Genomic Exploration of Essential Hypertension in African-Brazilian Quilombo Populations: A Comprehensive Approach with Pedigree Analysis and Family-Based Association Studies

Author:

Borges Vinícius MagalhãesORCID,Horimoto Andrea R.V.R.ORCID,Wijsman Ellen Marie,Kimura Lilian,Nunes Kelly,Nato Alejandro Q.ORCID,Mingroni-Netto Regina Célia

Abstract

ABSTRACTBackground: Essential Hypertension (EH) is a global health issue, responsible for approximately 9.4 million deaths annually. Its prevalence varies by region, with genetic factors contributing 30-60% to blood pressure variation. Despite extensive research, the genetic complexity of EH remains largely unexplained. This study aimed to investigate the genetic basis of EH in African-derived individuals from partially isolated quilombo remnant populations in Vale do Ribeira (SP-Brazil). Methods: Samples from 431 individuals (167 affected, 261 unaffected, 3 with unknown phenotype) were genotyped using a 650k SNP array. Global ancestry proportions were estimated at 47% African, 36% European, and 16% Native American. Additional data from 673 individuals were used to construct six pedigrees. Pedigrees were pruned, and three non-overlapping marker subpanels were created. We phased haplotypes and performed local ancestry analysis to account for admixture. We then conducted genome-wide linkage analysis (GWLA) and performed fine-mapping through family-based association studies (FBAS) on imputed data and through EH-related genes investigation. Results: Linkage analysis identified 22 ROIs with LOD scores ranging from 1.45 to 3.03, encompassing 2363 genes. Fine-mapping identified 60 EH-related candidate genes and 118 suggestive or significant variants (FBAS). Among these, 14 genes, including PHGDH, S100A10, MFN2, and RYR2, were strongly associated with hypertension and harbors 29 SNPs. Conclusions: Through a complementary approach — combining admixture-adjusted genome-wide linkage analysis based on Markov chain Monte Carlo (MCMC) methods, association studies on imputed data, and in silico investigations — genetic regions, variants, and candidate genes were identified, offering insights into the genetic etiology of EH in quilombo remnant populations.

Publisher

Cold Spring Harbor Laboratory

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