Statistical Genetic Approaches to Investigate Genotype-by-Environment Interaction: Review and Novel Extension of Models.

Sandra Laston, Sarah Williams-Blangero, John Blangero, Vincent P Diego, Eron G Manusov, Marcio Almeida, David Ortiz

Journal: Genes 2024;15(5):

PMID: 38790175

Abstract

Statistical genetic models of genotype-by-environment (G×E) interaction can be divided into two general classes, one on G×E interaction in response to dichotomous environments (e.g., sex, disease-affection status, or presence/absence of an exposure) and the other in response to continuous environments (e.g., physical activity, nutritional measurements, or continuous socioeconomic measures). Here we develop a novel model to jointly account for dichotomous and continuous environments. We develop the model in terms of a joint genotype-by-sex (for the dichotomous environment) and genotype-by-social determinants of health (SDoH; for the continuous environment). Using this model, we show how a depression variable, as measured by the Beck Depression Inventory-II survey instrument, is not only underlain by genetic effects (as has been reported elsewhere) but is also significantly determined by joint G×Sex and G×SDoH interaction effects. This model has numerous applications leading to potentially transformative research on the genetic and environmental determinants underlying complex diseases.

Address: Department of Human Genetics, School of Medicine, University of Texas Rio Grande Valley, Brownsville, TX 78520, USA.; South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville, TX 78520, USA.; Department of Family Medicine, School of Medicine, University of Texas Rio Grande Valley, Brownsville, TX 78520, USA.
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