Distinguishing differential susceptibility, diathesis-stress and vantage sensitivity: beyond the single gene and environment model

TL;DR

This paper introduces a new R package called LEGIT for modeling complex genotype x environment interactions involving multiple genes and environments, addressing limitations of existing methods through simulation studies.

Contribution

The study develops and tests the LEGIT R package, enabling more accurate modeling of multi-gene and multi-environment GxE interactions beyond single-factor approaches.

Findings

RoS and confirmatory methods are accurate with large samples.

Confirmatory approach performs well with moderate to large effects and N >= 250.

RoS performs poorly in small samples and effect sizes.

Abstract

Currently, two main approaches exist to distinguish differential susceptibility from diathesis-stress and vantage sensitivity in genotype x environment interaction (GxE) research: Regions of significance (RoS) and competitive-confirmatory approaches. Each is limited by their single-gene/single-environment foci given that most phenotypes are the product of multiple interacting genetic and environmental factors. We thus addressed these two concerns in a recently developed R package (LEGIT) for constructing GxE interaction models with latent genetic and environmental scores using alternating optimization. Herein we test, by means of computer simulation, diverse GxE models in the context of both single and multiple genes and environments. Results indicate that the RoS and competitive-confirmatory approaches were highly accurate when the sample size was large, whereas the latter performed better in small samples and for small effect sizes. The confirmatory approach generally had good accuracy (a) when effect size was moderate and N >= 500 and (b) when effect size was large and N >= 250, whereas RoS performed poorly. Computational tools to determine the type of GxE of multiple genes and environments are provided as extensions in our LEGIT R package.