| Title: | Gene-environment interactions contribute to blood pressure variation across global populations |
| Journal: | Human Genetics and Genomics Advances |
| Published: | 24 Jul 2026 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/42499188/ |
| DOI: | https://doi.org/10.1016/j.xhgg.2026.100656 |
Publication 21370
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Abstract
Understanding the interplay between genetics and environment is essential for elucidating the biological basis of complex traits such as blood pressure (BP). Although gene-environment interactions (G×E) contribute to BP variation, their role in multi-ancestry cohorts remains underexplored. We hypothesize that G×E may explain additional variance in BP across diverse populations, where environmental exposures and genetic backgrounds are more heterogeneous. Here, we evaluate the importance of G×E on diastolic pressure (DP), systolic pressure (SP), and pulse pressure (PP) in a multi-ethnic subset of 24,000 UK Biobank individuals. We considered 23 lifestyle variables as the environmental exposures and estimated variance components attributed to genetic effects, environmental effects, and gene-environment interactions. Our results revealed that G×E accounts for 7% of variance in DP, 4% in SP, and 3% in PP. While these estimates are not statistically different from the ones obtained from an analysis restricted to White British individuals using the same lifestyle variables and methodology (4%, 3%, and 4% for DP, SP, and PP, respectively), the point estimate for DP is almost twice as large in the multi-ethnic sample. Including G×E in the models did not improve out-of-sample prediction accuracy. We also performed a G×E genome-wide association study (G×E-GWAS) to uncover individual interactions affecting BP traits. Although no interaction surpassed genome-wide significance, suggestive hits were enriched in BP-relevant pathways. Our hypothesis-generating study suggests that higher environmental and genetic heterogeneity in multi-ethnic cohorts may amplify the role of G×E for some traits and serves as a basis for future studies with larger sample sizes and higher power.</p>
5 Authors
- Khushi Goda
- Noah Klimkowski Arango
- Francesco Tiezzi
- Trudy F.C. Mackay
- Fabio Morgante
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