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

View the full research paper on Nature Communications

Objectives:

This study aimed to explore how gene-environment interactions (GEIs) affect protein levels in the human body, specifically within the plasma proteome. The focus was on identifying variance quantitative trait loci (vQTLs) that signal these interactions, and understanding how genetic and environmental factors together influence protein expression. By doing so, the research sought to enhance biomarker discovery for disease states and inform the development of precision medicine.

Solutions:

The researchers performed vQTL association studies on plasma protein levels using data from 52,363 participants in the UK Biobank. They identified 677 independent vQTLs across 568 proteins, including 67 that lacked typical genetic main effects on protein levels.

By examining how these vQTLs interacted with environmental factors like lifestyle and health-related exposures, they uncovered over 1,100 GEIs.

The study also explored why certain genetic variants influence protein variability without altering mean levels, providing new insights into gene-environment dynamics. This approach offered a more nuanced understanding of protein biology beyond conventional genome-wide association studies (GWAS).

Challenges:

• Gene-environment interactions are often subtle and difficult to detect, requiring sophisticated statistical methods.
• It is challenging to measure environmental exposures consistently and accurately across participants.
• Analysing variance, rather than mean changes, introduces complexity in distinguishing true biological signals from noise.
• Understanding the functional relevance of interactions between genes and the environment, given the vast number of potential factors involved, required careful analysis.

Impact:

• The study established the largest database of vQTLs and GEIs in the human proteome, a resource for future research.
• Identifying vQTLs that affect protein variability highlighted potential biomarkers for diseases that may have been missed in traditional studies.
• The findings offer potential for precision medicine by helping to predict how different genetic and environmental factors influence patient outcomes, aiding in more tailored treatments.