Genetic variation plays an important role in the development of non-small cell lung
cancer (NSCLC). However, major genetic factors for lung cancer have not been fully
identified, especially in Chinese populations, which deters us from using a polygenic
risk score (PRS) to identify sub-populations at high-risk of lung cancer for prevention.
To systematically identify genetic variants for NSCLC risk, we newly genotyped 19,546
samples and conducted a meta-analysis of genome-wide association studies (GWASs) of
27,120 cases and 27,355 controls. We then built a PRS for Chinese populations and
evaluated its utility and effectiveness in predicting high-risk populations of lung
cancer in an independent prospective cohort of 95,408 individuals from China Kadoorie
Biobank (CKB). We identified 19 susceptibility loci to be significantly associated
with NSCLC risk at 5·0×10 -8 , including six novel ones. When applied to the CKB cohort,
the PRS of the risk loci successfully predicted lung cancer incidence in a dose-response
manner ( P trend =2·02×10 -9 ). Specially, we observed apparently separate predictive
morbidity curves for low, intermediate, and high genetic risk populations respectively,
and PRS was an independent effective risk stratification indicator beyond age and
pack-years during a 10-year follow-up time of the cohort. Based on the systematic
identification of the risk loci for NSCLC, we have proved for the first time that
GWAS-derived PRS can be effectively used in screening for high-risk populations of
lung cancer, potentially leading to a feasible PRS-based lung cancer screening program
for individualized prevention in Chinese populations. 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, and China’s Thousand Talents Program.