Abstract 4337642: Genomic Insights into Cardiometabolic Risk and Admixture Patterns in Black Hawaiians

Black Hawaiian (BH) individuals, or Popolo, are a Native Hawaiian and Pacific Islander (NHPI) group characterized by significant African ancestry and a unique sociocultural history. Despite their distinct identity, BH individuals have been largely overlooked in genetic and biomedical research, with no prior studies in cardiovascular disease (CVD) that focus on treating BH as a unique population, rather than aggregating them with data from other NHPI subgroups (e.g., NHPI individuals of mixed European or Asian ancestry). Here, we present the first population genetic analysis of BH individuals, integrating ancestry deconvolution, demographic inference, and natural selection scans to elucidate their genetic profile and its potential cardiometabolic implications. We analyzed 287 BH whole-genome sequences from the NIH All of Us Research Program database and applied an ancestry deconvolution pipeline that included global ancestry inference (Neural ADMIXTURE) and local ancestry mapping (LAMP-LD). We reconstructed BH demographic history using the sequential Markovian coalescent model (smc++) and inferred a population-specific recombination map with recurrent learning for estimating recombination using neural networks (ReLERNN). To detect recent adaptation, we scanned BH genomes for signals of positive selection using integrated haplotype scores (iHS) and raised accuracy in sweep detection (RAiSD). Our results indicate that BH individuals form a genetically distinct cluster, separate from other admixed NHPI groups. However, they exhibit high internal genetic heterogeneity and lack clear population substructure, reflecting complex admixture sources and assimilation histories. We identified several candidate loci with notable allele frequency differentiation in BH genomes, featuring variants in genes associated with metabolic and cardiovascular traits such as lipid metabolism and inflammatory signaling pathways, some of which overlap with GWAS loci for CVD risk. This study provides the first genomic insights into BH groups and underscores the need for disaggregated genetic data in highly admixed populations such as those of Hawai'i to better understand and address CVD risk. Our findings establish a foundation for future genetic association studies involving BH individuals and have important implications for cardiometabolic disease mapping and precision medicine.