ArticleAmerican journal of human genetics2014
Gene-environment dependence creates spurious gene-environment interaction.
Article in American journal of human genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 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.
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Who cites it
60 citing papers in PubMed, 97 citations in OpenAlex.
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- Discovery of gene-alcohol interaction loci influencing blood pressure in 1.1 million individuals from multiple populations.Research square · 2026Article
- The geometry of G × E: How scaling and endogenous treatment effects shape interaction direction.PLoS genetics · 2026Article
- A biobank-scale test of marginal epistasis reveals genome-wide signals of polygenic interaction effects.Nature genetics · 2025Article
- Incorporating additive genetic effects and linkage disequilibrium information to discover gene-environment interactions using BV-LDER-GE.Genome biology · 2025Article
- PIGEON: a statistical framework for estimating gene-environment interaction for polygenic traits.Nature human behaviour · 2025Article
- Switch-like gene expression modulates disease risk.Nature communications · 2025Article
- Hierarchical selection of genetic and gene by environment interaction effects in high-dimensional mixed models.Statistical methods in medical research · 2025Review
- Genetic-by-age interaction analyses on complex traits in UK Biobank and their potential to identify effects on longitudinal trait change.Genome biology · 2024Article
- Gene-environment interactions in human health.Nature reviews. Genetics · 2024Review
- A scalable adaptive quadratic kernel method for interpretable epistasis analysis in complex traits.Genome research · 2024Article
- A scalable and robust variance components method reveals insights into the architecture of gene-environment interactions underlying complex traits.American journal of human genetics · 2024Article
- Variability of polygenic prediction for body mass index in Africa.Genome medicine · 2024Article
- Many roads to a gene-environment interaction.American journal of human genetics · 2024Review
- Fast kernel-based association testing of non-linear genetic effects for biobank-scale data.Nature communications · 2023Article
- Schooling substantially improves intelligence, but neither lessens nor widens the impacts of socioeconomics and genetics.NPJ science of learning · 2022Article
- Dissecting Complex Traits Using Omics Data: A Review on the Linear Mixed Models and Their Application in GWAS.Plants (Basel, Switzerland) · 2022Review
- Education interacts with genetic variants near GJD2, RBFOX1, LAMA2, KCNQ5 and LRRC4C to confer susceptibility to myopia.PLoS genetics · 2022Article
- A robust and adaptive framework for interaction testing in quantitative traits between multiple genetic loci and exposure variables.PLoS genetics · 2022Article
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
Abstract
Gene-environment interactions have the potential to shed light on biological processes leading to disease and to improve the accuracy of epidemiological risk models. However, relatively few such interactions have yet been confirmed. In part this is because genetic markers such as tag SNPs are usually studied, rather than the causal variants themselves. Previous work has shown that this leads to substantial loss of power and increased sample size when gene and environment are independent. However, dependence between gene and environment can arise in several ways including mediation, pleiotropy, and confounding, and several examples of gene-environment interaction under gene-environment dependence have recently been published. Here we show that under gene-environment dependence, a statistical interaction can be present between a marker and environment even if there is no interaction between the causal variant and the environment. We give simple conditions under which there is no marker-environment interaction and note that they do not hold in general when there is gene-environment dependence. Furthermore, the gene-environment dependence applies to the causal variant and cannot be assessed from marker data. Gene-gene interactions are susceptible to the same problem if two causal variants are in linkage disequilibrium. In addition to existing concerns about mechanistic interpretations, we suggest further caution in reporting interactions for genetic markers.
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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.