ArticleNature genetics2013
Projecting the performance of risk prediction based on polygenic analyses of genome-wide association studies.
Article in Nature genetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 220 papers, 10 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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
220 citing papers in PubMed, 10 syntheses or guidelines pooled it.
- Polygenic Scores for ADHD: A Meta-Analysis.Research on child and adolescent psychopathology · 2021Pooled it
- Systematic Review of Polygenic Risk Scores for Type 1 and Type 2 Diabetes.International journal of molecular sciences · 2020Pooled it
- Systematic Review of Polygenic Gene-Environment Interaction in Tobacco, Alcohol, and Cannabis Use.Behavior genetics · 2019Pooled it
- Validation of Genome-Wide Polygenic Risk Scores for Coronary Artery Disease in French Canadians.Circulation. Genomic and precision medicine · 2019Pooled it
- The genetic underpinnings of callous-unemotional traits: A systematic research review.Neuroscience and biobehavioral reviews · 2019Pooled it
- Combining common genetic variants and non-genetic risk factors to predict risk of cutaneous melanoma.Human molecular genetics · 2018Pooled it
- Identification of multiple risk loci and regulatory mechanisms influencing susceptibility to multiple myeloma.Nature communications · 2018Pooled it
- Validation of Polygenic Scores for QT Interval in Clinical Populations.Circulation. Cardiovascular genetics · 2017Pooled it
- Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2016Pooled it
- Pooled it
- DeepU-PRS: nonlinear and uncertainty-aware SNP heritability modeling for annotation-informed polygenic risk scoring.Briefings in bioinformatics · 2026Article
- Constructing Genetic Risk Scores: Robust Bayesian Approach through Projected Summary Statistics and Flexible Shrinkage.Journal of the American Statistical Association · 2026Article
- Molecular mastery: Harnessing DNA technology for disease prevention.Genes & diseases · 2026Review
- Polygenic risk score and risk of drug-induced liver injury after initiating antiretroviral therapy in people living with HIV.Pharmacogenomics · 2026Article
- Association of a polygenic risk score with low trauma fractures in people with HIV - The swiss HIV cohort study.PloS one · 2026Article
- Alzheimer's disease polygenic risk in early- and late-onset Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Ge-SAND: an explainable deep learning-driven framework for disease risk prediction by uncovering complex genetic interactions in parallel.BMC genomics · 2025Article
- Plant-based dietary patterns, genetic risk, proteome, and lung cancer risk: a large prospective cohort study.European journal of nutrition · 2025Article
- Polygenic scores and their applications in kidney disease.Nature reviews. Nephrology · 2025Review
- Polygenic prediction for underrepresented populations through transfer learning by utilizing genetic similarity shared with European populations.Briefings in bioinformatics · 2024Article
160 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
We report a new method to estimate the predictive performance of polygenic models for risk prediction and assess predictive performance for ten complex traits or common diseases. Using estimates of effect-size distribution and heritability derived from current studies, we project that although 45% of the variance of height has been attributed to SNPs, a model trained on one million people may only explain 33.4% of variance of the trait. Models based on current studies allow for identification of 3.0%, 1.1% and 7.0% of the populations at twofold or higher than average risk for type 2 diabetes, coronary artery disease and prostate cancer, respectively. Tripling of sample sizes could elevate these percentages to 18.8%, 6.1% and 12.2%, respectively. The utility of polygenic models for risk prediction will depend on achievable sample sizes for the training data set, the underlying genetic architecture and the inclusion of information on other risk factors, including family history.
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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.