ORIGINAL RESEARCH article

Front. Genet.

Sec. Applied Genetic Epidemiology

Volume 16 - 2025 | doi: 10.3389/fgene.2025.1646997

This article is part of the Research TopicInsights in Applied Genetic Epidemiology 2025View all 5 articles

Evaluation of Diverse Polygenic Risk Score Models for Lung Cancer in a Small-Scale Chinese Cohort

Provisionally accepted
Min  GaoMin Gao1Qiwen  ZhengQiwen Zheng2Yue  JiangYue Jiang3Xiao  ChangXiao Chang3*Xin  ZhengXin Zheng1
  • 1Shandong University of Traditional Chinese Medicine Affiliated Hospital, Jinan, China
  • 2Chinese Academy of Sciences Beijing Institute of Genomics, Beijing, China
  • 3Shandong First Medical University, Jinan, China

The final, formatted version of the article will be published soon.

Introduction: Lung cancer is a leading cause of cancer-related mortality globally, with distinct epidemiological and genetic patterns in East Asian populations. However, most polygenic risk score (PRS) models have been developed using European-ancestry cohorts, raising concerns about their applicability in non-European populations.Materials & methods: In this study, we systematically evaluated the predictive performance of three PRS approaches in a Chinese lung cancer cohort consisting of 97 cases and 667 controls. We assessed (i) a previously reported 19-SNP PRS developed in Chinese individuals, (ii) genome-wide PRS derived using PRS-CS with East Asian and European GWAS summary statistics, and (iii) PRS-CSx, a cross-population Bayesian framework that integrates summary sta-tistics across ancestries.Results: The 19-SNP PRS demonstrated limited discriminative power in our cohort. In contrast, PRS-CS using East Asian summary statistics showed sig-nificant associations with overall lung cancer and specific histological subtypes, particularly NSCLC and LUAD. PRS-CS based on European data yielded weaker performance, underscoring the importance of ancestry matching. Notably, PRS-CSx outperformed single-ancestry models, achieving improved risk stratification for NSCLC and LUAD. However, its predictive performance for LUSC and SCLC remained limited, likely due to sample size constraints and subtype heterogeneity.Conclusion: Our findings emphasize the critical role of ancestry-matched data and integrative PRS approaches in enhancing risk prediction in underrepresented populations. PRS-CSx represents a promising tool for lung cancer risk assessment in East Asians, though further validation in larger cohorts are needed to improve generalizability and clinical utility.

Keywords: Polygenic risk score, lung cancer, PRS-CS, Chinese population, Genome-Wide Association Study

Received: 14 Jun 2025; Accepted: 02 Jul 2025.

Copyright: © 2025 Gao, Zheng, Jiang, Chang and Zheng. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Xiao Chang, Shandong First Medical University, Jinan, China

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