title: Studying gene and gene-environment effects of uncommon and common variants on continuous traits: a marker-set approach using gene-trait similarity regression.
abstract: Genomic association analyses of complex traits demand statistical tools that are capable of detecting small effects of common and rare variants and modeling complex interaction effects and yet are computationally feasible. In this work, we introduce a similarity-based regression method for assessing the main genetic and interaction effects of a group of markers on quantitative traits. The method uses genetic similarity to aggregate information from multiple polymorphic sites and integrates adaptive weights that depend on allele frequencies to accomodate common and uncommon variants. Collapsing information at the similarity level instead of the genotype level avoids canceling signals that have the opposite etiological effects and is applicable to any class of genetic variants without the need for dichotomizing the allele types. To assess gene-trait associations, we regress trait similarities for pairs of unrelated individuals on their genetic similarities and assess association by using a score test whose limiting distribution is derived in this work. The proposed regression framework allows for covariates, has the capacity to model both main and interaction effects, can be applied to a mixture of different polymorphism types, and is computationally efficient. These features make it an ideal tool for evaluating associations between phenotype and marker sets defined by linkage disequilibrium (LD) blocks, genes, or pathways in whole-genome analysis.
authors.affiliation: Department of Statistics, North Carolina State University, Raleigh, NC 27695, USA. jung-ying_tzeng@ncsu.edu
authors.forename: Jung-Ying
authors.initials: JY
authors.lastname: Tzeng
authors.forename: Daowen
authors.initials: D
authors.lastname: Zhang
authors.forename: Monnat
authors.initials: M
authors.lastname: Pongpanich
authors.forename: Chris
authors.initials: C
authors.lastname: Smith
authors.forename: Mark I
authors.initials: MI
authors.lastname: McCarthy
authors.forename: Michèle M
authors.initials: MM
authors.lastname: Sale
authors.forename: Bradford B
authors.initials: BB
authors.lastname: Worrall
authors.forename: Fang-Chi
authors.initials: FC
authors.lastname: Hsu
authors.forename: Duncan C
authors.initials: DC
authors.lastname: Thomas
authors.forename: Patrick F
authors.initials: PF
authors.lastname: Sullivan
mesh_terms: D002891:Chromosomes, Human, Pair 21 / Q000235:genetics; D003198:Computer Simulation; D030541:Databases, Genetic; D004777:Environment; D005796:Genes / Q000235:genetics*; D005819:Genetic Markers; D006801:Humans; D008957:Models, Genetic; D009154:Mutation / Q000235:genetics*; D019655:Quantitative Trait, Heritable; D012044:Regression Analysis
chemical_list: D005819:Genetic Markers