CardioGxE, a catalog of gene-environment interactions for cardiometabolic traits

Abstract

BackgroundGenetic understanding of complex traits has developed immensely over the past decade but remains hampered by incomplete descriptions of contribution to phenotypic variance. Gene-environment (GxE) interactions are one of these contributors and in the guise of diet and physical activity are important modulators of cardiometabolic phenotypes and ensuing diseases.ResultsWe mined the scientific literature to collect GxE interactions from 386 publications for blood lipids, glycemic traits, obesity anthropometrics, vascular measures, inflammation and metabolic syndrome, and introduce CardioGxE, a gene-environment interaction resource. We then analyzed the genes and SNPs supporting cardiometabolic GxEs in order to demonstrate utility of GxE SNPs and to discern characteristics of these important genetic variants. We were able to draw many observations from our extensive analysis of GxEs. 1) The CardioGxE SNPs showed little overlap with variants identified by main effect GWAS, indicating the importance of environmental interactions with genetic factors on cardiometabolic traits. 2) These GxE SNPs were enriched in adaptation to climatic and geographical features, with implications on energy homeostasis and response to physical activity. 3) Comparison to gene networks responding to plasma cholesterol-lowering or regression of atherosclerotic plaques showed that GxE genes have a greater role in those responses, particularly through high-energy diets and fat intake, than do GWAS-identified genes for the same traits. Other aspects of the CardioGxE dataset were explored.ConclusionsOverall, we demonstrate that SNPs supporting cardiometabolic GxE interactions often exhibit transcriptional effects or are under positive selection. Still, not all such SNPs can be assigned potential functional or regulatory roles often because data are lacking in specific cell types or from treatments that approximate the environmental factor of the GxE. With research on metabolic related complex disease risk embarking on genome-wide GxE interaction tests, CardioGxE will be a useful resource.

Genome-wide association study of triglyceride response to a high-fat meal among participants of the NHLBI Genetics of Lipid Lowering Drugs and Diet Network (GOLDN)

“…In this regard, APOA4 SNP rs5110 has been shown to associate with postprandial lipemia in a European population in a BMI-dependent manner [54]. Other similar gene-diet interactions have been catalogued [38]; although none of the lead SNPs or SNPs in LD with the lead SNPs identified here have been reported for other gene-diet interactions.…”

“…Figure 3 demonstrates the association results of SNPs around rs964184, and their LD with rs964184, created with LocusZoom [35]. This variant (rs964184) is not in high LD with other SNPs in our data, but lies in close proximity to the APOA1/C3/A4/A5 cluster, which harbors numerous variants with associations to baseline TG [36], and postprandial lipid metabolism parameters [37] as well as numerous gene-environment interactions involving TG as phenotype and fat intake as a modifying environmental factor [38]. The association of this SNP with all fasting and PPL phenotypes is provided in Table 4.…”

Nutrigenomics, the Microbiome, and Gene-Environment Interactions: New Directions in Cardiovascular Disease Research, Prevention, and Treatment

“…31 Gene-diet interactions in CVD have been analyzed for many years, with many reports demonstrating that those interactions have an impact on determining both intermediate and final CVD phenotypes, as cataloged in detail. 68 Some of these genetic variants have been highlighted through GWAS. For example, variation in the TCF7L2 gene, previously implicated in type 2 diabetes mellitus, 69 was shown to interact with diet through intervention with the Mediterranean diet and played a role in determining stroke risk.…”

“…A comprehensive review of cardiometabolic GxEs from 386 publications, 68 including blood lipids, glycemic traits, obesity anthropometrics, vascular measures, inflammation, and metabolic syndrome, allowed the following conclusions. First, the GxE single-nucleotide polymorphisms (SNPs) showed little overlap with variants identified by a main-effect GWAS, indicating the importance of environmental interactions with genetic factors on cardiometabolic traits.…”

Multiancestry Study of Gene–Lifestyle Interactions for Cardiovascular Traits in 610 475 Individuals From 124 Cohorts

“…These demonstrated the promise of G×E interactions for identifying genetic variants with large effects 10–13 . For example, mean triglyceride levels are 23 mg/dL lower in physically active versus sedentary individuals (88 vs 111 md/dL) who carry a C-allele at rs2070744 in NOS 3, but there is little difference by physical activity status in TT homozygotes 11 .…”