Risk assessment for colorectal cancer via polygenic risk score and lifestyle exposure: a large-scale association study of East Asian and European populations

作者：Junyi Xin, Mulong Du, Dongying Gu, Kewei Jiang, Mengyun Wang, Mengyun Wang, Mingjuan Jin, Yeting Hu, Silu Chen, Silu Chen, Shuwei Li, Shuwei Li, Linjun Zhu, Linjun Zhu, Kun Chen, Kun Chen, Kefeng Ding, Zhengdong Zhang, Hongbing Shen, Meilin Wang, Meilin Wang · 发表于：Genome Medicine · 年份：2023 · DOI：10.1186/s13073-023-01156-9 · 被引用次数：54 · 研究领域：Genetic Associations and Epidemiology、BRCA gene mutations in cancer、Genetic factors in colorectal cancer

Abstract Background The genetic architectures of colorectal cancer are distinct across different populations. To date, the majority of polygenic risk scores (PRSs) are derived from European (EUR) populations, which limits their accurate extrapolation to other populations. Here, we aimed to generate a PRS by incorporating East Asian (EAS) and EUR ancestry groups and validate its utility for colorectal cancer risk assessment among different populations. Methods A large-scale colorectal cancer genome-wide association study (GWAS), harboring 35,145 cases and 288,934 controls from EAS and EUR populations, was used for the EAS-EUR GWAS meta-analysis and the construction of candidate EAS-EUR PRSs via different approaches. The performance of each PRS was then validated in external GWAS datasets of EAS (727 cases and 1452 controls) and EUR (1289 cases and 1284 controls) ancestries, respectively. The optimal PRS was further tested using the UK Biobank longitudinal cohort of 355,543 individuals and ultimately applied to stratify individual risk attached by healthy lifestyle. Results In the meta-analysis across EAS and EUR populations, we identified 48 independent variants beyond genome-wide significance ( P < 5 × 10 −8 ) at previously reported loci. Among 26 candidate EAS-EUR PRSs, the PRS-CSx approach-derived PRS (defined as PRS CSx ) that harbored genome-wide variants achieved the optimal discriminatory ability in both validation datasets, as well as better performance in the EAS p...