ArticleNature communications2021
Population-specific causal disease effect sizes in functionally important regions impacted by selection.
Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 89 papers, 3 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
89 citing papers in PubMed, 3 syntheses or guidelines pooled it, 134 citations in OpenAlex.
- Shared genetic architectures of educational attainment in East Asian and European populations.Nature human behaviour · 2024Pooled it
- Causal effects on complex traits are similar for common variants across segments of different continental ancestries within admixed individuals.Nature genetics · 2023Pooled it
- Pooled it
- Migraines and the association of cognitive impairment: a one- and two-sample mendelian randomization analysis.Dialogues in clinical neuroscience · 2026Article
- Identifying independent causal cell types for human diseases and risk variants.Cell genomics · 2026Article
- Genome-wide association analyses highlight the neuronal contribution to multiple sclerosis susceptibility.Nature genetics · 2026Article
- Extending genome-wide association studies to admixed cohorts with high degrees of relatedness.Nature genetics · 2026Article
- Improved heritability partitioning and enrichment analyses using summary statistics with graphREML.Nature genetics · 2026Article
- Article
- Ancestral diversity in complex disease genetics: from discovery to translation.Nature reviews. Genetics · 2026Review
- Article
- Tracing the evolutionary histories of ultra-rare variants using variational dating of large ancestral recombination graphs.bioRxiv : the preprint server for biology · 2026Article
- Population-specific optimization of polygenic risk scores for breast cancer in East Asians.Genetics in medicine open · 2026Article
- Hidden structure in polygenic scores and the challenge of disentangling ancestry interactions in admixed populations.Genetics · 2025Article
- Towards improved fine-mapping of candidate causal variants.Nature reviews. Genetics · 2025Review
- Logica: A likelihood framework for cross-ancestry local genetic correlation estimation using summary statistics.American journal of human genetics · 2025Article
- A machine-learning framework to characterize functional disease architectures and prioritize disease variants.medRxiv : the preprint server for health sciences · 2025Article
- Improved multiancestry fine-mapping identifies cis-regulatory variants underlying molecular traits and disease risk.Nature genetics · 2025Article
- Article
- Distinct explanations underlie gene-environment interactions in the UK Biobank.American journal of human genetics · 2025Article
29 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors at 3 institutions in 3 countries.
Funding
Abstract
Many diseases exhibit population-specific causal effect sizes with trans-ethnic genetic correlations significantly less than 1, limiting trans-ethnic polygenic risk prediction. We develop a new method, S-LDXR, for stratifying squared trans-ethnic genetic correlation across genomic annotations, and apply S-LDXR to genome-wide summary statistics for 31 diseases and complex traits in East Asians (average N = 90K) and Europeans (average N = 267K) with an average trans-ethnic genetic correlation of 0.85. We determine that squared trans-ethnic genetic correlation is 0.82× (s.e. 0.01) depleted in the top quintile of background selection statistic, implying more population-specific causal effect sizes. Accordingly, causal effect sizes are more population-specific in functionally important regions, including conserved and regulatory regions. In regions surrounding specifically expressed genes, causal effect sizes are most population-specific for skin and immune genes, and least population-specific for brain genes. Our results could potentially be explained by stronger gene-environment interaction at loci impacted by selection, particularly positive selection.
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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.