Estimation of inbreeding and substructure levels in African-derived Brazilian quilombo populations

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

Essential Hypertension (EH) is a major global health concern, causing about 9.4 million deaths annually. Its prevalence varies across different regions, affecting 17% of the population in the Americas, 19.2% in the Western Pacific, 23.2% in Europe, 25.1% in Southeast Asia, 26.3% in the Eastern Mediterranean, and 27.2% in Africa. EH is a multifactorial disease influenced by both genetic and environmental factors. While genetic factors contribute 30-60% to blood pressure variation, the genetic complexity of EH remains largely unexplained due to limited knowledge of candidate genes and population-specific differences. Various methods, including candidate gene studies, genome-wide linkage analysis (GWLA), and genome-wide association studies (GWAS), have been employed to identify genetic factors, yet much of the heritability of EH is still unknown. This study aimed to investigate the genetic basis of EH by mapping regions of interest (ROIs) and identifying candidate genes and variants influencing EH in African-derived individuals from partially isolated populations of quilombo remnants in Vale do Ribeira, São Paulo, Brazil. Samples from 431 individuals (167 affected, 261 unaffected, 3 with unknown phenotype) from eight quilombo remnant populations were genotyped using a 650k SNP array. The global ancestry proportions were estimated at 47% African, 36% European, and 16% Native American. Genealogical information from 673 individuals was used to construct six pedigrees comprising 1104 individuals. The mapping strategy consisted of a multi-level computational approach. We constructed pedigrees based on interviews and kinship coefficient, pruned the dataset to obtain three non-overlapping markers subpanels, phased the haplotype and performed local ancestry to account for admixture. We performed GWLA and dense linkage analyses using markers subpanels and performed fine-mapping using family-based association studies (FBAS) based on population and pedigree imputed data, investigating EH-related genes and variants. The linkage analysis identified 22 ROIs with LOD scores 1.45-3.03, containing markers co-segregating with the phenotype. These ROIs encompassed 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 highlighted with strong evidence of association with hypertension. These genes, harboring 29 SNPs, were implicated in regulating blood pressure, sodium and potassium levels, and the aldosterone pathway. This study revealed, 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 that shed light on the genetic basis of essential hypertension, with significant potential to explain the genetic etiology in quilombo remnant populations.

Ancestry, diversity, and genetics of health-related traits in African-derived communities (quilombos) from Brazil

Brazilian quilombos are communities formed by enslaved Africans and their descendants all over the country during slavery and shortly after its abolition. Quilombos harbor a great fraction of the largely unknown genetic diversity of the African diaspora in Brazil. Thus, genetic studies in quilombos have the potential to provide important insights not only into the African roots of the Brazilian population but also into the genetic bases of complex traits and human adaptation to diverse environments. This review summarizes the main results of genetic studies performed on quilombos so far. Here, we analyzed the patterns of African, Amerindian, European, and subcontinental ancestry (within Africa) of quilombos from the five different geographic regions of Brazil. In addition, uniparental markers (from the mtDNA and the Y chromosome) studies are analyzed together to reveal demographic processes and sex-biased admixture that occurred during the formation of these unique populations. Lastly, the prevalence of known malaria-adaptive African mutations and other African-specific variants discovered in quilombos, as well as the genetic bases of health-related traits, are discussed here, together with their implication for the health of populations of African descent.

Inbreeding estimates in human populations: Applying new approaches to an admixed Brazilian isolate

The analysis of genomic data (~400,000 autosomal SNPs) enabled the reliable estimation of inbreeding levels in a sample of 541 individuals sampled from a highly admixed Brazilian population isolate (an African-derived quilombo in the State of São Paulo). To achieve this, different methods were applied to the joint information of two sets of markers (one complete and another excluding loci in patent linkage disequilibrium). This strategy allowed the detection and exclusion of markers that biased the estimation of the average population inbreeding coefficient (Wright's fixation index FIS), which value was eventually estimated as around 1% using any of the methods we applied. Quilombo demographic inferences were made by analyzing the structure of runs of homozygosity (ROH), which were adapted to cope with a highly admixed population with a complex foundation history. Our results suggest that the amount of ROH <2Mb of admixed populations should be somehow proportional to the genetic contribution from each parental population.

HLA imputation in an admixed population: An assessment of the 1000 Genomes data as a training set

Methods to impute HLA alleles based on dense single nucleotide polymorphism (SNP) data provide a valuable resource to association studies and evolutionary investigation of the MHC region. The availability of appropriate training sets is critical to the accuracy of HLA imputation, and the inclusion of samples with various ancestries is an important pre-requisite in studies of admixed populations. We assess the accuracy of HLA imputation using 1000 Genomes Project data as a training set, applying it to a highly admixed Brazilian population, the Quilombos from the state of São Paulo. To assess accuracy, we compared imputed and experimentally determined genotypes for 146 samples at 4 HLA classical loci. We found imputation accuracies of 82.9%, 81.8%, 94.8% and 86.6% for HLA-A, -B, -C and -DRB1 respectively (two-field resolution). Accuracies were improved when we included a subset of Quilombo individuals in the training set. We conclude that the 1000 Genomes data is a valuable resource for construction of training sets due to the diversity of ancestries and the potential for a large overlap of SNPs with the target population. We also show that tailoring training sets to features of the target population substantially enhances imputation accuracy.