ArticleBioData mining2014
CardioGxE, a catalog of gene-environment interactions for cardiometabolic traits.
Article in BioData mining, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 5 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
38 citing papers in PubMed, 5 syntheses or guidelines pooled it, 59 citations in OpenAlex.
- Variance-quantitative trait loci enable systematic discovery of gene-environment interactions for cardiometabolic serum biomarkers.Nature communications · 2022Pooled it
- Gene-by-Psychosocial Factor Interactions Influence Diastolic Blood Pressure in European and African Ancestry Populations: Meta-Analysis of Four Cohort Studies.International journal of environmental research and public health · 2017Pooled it
- The genetic overlap between mood disorders and cardiometabolic diseases: a systematic review of genome wide and candidate gene studies.Translational psychiatry · 2017Pooled it
- Review of the Gene-Environment Interaction Literature in Cancer: What Do We Know?Genetic epidemiology · 2016Pooled it
- Gene-Environment Interactions of Circadian-Related Genes for Cardiometabolic Traits.Diabetes care · 2015Pooled it
- Differential weight-loss responses of APOA2 genotype carriers to low-carbohydrate and low-fat diets: the DIETFITS trial.Obesity (Silver Spring, Md.) · 2025Trial
- Mediterranean Diet Adherence and Genetic Background Roles within a Web-Based Nutritional Intervention: The Food4Me Study.Nutrients · 2017Trial
- Interaction of an S100A9 gene variant with saturated fat and carbohydrates to modulate insulin resistance in 3 populations of different ancestries.The American journal of clinical nutrition · 2016Trial
- Metabolite Genome-Wide Association in Hispanics with Obesity Reveals Genetic Risk and Interactions with Dietary Factors for Type 2 Diabetes.Metabolites · 2025Article
- Exploration of Biomarkers of Food Intake in a Caribbean Hispanic Population.Molecular nutrition & food research · 2025Article
- G × E interactions as a basis for toxicological uncertainty.Archives of toxicology · 2023Article
- Article
- Research gaps and opportunities in precision nutrition: an NIH workshop report.The American journal of clinical nutrition · 2022Article
- Appraisal of Gene-Environment Interactions in GWAS for Evidence-Based Precision Nutrition Implementation.Current nutrition reports · 2022Review
- Effects of SNVs in ABCA1, ABCG1, ABCG5, ABCG8, and SCARB1 Genes on Plasma Lipids, Lipoproteins, and Adiposity Markers in a Brazilian Population.Biochemical genetics · 2022Article
- Personalized nutrition: A review of genotype-based nutritional supplementation.Frontiers in nutrition · 2022Review
- Biobank Scale Pharmacogenomics Informs the Genetic Underpinnings of Simvastatin Use.Clinical pharmacology and therapeutics · 2021Article
- Quantile-Dependent Expressivity and Gene-Lifestyle Interactions Involving High-Density Lipoprotein Cholesterol.Lifestyle genomics · 2021Review
- Using Machine Learning to Predict Obesity Based on Genome-Wide and Epigenome-Wide Gene-Gene and Gene-Diet Interactions.Frontiers in genetics · 2021Article
- Ketogenic Diets and Cardio-Metabolic Diseases.Frontiers in endocrinology · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 1 institution in 1 country.
Funding
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.