SynthesisNature genetics2023
Boosting the power of genome-wide association studies within and across ancestries by using polygenic scores.
Synthesis in Nature genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Joint modeling of whole-genome sequencing data for human height via approximate message passing.Cell genomics · 2026Article
- Non-cognitive skills mediate education-related polygenic score associations with academic achievement across development.Nature communications · 2026Article
- Associations of vegetarianism with circulating lipids across varying genetic capacity: a cross-sectional Polygenic Score-by-Vegetarianism interaction study in UK Biobank.medRxiv : the preprint server for health sciences · 2026Article
- Evaluating multi-ancestry genome-wide association methods: Statistical power, population structure, and practical implications.American journal of human genetics · 2025Article
- LDAK-KVIK performs fast and powerful mixed-model association analysis of quantitative and binary phenotypes.Nature genetics · 2025Article
- Uncovering causal gene-tissue pairs and variants through a multivariate TWAS controlling for infinitesimal effects.Nature communications · 2025Article
- Enhanced insights into the genetic architecture of 3D cranial vault shape using pleiotropy-informed GWAS.Communications biology · 2025Article
- Gene-environment correlation: the role of family environment in academic development.Molecular psychiatry · 2025Article
- From genetic disposition to academic achievement: The mediating role of non-cognitive skills across development.bioRxiv : the preprint server for biology · 2025Article
- SPANature communications · 2025Article
- A scalable variational inference approach for increased mixed-model association power.Nature genetics · 2025Article
- Uncovering causal gene-tissue pairs and variants: A multivariable TWAS method controlling for infinitesimal effects.Research square · 2024Article
- Uncovering causal gene-tissue pairs and variants: A multivariable TWAS method controlling for infinitesimal effects.medRxiv : the preprint server for health sciences · 2024Article
- Understanding the Genetic Architecture of Vitamin Status Biomarkers in the Genome-Wide Association Study Era: Biological Insights and Clinical Significance.Advances in nutrition (Bethesda, Md.) · 2024Review
- Genomic analysis of intracranial and subcortical brain volumes yields polygenic scores accounting for variation across ancestries.Nature genetics · 2024Article
- A phenome-wide association study of cross-disorder genetic liability in youth genetically similar to individuals from European reference populations.Nature. Mental health · 2024Article
- Genomic analysis of intracranial and subcortical brain volumes yields polygenic scores accounting for variation across ancestries.medRxiv : the preprint server for health sciences · 2024Article
Corrections and comments
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Authors and funding
15 authors.
Funding
Abstract
Genome-wide association studies (GWASs) have been mostly conducted in populations of European ancestry, which currently limits the transferability of their findings to other populations. Here, we show, through theory, simulations and applications to real data, that adjustment of GWAS analyses for polygenic scores (PGSs) increases the statistical power for discovery across all ancestries. We applied this method to analyze seven traits available in three large biobanks with participants of East Asian ancestry (n = 340,000 in total) and report 139 additional associations across traits. We also present a two-stage meta-analysis strategy whereby, in contributing cohorts, a PGS-adjusted GWAS is rerun using PGSs derived from a first round of a standard meta-analysis. On average, across traits, this approach yields a 1.26-fold increase in the number of detected associations (range 1.07- to 1.76-fold increase). Altogether, our study demonstrates the value of using PGSs to increase the power of GWASs in underrepresented populations and promotes such an analytical strategy for future GWAS meta-analyses.
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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.