ArticleNature genetics2025
Improved multiancestry fine-mapping identifies cis-regulatory variants underlying molecular traits and disease risk.
Article in Nature genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Translating genome-wide association studies at multiple scales: Drug target prioritization, cellular architectures, and organ imaging.Cell genomics · 2026Review
- Multi-ancestry modeling improves fine-mapping resolution, protein prediction, and discovery for proteome-wide association studies.medRxiv : the preprint server for health sciences · 2026Article
- Article
- Multi-ancestry transcriptome-wide association study reveals shared and population-specific genetic effects in Alzheimer disease.American journal of human genetics · 2026Article
- Genetic Regulation of Monocyte MicroRNAs and Their Implication in Musculoskeletal Diseases: A Cross-Ancestry Expression Quantitative Trait Loci and Imputation Study.International journal of molecular sciences · 2026Article
- Article
- Integrating multi-omics and multi-context QTL data with GWAS reveals the genetic architecture of complex traits and improves the discovery of risk genes.medRxiv : the preprint server for health sciences · 2026Article
- The Utility of Genome-Wide Association Studies in Inherited Arrhythmias and Cardiomyopathies.Genes · 2025Review
- Towards improved fine-mapping of candidate causal variants.Nature reviews. Genetics · 2025Review
- Multi-ancestry Transcriptome-Wide Association Study Reveals Shared and Population-Specific Genetic Effects in Alzheimer's Disease.bioRxiv : the preprint server for biology · 2025Article
- A machine-learning framework to characterize functional disease architectures and prioritize disease variants.medRxiv : the preprint server for health sciences · 2025Article
- Fine-mapping in admixed populations using CARMA-X, with applications to Latin American studies.American journal of human genetics · 2025Article
- An evolving understanding of multiple causal variants underlying genetic association signals.American journal of human genetics · 2025Review
- The breadth and impact of the Global Lipids Genetics Consortium.Current opinion in lipidology · 2025Review
- Efficient count-based models improve power and robustness for large-scale single-cell eQTL mapping.medRxiv : the preprint server for health sciences · 2025Article
- Cross-trait multivariate GWAS confirms health implications of pubertal timing.Nature communications · 2025Article
- Powerful mapping ofmedRxiv : the preprint server for health sciences · 2024Article
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11 authors.
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Abstract
Multiancestry statistical fine-mapping of cis-molecular quantitative trait loci (cis-molQTL) aims to improve the precision of distinguishing causal cis-molQTLs from tagging variants. Here we present the sum of shared single effects (SuShiE) model, which leverages linkage disequilibrium heterogeneity to improve fine-mapping precision, infer cross-ancestry effect size correlations and estimate ancestry-specific expression prediction weights. Through extensive simulations, we find that SuShiE consistently outperforms existing methods. We apply SuShiE to 36,907 molecular phenotypes including mRNA expression and protein levels from individuals of diverse ancestries in the TOPMed-MESA and GENOA studies. SuShiE fine-maps cis-molQTLs for 18.2% more genes compared with existing methods while prioritizing fewer variants and exhibiting greater functional enrichment. While SuShiE infers highly consistent cis-molQTL architectures across ancestries, it finds evidence of heterogeneity at genes with predicted loss-of-function intolerance. Lastly, using SuShiE-derived cis-molQTL effect sizes, we perform transcriptome- and proteome-wide association studies on six white blood cell-related traits in the All of Us biobank and identify 25.4% more genes compared with existing methods. Overall, SuShiE provides new insights into the cis-genetic architecture of molecular traits.
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