Invited commentary: Efficient testing of gene-environment interaction

Nilanjan Chatterjee, Sholom Wacholder

Research output: Contribution to journalComment/debatepeer-review

Abstract

Gene-environment-wide interaction studies of disease occurrence in human populations may be able to exploit the same agnostic approach to interrogating the human genome used by genome-wide association studies. The authors discuss 2 methods for taking advantage of possible independence between a single nucleotide polymorphism they call G (a genetic factor) and an environmental factor they call E while maintaining nominal type I error in studying G-E interaction when information on many genes is available. The first method is a simple 2-step procedure for testing the null hypothesis of no multiplicative interaction against the alternative hypothesis of a multiplicative interaction between an E and at least one of the markers genotyped in a genome-wide association study. The added power for the method derives from a clever work-around of a multiple testing procedure. The second is an empirical-Bayes-style shrinkage estimation framework for G-E interaction and the associated tests that can gain efficiency and power when the G-E independence assumption is met for most G's in the underlying population and yet, unlike the case-only method, is resistant to increased type I error when the underlying assumption of independence is violated. The development of new approaches to testing for interaction is an example of methodological progress leading to practical advantages.

Original languageEnglish (US)
Pages (from-to)231-233
Number of pages3
JournalAmerican journal of epidemiology
Volume169
Issue number2
DOIs
StatePublished - Jan 2009
Externally publishedYes

Keywords

  • Association
  • Environment
  • Genes
  • Genetic markers
  • Genetics
  • Genome

ASJC Scopus subject areas

  • Epidemiology

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