ArticleNature human behaviour2025
PIGEON: a statistical framework for estimating gene-environment interaction for polygenic traits.
Article in Nature human behaviour, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Cross-ancestry pleiotropic analysis of imaging-derived phenotypes enhances risk stratification of depression.Molecular psychiatry · 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
- Leveraging polygenic risk scores to infer causal directions in genotype-by-environment interactions between complex traits.Human genetics · 2026Article
- When does accounting for gene-environment interactions improve complex trait prediction? A case study with Drosophila lifespan.G3 (Bethesda, Md.) · 2026Article
- Causal effect heterogeneity estimation using summary statistics.Research square · 2026Article
- Methods for modeling gene-environment interplay using polygenic risk scores.Statistical applications in genetics and molecular biology · 2026Review
- Assessing Orthogonality in Gene-Environment Interaction Studies Using Polygenic Indices.Behavior genetics · 2026Article
- Sex-Specific Genetic Architecture and Comorbidities of Alcohol Use Behaviors.medRxiv : the preprint server for health sciences · 2025Article
- Exposure accumulation drives age-dependent disease architectures and polygenic risk scores.medRxiv : the preprint server for health sciences · 2025Article
- Polygenic prediction of treatment efficacy with causal transfer learning.medRxiv : the preprint server for health sciences · 2025Article
- When does accounting for gene-environment interactions improve complex trait prediction? A case study withbioRxiv : the preprint server for biology · 2025Article
- Transdisciplinary fetal-neonatal neurology training integrates women's and children's health with life-course brain capital strategies: a narrative review.Frontiers in neurologyReview
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Authors and funding
11 authors.
Funding
Abstract
Understanding gene-environment interaction (GxE) is crucial for deciphering the genetic architecture of human complex traits. However, current statistical methods for GxE inference face challenges in both scalability and interpretability. Here we introduce PIGEON-a unified statistical framework for quantifying polygenic GxE using a variance component analytical approach. Based on this framework, we outline the main objectives in GxE studies and introduce an estimation procedure that requires only summary statistics data as input. We demonstrate the effectiveness of PIGEON through theoretical and empirical analyses, including a quasi-experimental gene-by-education study of health outcomes and gene-by-sex interaction for 530 traits using UK Biobank. We also identify genetic interactors that explain the treatment effect heterogeneity in a clinical trial on smoking cessation. PIGEON suggests a path towards polygenic, summary statistics-based inference in future GxE studies.
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Registered trials
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