We aim to leverage UK Biobank data to validate and extend findings from our previous work on environmentally sensitive quantitative trait loci (QTLs) across multiple molecular layers. Our earlier studies identified genetic variants whose regulatory effects are modified by environmental exposures, focusing in particular on contextual methylation QTLs that interact with childhood adversity to influence DNA methylation levels.
We further explored gene-environment interactions using a model of glucocorticoid receptor activation induced by dexamethasone treatment, revealing genetic influences on stress-related transcriptional regulation. To functionally characterize these loci, we employed cell type-specific STARR-seq and massively parallel reporter assays, enabling high-resolution mapping of regulatory activity under varying environmental conditions. Collectively, these experiments have uncovered a set of environmentally responsive regulatory variants that may contribute to complex trait variation through interactions with stress-related or developmental exposures.
Objectives
Building on these experimental findings, our objective is to validate environmentally responsive QTLs in an independent, large-scale population cohort and to assess their relevance for health-related complex traits. By integrating our molecular data with UK Biobank’s extensive genotype, phenotype, and environmental measures, we aim to determine whether these variants exert measurable effects on disease risk and trait variation in the general population.
Research Questions
1. Trait association: Are environmentally responsive regulatory variants associated with health-related complex traits in the UK Biobank?
2. Comparative relevance: Are these associations stronger than those observed for regulatory variants not identified as environmentally responsive?
3. Interaction with adversity: Do these variants also also interact with childhood adversity to influence disease risk directly?
