Journal article
Population-specific causal disease effect sizes in functionally important regions impacted by selection
- 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.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Supplementary materials, zip, 4.5MB, Terms of use)
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(Preview, Version of record, pdf, 1.6MB, Terms of use)
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- Publisher copy:
- 10.1038/s41467-021-21286-1
Authors
+ National Institute of Health
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- Funder identifier:
- https://ror.org/05h1kgg64
- Grant:
- R01 HG006399
- U01 HG009379
- R37 MH107649
- R01 MH101244
- R01 CA222147
- Publisher:
- Nature Research
- Journal:
- Nature Communications More from this journal
- Volume:
- 12
- Issue:
- 1
- Article number:
- 1098
- Place of publication:
- England
- Publication date:
- 2021-02-17
- Acceptance date:
- 2021-01-15
- DOI:
- EISSN:
-
2041-1723
- Pmid:
-
33597505
- Language:
-
English
- Pubs id:
-
1280089
- Local pid:
-
pubs:1280089
- Deposit date:
-
2025-08-14
- ARK identifier:
Terms of use
- Copyright holder:
- Shi et al.
- Copyright date:
- 2021
- Rights statement:
- © The Author(s) 2021. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
- Licence:
- CC Attribution (CC BY)
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