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Updated: Sep 16, 2025

Assessing Murine Resistance Artery Function Using Pressure Myography
Published on: June 7, 2013
Gene-environment interactions contribute to blood pressure variation across global populations
Khushi Goda1,2, Noah Klimkowski Arango1,2, Francesco Tiezzi1,3
1Center for Human Genetics, Clemson University, Greenwood, SC, USA.
Abstract:
Understanding the interplay between genetic architecture and environmental exposures is essential for elucidating the biological basis of complex traits such as blood pressure (BP). Although gene-by-environment interactions (G×E) have been previously shown to contribute to BP variation, their role in multi-ancestry cohorts remains underexplored. We hypothesize that G×E effects may explain additional variance in BP traits across diverse populations, where environmental exposures and genetic backgrounds are more heterogeneous. Here, we present an evaluation of the importance of G×E on systolic (SP), diastolic (DP), and pulse pressure (PP) in a multi-ancestry subset of 25,000 individuals from the UK Biobank. We considered 23 lifestyle variables as the environmental exposures, and estimated variance components attributed to demographics, population structure, genetic effects, environmental effects and gene-by-environment interactions. Our results revealed that G×E accounts for 7% of variance in DP, 4% in SP, and 3% in PP. Notably, these estimates exceed those previously reported (2% for all BP traits) in a UK Biobank analysis restricted to White British individuals using similar lifestyle variables and methodology. However, accounting for G×E did not improve prediction accuracy in two cross-validation schemes. We also tried to uncover individual interactions affecting each trait by conducting G×E-GWAS. Although no interaction surpassed genome-wide significance, we annotated suggestive hits and uncovered genes enriched in blood pressure-relevant pathways. Our study suggests that environmental heterogeneity and diverse genetic backgrounds in multi-ancestry cohorts may amplify the role of G×E, underscoring the importance of diverse populations in capturing the full spectrum of trait architecture.
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