Risk loci identification and polygenic risk score in prediction of lung cancer: a large-scale prospective cohort study in Chinese
Abstract
Summary Background 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. Methods 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). Findings 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 (Ptrend=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. Interpretation Based on the systematic identification of the risk loci for NSCLC, we have proved for the first time that…
How strong is the evidence?
Evidence Hub reads this as a cohort study, done in people. Its evidence level is 3 of 5 (Moderate · trial / cohort / secondary analysis). Trials without a large randomized design, cohorts and secondary analyses give moderate evidence. Reported size: 95,408 participants or records.
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