SynthesisPLoS genetics2017
Ranking and characterization of established BMI and lipid associated loci as candidates for gene-environment interactions.
Synthesis in PLoS genetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
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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.
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Who cites it
16 citing papers in PubMed, 25 citations in OpenAlex.
- A biobank-scale method for learning modulators of gene-environment interaction underlying human complex traits from multiple environmental exposures.bioRxiv : the preprint server for biology · 2026Article
- Gene-environment interaction analysis in atopic eczema: evidence from large population datasets and modellingmedRxiv : the preprint server for health sciences · 2025Article
- Gene-Environment Interaction Affects Risk of Atopic Eczema: Population and In Vitro Studies.Allergy · 2025Article
- Distinct explanations underlie gene-environment interactions in the UK Biobank.American journal of human genetics · 2025Article
- Considerations on efforts needed to improve our understanding of the genetics of obesity.International journal of obesity (2005) · 2025Review
- Diabetes and obesity: leveraging heterogeneity for precision medicine.European heart journal · 2024Review
- Distinct explanations underlie gene-environment interactions in the UK Biobank.medRxiv : the preprint server for health sciences · 2024Article
- gJLS2: an R package for generalized joint location and scale analysis in X-inclusive genome-wide association studies.G3 (Bethesda, Md.) · 2022Article
- Sortilin as a Biomarker for Cardiovascular Disease Revisited.Frontiers in cardiovascular medicine · 2021Article
- Large-Scale Analyses Provide No Evidence for Gene-Gene Interactions Influencing Type 2 Diabetes Risk.Diabetes · 2020Article
- Precision medicine in diabetes: a Consensus Report from the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD).Diabetologia · 2020Article
- Gene Lifestyle Interactions With Relation to Obesity, Cardiometabolic, and Cardiovascular Traits Among South Asians.Frontiers in endocrinology · 2019Review
- Gene-lifestyle interplay in type 2 diabetes.Current opinion in genetics & development · 2018Review
- Review
- Systems Genomics of Thigh Adipose Tissue From Asian Indian Type-2 Diabetics Revealed Distinct Protein Interaction Hubs.Frontiers in genetics · 2018Article
- Exploring Coronary Artery Disease GWAs Targets With Functional Links to Immunometabolism.Frontiers in cardiovascular medicine · 2018Review
Corrections and comments
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Authors and funding
31 authors at 16 institutions in 7 countries.
Funding
Abstract
Phenotypic variance heterogeneity across genotypes at a single nucleotide polymorphism (SNP) may reflect underlying gene-environment (G×E) or gene-gene interactions. We modeled variance heterogeneity for blood lipids and BMI in up to 44,211 participants and investigated relationships between variance effects (Pv), G×E interaction effects (with smoking and physical activity), and marginal genetic effects (Pm). Correlations between Pv and Pm were stronger for SNPs with established marginal effects (Spearman's ρ = 0.401 for triglycerides, and ρ = 0.236 for BMI) compared to all SNPs. When Pv and Pm were compared for all pruned SNPs, only BMI was statistically significant (Spearman's ρ = 0.010). Overall, SNPs with established marginal effects were overrepresented in the nominally significant part of the Pv distribution (Pbinomial <0.05). SNPs from the top 1% of the Pm distribution for BMI had more significant Pv values (PMann-Whitney = 1.46×10-5), and the odds ratio of SNPs with nominally significant (<0.05) Pm and Pv was 1.33 (95% CI: 1.12, 1.57) for BMI. Moreover, BMI SNPs with nominally significant G×E interaction P-values (Pint<0.05) were enriched with nominally significant Pv values (Pbinomial = 8.63×10-9 and 8.52×10-7 for SNP × smoking and SNP × physical activity, respectively). We conclude that some loci with strong marginal effects may be good candidates for G×E, and variance-based prioritization can be used to identify them.
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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.