Comparison of haplotype-based tests for detecting gene-environment interactions with rare variants

    Research output: Contribution to journalReview articlepeer-review

    2 Scopus citations

    Abstract

    Dissecting the genetic mechanism underlying a complex disease hinges on discovering gene-environment interactions (GXE). However, detecting GXE is a challenging problem especially when the genetic variants under study are rare. Haplotype-based tests have several advantages over the so-called collapsing tests for detecting rare variants as highlighted in recent literature. Thus, it is of practical interest to compare haplotype-based tests for detecting GXE including the recent ones developed specifically for rare haplotypes. We compare the following methods: haplo.glm, hapassoc, HapReg, Bayesian hierarchical generalized linear model (BhGLM) and logistic Bayesian LASSO (LBL). We simulate data under different types of association scenarios and levels of gene-environment dependence. We find that when the type I error rates are controlled to be the same for all methods, LBL is the most powerful method for detecting GXE. We applied the methods to a lung cancer data set, in particular, in region 15q25.1 as it has been suggested in the literature that it interacts with smoking to affect the lung cancer susceptibility and that it is associated with smoking behavior. LBL and BhGLM were able to detect a rare haplotype-smoking interaction in this region. We also analyzed the sequence data from the Dallas Heart Study, a population-based multi-ethnic study. Specifically, we considered haplotype blocks in the gene ANGPTL4 for association with trait serum triglyceride and used ethnicity as a covariate. Only LBL found interactions of haplotypes with race (Hispanic). Thus, in general, LBL seems to be the best method for detecting GXE among the ones we studied here. Nonetheless, it requires the most computation time.

    Original languageEnglish (US)
    Pages (from-to)851-862
    Number of pages12
    JournalBriefings in bioinformatics
    Volume21
    Issue number3
    DOIs
    StatePublished - May 21 2020

    All Science Journal Classification (ASJC) codes

    • Information Systems
    • Molecular Biology

    Fingerprint

    Dive into the research topics of 'Comparison of haplotype-based tests for detecting gene-environment interactions with rare variants'. Together they form a unique fingerprint.

    Cite this