ArticleGenetic epidemiology2015
Explicit Modeling of Ancestry Improves Polygenic Risk Scores and BLUP Prediction.
Article in Genetic epidemiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed, 57 citations in OpenAlex.
- Rare variant effect estimation and polygenic risk prediction.Nature genetics · 2026Article
- Cross-ancestry polygenic risk scores enhance Alzheimer's disease risk prediction in multiethnic cohorts.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Explicitly modeling genetic ancestry to improve polygenic prediction accuracy for height in a large, admixed cohort of US Latinos: Findings from HCHS/SOL.HGG advances · 2026Article
- Sharing approaches in predictive genomics across animals, plants and humans.Nature genetics · 2026Review
- Using genomic context informed genotype data and within-model ancestry adjustment to classify type 2 diabetes.Communications medicine · 2025Article
- Cross-Ancestry Polygenic Risk Scores Enhance Alzheimer's Disease Risk Prediction in Multiethnic Cohorts.medRxiv : the preprint server for health sciences · 2025Article
- Population structure limits the use of genomic data for predicting phenotypes and managing genetic resources in forest trees.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Article
- The GenoPred pipeline: a comprehensive and scalable pipeline for polygenic scoring.Bioinformatics (Oxford, England) · 2024Article
- Ancestry-aligned polygenic scores combined with conventional risk factors improve prediction of cardiometabolic outcomes in African populations.Genome medicine · 2024Article
- Machine learning models for predicting blood pressure phenotypes by combining multiple polygenic risk scores.Scientific reports · 2024Article
- Genome-wide polygenic risk score for major osteoporotic fractures in postmenopausal women using associated single nucleotide polymorphisms.Journal of translational medicine · 2023Article
- Polygenic risk score improves the accuracy of a clinical risk score for coronary artery disease.BMC medicine · 2022Observational
- Polygenic transcriptome risk scores for COPD and lung function improve cross-ethnic portability of prediction in the NHLBI TOPMed program.American journal of human genetics · 2022Article
- Canalization of the Polygenic Risk for Common Diseases and Traits in the UK Biobank Cohort.Molecular biology and evolution · 2022Article
- Polygenic Risk Score in African populations: progress and challenges.F1000Research · 2022Review
- Of Screening, Stratification, and Scores.Journal of personalized medicine · 2021Review
- Highly elevated polygenic risk scores are better predictors of myocardial infarction risk early in life than later.Genome medicine · 2021Article
- Localizing Components of Shared Transethnic Genetic Architecture of Complex Traits from GWAS Summary Data.American journal of human genetics · 2020Article
- Comparative genetic architectures of schizophrenia in East Asian and European populations.Nature genetics · 2019Article
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
Abstract
Polygenic prediction using genome-wide SNPs can provide high prediction accuracy for complex traits. Here, we investigate the question of how to account for genetic ancestry when conducting polygenic prediction. We show that the accuracy of polygenic prediction in structured populations may be partly due to genetic ancestry. However, we hypothesized that explicitly modeling ancestry could improve polygenic prediction accuracy. We analyzed three GWAS of hair color (HC), tanning ability (TA), and basal cell carcinoma (BCC) in European Americans (sample size from 7,440 to 9,822) and considered two widely used polygenic prediction approaches: polygenic risk scores (PRSs) and best linear unbiased prediction (BLUP). We compared polygenic prediction without correction for ancestry to polygenic prediction with ancestry as a separate component in the model. In 10-fold cross-validation using the PRS approach, the R(2) for HC increased by 66% (0.0456-0.0755; P < 10(-16)), the R(2) for TA increased by 123% (0.0154 to 0.0344; P < 10(-16)), and the liability-scale R(2) for BCC increased by 68% (0.0138-0.0232; P < 10(-16)) when explicitly modeling ancestry, which prevents ancestry effects from entering into each SNP effect and being overweighted. Surprisingly, explicitly modeling ancestry produces a similar improvement when using the BLUP approach, which fits all SNPs simultaneously in a single variance component and causes ancestry to be underweighted. We validate our findings via simulations, which show that the differences in prediction accuracy will increase in magnitude as sample sizes increase. In summary, our results show that explicitly modeling ancestry can be important in both PRS and BLUP prediction.
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