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Shared Genetics of Hypertension and Preeclampsia Converges on Immune Regulation
Mohammed Farahat1,2, Malak Abbas3, Mileati Melese1
1Department of Integrative Genomics and Epidemiology, School of Graduate Studies, Meharry Medical College, Nashville, TN, USA.
Background:
Hypertension and preeclampsia are clinically distinct, yet biologically related conditions characterized by vascular dysfunction and elevated cardiovascular risk. Although genome-wide association studies (GWAS) have identified loci associated with blood pressure traits and preeclampsia, the functional mechanisms linking shared variants to gene regulation and clinical phenotypes remain unclear.
Methods:
We integrated GWAS summary statistics for hypertension, systolic blood pressure (SBP), diastolic blood pressure (DBP), and preeclampsia to identify shared variants (p ≤ 1×10-4). Cis-expression quantitative trait loci (eQTL) analyses were performed in whole blood using RNA-seq data from 180 African American women. Significant associations (FDR ≤ 0.05) were evaluated for replication across vascular, metabolic, and endocrine tissues in the Genotype-Tissue Expression (GTEx) project. Associations between gene expression and blood pressure traits were also assessed.
Results:
We identified 4,792 shared GWAS variants, of which 4,663 were tested in eQTL analyses, yielding 1,837 significant variant-gene associations across 78 genes. Replication in GTEx confirmed 645 associations involving 24 genes, many showing cross-tissue regulatory effects. Three genes (C4B, HLA-C, and HLA-DQB1) demonstrated convergent evidence across GWAS, gene regulation, and expression-trait analyses. C4B expression was positively associated with hypertension and SBP, while HLA-C showed consistent negative associations with hypertension, SBP, and DBP. HLA-DQB1 expression was specifically associated with DBP, suggesting trait-specific effects.
Conclusions:
These findings highlight immune-related pathways as key mediators linking hypertension and preeclampsia. Integrating genetic, transcriptomic, and phenotypic data provides a framework for identifying functionally relevant loci and advancing mechanistic insights into cardiometabolic and pregnancy-related disorders.
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