ArticleAmerican journal of human genetics2021
Leveraging both individual-level genetic data and GWAS summary statistics increases polygenic prediction.
Article in American journal of human genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.
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Who cites it
34 citing papers in PubMed, 1 synthesis or guideline pooled it, 49 citations in OpenAlex.
- Postpartum and non-postpartum depression: a population-based matched case-control study comparing polygenic risk scores for severe mental disorders.Translational psychiatry · 2023Pooled it
- SPLENDID incorporates continuous genetic ancestry in biobank-scale data to improve polygenic risk prediction across diverse populations.Nature methods · 2026Article
- Univariate-guided sparse regression for Biobank-scale high-dimensional omics data.PLoS genetics · 2026Article
- Genetic confounding in the associations between maternal health and autism.medRxiv : the preprint server for health sciences · 2026Article
- Common and rare variant contributions to discontinuation of stimulant treatment in ADHD.Translational psychiatry · 2026Article
- Improving polygenic score prediction for underrepresented groups through transfer learning.Nature communications · 2026Article
- Associations of novel visceral obesity indices (METS-VF and BRI) with dementia: the role of metabolic mediators and genetic susceptibility.Frontiers in nutrition · 2026Article
- Interaction between genetic predisposition to successful ageing and chronic air pollution on lung disease in elderly women: results of the German SALIA cohort.BMJ open respiratory research · 2025Article
- Evaluating multi-ancestry genome-wide association methods: Statistical power, population structure, and practical implications.American journal of human genetics · 2025Article
- Descriptives and Genetic Correlates of Eating Disorder Diagnostic Transitions and Presumed Remission in the Danish Registry.Biological psychiatry · 2025Article
- Beyond predictive RAmerican journal of human genetics · 2025Article
- Deep learning-based polygenic scores enhance generalizability of psychiatric disorders prediction.medRxiv : the preprint server for health sciences · 2025Article
- Leveraging haplotype information in heritability estimation and polygenic prediction.Nature communications · 2025Article
- Association of estimated glucose disposal rate with atrial fibrillation, heart failure and cardiovascular mortality in patients with diabetes: a prospective cohort study from the UK Biobank.Frontiers in endocrinology · 2025Article
- Healthy lifestyle practice correlates with decreased obesity prevalence in individuals with high polygenic risk: TMM CommCohort study.Journal of human genetics · 2025Article
- Advancements and limitations in polygenic risk score methods for genomic prediction: a scoping review.Human genetics · 2024Article
- Genetic liability estimated from large-scale family data improves genetic prediction, risk score profiling, and gene mapping for major depression.American journal of human genetics · 2024Article
- Single-Ancestry versus Multi-Ancestry Polygenic Risk Scores for CKD in Black American Populations.Journal of the American Society of Nephrology : JASN · 2024Article
- Descriptives and genetic correlates of eating disorder diagnostic transitions and presumed remission in the Danish registry.medRxiv : the preprint server for health sciences · 2024Article
- Fast and scalable ensemble learning method for versatile polygenic risk prediction.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
Corrections and comments
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Authors and funding
13 authors at 6 institutions in 4 countries.
Funding
Abstract
The accuracy of polygenic risk scores (PRSs) to predict complex diseases increases with the training sample size. PRSs are generally derived based on summary statistics from large meta-analyses of multiple genome-wide association studies (GWASs). However, it is now common for researchers to have access to large individual-level data as well, such as the UK Biobank data. To the best of our knowledge, it has not yet been explored how best to combine both types of data (summary statistics and individual-level data) to optimize polygenic prediction. The most widely used approach to combine data is the meta-analysis of GWAS summary statistics (meta-GWAS), but we show that it does not always provide the most accurate PRS. Through simulations and using 12 real case-control and quantitative traits from both iPSYCH and UK Biobank along with external GWAS summary statistics, we compare meta-GWAS with two alternative data-combining approaches, stacked clumping and thresholding (SCT) and meta-PRS. We find that, when large individual-level data are available, the linear combination of PRSs (meta-PRS) is both a simple alternative to meta-GWAS and often more accurate.
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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.