title: Detecting rare and common haplotype-environment interaction under uncertainty of gene-environment independence assumption.
abstract: Finding rare variants and gene-environment interactions (GXE) is critical in dissecting complex diseases. We consider the problem of detecting GXE where G is a rare haplotype and E is a nongenetic factor. Such methods typically assume G-E independence, which may not hold in many applications. A pertinent example is lung cancer-there is evidence that variants on Chromosome 15q25.1 interact with smoking to affect the risk. However, these variants are associated with smoking behavior rendering the assumption of G-E independence inappropriate. With the motivation of detecting GXE under G-E dependence, we extend an existing approach, logistic Bayesian LASSO, which assumes G-E independence (LBL-GXE-I) by modeling G-E dependence through a multinomial logistic regression (referred to as LBL-GXE-D). Unlike LBL-GXE-I, LBL-GXE-D controls type I error rates in all situations; however, it has reduced power when G-E independence holds. To control type I error without sacrificing power, we further propose a unified approach, LBL-GXE, to incorporate uncertainty in the G-E independence assumption by employing a reversible jump Markov chain Monte Carlo method. Our simulations show that LBL-GXE has power similar to that of LBL-GXE-I when G-E independence holds, yet has well-controlled type I errors in all situations. To illustrate the utility of LBL-GXE, we analyzed a lung cancer dataset and found several significant interactions in the 15q25.1 region, including one between a specific rare haplotype and smoking.
authors.affiliation: Department of Mathematical Sciences, University of Texas at Dallas, Richardson, Texas 75080, U.S.A.
authors.forename: Yuan
authors.initials: Y
authors.lastname: Zhang
authors.affiliation: Department of Statistics, The Ohio State University, Columbus, Ohio 43210, U.S.A.
authors.forename: Shili
authors.initials: S
authors.lastname: Lin
authors.affiliation: Department of Mathematical Sciences, University of Texas at Dallas, Richardson, Texas 75080, U.S.A.
authors.forename: Swati
authors.initials: S
authors.lastname: Biswas
mesh_terms: D001699:Biometry / Q000379:methods*; D002884:Chromosomes, Human, Pair 15; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D059647:Gene-Environment Interaction; D014644:Genetic Variation; D006239:Haplotypes; D006801:Humans; D016015:Logistic Models; D008175:Lung Neoplasms / Q000209:etiology* / Q000235:genetics; D008957:Models, Genetic; D012306:Risk; D012907:Smoking / Q000009:adverse effects* / Q000235:genetics
keywords: G-E dependence; GXE; LBL; Missing heritability; Rare variants; Reversible jump MCMC