ArticleAmerican journal of human genetics2024
Evaluation of polygenic scoring methods in five biobanks shows larger variation between biobanks than methods and finds benefits of ensemble learning.
Article in American journal of human genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 2 of them syntheses that pooled it.
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Who cites it
29 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Meta-analysis across six global biobanks identifies recessive coding associations with complex traits and diseases.American journal of human genetics · 2026Pooled it
- STROBE-causal machine learning for the human microbiome: systematic review on methodological innovations and validation frameworks.Frontiers in microbiology · 2026Pooled it
- All of Us diversity and scale yield context-dependent improvements in polygenic prediction.Nature genetics · 2026Article
- SPLENDID incorporates continuous genetic ancestry in biobank-scale data to improve polygenic risk prediction across diverse populations.Nature methods · 2026Article
- A pre-train and fine-tune framework for adaptive boosting of pre-trained polygenic risk scores.Nature communications · 2026Article
- Article
- Evidence standards for multi-ancestry polygenic prediction.Genome biology · 2026Review
- An introduction to polygenic scores - methodological basics and recent advances.Medizinische Genetik : Mitteilungsblatt des Berufsverbandes Medizinische Genetik e.V · 2026Article
- Additive effects of common and rare genetic variants on inflammatory bowel disease risk in a cohort with immunodeficiency.The Journal of allergy and clinical immunology · 2026Article
- Longitudinal prediction of BMI using explainable AI: integrating polygenic scores, maternal, early-life and familial factors.International journal of obesity (2005) · 2026Observational
- Performance of different polygenic risk scores for breast cancer risk prediction: in-depth evaluations across large UK and Australian cohorts.European journal of human genetics : EJHG · 2026Article
- Comprehensive benchmarking single and multi ancestry polygenic score methods with the PGS-hub platform.Nature communications · 2026Article
- Genomic risk prediction of type 2 diabetes in people living with and without HIV.Scientific reports · 2026Article
- Polygenic risk score translation across diverse populations.Frontiers in cardiovascular medicine · 2026Review
- Whole-Genome Sequencing in Galicia Reveals Male-Biased Pre-Islamic North African Ancestry, Subtle Population Structure, and Microgeographic Patterns of Disease Risk.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2025Article
- From Polymorphisms to Phenotypes:Genes · 2025Article
- Transferability of polygenic risk scores for metabolic and cardiovascular traits in an underrepresented population.NPJ genomic medicine · 2025Article
- Preclinical Diagnosis of Type 1 Diabetes: Reality or Utopia.Biomedicines · 2025Review
- PGSFusion streamlines polygenic score construction and epidemiological applications in biobank-scale cohorts.Genome medicine · 2025Article
- Evaluating metabolome-wide causal effects on risk for psychiatric and neurodegenerative disorders.BMC medicine · 2025Article
Corrections and comments
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Authors and funding
24 authors.
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Abstract
Methods of estimating polygenic scores (PGSs) from genome-wide association studies are increasingly utilized. However, independent method evaluation is lacking, and method comparisons are often limited. Here, we evaluate polygenic scores derived via seven methods in five biobank studies (totaling about 1.2 million participants) across 16 diseases and quantitative traits, building on a reference-standardized framework. We conducted meta-analyses to quantify the effects of method choice, hyperparameter tuning, method ensembling, and the target biobank on PGS performance. We found that no single method consistently outperformed all others. PGS effect sizes were more variable between biobanks than between methods within biobanks when methods were well tuned. Differences between methods were largest for the two investigated autoimmune diseases, seropositive rheumatoid arthritis and type 1 diabetes. For most methods, cross-validation was more reliable for tuning hyperparameters than automatic tuning (without the use of target data). For a given target phenotype, elastic net models combining PGS across methods (ensemble PGS) tuned in the UK Biobank provided consistent, high, and cross-biobank transferable performance, increasing PGS effect sizes (β coefficients) by a median of 5.0% relative to LDpred2 and MegaPRS (the two best-performing single methods when tuned with cross-validation). Our interactively browsable online-results and open-source workflow prspipe provide a rich resource and reference for the analysis of polygenic scoring methods across biobanks.
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