Identification of risk loci and a polygenic risk score for lung cancer: a large-scale prospective cohort study in Chinese populations.

Journal Article (Journal Article)

BACKGROUND: Genetic variation has an important role in the development of non-small-cell lung cancer (NSCLC). However, genetic factors for lung cancer have not been fully identified, especially in Chinese populations, which limits the use of existing polygenic risk scores (PRS) to identify subpopulations at high risk of lung cancer for prevention. We therefore aimed to identify novel loci associated with NSCLC risk, and generate a PRS and evaluate its utility and effectiveness in the prediction of lung cancer risk in Chinese populations. METHODS: To systematically identify genetic variants for NSCLC risk, we newly genotyped 19 546 samples from Chinese NSCLC cases and controls from the Nanjing Medical University Global Screening Array Project and did a meta-analysis of genome-wide association studies (GWASs) of 27 120 individuals with NSCLC and 27 355 without NSCLC (13 327 cases and 13 328 controls of Chinese descent as well as 13 793 cases and 14 027 controls of European descent). We then built a PRS for Chinese populations from all reported single-nucleotide polymorphisms that have been reported to be associated with lung cancer risk at genome-wide significance level. We evaluated the utility and effectiveness of the generated PRS in predicting subpopulations at high-risk of lung cancer in an independent prospective cohort of 95 408 individuals from the China Kadoorie Biobank (CKB) with more than 10 years' follow-up. FINDINGS: We identified 19 susceptibility loci to be significantly associated with NSCLC risk at p≤5·0 × 10-8, including six novel loci. When applied to the CKB cohort, the PRS of the risk loci successfully predicted lung cancer incident cases in a dose-response manner in participants at a high genetic risk (top 10%) than those at a low genetic risk (bottom 10%; adjusted hazard ratio 1·96, 95% CI 1·53-2·51; ptrend=2·02 × 10-9). Specially, we observed consistently separated curves of lung cancer events in individuals at low, intermediate, and high genetic risk, respectively, and PRS was an independent effective risk stratification indicator beyond age and smoking pack-years. INTERPRETATION: We have shown for the first time that GWAS-derived PRS can be effectively used in discriminating subpopulations at high risk of lung cancer, who might benefit from a practically feasible PRS-based lung cancer screening programme for precision prevention in Chinese populations. FUNDING: National Natural Science Foundation of China, the Priority Academic Program for the Development of Jiangsu Higher Education Institutions, National Key R&D Program of China, Science Foundation for Distinguished Young Scholars of Jiangsu, and China's Thousand Talents Program.

Full Text

Duke Authors

Cited Authors

  • Dai, J; Lv, J; Zhu, M; Wang, Y; Qin, N; Ma, H; He, Y-Q; Zhang, R; Tan, W; Fan, J; Wang, T; Zheng, H; Sun, Q; Wang, L; Huang, M; Ge, Z; Yu, C; Guo, Y; Wang, T-M; Wang, J; Xu, L; Wu, W; Chen, L; Bian, Z; Walters, R; Millwood, IY; Li, X-Z; Wang, X; Hung, RJ; Christiani, DC; Chen, H; Wang, M; Wang, C; Jiang, Y; Chen, K; Chen, Z; Jin, G; Wu, T; Lin, D; Hu, Z; Amos, CI; Wu, C; Wei, Q; Jia, W-H; Li, L; Shen, H

Published Date

  • October 2019

Published In

Volume / Issue

  • 7 / 10

Start / End Page

  • 881 - 891

PubMed ID

  • 31326317

Pubmed Central ID

  • PMC7015703

Electronic International Standard Serial Number (EISSN)

  • 2213-2619

Digital Object Identifier (DOI)

  • 10.1016/S2213-2600(19)30144-4


  • eng

Conference Location

  • England