ArticleFrontiers in genetics2021
Admixed Populations Improve Power for Variant Discovery and Portability in Genome-Wide Association Studies.
Article in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed.
- Topological stratification of continuous genetic variation in large biobanks.PLoS genetics · 2026Article
- Suggestive genome-wide associations with inflammatory biomarkers in an admixed population, including a missense variant in theFrontiers in immunology · 2026Article
- Ancestry-informative regulatory variants at KCNB1 modulate adipogenesis and body mass index.Frontiers in endocrinology · 2026Article
- Improved allele frequencies in gnomAD through local ancestry inference.Nature communications · 2025Article
- Interpreting SNP heritability in admixed populations.Genetics · 2025Article
- Enabling reproducible type 1 diabetes polygenic risk scoring for clinical and translational applications.medRxiv : the preprint server for health sciences · 2025Article
- Insights from the Biorepository and Integrative Genomics pediatric resource.Nature communications · 2025Article
- Fine-mapping in admixed populations using CARMA-X, with applications to Latin American studies.American journal of human genetics · 2025Article
- Interpreting SNP heritability in admixed populations.bioRxiv : the preprint server for biology · 2025Article
- Multiancestry Genome-Wide Association Study of Early Childhood Caries.Journal of dental research · 2025Article
- The Biorepository and Integrative Genomics resource for inclusive genomics: insights from a diverse pediatric and admixed cohort.medRxiv : the preprint server for health sciences · 2025Article
- Genes, culture, and scientific racism.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- NOTCH3 p.Arg1231Cys is markedly enriched in South Asians and associated with stroke.Nature communications · 2024Article
- Novel loci linked to serum lipid traits are identified in a genome-wide association study of a highly admixed Brazilian population - the 2015 ISA Nutrition.Lipids in health and disease · 2024Article
- Complex trait susceptibilities and population diversity in a sample of 4,145 Russians.Nature communications · 2024Article
- Identification of Genetic Variants for Diabetic Retinopathy Risk Applying Exome Sequencing in Extreme Phenotypes.BioMed research international · 2024Article
- Joint multi-ancestry and admixed GWAS reveals the complex genetics behind human cranial vault shape.Nature communications · 2023Review
- Article
- Strategies for the Genomic Analysis of Admixed Populations.Annual review of biomedical data science · 2023Review
- Impact of cross-ancestry genetic architecture on GWASs in admixed populations.American journal of human genetics · 2023Article
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Authors and funding
5 authors.
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Abstract
Genome-wide association studies (GWAS) are primarily conducted in single-ancestry settings. The low transferability of results has limited our understanding of human genetic architecture across a range of complex traits. In contrast to homogeneous populations, admixed populations provide an opportunity to capture genetic architecture contributed from multiple source populations and thus improve statistical power. Here, we provide a mechanistic simulation framework to investigate the statistical power and transferability of GWAS under directional polygenic selection or varying divergence. We focus on a two-way admixed population and show that GWAS in admixed populations can be enriched for power in discovery by up to 2-fold compared to the ancestral populations under similar sample size. Moreover, higher accuracy of cross-population polygenic score estimates is also observed if variants and weights are trained in the admixed group rather than in the ancestral groups. Common variant associations are also more likely to replicate if first discovered in the admixed group and then transferred to an ancestral population, than the other way around (across 50 iterations with 1,000 causal SNPs, training on 10,000 individuals, testing on 1,000 in each population,
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