ArticleAmerican journal of human genetics2020
A Robust Method Uncovers Significant Context-Specific Heritability in Diverse Complex Traits.
Article in American journal of human genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers, 1 of them a synthesis that pooled it.
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Who cites it
55 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Kernel-based gene-environment interaction tests for rare variants with multiple quantitative phenotypes.PloS one · 2022Pooled it
- Article
- Gene-environment interactions contribute to blood pressure variation across global populations.HGG advances · 2026Article
- Context-specific genetic effects inform endotypes and treatment in asthma.The Journal of allergy and clinical immunology · 2026Article
- Heritable variation drives rapid evolution of thermal performance curves in the protist Tetrahymena thermophila.Communications biology · 2026Article
- Detecting gene-environment interactions to guide personalized intervention: Boosting distributional regression for polygenic scores.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- The geometry of G × E: How scaling and endogenous treatment effects shape interaction direction.PLoS genetics · 2026Article
- 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
- Mapping the Analytical Landscape of Gene-Diet Interactions in Epidemiology: From Classical Models to Causal and Multi-Omics Frameworks.Nutrients · 2026Review
- When does accounting for gene-environment interactions improve complex trait prediction? A case study with Drosophila lifespan.G3 (Bethesda, Md.) · 2026Article
- Moderating the Heritability of Body Mass Index by Age and Sex With Genomic Data.Genetic epidemiology · 2026Article
- Choice of phenotype scale is critical in biobank-based G×E tests.bioRxiv : the preprint server for biology · 2026Article
- Methods for modeling gene-environment interplay using polygenic risk scores.Statistical applications in genetics and molecular biology · 2026Review
- Exposure accumulation drives age-dependent disease architectures and polygenic risk scores.medRxiv : the preprint server for health sciences · 2025Article
- Incorporating additive genetic effects and linkage disequilibrium information to discover gene-environment interactions using BV-LDER-GE.Genome biology · 2025Article
- Hypothesis test of specific parametric structure in a generalized additive model.medRxiv : the preprint server for health sciences · 2025Article
- PIGEON: a statistical framework for estimating gene-environment interaction for polygenic traits.Nature human behaviour · 2025Article
- When does accounting for gene-environment interactions improve complex trait prediction? A case study withbioRxiv : the preprint server for biology · 2025Article
- Protocol to estimate the heritability of drug response with GxEMM and identify gene-drug interactions with TxEWAS.STAR protocols · 2025Article
- Efficient and accurate framework for genome-wide gene-environment interaction analysis in large-scale biobanks.Nature communications · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Gene-environment interactions (GxE) can be fundamental in applications ranging from functional genomics to precision medicine and is a conjectured source of substantial heritability. However, unbiased methods to profile GxE genome-wide are nascent and, as we show, cannot accommodate general environment variables, modest sample sizes, heterogeneous noise, and binary traits. To address this gap, we propose a simple, unifying mixed model for gene-environment interaction (GxEMM). In simulations and theory, we show that GxEMM can dramatically improve estimates and eliminate false positives when the assumptions of existing methods fail. We apply GxEMM to a range of human and model organism datasets and find broad evidence of context-specific genetic effects, including GxSex, GxAdversity, and GxDisease interactions across thousands of clinical and molecular phenotypes. Overall, GxEMM is broadly applicable for testing and quantifying polygenic interactions, which can be useful for explaining heritability and invaluable for determining biologically relevant environments.
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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 Socratic graph.