ArticleNature communications2025
JointPRS: A data-adaptive framework for multi-population genetic risk prediction incorporating genetic correlation.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Identifying shared polygenic risk across cancers.PLoS genetics · 2026Article
- Evidence standards for multi-ancestry polygenic prediction.Genome biology · 2026Review
- Cell-type-specific polygenic risk scores reveal adipocyte-related interactions with lipids in coronary artery disease.medRxiv : the preprint server for health sciences · 2026Article
- MIXPRS enables multi-population and multi-method polygenic risk scores using summary statistics.Nature genetics · 2026Article
- Development and validation of a trans-ancestry polygenic risk score for type 1 diabetes.Diabetologia · 2026Article
- Integrating common and rare variants improves polygenic risk prediction across diverse populations.Nature communications · 2026Article
- A deep ensemble encoder network method for improved polygenic risk score prediction.BioData mining · 2026Article
- Joint modeling of effect sizes for two correlated traits: Characterizing trait properties to enhance polygenic risk prediction.PLoS genetics · 2026Article
- Improving polygenic risk prediction performance by integrating electronic health records through phenotype embedding.American journal of human genetics · 2025Article
- An Integrative Polygenic and Epigenetic Risk Score for Overweight-related Hypertension in Chinese Population.Genomics, proteomics & bioinformatics · 2025Article
- PTL-PRS: an R package for transfer learning of polygenic risk scores with pseudovalidation.Bioinformatics (Oxford, England) · 2025Article
- Differential results of genetic risk scoring for multiple sclerosis in European and African American populations.Multiple sclerosis (Houndmills, Basingstoke, England) · 2025Article
- Leveraging local ancestry and cross-ancestry genetic architecture to improve genetic prediction of complex traits in admixed populations.American journal of human genetics · 2025Article
- Almost Free Enhancement of Multi-Population PRS: From Data-Fission to Pseudo-GWAS Subsampling.bioRxiv : the preprint server for biology · 2025Article
- JointPRS: A data-adaptive framework for multi-population genetic risk prediction incorporating genetic correlation.Nature communications · 2025Article
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7 authors.
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Abstract
Genetic risk prediction for non-European populations is hindered by limited Genome-Wide Association Study (GWAS) sample sizes and small tuning datasets. We propose JointPRS, a data-adaptive framework that leverages genetic correlations across multiple populations using GWAS summary statistics. It achieves accurate predictions without individual-level tuning data and remains effective in the presence of a small tuning set thanks to its data-adaptive approach. Through extensive simulations and real data applications to 22 quantitative and four binary traits in five continental populations evaluated using the UK Biobank (UKBB) and All of Us (AoU), JointPRS consistently outperforms six state-of-the-art methods across three data scenarios: no tuning data, same-cohort tuning and testing, and cross-cohort tuning and testing. Notably, in the Admixed American population, JointPRS improves lipid trait prediction in AoU by 6.46%-172.00% compared to the other existing methods.
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