Heuristic Approach Uncovering Biological Significance of Gene-Lifestyle Interactions in Cardiometabolic Traits

Background: Gene-lifestyle interaction studies using genome-wide association studies (GWAS) data contribute to a better understanding of individual responses to environmental exposures. Objectives: Herein, we aimed at assessing the biological significance of overlapping genes reported in gene-lifest...

Full description

Saved in:
Bibliographic Details
Published in:Lifestyle genomics 2023-01, Vol.16 (1), p.106-112
Main Authors: San-Cristobal, Rodrigo, de Toro-Martín, Juan, Vohl, Marie-Claude
Format: Article
Language:English
Subjects:
Alcohol
Blood pressure
Body fat
Body mass index
Brief Report
cardiometabolic health
Cardiovascular Diseases - epidemiology
Cardiovascular Diseases - genetics
Cholesterol
Clinical medicine
Cluster analysis
Disease
Enrichment
Exercise
Gene-Environment Interaction
gene-lifestyle interaction
Genes
Genome-wide association studies
Genome-Wide Association Study
genome-wide interaction study
Genomes
Health risk assessment
Health risks
Heuristic
heuristic analysis
Heuristic methods
Heuristics
Humans
Lifestyles
Metabolic disorders
Metabolic pathways
Metabolism
Phenotype
precision nutrition
Problem solving
Uric acid
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Background: Gene-lifestyle interaction studies using genome-wide association studies (GWAS) data contribute to a better understanding of individual responses to environmental exposures. Objectives: Herein, we aimed at assessing the biological significance of overlapping genes reported in gene-lifestyle interaction studies in cardiometabolic health. Method: A heuristic analysis of genes reporting significant interactions related to cardiometabolic traits was performed to determine the biological pathways common to the different traits. Results: A total of 873 genes were analyzed. Fine and condensed phenotypic solutions were obtained from overlapping genes common to more than one trait. Conclusions: This study revealed significant metabolic pathways associated with the impact of gene-environment interactions on cardiometabolic risk. Graphical Abstract: Publicly available data in cloud-based repositories were used to perform enrichment analyses of genes previously described in GWAS studies that showed interaction with lifestyles. From the enriched pathways, cluster analysis was performed to group enriched metabolic disorders.
ISSN:2504-3161
2504-3188
DOI:10.1159/000531181