Explaining the unexplained admixture mapping signals via rare variants: the HCHS/SOL

In admixed populations, formed by a mixing of two or more previously isolated populations, genomic segments can be traced to their ancestral populations ('ancestries'). Admixture mapping (AM) associates local ancestry with outcomes in admixed populations, detecting signals when causal variants differ in frequency or effect across ancestral populations. Prior work showed that adjusting for nearby GWAS-identified common variants does not fully explain some AM signals. Here, we assessed two approaches to explain the previously unexplained AM signal: (1) including sets of rare variants; (2) increasing the genomic region considered when searching for common variants. We studied these hypotheses comprehensively using a whole-genome sequencing dataset coupled with metabolomics from the Hispanic Community Health Study/Study of Latinos. From 16 genomic regions of interest, we identified 35 rare-variant sets associated with metabolite levels, of which 4 associations replicated. The locations of identified rare variant sets are either within the same gene or in proximity to adjusted common variants. Overall, our study provides new insight into the genetic architecture underlying AM signals via evaluating the contributions of common and rare variant sets. By integrating rare-variant analysis within the AM framework, our work highlights the potential interplay between variant types and establishes a novel strategy to guide future fine-mapping and causal variant identification in admixed populations. Yet the detected rare variants appear to explain only a small fraction of the AM signal, while inclusion of common variants from a larger genomic region appears to explain most of the AM signals.