| Title: | A method for an unbiased estimate of cross-ancestry genetic correlation using individual-level data |
| Journal: | Nature Communications |
| Published: | 9 Feb 2023 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/36759513/ |
| DOI: | https://doi.org/10.1038/s41467-023-36281-x |
| URL: | https://www.nature.com/articles/s41467-023-36281-x.pdf |
| Citations: | 11 (11 in last 2 years) as of 8 Aug 2024 |
Publication 7951
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Abstract
Cross-ancestry genetic correlation is an important parameter to understand the genetic relationship between two ancestry groups. However, existing methods cannot properly account for ancestry-specific genetic architecture, which is diverse across ancestries, producing biased estimates of cross-ancestry genetic correlation. Here, we present a method to construct a genomic relationship matrix (GRM) that can correctly account for the relationship between ancestry-specific allele frequencies and ancestry-specific allelic effects. Through comprehensive simulations, we show that the proposed method outperforms existing methods in the estimations of SNP-based heritability and cross-ancestry genetic correlation. The proposed method is further applied to anthropometric and other complex traits from the UK Biobank data across ancestry groups. For obesity, the estimated genetic correlation between African and European ancestry cohorts is significantly different from unity, suggesting that obesity is genetically heterogenous between these two ancestries.6 Authors
- Md. Moksedul Momin
- Jisu Shin
- Soohyun Lee
- Buu Truong
- Beben Benyamin
- S. Hong Lee
1 Application
| Application ID | Title |
|---|---|
| 14575 | Whole-genome approaches for dissecting (shared) genetic architecture and individual risk prediction of complex traits in human populations |
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