Common and rare genetic markers of lipid variation in subjects with type 2 diabetes from the ACCORD clinical trial

PeerJ

Volumn 2017, Issue 5, 2017, Pages

  Marvel, Skylar W ^a   Rotroff, Daniel M ^a   Wagner, Michael J ^b   Buse, John B ^c   Havener, Tammy M ^b   McLeod, Howard L ^d   Motsinger Reif, Alison A ^a  

^a NORTH CAROLINA STATE UNIVERSITY   (United States)

^b University of North Carolina at Chapel Hill   (United States)

^c UNIVERSITY OF NORTH CAROLINA SCHOOL OF MEDICINE   (United States)

^d H LEE MOFFITT CANCER CENTER AND RESEARCH INSTITUTE   (United States)

Author keywords

Diabetes; Exome; Genetics; Genomics; Lipids; Rare variants

Indexed keywords

HIGH DENSITY LIPOPROTEIN; LIPID; LOW DENSITY LIPOPROTEIN; TRIACYLGLYCEROL;

ADULT; ARTICLE; BLOOD SAMPLING; CHOLESTEROL BLOOD LEVEL; CLINICAL TRIAL (TOPIC); CONTROLLED STUDY; DNA EXTRACTION; ETHNICITY; EXOME; FEMALE; GENE FREQUENCY; GENETIC MARKER; GENETIC VARIABILITY; GENOTYPE; HEREDITY; HERITABILITY; HUMAN; LIPID ANALYSIS; MAJOR CLINICAL STUDY; NON INSULIN DEPENDENT DIABETES MELLITUS; PHENOTYPIC VARIATION;

EID: 85018983250     PISSN: None     EISSN: 21678359     Source Type: Journal    
DOI: 10.7717/peerj.3187     Document Type: Article

References (55)

1. ACCORD Study Group. 2010. Effects of intensive blood-pressure control in type 2 diabetes mellitus. The New England Journal of Medicine 362:1575-1585 DOI 10.1056/NEJMoa1001286
2. ACCORD Study Group. 2010. Effects of combination lipid therapy in type 2 diabetes mellitus. The New England Journal of Medicine 362:1563-1574 DOI 10.1056/NEJMoa1001282
3. Arvind P, Nair J, Jambunathan S, Kakkar VV, Shanker J. 2014. CELSR2-PSRC1-SORT1 gene expression and association with coronary artery disease and plasma lipid levels in an Asian Indian cohort. Journal of Cardiology 64:339-346 DOI 10.1016/j.jjcc.2014.02.012
4. Aung LHH, Yin R-X, Wu D-F, Wang W, Liu C-W, Pan S-L. 2014. Association of the variants in the BUD13-ZNF259 genes and the risk of hyperlipidaemia. Journal of Cellular and Molecular Medicine 18:1417-1428 DOI 10.1111/jcmm.12291
5. Bansal V, Libiger O, Torkamani A, Schork NJ. 2010. Statistical analysis strategies for association studies involving rare variants. Nature Reviews Genetics 11:773-785 DOI 10.1038/nrg2867
6. Buse JB. 2007. Action to control cardiovascular risk in diabetes (ACCORD) trial: design and methods. The American Journal of Cardiology 99:S21-S33 DOI 10.1016/j.amjcard.2007.03.003
7. Centers for Disease Control and Prevention. 2014. National diabetes statistics report: estimates of diabetes and its burden in the United States, 2014. US Department of Health and Human Services, Atlanta
8. Cuff J, Salari K, Clarke N, Esheba GE, Forster AD, Huang S, West RB, Higgins JP, Longacre TA, Pollack JR. 2013. Integrative bioinformatics links HNF1B with clear cell carcinoma and tumor-associated thrombosis. PLOS ONE 8:e74562 DOI 10.1371/journal.pone.0074562
9. Dabney A, Storey JD, Warnes G. 2004. Q-value estimation for false discovery rate control. Medicine 344:539-548
10. Dai H, Leeder J, Cui Y. 2014. A modified generalized Fisher method for combining probabilities from dependent tests. Frontiers in Genetics 5:32 DOI 10.3389/fgene.2014.00032
11. Delaneau O, Marchini J, Zagury J-F. 2012. A linear complexity phasing method for thousands of genomes. Nature Methods 9:179-181 DOI 10.1038/nmeth.1785
12. Delaneau O, Zagury J-F, Marchini J. 2013. Improved whole-chromosome phasing for disease and population genetic studies. Nature Methods 10:5-6
13. Dering C, Hemmelmann C, Pugh E, Ziegler A. 2011. Statistical analysis of rare sequence variants: an overview of collapsing methods. Genetic Epidemiology 35:S12-S17 DOI 10.1002/gepi.20643
14. Devlin B, Roeder K. 1999. Genomic control for association studies. Biometrics 55:997-1004 DOI 10.1111/j.0006-341X.1999.00997.x
15. Diabetes Genetics Initiative of Broad Institute of Harvard and MIT, Lund University, Novartis Institutes of BioMedical Research, Saxena R, Voight BF, Lyssenko V, Burtt NP, De Chen H, Roix JJ, Kathiresan S, Hirschhorn JN, Daly MJ, Hughes TE, Groop L, Altshuler D, Almgren P, Florez JC, Meyer J, Ardlie K, Boström KB, Isomaa B, Lettre G, Lindblad U, Lyon HN, Melander O, Newton-Cheh C, Nilsson P, Orho-Melander M, Råstam L, Speliotes EK, Taskinen M-R, Tuomi T, Guiducci C, Berglund A, Carlson J, Gianniny L, Hackett R, Hall L, Holmkvist J, Laurila E, Sjögren M, Sterner M, Surti A, Svensson M, Svensson M, Tewhey R, Blumenstiel B, Parkin M, DeFelice M, Barry R, Brodeur W, Camarata J, Chia N, Fava M, Gibbons J, Handsaker B, Healy C, Nguyen K, Gates C, Sougnez C, Gage D, Nizzari M, Gabriel SB, Chirn G-W, Ma Q, Parikh H, Richardson D, Ricke D, Purcell S. 2007. Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels. Science 316:1331-1336 DOI 10.1126/science.1142358
16. Global Lipids Genetics Consortium. 2013. Discovery and refinement of loci associated with lipid levels. Nature Genetics 45:1274-1283 DOI 10.1038/ng.2797
17. Gerstein HC, Riddle MC, Kendall DM, Cohen RM, Gol R, Feinglos MN, Kirk JK, Hamilton BP, Ismail-Beigi F, Feeney P, ACCORD Study Group. 2007. Glycemia treatment strategies in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial. The American Journal of Cardiology 99:S34-S43
18. Ginsberg HN, Bonds DE, Lovato LC, Crouse JR, Elam MB, Linz PE, O'Connor PJ, Leiter LA, Weiss D, Lipkin E, Fleg JL, ACCORD Study Group. 2007. Evolution of the lipid trial protocol of the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial. The American Journal of Cardiology 99:S56-S67
19. Goff DC, Gerstein HC, Ginsberg HN, Cushman WC, Margolis KL, Byington RP, Buse JB, Genuth S, Probstfield JL, Simons-Morton DG, ACCORD Study Group. 2007. Prevention of cardiovascular disease in persons with type 2 diabetes mellitus: current knowledge and rationale for the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial. The American Journal of Cardiology 99:S4-S20 DOI 10.1016/S0002-9149(07)00488-2
20. Howie BN, Donnelly P, Marchini J. 2009. A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLOS Genetics 5:e1000529 DOI 10.1371/journal.pgen.1000529
21. Howie B, Marchini J, Stephens M. 2011. Genotype imputation with thousands of genomes G3: genes, genomes. Genetics 1:457-470 DOI 10.1534/g3.111.001198
22. Ito Y, Azrolan N, O'Connell A, Walsh A, Breslow JL. 1990. Hypertriglyceridemia as a result of human apo CIII gene expression in transgenic mice. Science 249:790-793 DOI 10.1126/science.2167514
23. Kanthimathi S, Balamurugan K, Mohan V, Shanthirani CS, Gayathri V, Radha V. 2015. Identification and molecular characterization of HNF1B gene mutations in Indian diabetic patients with renal abnormalities. Annals of Human Genetics 79:10-19 DOI 10.1111/ahg.12093
24. Kathiresan S, Manning AK, Demissie S, D'Agostino RB, Surti A, Guiducci C, Gianniny L, Burtt NP, Melander O, Orho-Melander M, Arnett DK, Peloso GM, Ordovas JM, Cupples LA. 2007. A genome-wide association study for blood lipid phenotypes in the Framingham Heart Study. BMC Medical Genetics 8:S17 DOI 10.1186/1471-2350-8-S1-S17
25. Koren MJ, Lundqvist P, Bolognese M, Neutel JM, Monsalvo ML, Yang J, Kim JB, Scott R, Wasserman SM, Bays H. 2014. Anti-PCSK9 monotherapy for hyperc-holesterolemia the MENDEL-2 randomized, controlled phase III clinical trial of evolocumab. Journal of the American College of Cardiology 63:2531-2540 DOI 10.1016/j.jacc.2014.03.018
26. Kornfeld J-W, Baitzel C, Könner AC, Nicholls HT, Vogt MC, Herrmanns K, Scheja L, Haumaitre C, Wolf AM, Knippschild U, Seibler J, Cereghini S, Heeren J, Stoffel M, Brüning JC. 2013. Obesity-induced overexpression of miR-802 impairs glucose metabolism through silencing of Hnf1b. Nature 494:111-115 DOI 10.1038/nature11793
27. Lange LA, Hu Y, Zhang H, Xue C, Schmidt EM, Tang Z-Z, Bizon C, Lange EM, Smith JD, Turner EH, Jun G, Kang HM, Peloso G, Auer P, Li K, Flannick J, Zhang J, Fuchsberger C, Gaulton K, Lindgren C, Locke A, Manning A, Sim X, Rivas MA, Holmen OL, Gottesman O, Lu Y, Ruderfer D, Stahl EA, Duan Q, Li Y, Durda P, Jiao S, Isaacs A, Hofman A, Bis JC, Correa A, Griswold ME, Jakobsdottir J, Smith AV, Schreiner PJ, Feitosa MF, Zhang Q, Huffman JE, Crosby J, Wassel CL, Do R, Franceschini N, Martin LW, Robinson JG, Assimes TL, Crosslin DR, Rosenthal EA, Tsai M, Rieder MJ, Farlow DN, Folsom AR, Lumley T, Fox ER, Carlson CS, Peters U, Jackson RD, van Duijn CM, Uitterlinden AG, Levy D, Rotter JI, Taylor HA, Gudnason Jr V, Siscovick DS, Fornage M, Borecki IB, Hayward C, Rudan I, Chen YE, Bottinger EP, Loos RJF, Sætrom P, Hveem K, Boehnke M, Groop L, McCarthy M, Meitinger T, Ballantyne CM, Gabriel SB, O'Donnell CJ, Post WS, North KE, Reiner AP, Boerwinkle E, Psaty BM, Altshuler D, Kathiresan S, Lin D-Y, Jarvik GP, Cupples LA, Kooperberg C, Wilson JG, Nickerson DA, Abecasis GR, Rich SS, Tracy RP, Willer CJ. 2014. Whole-exome sequencing identifies rare and low-frequency coding variants associated with LDL cholesterol. The American Journal of Human Genetics 94:233-245 DOI 10.1016/j.ajhg.2014.01.010
28. Lee S, Abecasis GR, Boehnke M, Lin X. 2014. Rare-variant association analysis: study designs and statistical tests. The American Journal of Human Genetics 95:5-23 DOI 10.1016/j.ajhg.2014.06.009
29. Lee S, Miropolsky L, Wu M. 2013. SKAT: SNP-set (Sequence) kernel association test. R Package Version 0.95
30. Lee S, Wu MC, Lin X. 2012. Optimal tests for rare variant effects in sequencing associa-tion studies. Biostatistics 13:762-775 DOI 10.1093/biostatistics/kxs014
31. Liu DJ, Peloso GM, Zhan X, Holmen OL, Zawistowski M, Feng S, Nikpay M, Auer PL, Goel A, Zhang H, Peters U, Farrall M, Orho-Melander M, Kooperberg C, McPherson R, Watkins H, Willer CJ, Hveem K, Melander O, Kathiresan S, Abecasis GR. 2014. Meta-analysis of gene-level tests for rare variant association. Nature Genetics 46:200-204 DOI 10.1038/ng.2852
32. Madsen BE, Browning SR. 2009. A groupwise association test for rare mutations using a weighted sum statistic. PLOS Genetics 5:e1000384 DOI 10.1371/journal.pgen.1000384
33. Malmberg K, Yusuf S, Gerstein HC, Brown J, Zhao F, Hunt D, Piegas L, Calvin J, Keltai M, Budaj A. 2000. Impact of diabetes on long-term prognosis in patients with unstable angina and non-Q-wave myocardial infarction: results of the OASIS (Organization to Assess Strategies for Ischemic Syndromes) Registry. Circulation 102:1014-1019 DOI 10.1161/01.CIR.102.9.1014
34. Manichaikul A, Mychaleckyj JC, Rich SS, Daly K, Sale M, Chen W-M. 2010. Robust rela-tionship inference in genome-wide association studies. Bioinformatics 26:2867-2873 DOI 10.1093/bioinformatics/btq559
35. Manolio TA, Collins FS, Cox NJ, Goldstein DB, Hindorff LA, Hunter DJ, McCarthy MI, Ramos EM, Cardon LR, Chakravarti A, Cho JH, Guttmacher AE, Kong A, Kruglyak L, Mardis E, Rotimi CN, Slatkin M, Valle D, Whittemore AS, Boehnke M, Clark AG, Eichler EE, Gibson G, Haines JL, Mackay TF, McCarroll SA, Visscher PM. 2009. Finding the missing heritability of complex diseases. Nature 461:747-753 DOI 10.1038/nature08494
36. Mendis S, Puska P, Norrving B. 2011. Global atlas on cardiovascular disease prevention and control. Geneva: World Health Organization
37. Morris AP, Zeggini E. 2010. An evaluation of statistical approaches to rare variant analysis in genetic association studies. Genetic Epidemiology 34:188-193 DOI 10.1002/gepi.20450
38. Musunuru K, Strong A, Frank-Kamenetsky M, Lee NE, Ahfeldt T, Sachs KV, Li X, Li H, Kuperwasser N, Ruda VM, Pirruccello JP, Muchmore B, Prokunina-Olsson L, Hall JL, Schadt EE, Morales CR, Lund-Katz S, Phillips MC, Wong J, Cantley W, Racie T, Ejebe KG, Orho-Melander M, Melander O, Koteliansky V, Fitzgerald K, Krauss RM, Cowan CA, Kathiresan S, Rader DJ. 2010. From noncoding variant to phenotype via SORT1 at the 1p13 cholesterol locus. Nature 466:714-719 DOI 10.1038/nature09266
39. National Heart Institute B. 1997. Report of the special emphasis panel on opportunities and obstacles to genetic research in NHLBI clinical studies. Bethesda: National Institutes of Health
40. Ota VK, Chen ES, Ejchel TF, Furuya TK, Mazzotti DR, Cendoroglo MS, Ramos LR, Araujo LQ, Burbano RR, SmithMde AC. 2011. APOA4 polymorphism as a risk factor for unfavorable lipid serum profile and depression: a cross-sectional study. Journal of Investigative Medicine: The Official Publication of the American Federation for Clinical Research 59:966-970 DOI 10.2310/JIM.0b013e31822467cd
41. Peloso GM, Auer PL, Bis JC, Voorman A, Morrison AC, Stitziel NO, Brody JA, Khetarpal SA, Crosby JR, Fornage M, Isaacs A, Jakobsdottir J, Feitosa MF, Davies G, Huffman JE, Manichaikul A, Davis B, Lohman K, Joon AY, Smith AV, Grove ML, Zanoni P, Redon V, Demissie S, Lawson K, Peters U, Carlson C, Jackson RD, Ryckman KK, Mackey RH, Robinson JG, Siscovick DS, Schreiner PJ, Mychaleckyj JC, Pankow JS, Hofman A, Uitterlinden AG, Harris TB, Taylor KD, Stafford JM, Reynolds LM, Marioni RE, Dehghan A, Franco OH, Patel AP, Lu Y, Hindy G, Gottesman O, Bottinger EP, Melander O, Orho-Melander M, Loos RJF, Duga S, Merlini PA, Farrall M, Goel A, Asselta R, Girelli D, Martinelli N, Shah SH, Kraus WE, Li M, Rader DJ, Reilly MP, McPherson R, Watkins H, Ardissino D, Zhang Q, Wang J, Tsai MY, Taylor HA, Correa A, Griswold ME, Lange LA, Starr JM, Rudan I, Eiriksdottir G, Launer LJ, Ordovas JM, Levy D, Chen Y-DI, Reiner AP, Hayward C, Polasek O, Deary IJ, Borecki IB, Liu Y, Gudnason V, Wilson JG, van Duijn CM, Kooperberg C, Rich SS, Psaty BM, Rotter JI, O'Donnell CJ, Rice K, Boerwinkle E, Kathiresan S, Cupples LA. 2014. Association of low-frequency and rare coding-sequence variants with blood lipids and coronary heart disease in 56,000 whites and blacks. The American Journal of Human Genetics 94:223-232 DOI 10.1016/j.ajhg.2014.01.009
42. Pennacchio LA, Rubin EM. 2003. Apolipoprotein A5, a newly identified gene that affects plasma triglyceride levels in humans and mice. Arteriosclerosis, Thrombosis, and Vascular Biology 23:529-534 DOI 10.1161/01.ATV.0000054194.78240.45
43. Pollin TI, Damcott CM, Shen H, Ott SH, Shelton J, Horenstein RB, Post W, McLenithan JC, Bielak LF, Peyser PA, Mitchell BD, Miller M, O'Connell JR, Shuldiner AR. 2008. A null mutation in human APOC3 confers a favorable plasma lipid profile and apparent cardioprotection. Science 322:1702-1705 DOI 10.1126/science.1161524
44. Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich D. 2006. Principal components analysis corrects for stratification in genome-wide association studies. Nature Genetics 38:904-909 DOI 10.1038/ng1847
45. Raaijmakers A, Corveleyn A, Devriendt K, Van Tienoven TP, Allegaert K, Dyck MV, Van den Heuvel, L, Kuypers D, Claes K, Mekahli D, Levtchenko E. 2015. Criteria for HNF1B analysis in patients with congenital abnormalities of kidney and urinary tract. Nephrology Dialysis Transplantation 30:835-842 DOI 10.1093/ndt/gfu370
46. R Development Core Team. 2014. R: a language and environment for statistical comput-ing. Vienna: R Foundation for Statistical Computing
47. Rubin EM, Krauss RM, Spangler EA, Verstuyft JG, Clift SM. 1991. Inhibition of early atherogenesis in transgenic mice by human apolipoprotein AI. Nature 353:265-267 DOI 10.1038/353265a0
48. Storey JD. 2002. A direct approach to false discovery rates. Journal of the Royal Statistical Society: Series B 64:479-498 DOI 10.1111/1467-9868.00346
49. Stroes E, Colquhoun D, Sullivan D, Civeira F, Rosenson RS, Watts GF, Bruckert E, Cho L, Dent R, Knusel B, Xue A, Scott R, Wasserman SM, Rocco M. 2014. Anti-PCSK9 antibody effectively lowers cholesterol in patients with statin intolerance the GAUSS-2 Randomized, placebo-controlled phase 3 clinical trial of evolocumab. Journal of the American College of Cardiology 63:2541-2548 DOI 10.1016/j.jacc.2014.03.019
50. Teslovich TM, Musunuru K, Smith AV, Edmondson AC, Stylianou IM, Koseki M, Pirruccello JP, Ripatti S, Chasman DI, Willer CJ, Johansen CT, Fouchier SW, Isaacs A, Peloso GM, Barbalic M, Ricketts SL, Bis JC, Aulchenko YS, Thorleifsson G, Feitosa MF, Chambers J, Orho-Melander M, Melander O, Johnson T, Li X, Guo X, Li M, Shin Cho Y, Jin Go M, Jin Kim Y, Lee JY, Park T, Kim K, Sim X, Twee-Hee Ong R, Croteau-Chonka DC, Lange LA, Smith JD, Song K, Hua Zhao J, Yuan X, Luan J, Lamina C, Ziegler A, Zhang W, Zee RY, Wright AF, Witteman JC, Wilson JF, Willemsen G, Wichmann HE, Whitfield JB, Waterworth DM, Wareham NJ, Waeber G, Vollenweider P, Voight BF, Vitart V, Uitterlinden AG, Uda M, Tuomilehto J, Thompson JR, Tanaka T, Surakka I, Stringham HM, Spector TD, Soranzo N, Smit JH, Sinisalo J, Silander K, Sijbrands EJ, Scuteri A, Scott J, Schlessinger D, Sanna S, Salomaa V, Saharinen J, Sabatti C, Ruokonen A, Rudan I, Rose LM, Roberts R, Rieder M, Psaty BM, Pramstaller PP, Pichler I, Perola M, Penninx BW, Pedersen NL, Pattaro C, Parker AN, Pare G, Oostra BA, O'Donnell CJ, Nieminen MS, Nickerson DA, Montgomery GW, Meitinger T, McPherson R, McCarthy MI, McArdle W, Masson D, Martin NG, Marroni F, Mangino M, Magnusson PK, Lucas G, Luben R, Loos RJ, Lokki ML, Lettre G, Langenberg C, Launer LJ, Lakatta EG, Laaksonen R, Kyvik KO, Kronenberg F, König IR, Khaw KT, Kaprio J, Kaplan LM, Johansson A, Jarvelin MR, Janssens AC, Ingelsson E, Igl W, Kees Hovingh G, Hottenga JJ, Hofman A, Hicks AA, Hengstenberg C, Heid IM, Hayward C, Havulinna AS, Hastie ND, Harris TB, Haritunians T, Hall AS, Gyllensten U, Guiducci C, Groop LC, Gonzalez E, Gieger C, Freimer NB, Ferrucci L, Erdmann J, Elliott P, Ejebe KG, Döring A, Dominiczak AF, Demissie S, Deloukas P, de Geus EJ, de Faire U, Crawford G, Collins FS, Chen YD, Caulfield MJ, Campbell H, Burtt NP, Bonnycastle LL, Boomsma DI, Boekholdt SM, Bergman RN, Barroso I, Bandinelli S, Ballantyne CM, Assimes TL, Quertermous T, Altshuler D, Seielstad M, Wong TY, Tai ES, Feranil AB, Kuzawa CW, Adair LS, Taylor Jr HA, Borecki IB, Gabriel SB, Wilson JG, Holm H, Thorsteinsdottir U, Gudnason V, Krauss RM, Mohlke KL, Ordovas JM, Munroe PB, Kooner JS, Tall AR, Hegele RA, Kastelein JJ, Schadt EE, Rotter JI, Boerwinkle E, Strachan DP, Mooser V, Stefansson K, Reilly MP, Samani NJ, Schunkert H. 2010. Biological, clinical and population relevance of 95 loci for blood lipids. Nature 466:707-713 DOI 10.1038/nature09270
51. United States Food and Drug Administration. 2015. FDA briefing document-endocrinologic and metabolic drugs advisory commitee (EMDAC)
52. Vattikuti S, Guo J, Chow CC. 2012. Heritability and genetic correlations explained by common SNPs for metabolic syndrome traits. PLOS Genetics 8:e1002637 DOI 10.1371/journal.pgen.1002637
53. Waterworth DM, Ricketts SL, Song K, Chen L, Zhao JH, Ripatti S, Aulchenko YS, Zhang W, Yuan X, Lim N, Luan J'an, Ashford S, Wheeler E, Young EH, Hadley D, Thompson JR, Braund PS, Johnson T, Struchalin M, Surakka I, Luben R, Khaw K-T, Rodwell SA, Loos RJF, Boekholdt SM, Inouye M, Deloukas P, Elliott P, Schlessinger D, Sanna S, Scuteri A, Jackson A, Mohlke KL, Tuomilehto J, Roberts R, Stewart A, Kesäniemi YA, Mahley RW, Grundy SM, WTCC Consortium, McArdle W, Cardon L, Waeber G, Vollenweider P, Chambers JC, Boehnke M, Abecasis GR, Salomaa V, Järvelin M-R, Ruokonen A, Barroso I, Epstein SE, Hakonarson HH, Rader DJ, Reilly MP, Witteman JCM, Hall AS, Samani NJ, Strachan DP, Barter P, van Duijn CM, Kooner JS, Peltonen L, Wareham NJ, McPherson R, Mooser V, Sandhu MS. 2010. Genetic variants influencing circulating lipid levels and risk of coronary artery disease. Arteriosclerosis, Thrombosis, and Vascular Biology 30:2264-2276 DOI 10.1161/ATVBAHA.109.201020
54. Wu MC, Lee S, Cai T, Li Y, Boehnke M, Lin X. 2011. Rare-variant association testing for sequencing data with the sequence kernel association test. The American Journal of Human Genetics 89:82-93 DOI 10.1016/j.ajhg.2011.05.029
55. Yang J, Lee SH, Goddard ME, Visscher PM. 2011. GCTA: a tool for genome-wide complex trait analysis. The American Journal of Human Genetics 88:76-82 DOI 10.1016/j.ajhg.2010.11.011