ArticleNature genetics2024
Calibrated prediction intervals for polygenic scores across diverse contexts.
Article in Nature genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.
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Who cites it
52 citing papers in PubMed.
- Genome-wide detection of genotype-environment interactions at biobank scale with fastGxE.Nature genetics · 2026Article
- All of Us diversity and scale yield context-dependent improvements in polygenic prediction.Nature genetics · 2026Article
- Genome-wide analysis of social behaviour across social domains, reporters and developmental stages: a meta-regression approach.Nature human behaviour · 2026Article
- GeneSIS: enhancing transferability of polygenic scores with variant-level gene-by-sex interaction effects.bioRxiv : the preprint server for biology · 2026Article
- Development and application of type 1 diabetes polygenic scores across diverse populations.Diabetologia · 2026Review
- Pervasive interactions between exposures and polygenic risk can inform more effective clinical and behavioral interventions.Nature genetics · 2026Article
- Evidence standards for multi-ancestry polygenic prediction.Genome biology · 2026Review
- Within-sibling attenuation of polygenic risk score accuracy: investigating the effects of principal component analysis, LD score regression, and mixed model association in the UK Biobank.Human genetics · 2026Article
- Improving Polygenic Risk Prediction for Atherosclerotic Cardiovascular Disease in East Asian Populations.JACC. Asia · 2026Review
- The Multiethnic Cohort: A Resource for the Study of Genetic and Nongenetic Cancer Risk across Populations.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2026Article
- Breast cancer polygenic risk score performance varies by socioeconomic status.medRxiv : the preprint server for health sciences · 2026Article
- Contextualizing the Utility of Polygenic Risk Scores using Absolute Risk Models in Diverse Ancestry Populations.medRxiv : the preprint server for health sciences · 2026Article
- Article
- Calibrated Prediction Intervals for Polygenic Scores: Updated Comparisons, Contextual Calibration, and Data Normalization.medRxiv : the preprint server for health sciences · 2026Article
- Characterizing the Uncertainty, Misclassification and Inconsistency of Polygenic Prediction.medRxiv : the preprint server for health sciences · 2026Article
- CalPred yields calibrated intervals for polygenic risk prediction.medRxiv : the preprint server for health sciences · 2026Article
- Phenome-derived polygenic scores and social determinants jointly shape context-dependent disease risk.medRxiv : the preprint server for health sciences · 2026Article
- Incorporating polygenic risk scores and social determinants of health across populations: Considerations and best practices in research.American journal of human genetics · 2026Review
- Inclusion bias affects common variant discovery and replication in a health-system linked biobank.American journal of human genetics · 2026Article
- Clinical use of polygenic risk scores: current status, barriers and future directions.Nature reviews. Genetics · 2026Review
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8 authors.
Funding
Abstract
Polygenic scores (PGS) have emerged as the tool of choice for genomic prediction in a wide range of fields. We show that PGS performance varies broadly across contexts and biobanks. Contexts such as age, sex and income can impact PGS accuracy with similar magnitudes as genetic ancestry. Here we introduce an approach (CalPred) that models all contexts jointly to produce prediction intervals that vary across contexts to achieve calibration (include the trait with 90% probability), whereas existing methods are miscalibrated. In analyses of 72 traits across large and diverse biobanks (All of Us and UK Biobank), we find that prediction intervals required adjustment by up to 80% for quantitative traits. For disease traits, PGS-based predictions were miscalibrated across socioeconomic contexts such as annual household income levels, further highlighting the need of accounting for context information in PGS-based prediction across diverse populations.
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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.