| Title: | MultiSuSiE improves multi-ancestry fine-mapping in All of Us whole-genome sequencing data |
| Journal: | Nature Genetics |
| Published: | 5 Jan 2026 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/41491094/ |
| DOI: | https://doi.org/10.1038/s41588-025-02450-5 |
Publication 16878
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Abstract
Leveraging multi-ancestry data can improve fine-mapping power. We propose MultiSuSiE, an extension of Sum of Single Effects (SuSiE), to multiple ancestries that allows causal effect sizes to vary across ancestries. We evaluated MultiSuSiE using whole-genome sequencing data from 47,000 African-ancestry, 36,000 Latino-ancestry and 116,000 European-ancestry individuals from All of Us. In simulations, MultiSuSiE applied to Afr36k + Lat36k + Eur36k was well-calibrated and attained higher power than SuSiE applied to Eur109k; compared to recent multi-ancestry methods (SuSiEx and MESuSiE), MultiSuSiE attained higher power and lower computational cost. In analyses of 14 quantitative traits, MultiSuSiE applied to Afr47k + Lat36k + Eur116k identified 348 fine-mapped variants with posterior inclusion probability (PIP) > 0.9, and MultiSuSiE applied to Afr36k + Lat36k + Eur36k identified 59% more PIP > 0.9 variants than SuSiE applied to Eur109k; MultiSuSiE identified 29% more PIP > 0.9 variants than SuSiEx, and MESuSiE was not included due to its high computational cost. We validated these findings through functional enrichment of fine-mapped variants and highlighted examples implicating biologically plausible fine-mapped variants.</p>
9 Authors
- Jordan Rossen
- Huwenbo Shi
- Benjamin J. Strober
- Martin Jinye Zhang
- Masahiro Kanai
- Zachary R. McCaw
- Liming Liang
- Omer Weissbrod
- Alkes L. Price
1 Application
| Application ID | Title |
|---|---|
| 16549 | Components of heritability in a UK Biobank cohort |
Enabling scientific discoveries that improve human health