ArticleNature communications2024
Systematic discovery of gene-environment interactions underlying the human plasma proteome in UK Biobank.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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
13 citing papers in PubMed.
- Genetic drivers of protein changes over time: Findings, considerations, and approaches in TOPMed cohorts and UK Biobank.bioRxiv : the preprint server for biology · 2026Article
- Genetic influences on haematopoiesis.Nature reviews. Genetics · 2026Review
- A dish-to-biobank framework links β-cell nutrient-stress programs to genetic and dietary risk for Type 2 Diabetes.bioRxiv : the preprint server for biology · 2026Article
- Optimizing phenotype scale improves genetic analyses in large-scale biobanks.bioRxiv : the preprint server for biology · 2026Article
- Characterizing breed-shared and breed-specific genetic regulatory effects of gene expression across three pig breeds.Journal of animal science and biotechnology · 2026Article
- Genome-Wide by Lifetime Environment Interaction Studies of Brain Imaging Phenotypes.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Choice of phenotype scale is critical in biobank-based G×E tests.bioRxiv : the preprint server for biology · 2026Article
- Mendelian Randomization With Longitudinal Exposure Data: Simulation Study and Real Data Application.Statistics in medicine · 2026Article
- Polygenic modeling of genetic effects on both phenotypic mean and variance: distributional regression for BMI, blood and urine biomarkers in the UK Biobank.Frontiers in bioinformatics · 2026Article
- Complex genetic effects linked to plasma protein abundance in the UK Biobank.Nature communications · 2025Article
- Human Plasma Proteomics Links Modifiable Lifestyle Exposome to Disease Risk.medRxiv : the preprint server for health sciences · 2025Article
- Variance quantitative trait loci reveal gene-gene interactions which alter blood traits.medRxiv : the preprint server for health sciences · 2024Article
- Systematic discovery of gene-environment interactions underlying the human plasma proteome in UK Biobank.Nature communications · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
Abstract
Understanding how gene-environment interactions (GEIs) influence the circulating proteome could aid in biomarker discovery and validation. The presence of GEIs can be inferred from single nucleotide polymorphisms that associate with phenotypic variability - termed variance quantitative trait loci (vQTLs). Here, vQTL association studies are performed on plasma levels of 1463 proteins in 52,363 UK Biobank participants. A set of 677 independent vQTLs are identified across 568 proteins. They include 67 variants that lack conventional additive main effects on protein levels. Over 1100 GEIs are identified between 101 proteins and 153 environmental exposures. GEI analyses uncover possible mechanisms that explain why 13/67 vQTL-only sites lack corresponding main effects. Additional analyses also highlight how age, sex, epistatic interactions and statistical artefacts may underscore associations between genetic variation and variance heterogeneity. This study establishes the most comprehensive database yet of vQTLs and GEIs for the human proteome.
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.