Systematic discovery of gene-environment interactions underlying the human plasma proteome in UK Biobank

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.

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Publication Details

Journal
Nature Communications
Published
2024-08-26
DOI
https://doi.org/10.1038/s41467-024-51744-5
Citations
11
Primary Topic
Genetic Associations and Epidemiology
Type
article
Field-Weighted Citation Impact
6.05

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article

Systematic discovery of gene-environment interactions underlying the human plasma proteome in UK Biobank

Benjamin B. Sun, Eric Marshall, Danni A. Gadd, Tasos Mangelis et al.
11 citations
Nature Communications
Genetic Associations and Epidemiology
6.05
article

Systematic discovery of gene-environment interactions underlying the human plasma proteome in UK Biobank

Benjamin B. Sun, Eric Marshall, Danni A. Gadd, Tasos Mangelis, Kyle Ferber, Zhana Kuncheva, Christopher N. Foley, Robert F. Hillary, Riccardo E. Marioni, Tin-Chi Lin, Helen McLaughlin, Heiko Runz
article en
11 citations

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.

Nature CommunicationsVol. 15(1)
Biogen (United States) (US), University of Cambridge (GB), Edinburgh Cancer Research (GB), Optimat (United Kingdom) (GB), Massachusetts Health Quality Partners (US), University of Edinburgh (GB)
Amgen, Bristol-Myers Squibb, Pfizer, AstraZeneca, Wellcome, Biogen, Alnylam Pharmaceuticals, Regeneron Pharmaceuticals, Wellcome Trust, Alzheimer's Society, British Heart Foundation, Novo Nordisk, Genentech, Janssen Pharmaceuticals
Life in Land
Openalex Percentile: Top 3%
Genetic Associations and Epidemiology
6.05
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