Mixed model with correction for case-control ascertainment increases association power

American Journal of Human Genetics

Volumn 96, Issue 5, 2015, Pages 720-730

  Hayeck, Tristan J ^a,b   Zaitlen, Noah A ^c   Loh, Po Ru ^a,b   Vilhjalmsson, Bjarni ^a,b   Pollack, Samuela ^a,b   Gusev, Alexander ^a,b   Yang, Jian ^d   Chen, Guo Bo ^d   Goddard, Michael E ^e   Visscher, Peter M ^d   Patterson, Nick ^b   Price, Alkes L ^a,b  

^a HARVARD SCHOOL OF PUBLIC HEALTH   (United States)

^b BROAD INSTITUTE OF MIT AND HARVARD   (United States)

^c UNIVERSITY OF CALIFORNIA   (United States)

^d UNIVERSITY OF QUEENSLAND   (Australia)

^e UNIVERSITY OF MELBOURNE   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; ASCERTAINMENT BIAS; CALIBRATION; CASE CONTROL STUDY; GENETIC ASSOCIATION; GENETIC MODEL; GENOTYPE; HERITABILITY; HUMAN; LIABILITY THRESHOLD MIXED LINEAR MODEL; MOLECULAR PHYLOGENY; MULTIPLE SCLEROSIS; PHENOTYPE; PHENOTYPIC VARIATION; PREVALENCE; PRIORITY JOURNAL; SAMPLE SIZE; SIMULATION; STATISTICAL MODEL; BIOLOGICAL MODEL; CHROMOSOME MAP; COMPUTER SIMULATION; GENETICS; PATHOLOGY; SINGLE NUCLEOTIDE POLYMORPHISM; THEORETICAL MODEL;

CASE-CONTROL STUDIES; CHROMOSOME MAPPING; COMPUTER SIMULATION; GENETIC ASSOCIATION STUDIES; HUMANS; MODELS, GENETIC; MODELS, THEORETICAL; MULTIPLE SCLEROSIS; PHENOTYPE; POLYMORPHISM, SINGLE NUCLEOTIDE; SAMPLE SIZE;

EID: 84929274500     PISSN: 00029297     EISSN: 15376605     Source Type: Journal    
DOI: 10.1016/j.ajhg.2015.03.004     Document Type: Article

References (35)

1. J. Yu, G. Pressoir, W.H. Briggs, I. Vroh Bi, M. Yamasaki, J.F. Doebley, M.D. McMullen, B.S. Gaut, D.M. Nielsen, and J.B. Holland A unified mixed-model method for association mapping that accounts for multiple levels of relatedness Nat. Genet. 38 2006 203 208
2. K. Zhao, M.J. Aranzana, S. Kim, C. Lister, C. Shindo, C. Tang, C. Toomajian, H. Zheng, C. Dean, P. Marjoram, and M. Nordborg An Arabidopsis example of association mapping in structured samples PLoS Genet. 3 2007 e4
3. H.M. Kang, N.A. Zaitlen, C.M. Wade, A. Kirby, D. Heckerman, M.J. Daly, and E. Eskin Efficient control of population structure in model organism association mapping Genetics 178 2008 1709 1723
4. H.M. Kang, J.H. Sul, S.K. Service, N.A. Zaitlen, S.Y. Kong, N.B. Freimer, C. Sabatti, and E. Eskin Variance component model to account for sample structure in genome-wide association studies Nat. Genet. 42 2010 348 354
5. G.R. Svishcheva, T.I. Axenovich, N.M. Belonogova, C.M. van Duijn, and Y.S. Aulchenko Rapid variance components-based method for whole-genome association analysis Nat. Genet. 44 2012 1166 1170
6. J. Listgarten, C. Lippert, C.M. Kadie, R.I. Davidson, E. Eskin, and D. Heckerman Improved linear mixed models for genome-wide association studies Nat. Methods 9 2012 525 526
7. A. Korte, B.J. Vilhjálmsson, V. Segura, A. Platt, Q. Long, and M. Nordborg A mixed-model approach for genome-wide association studies of correlated traits in structured populations Nat. Genet. 44 2012 1066 1071
8. X. Zhou, and M. Stephens Genome-wide efficient mixed-model analysis for association studies Nat. Genet. 44 2012 821 824
9. V. Segura, B.J. Vilhjálmsson, A. Platt, A. Korte, Ü. Seren, Q. Long, and M. Nordborg An efficient multi-locus mixed-model approach for genome-wide association studies in structured populations Nat. Genet. 44 2012 825 830
10. J. Listgarten, C. Lippert, and D. Heckerman FaST-LMM-Select for addressing confounding from spatial structure and rare variants Nat. Genet. 45 2013 470 471
11. J. Yang, N.A. Zaitlen, M.E. Goddard, P.M. Visscher, and A.L. Price Advantages and pitfalls in the application of mixed-model association methods Nat. Genet. 46 2014 100 106
12. N. Zaitlen, S. Lindström, B. Pasaniuc, M. Cornelis, G. Genovese, S. Pollack, A. Barton, H. Bickeböller, D.W. Bowden, and S. Eyre Informed conditioning on clinical covariates increases power in case-control association studies PLoS Genet. 8 2012 e1003032
13. N. Zaitlen, B. Pasaniuc, N. Patterson, S. Pollack, B. Voight, L. Groop, D. Altshuler, B.E. Henderson, L.N. Kolonel, and L. Le Marchand Analysis of case-control association studies with known risk variants Bioinformatics 28 2012 1729 1737
14. J. Mefford, and J.S. Witte The Covariate's Dilemma PLoS Genet. 8 2012 e1003096
15. D.D. Campbell, P.C. Sham, J. Knight, H. Wickham, and S. Landau Software for generating liability distributions for pedigrees conditional on their observed disease states and covariates Genet. Epidemiol. 34 2010 159 170
16. D.S. Falconer The inheritance of liability to diseases with variable age of onset, with particular reference to diabetes mellitus Ann. Hum. Genet. 31 1967 1 20
17. J. Yang, B. Benyamin, B.P. McEvoy, S. Gordon, A.K. Henders, D.R. Nyholt, P.A. Madden, A.C. Heath, N.G. Martin, and G.W. Montgomery Common SNPs explain a large proportion of the heritability for human height Nat. Genet. 42 2010 565 569
18. J.K. Haseman, and R.C. Elston The investigation of linkage between a quantitative trait and a marker locus Behav. Genet. 2 1972 3 19
19. G.-B. Chen Estimating heritability of complex traits from genome-wide association studies using IBS-based Haseman-Elston regression Front. Genet. 5 2014 107
20. S.H. Lee, N.R. Wray, M.E. Goddard, and P.M. Visscher Estimating missing heritability for disease from genome-wide association studies Am. J. Hum. Genet. 88 2011 294 305
21. T. Thornton, and M.S. McPeek Case-control association testing with related individuals: a more powerful quasi-likelihood score test Am. J. Hum. Genet. 81 2007 321 337
22. A.L. Price, N.J. Patterson, R.M. Plenge, M.E. Weinblatt, N.A. Shadick, and D. Reich Principal components analysis corrects for stratification in genome-wide association studies Nat. Genet. 38 2006 904 909
23. C.C. Heyde Quasi-likelihood and its application: a general approach to optimal parameter estimation 1997 Springer
24. J. Yang, S.H. Lee, M.E. Goddard, and P.M. Visscher GCTA: a tool for genome-wide complex trait analysis Am. J. Hum. Genet. 88 2011 76 82
25. B. Devlin, and K. Roeder Genomic control for association studies Biometrics 55 1999 997 1004
26. S.H. Lee, D. Harold, D.R. Nyholt, M.E. Goddard, K.T. Zondervan, J. Williams, G.W. Montgomery, N.R. Wray, P.M. Visscher ANZGene Consortium International Endogene Consortium Genetic and Environmental Risk for Alzheimer's disease Consortium Estimation and partitioning of polygenic variation captured by common SNPs for Alzheimer's disease, multiple sclerosis and endometriosis Hum. Mol. Genet. 22 2013 832 841
27. S.H. Lee, T.R. DeCandia, S. Ripke, J. Yang, P.F. Sullivan, M.E. Goddard, M.C. Keller, P.M. Visscher, N.R. Wray Schizophrenia Psychiatric Genome-Wide Association Study Consortium (PGC-SCZ) International Schizophrenia Consortium (ISC) Molecular Genetics of Schizophrenia Collaboration (MGS) Estimating the proportion of variation in susceptibility to schizophrenia captured by common SNPs Nat. Genet. 44 2012 247 250
28. S. Sawcer, G. Hellenthal, M. Pirinen, C.C. Spencer, N.A. Patsopoulos, L. Moutsianas, A. Dilthey, Z. Su, C. Freeman, S.E. Hunt International Multiple Sclerosis Genetics Consortium Wellcome Trust Case Control Consortium 2 Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis Nature 476 2011 214 219
29. D. Golan, E.S. Lander, and S. Rosset Measuring missing heritability: inferring the contribution of common variants Proc. Natl. Acad. Sci. USA 111 2014 E5272 E5281
30. J. Yang, M.N. Weedon, S. Purcell, G. Lettre, K. Estrada, C.J. Willer, A.V. Smith, E. Ingelsson, J.R. O'Connell, M. Mangino GIANT Consortium Genomic inflation factors under polygenic inheritance Eur. J. Hum. Genet. 19 2011 807 812
31. B.K. Bulik-Sullivan, P.-R. Loh, H.K. Finucane, S. Ripke, J. Yang, N. Patterson, M.J. Daly, A.L. Price, B.M. Neale Schizophrenia Working Group of the Psychiatric Genomics Consortium LD Score regression distinguishes confounding from polygenicity in genome-wide association studies Nat. Genet. 47 2015 291 295
32. P.M. Visscher, W.G. Hill, and N.R. Wray Heritability in the genomics era - concepts and misconceptions Nat. Rev. Genet. 9 2008 255 266
33. R. Plomin, C.M.A. Haworth, and O.S.P. Davis Common disorders are quantitative traits Nat. Rev. Genet. 10 2009 872 878
34. P.-R. Loh, G. Tucker, B.K. Bulik-Sullivan, B.J. Vilhjálmsson, H.K. Finucane, R.M. Salem, D.I. Chasman, P.M. Ridker, B.M. Neale, and B. Berger Efficient Bayesian mixed-model analysis increases association power in large cohorts Nat. Genet. 47 2015 284 290
35. X. Zhou, and M. Stephens Efficient multivariate linear mixed model algorithms for genome-wide association studies Nat. Methods 11 2014 407 409