ArticleNature communications2018
Improving genetic prediction by leveraging genetic correlations among human diseases and traits.
Article in Nature communications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 103 papers, 7 of them syntheses that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
103 citing papers in PubMed, 7 syntheses or guidelines pooled it.
- Pharmacogenomic scores in psychiatry: systematic review of current evidence.Translational psychiatry · 2024Pooled it
- Uncovering the genetic architecture of broad antisocial behavior through a genome-wide association study meta-analysis.Molecular psychiatry · 2022Pooled it
- MetaGS: an accurate method to impute and combine SNP effects across populations using summary statistics.Genetics, selection, evolution : GSE · 2022Pooled it
- Reconstructing SNP allele and genotype frequencies from GWAS summary statistics.Scientific reports · 2022Pooled it
- Genome-wide pleiotropy analysis identifies novel blood pressure variants and improves its polygenic risk scores.Genetic epidemiology · 2022Pooled it
- Incorporating functional priors improves polygenic prediction accuracy in UK Biobank and 23andMe data sets.Nature communications · 2021Pooled it
- Meta-analysis of genome-wide DNA methylation identifies shared associations across neurodegenerative disorders.Genome biology · 2021Pooled it
- Rare variant effect estimation and polygenic risk prediction.Nature genetics · 2026Article
- Article
- Pleiotropic shared heritability quantifies the shared genetic variance of common diseases.Nature genetics · 2026Article
- Metabolic polygenic risk scores for prediction of obesity, type 2 diabetes, and related morbidities.Cell metabolism · 2026Article
- Combining polygenic risk scores to understand genetic liability to physical-mental health multimorbidity in UK Biobank.Human molecular genetics · 2026Article
- Integrating network annotation from multiple correlated traits to improve polygenic risk scores based on GWAS summary statistics.Research square · 2026Article
- MAJA: multivariate Bayesian model for discovery of shared epigenetic pathways across human phenotypes.Bioinformatics advances · 2026Article
- Genetics to Improve Outcomes in Schizophrenia (GENios): A within-case molecular genetic study protocol.PloS one · 2026Article
- Charting the cognitive development of children using adult 'polygenic g scores'.bioRxiv : the preprint server for biology · 2025Article
- Genome-wide association study of seedling leaf rust resistance in European winter wheat cultivars.Journal of applied genetics · 2025Article
- Statistical construction of calibrated prediction intervals for polygenic score-based phenotype prediction.Nature genetics · 2025Article
- Low Stability and Specificity of Polygenic Risk Scores for Major Psychiatric Disorders Limit Their Clinical Utility.Biological psychiatry · 2025Article
- Incorporating multiple functional annotations to improve polygenic risk prediction accuracy.Cell genomics · 2025Article
43 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
Genomic prediction has the potential to contribute to precision medicine. However, to date, the utility of such predictors is limited due to low accuracy for most traits. Here theory and simulation study are used to demonstrate that widespread pleiotropy among phenotypes can be utilised to improve genomic risk prediction. We show how a genetic predictor can be created as a weighted index that combines published genome-wide association study (GWAS) summary statistics across many different traits. We apply this framework to predict risk of schizophrenia and bipolar disorder in the Psychiatric Genomics consortium data, finding substantial heterogeneity in prediction accuracy increases across cohorts. For six additional phenotypes in the UK Biobank data, we find increases in prediction accuracy ranging from 0.7% for height to 47% for type 2 diabetes, when using a multi-trait predictor that combines published summary statistics from multiple traits, as compared to a predictor based only on one trait.
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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.