ArticleScientific reports2025
Optimization of multi-ancestry polygenic risk score disease prediction models.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Weighing the evidence on costs and benefits of polygenic risk-based approaches in clinical practice: A systematic review of economic evaluations.American journal of human genetics · 2025Pooled it
- Clinical utility of polygenic risk scores in cardiovascular disorders.Medizinische Genetik : Mitteilungsblatt des Berufsverbandes Medizinische Genetik e.V · 2026Article
- Neuroimaging Summary Scores Predict Trajectories of Psychotic-Like Experiences in Youth.medRxiv : the preprint server for health sciences · 2026Article
- Multi-trait polygenic risk scores improve genomic prediction of atrial fibrillation across diverse ancestries.Nature communications · 2026Article
- Why Should a Genome Be Protected? Ethical, Legal, and Security Challenges in the Protection of Genomic Data.Biology · 2026Review
- An evaluation of age-varying genetic effects underlying body-mass index and blood pressure in the UK Biobank.PLoS genetics · 2026Article
- The Utility of Genome-Wide Association Studies in Inherited Arrhythmias and Cardiomyopathies.Genes · 2025Review
- Multi-trait polygenic risk scores improve genomic prediction of atrial fibrillation across diverse ancestries.Research square · 2025Article
- Genomic and Precision Medicine Approaches in Atherosclerotic Cardiovascular Disease: From Risk Prediction to Therapy-A Review.Biomedicines · 2025Review
- A review of methods and software for polygenic risk score analysis.PeerJ. Computer science · 2025Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Polygenic risk scores (PRS) have ushered in a new era in genetic epidemiology, offering insights into individual predispositions to a wide range of diseases. However, despite recent marked enhancements in predictive power, PRS-based models still need to overcome several hurdles before they can be broadly applied in the clinic. Chiefly, they need to achieve sufficient accuracy, easy interpretability and portability across diverse populations. Leveraging trans-ancestry genome-wide association study (GWAS) meta-analysis, we generated novel, diverse summary statistics for 30 medically-related traits and benchmarked the performance of six existing PRS algorithms using UK Biobank. We built an ensemble model using logistic regression to combine outputs of top-performing algorithms and validated it on the diverse eMERGE and PAGE MEC cohorts. It surpassed current state-of-the-art PRS models, with minimal performance drops in external cohorts, indicating good calibration. To enhance predictive accuracy for clinical application, we incorporated easily-accessible clinical characteristics such as age, gender, ancestry and risk factors, creating disease prediction models intended as prospective diagnostic tests, with easily interpretable positive or negative outcomes. After adding clinical characteristics, 12 out of 30 models surpassed 80% AUC. Further, 25 traits exceeded the diagnostic odds ratio (DOR) of five, and 19 traits exceeded DOR of 10 for all ancestry groups, indicating high predictive value. Our PRS model for coronary artery disease identified 55-80 times more true coronary events than rare pathogenic variant models, reinforcing its clinical potential. The polygenic component modulated the effect of high-risk rare variants, stressing the need to consider all genetic components in clinical settings. These findings show that newly developed PRS-based disease prediction models have sufficient accuracy and portability to warrant consideration of being used in the clinic.
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