Rodrigo San-Cristobal1,2, Juan de Toro-Martín1,2, Marie-Claude Vohl3,4. 1. Centre Nutrition, Santé Et Société (NUTRISS), Institut Sur La Nutrition Et Les Aliments Fonctionnels (INAF), Université Laval, Québec, QC, Canada. 2. School of Nutrition, Université Laval, Quebec, QC, G1V 0A6, Canada. 3. Centre Nutrition, Santé Et Société (NUTRISS), Institut Sur La Nutrition Et Les Aliments Fonctionnels (INAF), Université Laval, Québec, QC, Canada. marie-claude.vohl@fsaa.ulaval.ca. 4. School of Nutrition, Université Laval, Quebec, QC, G1V 0A6, Canada. marie-claude.vohl@fsaa.ulaval.ca.
Abstract
PURPOSE OF REVIEW: This review aims to analyse the currently reported gene-environment (G × E) interactions in genome-wide association studies (GWAS), involving environmental factors such as lifestyle and dietary habits related to metabolic syndrome phenotypes. For this purpose, the present manuscript reviews the available GWAS registered on the GWAS Catalog reporting the interaction between environmental factors and metabolic syndrome traits. RECENT FINDINGS: Advances in omics-related analytical and computational approaches in recent years have led to a better understanding of the biological processes underlying these G × E interactions. A total of 42 GWAS were analysed, reporting over 300 loci interacting with environmental factors. Alcohol consumption, sleep time, smoking habit and physical activity were the most studied environmental factors with significant G × E interactions. The implementation of more comprehensive GWAS will provide a better understanding of the metabolic processes that determine individual responses to environmental exposures and their association with the development of chronic diseases such as obesity and the metabolic syndrome. This will facilitate the development of precision approaches for better prevention, management and treatment of these diseases.
PURPOSE OF REVIEW: This review aims to analyse the currently reported gene-environment (G × E) interactions in genome-wide association studies (GWAS), involving environmental factors such as lifestyle and dietary habits related to metabolic syndrome phenotypes. For this purpose, the present manuscript reviews the available GWAS registered on the GWAS Catalog reporting the interaction between environmental factors and metabolic syndrome traits. RECENT FINDINGS: Advances in omics-related analytical and computational approaches in recent years have led to a better understanding of the biological processes underlying these G × E interactions. A total of 42 GWAS were analysed, reporting over 300 loci interacting with environmental factors. Alcohol consumption, sleep time, smoking habit and physical activity were the most studied environmental factors with significant G × E interactions. The implementation of more comprehensive GWAS will provide a better understanding of the metabolic processes that determine individual responses to environmental exposures and their association with the development of chronic diseases such as obesity and the metabolic syndrome. This will facilitate the development of precision approaches for better prevention, management and treatment of these diseases.
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