

  19. Wallace C, Newhouse SJ, Braund P, Zhang F, Tobin M, Falchi M, Ahmadi K, Dobson RJ, Marçano AC, Hajat C, Burton P, Deloukas P, Brown M, Connell JM, Dominiczak A, Lathrop GM, Webster J, Farrall M, Spector T, Samani NJ, Caulfield MJ, Munroe PB (2008) Genome-wide association study identifies genes for biomarkers of cardiovascular disease: serum urate and dyslipidemia. Am J Hum Genet 82:139–149

    Article  PubMed  CAS  Google Scholar 

  20. Kathiresan S, Melander O, Guiducci C, Surti A, Burtt NP, Rieder MJ, Cooper GM, Roos C, Voight BF, Havulinna AS, Wahlstrand B, Hedner T, Corella D, Tai ES, Ordovas JM, Berglund G, Vartiainen E, Jousilahti P, Hedblad B, Taskinen MR, Newton-Cheh C, Salomaa V, Peltonen L, Groop L, Altshuler DM, Orho-Melander M (2008) Six new loci associated with blood low-density lipoprotein cholesterol, high-density lipoprotein cholesterol or triglycerides in humans. Nat Genet 40:189–197

    Article  PubMed  CAS  Google Scholar 

  21. Willer CJ, Sanna S, Jackson AU, Scuteri A, Bonnycastle LL, Clarke R, Heath SC, Timpson NJ, Najjar SS, Stringham HM, Strait J, Duren WL, Maschio A, Busonero F, Mulas A, Albai G, Swift AJ, Morken MA, Narisu N, Bennett D, Parish S, Shen H, Galan P, Meneton P, Hercberg S, Zelenika D, Chen WM, Li Y, Scott LJ, Scheet PA, Sundvall J, Watanabe RM, Nagaraja R, Ebrahim S, Lawlor DA, Ben-Shlomo Y, Davey-Smith G, Shuldiner AR, Collins R, Bergman RN, Uda M, Tuomilehto J, Cao A, Collins FS, Lakatta E, Lathrop GM, Boehnke M, Schlessinger D, Mohlke KL, Abecasis GR (2008) Newly identified loci that influence lipid concentrations and risk of coronary artery disease. Nat Genet 40:161–169

    Article  PubMed  CAS  Google Scholar 

  22. Sandhu MS, Waterworth DM, Debenham SL, Wheeler E, Papadakis K, Zhao JH, Song K, Yuan X, Johnson T, Ashford S, Inouye M, Luben R, Sims M, Hadley D, McArdle W, Barter P, Kesäniemi YA, Mahley RW, McPherson R, Grundy SM, Bingham SA, Khaw KT, Loos RJ, Waeber G, Barroso I, Strachan DP, Deloukas P, Vollenweider P, Wareham NJ, Mooser V, Wellcome Trust Case Control Consortium (2008) LDL-cholesterol concentrations: a genome-wide association study. Lancet 371:483–491

    Article  PubMed  CAS  Google Scholar 

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

    Article  Google Scholar 

  24. Schadt EE, Molony C, Chudin E, Hao K, Yang X, Lum PY, Kasarskis A, Zhang B, Wang S, Suver C, Zhu J, Millstein J, Sieberts S, Lamb J, Guhathakurta D, Derry J, Storey JD, Avila-Campillo I, Kruger MJ, Johnson JM, Rohl CA, van Nas A, Mehrabian M, Drake TA, Lusis AJ, Smith RC, Guengerich FP, Strom SC, Schuetz E, Rushmore TH, Ulrich R (2008) Mapping the genetic architecture of gene expression in human liver. PLoS Biol 6:e107

    Article  PubMed  Google Scholar 

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

    Article  PubMed  CAS  Google Scholar 

  26. Barrett JC, Fry B, Maller J, Daly MJ (2005) Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 21:263–265

    Article  PubMed  CAS  Google Scholar 

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Acknowledgments

We thank all the participants, collaborating general practitioners, research nurses and laboratory staff who contributed to the GRAPHIC and German Studies.

Funding

The GRAPHIC Study was funded by the British Heart Foundation. Genotyping was funded by the CARDIOGENICS project of the European Union. NJS holds a Chair supported by the British Heart Foundation, CH holds an MRC Training Fellowship and MDT holds a Medical Research Council (MRC) Clinician Scientist Fellowship.

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Correspondence to Nilesh J. Samani.

Additional information

Nilesh J. Samani, Peter S. Braund and Jeanette Erdmann contributed equally to this work.

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Table S1

Distribution of serum lipid levels in the German MI Cases and stratified by lipid lowering medication (DOC 38.5 KB)

Table S2

Association findings for all quantitative traits in the GRAPHIC Study for the seven analysed SNPs (DOC 163 KB)

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Samani, N.J., Braund, P.S., Erdmann, J. et al. The novel genetic variant predisposing to coronary artery disease in the region of the PSRC1 and CELSR2 genes on chromosome 1 associates with serum cholesterol. J Mol Med 86, 1233–1241 (2008). https://doi.org/10.1007/s00109-008-0387-2

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