SynthesisNature communications2021
Incorporating functional priors improves polygenic prediction accuracy in UK Biobank and 23andMe data sets.
Synthesis in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 116 papers, 5 of them syntheses that pooled it.
What it found
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Who cites it
116 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Multi-ancestry genome-wide association analyses of refractive error augment genetic discovery and polygenic prediction.Nature genetics · 2026Pooled it
- Overcoming attenuation bias in regressions using polygenic indices.Nature communications · 2023Pooled it
- Multi-ancestry and multi-trait genome-wide association meta-analyses inform clinical risk prediction for systemic lupus erythematosus.Nature communications · 2023Pooled it
- Incorporating functional priors improves polygenic prediction accuracy in UK Biobank and 23andMe data sets.Nature communications · 2021Pooled it
- Incorporating European GWAS findings improve polygenic risk prediction accuracy of breast cancer among East Asians.Genetic epidemiology · 2021Pooled it
- Predictive Accuracy of a Clinical and Genetic Risk Model for Atrial Fibrillation.Circulation. Genomic and precision medicine · 2021Trial
- Genome-wide detection of genotype-environment interactions at biobank scale with fastGxE.Nature genetics · 2026Article
- Article
- DeepU-PRS: nonlinear and uncertainty-aware SNP heritability modeling for annotation-informed polygenic risk scoring.Briefings in bioinformatics · 2026Article
- Development and application of type 1 diabetes polygenic scores across diverse populations.Diabetologia · 2026Review
- Constructing Genetic Risk Scores: Robust Bayesian Approach through Projected Summary Statistics and Flexible Shrinkage.Journal of the American Statistical Association · 2026Article
- Integrating Genetic, Environmental, Cognitive, and Temperament Data for ADHD Prediction in Explainable Deep Learning Models.medRxiv : the preprint server for health sciences · 2026Article
- Functionally informed annotation influences pathway-specific polygenic risk and disease inference in Alzheimer's disease.medRxiv : the preprint server for health sciences · 2026Article
- Shared genetic architecture between Alzheimer's disease and brain morphology.Alzheimer's research & therapy · 2026Article
- Multi-trait polygenic risk scores improve genomic prediction of atrial fibrillation across diverse ancestries.Nature communications · 2026Article
- Polygenic predisposition modifies the associations of fish oil supplementation with circulating omega-3 fatty acids: a cross-sectional gene-diet interaction study in UK Biobank.medRxiv : the preprint server for health sciences · 2026Article
- Improving genomic prediction accuracy of complex traits by integrating massive types of functional annotation information.Nature communications · 2026Article
- Integrating network annotation from multiple correlated traits to improve polygenic risk scores based on GWAS summary statistics.Research square · 2026Article
- The polygenic, omnigenic and stratagenic models of complex disease risk.Nature genetics · 2026Review
- Leveraging the shared and opposing genetic mechanisms in the heritable cardiomyopathies.Research square · 2026Article
56 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Polygenic risk prediction is a widely investigated topic because of its promising clinical applications. Genetic variants in functional regions of the genome are enriched for complex trait heritability. Here, we introduce a method for polygenic prediction, LDpred-funct, that leverages trait-specific functional priors to increase prediction accuracy. We fit priors using the recently developed baseline-LD model, including coding, conserved, regulatory, and LD-related annotations. We analytically estimate posterior mean causal effect sizes and then use cross-validation to regularize these estimates, improving prediction accuracy for sparse architectures. We applied LDpred-funct to predict 21 highly heritable traits in the UK Biobank (avg N = 373 K as training data). LDpred-funct attained a +4.6% relative improvement in average prediction accuracy (avg prediction R
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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.