Population-specific optimization of polygenic risk scores for breast cancer in East Asians

Genetics in Medicine Open Pub Date : 2026-01-01 Epub Date: 2026-08-03 DOI:10.1016/j.gimo.2026.104487
Shu-Hsuan Liu, Yu-Chun Wang, Yun-Jer Shieh, Hai-Feng Tan, Kuo-Jang Kao, Chih-Chiang Hung, Ming-Feng Hou, Chi-Cheng Huang, Ching-Hung Lin, An-Chieh Feng, Jeng-Fong Chiou, Chien-Hsiun Chen, Ling-Hui Li
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Abstract

Purpose

Polygenic risk scores (PRS) have shown promise in predicting disease susceptibility, but their accuracy varies across populations due to the limited representation of non-European ancestries in genomic studies. While European-derived PRS demonstrate some transferability to Asian populations, optimizing these scores for specific populations remains crucial for improving risk prediction.

Methods

Using data from the Taiwan Precision Medicine Initiative (n = 46,422) and an external validation cohort (n = 891), we developed an approach to optimize European-derived PRS for breast cancer prediction in East Asians. Our method involved 2 key steps: (1) replacing European PRS variants with Asian-specific single nucleotide polymorphisms within the same linkage disequilibrium blocks (r2 > 0.8) and (2) incorporating additional population-specific variants. We validated this approach using both breast and prostate cancer data sets.

Results

The optimized PRS (PRSEUR_replace+TPMI) showed improved predictive performance compared with the original European PRS (PRSEUR) in our main cohort, with an increased area under the curve from 0.608 to 0.617 and odds ratios per SD from 1.47 (95% CI 1.36-1.60) to 1.51 (95% CI 1.39-1.63). Individuals in the top 5% of PRSEUR_replace+TPMI demonstrated a 2.09-fold increased risk of developing breast cancer compared with those in the 40th to 60th percentile. External validation confirmed enhanced performance, and similar improvements were observed when this method was applied to prostate cancer prediction.

Conclusion

Our study presents a practical approach for optimizing European-derived PRS in non-European populations, which is particularly beneficial for populations with limited genetic data. As genetic data collection expands in these populations, this approach may help reduce health care disparities in the implementation of precision medicine.
东亚乳腺癌多基因风险评分人群特异性优化
目的多基因风险评分(PRS)在预测疾病易感性方面显示出前景,但由于基因组研究中非欧洲血统的代表性有限,其准确性在人群中存在差异。虽然源自欧洲的PRS显示出对亚洲人群的一些可转移性,但优化特定人群的这些评分对于提高风险预测仍然至关重要。方法使用来自台湾精准医疗计划(n = 46,422)和外部验证队列(n = 891)的数据,我们开发了一种方法来优化欧洲来源的PRS用于东亚乳腺癌预测。我们的方法包括两个关键步骤:(1)在相同的连锁不平衡区(r2 > 0.8)中用亚洲特异性的单核苷酸多态性替换欧洲PRS变异;(2)纳入其他群体特异性变异。我们用乳腺癌和前列腺癌的数据集验证了这种方法。结果在我们的主要队列中,优化后的PRS (PRSEUR_replace+TPMI)与原始欧洲PRS (PRSEUR)相比,预测性能有所提高,曲线下面积从0.608增加到0.617,每SD的优势比从1.47 (95% CI 1.36-1.60)增加到1.51 (95% CI 1.39-1.63)。PRSEUR_replace+TPMI排名前5%的人患乳腺癌的风险比排名第40到60百分位的人高2.09倍。外部验证证实了性能的提高,当该方法应用于前列腺癌预测时,也观察到类似的改进。结论本研究提出了一种实用的方法来优化非欧洲人群的欧洲衍生PRS,这对遗传数据有限的人群尤其有益。随着基因数据收集在这些人群中的扩展,这种方法可能有助于减少精准医疗实施中的医疗保健差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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