Hypertension is a polygenic disease that affects over 1.2 billion adults aged 30–79 worldwide. It is a major risk factor for renal, cerebrovascular, and cardiovascular diseases. The heritability of hypertension is estimated to be high; nevertheless, our understanding of its underlying mechanisms remains scarce and incomplete. This study covered the entries from European ancestry from the UK-Biobank (UKB), with 74,090 cases diagnosed with essential (primary) hypertension and 200,734 controls. We compared the findings from large-scale genome-wide association studies (GWAS) to the gene-based method of proteome-wide association studies (PWAS). We focused on 70 statistically significant associated genes, most of which failed to reach significance in variant-based GWAS. A total of 30% of the PWAS-associated genes were validated against independent cohorts, including the Finnish Biobank. Furthermore, gene-based analyses that were performed on both sexes revealed sex-dependent genetics with a stronger genetic component associated with females. Analysis of systolic and diastolic blood pressure measurements confirms a strong genetic effect associated with females. We demonstrated that gene-based approaches provide insight into the underlying biology of hypertension. Specifically, the expression profiles of the identified genes exposed the enrichment of endothelial cells from multiple organs. Furthermore, females' top-ranked significant genes are involved in cellular immunity. We conclude that studying hypertension and blood pressure via gene-based association methods improves interpretability and exposes sex-dependent genetic effects, which enhances clinical utility.
Bibliographical noteFunding Information:
We thank Dr. Nadav Brandes for the support in using the UKB parser, the PWAS algorithm and commenting on the initial draft. We thank Dr. Guy Kelman for his help in the implementation of PWAS. We thank Dr. Ronen Durst and Idit Gabay for commenting on the initial draft. We thank Amos Stern from the Linial lab for useful discussion. We appreciate the constant support of the system team of the School of Computer Science at the Hebrew University.
© 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.