Considering interactive effects in the identification of influential regions with extremely rare variants via fixed bin approach

Abstract

In this study, we analyze the Genetic Analysis Workshop 18 (GAW18) data to identify regions of single-nucleotide polymorphisms (SNPs), which significantly influence hypertension status among individuals. We have studied the marginal impact of these regions on disease status in the past, but we extend the method to deal with environmental factors present in data collected over several exam periods. We consider the respective interactions between such traits as smoking status and age with the genetic information and hope to augment those genetic regions deemed influential marginally with those that contribute via an interactive effect. In particular, we focus only on rare variants and apply a procedure to combine signal among rare variants in a number of "fixed bins" along the chromosome. We extend the procedure in Agne et al [1] to incorporate environmental factors by dichotomizing subjects via traits such as smoking status and age, running the marginal procedure among each respective category (i.e., smokers or nonsmokers), and then combining their scores into a score for interaction. To avoid overlap of subjects, we examine each exam period individually. Out of a possible 629 fixed-bin regions in chromosome 3, we observe that 11 show up in multiple exam periods for gene-smoking score. Fifteen regions exhibit significance for multiple exam periods for gene-age score, with 4 regions deemed significant for all 3 exam periods. The procedure pinpoints SNPs in 8 "answer" genes, with 5 of these showing up as significant in multiple testing schemes (Gene-Smoking, Gene-Age for Exams 1, 2, and 3).

Methods for Collapsing Multiple Rare Variants in Whole‐Genome Sequence Data

“…In addition to gene‐based bins, several research groups used a competing strategy in which nonoverlapping sliding windows were constructed across the entire genome. The number of variants contained in each window could either be fixed [Agne et al., ; Yang and Li, ] or depend on the number of variants observed within a set number of base pairs [Xuan et al., ; Yang and Li, ]. The choice of window sizing was somewhat arbitrary.…”

Population‐Based Association and Gene by Environment Interactions in Genetic Analysis Workshop 18

“…In fact, in the absence of interaction, these two proportions are expected to be the same on average; thus their sum will correspond to a burden test for genetic main effects. This may explain the success that Agne et al [] had in finding risk genes in the simulated data.…”

“…Environmental interactions with genetic factors are an important part of association analysis. To consider the problem of estimating gene‐environment interactions, Fan et al [] and Wang et al [, b] used the GAW18 genome‐wide association data with real phenotypes and Agne et al [] used the sequence data on simulated phenotypes. Accordingly, the first three studies considered methods for testing interaction with a single (common) SNP, whereas Agne and colleagues considered interactions between rare variants and environmental covariates.…”

“…Unlike Fan et al [] and Wang et al [, b], who considered common variants, Agne et al [] considered the problem of detecting interactions between rare variants and environmental factors. Similar to Wang et al [] and Fan et al [], Agne et al [] considered only exposures that are binary or that had been discretized into two categories. As with the rare variant tests described previously, the data must be combined in some way.…”

“…Population association techniques were also used by members of our working group to study gene‐environment interactions. Agne et al [], Fan et al [], and Wang et al [, b] used a variety of techniques to test for interaction between genotypes and environmental covariates such as age, sex, and treatment for hypertension. Although different definitions of interaction are used in the context of clinical epidemiology [Rothman et al., ], the focus here is on statistical interactions.…”