Efficient Two-Step Testing of Gene-Gene Interactions in Genome-Wide Association Studies

Genetic Epidemiology

Volumn 37, Issue 5, 2013, Pages 440-451

  Lewinger, Juan Pablo ^a   Morrison, John L ^a   Thomas, Duncan C ^a   Murcray, Cassandra E ^a,b   Conti, David V ^a   Li, Dalin ^a,c,d   Gauderman, W James ^a  

^a UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

^b AMGEN INC   (United States)

^c CEDARS SINAI MEDICAL CENTER   (United States)

^d UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Case control studies; Epistasis; Marginal effects; Missing heritability; Screening

Indexed keywords

ARTICLE; CASE CONTROL STUDY; COMPARATIVE STUDY; FOLLOW UP; GENE FREQUENCY; GENE INTERACTION; GENE LINKAGE DISEQUILIBRIUM; GENETIC ASSOCIATION; GENETIC CODE; GENETIC SCREENING; GENOTYPE; HUMAN; POPULATION STRUCTURE; PREVALENCE; SINGLE NUCLEOTIDE POLYMORPHISM;

ALGORITHMS; DATA INTERPRETATION, STATISTICAL; EPISTASIS, GENETIC; GENOME-WIDE ASSOCIATION STUDY; HUMANS; POLYMORPHISM, SINGLE NUCLEOTIDE;

EID: 84879157670     PISSN: 07410395     EISSN: 10982272     Source Type: Journal    
DOI: 10.1002/gepi.21720     Document Type: Article

References (27)

1. Agresti A. 2002. Categorical Data Analysis. New York: Wiley.
2. Bhattacharjee S, Wang Z, Ciampa J, Kraft P, Chanock S, Yu K, Chatterjee N. 2010. Using principal components of genetic variation for robust and powerful detection of gene-gene interactions in case-control and case-only studies. Am J Hum Genet 86(3):331-342.
3. Bhattacharya K, McCarthy MI, Morris AP. 2011. Rapid testing of gene-gene interactions in genome-wide association studies of binary and quantitative phenotypes. Genet Epidemiol 35(8):800-808.
4. Brown BW, Lovato J, Russell K. 1999. Asymptotic power calculations: description, examples, computer code. Stat Med 18(22):3137-3151.
5. Cordell HJ. 2009. Genome-wide association studies: detecting gene-gene interactions that underlie human diseases. Nat Rev Genet 10(6):392-404.
6. Dai JY, Kooperberg C, LeBlanc M, Prentice LR. 2010. On two-stage hypothesis testing procedures via asymptotically independent statistics. University of Washington Biostatistics Working Paper Series Paper 367.
7. Evans DM, Marchini J, Morris AP, Cardon LR. 2006. Two-stage two-locus models in genome-wide association. PLoS Genet 2(9):e157.
8. Gauderman W. 2002a. Sample size requirements for association studies of gene-gene interaction. Am J Epidemiol 155:478-484.
9. Gauderman WJ. 2002b. Sample size requirements for association studies of gene-gene interaction. Am J Epidemiol 155(5):478-484.
10. Hindorff LA, MacArthur JWA, Junkins HA, Hall PN, Klemm AK, Manolio TA. 2012. A catalog of published genome-wide association studies. Available at: www.genome.gov/gwastudies
11. Kam-Thong T, Czamara D, Tsuda K, Borgwardt K, Lewis CM, Erhardt-Lehmann A, Hemmer B, Rieckmann P, Daake M, Weber F and others. 2011. EPIBLASTER-fast exhaustive two-locus epistasis detection strategy using graphical processing units. Eur J Hum Genet 19(4):465-471.
12. Kooperberg C, Leblanc M. 2008. Increasing the power of identifying gene x gene interactions in genome-wide association studies. Genet Epidemiol 32(3):255-263.
13. Li D, Conti DV. 2009. Detecting gene-environment interactions using a combined case-only and case-control approach. Am J Epidemiol 169(4):497-504.
14. Marchini J, Donnelly P, Cardon LR. 2005. Genome-wide strategies for detecting multiple loci that influence complex diseases. Nat Genet 37(4):413-417.
15. Mukherjee B, Chatterjee N. 2008. Exploiting gene-environment independence for analysis of case-control studies: an empirical Bayes-type shrinkage estimator to trade-off between bias and efficiency. Biometrics 64(3):685-694.
16. Murcray CE, Lewinger JP, Gauderman WJ. 2009. Gene-environment interaction in genome-wide association studies (with commentaries and rejoinder). Am J Epidemiol 169(2):219-226.
17. Murcray CE, Lewinger JP, Conti DV, Thomas DC, Gauderman WJ. 2011. Sample size requirements to detect gene-environment interactions in genome-wide association studies. Genet Epidemiol 35(3):201-210.
18. Peters JM, Avol E, Navidi W, London SJ, Gauderman WJ, Lurmann F, Linn WS, Margolis H, Rappaport E, Gong H and others. 1999. A study of twelve Southern California communities with differing levels and types of air pollution. I. Prevalence of respiratory morbidity. Am J Respir Crit Care Med 159(3):760-767.
19. Piegorsch WW, Weinberg CR, Taylor JA. 1994. Non-hierarchical logistic models and case-only designs for assessing susceptibility in population-based case-control studies. Stat Med 13(2):153-162.
20. Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich D. 2006. Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet 38(8):904-909.
21. Pritchard JK, Stephens M, Donnelly P. 2000. Inference of population structure using multilocus genotype data. Genetics 155(2):945-959.
22. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, Maller J, Sklar P, de Bakker PI, Daly MJ and others. 2007. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 81(3):559-575.
23. Self SG, Mauritsen RH, Ohara J. 1992. Power calculations for likelihood ratio tests in generalized linear-models. Biometrics 48(1):31-39.
24. Steen KV. 2012. Travelling the world of gene-gene interactions. Brief Bioinform 13(1):1-19.
25. Wang LY, Lee WC. 2008. Population stratification bias in the case-only study for gene-environment interactions. Am J Epidemiol 168(2):197-201.
26. Wang Y, Localio R, Rebbeck TR. 2006. Evaluating bias due to population stratification in epidemiologic studies of gene-gene or gene-environment interactions. Cancer Epidemiol Biomarkers Prev 15(1):124-132.
27. Zuk O, Hechter E, Sunyaev SR, Lander ES. 2012. The mystery of missing heritability: genetic interactions create phantom heritability. Proc Natl Acad Sci USA 109(4):1193-1198.