https://scholars.lib.ntu.edu.tw/handle/123456789/639437
標題: | Boosting the power of genome-wide association studies within and across ancestries by using polygenic scores | 作者: | Campos, Adrian I Namba, Shinichi Lin, Shu-Chin Nam, Kisung Sidorenko, Julia Wang, Huanwei Kamatani, Yoichiro Wang, Ling-Hua Lee, Seunggeun Lin, Yen-Feng YEN-CHEN ANNE FENG Okada, Yukinori Visscher, Peter M Yengo, Loic |
公開日期: | 十月-2023 | 卷: | 55 | 期: | 10 | 起(迄)頁: | 1169 | 來源出版物: | Nature Genetics | 摘要: | 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. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/639437 | ISSN: | 10614036 | DOI: | 10.1038/s41588-023-01500-0 |
顯示於: | 健康數據拓析統計研究所 |
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