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

Area of Science:

• Genetics
• Population Genetics
• Genomic Medicine

Background:

• Admixed populations result from the mixing of previously isolated ancestral populations.
• Admixture mapping (AM) links local ancestry to health outcomes, identifying genetic signals when causal variants differ in frequency or effect between ancestries.
• Previous studies indicated that common variants identified by Genome-Wide Association Studies (GWAS) do not fully account for all AM signals.

Purpose of the Study:

• To investigate two hypotheses for unexplained admixture mapping signals: the inclusion of rare variants and the expansion of the genomic region considered for common variants.
• To comprehensively assess these hypotheses using whole-genome sequencing and metabolomics data.

Main Methods:

• Utilized whole-genome sequencing data from the Hispanic Community Health Study/Study of Latinos.
• Employed metabolomics data alongside genetic data to analyze associations.
• Evaluated the contribution of rare variants and common variants within expanded genomic regions to admixture mapping signals.

Main Results:

• Identified multiple sets of rare variants significantly associated with metabolite levels.
• Observed that these rare variants explained only a minor portion of the admixture mapping signals.
• Found that including common variants from larger genomic regions explained the majority of the previously unexplained admixture mapping signals.

Conclusions:

• Rare variants contribute to metabolite level associations in admixed populations but explain a limited part of admixture mapping signals.
• Expanding the genomic search region for common variants is a more effective strategy for explaining substantial portions of admixture mapping signals.
• These findings refine our understanding of genetic architecture in admixed populations and improve admixture mapping approaches.