ArticleNature genetics2026
MultiSuSiE improves multi-ancestry fine-mapping in All of Us whole-genome sequencing data.
Article in Nature genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Article
- Decoding the shared genetic liability of lower respiratory tract infections via genomic structural equation modeling.BMC pulmonary medicine · 2026Article
- Multi-ancestry modeling improves fine-mapping resolution, protein prediction, and discovery for proteome-wide association studies.medRxiv : the preprint server for health sciences · 2026Article
- Multi-ancestry colocalization approaches.PLoS genetics · 2026Article
- Disease-associated genetic variants can cause missense effects in tissue-specific protein isoforms.Nature communications · 2026Article
- A genomic structural equation modelling study elucidates shared genetic architecture of polygenic traits associated with post-intensive care syndrome.Scientific reports · 2026Article
- MultiSuSiE improves multi-ancestry fine-mapping in All of Us whole-genome sequencing data.Nature genetics · 2026Article
- Towards improved fine-mapping of candidate causal variants.Nature reviews. Genetics · 2025Review
- Characterization of shared and ancestry-specific signals driving complex traits using multi-ancestry fine-mapping.medRxiv : the preprint server for health sciences · 2025Article
- A machine-learning framework to characterize functional disease architectures and prioritize disease variants.medRxiv : the preprint server for health sciences · 2025Article
- Expanding scope of genetic studies in the era of biobanks.Human molecular genetics · 2025Article
- Fine-mapping in admixed populations using CARMA-X, with applications to Latin American studies.American journal of human genetics · 2025Article
- Powerful mapping ofmedRxiv : the preprint server for health sciences · 2024Article
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9 authors.
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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.
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