ArticleGenome biology2024
Optimizing and benchmarking polygenic risk scores with GWAS summary statistics.
Article in Genome biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
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Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Development and validation of a multiancestry and multitrait polygenic risk score for lung cancer.Nature communications · 2026Pooled it
- Evidence standards for multi-ancestry polygenic prediction.Genome biology · 2026Review
- MIXPRS enables multi-population and multi-method polygenic risk scores using summary statistics.Nature genetics · 2026Article
- Preimplantation genetic testing for polygenic diseases: A novel paradigm in embryo selection.Biochemistry and biophysics reports · 2026Review
- Moderating effects of educational inequality on education polygenic scores, attained education and dementia-risk relationships.SSM - population health · 2026Article
- Integrating common and rare variants improves polygenic risk prediction across diverse populations.Nature communications · 2026Article
- Evaluating genetic-based disease prediction approaches through simulation.Human genetics · 2026Article
- Identifying a Common Autoimmune Gene Core as a Tool for Verifying Biological Significance and Applicability of Polygenic Risk Scores.International journal of molecular sciences · 2026Article
- Integrating Imaging-Derived Clinical Endotypes with Plasma Proteomics and External Polygenic Risk Scores Enhances Coronary Microvascular Disease Risk Prediction.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2026Article
- Bioinformatics and artificial intelligence in genomic data analysis: current advances and future directions.Molecular genetics and genomics : MGG · 2025Review
- Polygenic prediction of treatment efficacy with causal transfer learning.medRxiv : the preprint server for health sciences · 2025Article
- Integrating Imaging-Derived Clinical Endotypes with Plasma Proteomics and External Polygenic Risk Scores Enhances Coronary Microvascular Disease Risk Prediction.medRxiv : the preprint server for health sciences · 2025Article
- Almost Free Enhancement of Multi-Population PRS: From Data-Fission to Pseudo-GWAS Subsampling.bioRxiv : the preprint server for biology · 2025Article
- Enhancing the discriminatory power of polygenic scores for ADHD and autism in clinical and non-clinical samples.Journal of neurodevelopmental disorders · 2025Article
- PennPRS: a centralized cloud computing platform for efficient polygenic risk score training in precision medicine.medRxiv : the preprint server for health sciences · 2025Article
- Ancestry gaps in cardiovascular GWAS: a multi-database review of African representation in genomic studies.Frontiers in genetics · 2025Review
- One score to rule them all: regularized ensemble polygenic risk prediction with GWAS summary statistics.bioRxiv : the preprint server for biology · 2024Article
- Task-Agnostic Machine-Learning-Assisted Inference.Advances in neural information processing systems · 2024Article
- Optimizing and benchmarking polygenic risk scores with GWAS summary statistics.Genome biology · 2024Article
- Leveraging genetic correlations and multiple populations to improve genetic risk prediction for non-European populations.Research square · 2023Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
backgroundPolygenic risk score (PRS) is a major research topic in human genetics. However, a significant gap exists between PRS methodology and applications in practice due to often unavailable individual-level data for various PRS tasks including model fine-tuning, benchmarking, and ensemble learning.
resultsWe introduce an innovative statistical framework to optimize and benchmark PRS models using summary statistics of genome-wide association studies. This framework builds upon our previous work and can fine-tune virtually all existing PRS models while accounting for linkage disequilibrium. In addition, we provide an ensemble learning strategy named PUMAS-ensemble to combine multiple PRS models into an ensemble score without requiring external data for model fitting. Through extensive simulations and analysis of many complex traits in the UK Biobank, we demonstrate that this approach closely approximates gold-standard analytical strategies based on external validation, and substantially outperforms state-of-the-art PRS methods.
conclusionsOur method is a powerful and general modeling technique that can continue to combine the best-performing PRS methods out there through ensemble learning and could become an integral component for all future PRS applications.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.