The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.
Identification of risk loci and a polygenic risk score for lung cancer: a large-scale prospective cohort study in Chinese populations
Open accessAbstract
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 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. 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, and China’s Thousand Talents Program.
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Cited by
Polygenic risk scores: from research tools to clinical instruments
Lewis, C. M., & Vassos, E. (2020) · Genome Medicine · doi:10.1186/s13073-020-00742-5 · Cited by 1,360
Mapping the human genetic architecture of COVID-19
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Self-citationNon‐small cell lung cancer in China
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Metadata
- 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, I. Y., Li, X.-Z., Wang, X., Hung, R. J., Christiani, D. C., Chen, H., Wang, M., Wang, C., Jiang, Y., Chen, K., Chen, Z., Jin, G., Wu, T., Lin, D., Hu, Z., Amos, C. I., Wu, C., Wei, Q., Jia, W.-H., Li, L., & Shen, H.
- Venue
- The Lancet Respiratory Medicine
- Publisher
- Elsevier BV
- Published
- 2019-10
- Volume
- 7
- Issue
- 10
- Pages
- 881-891
- ISSN
- 2213-2600 (ISSN-L)
- OpenAlex
- W2956442594
- Cited by
- 265
- References
- 39
- FWCI
- 14.09
- Type
- journal article
- Language
- en
- Open access
- green
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- 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., . . . Shen, H. (2019). Identification of risk loci and a polygenic risk score for lung cancer: a large-scale prospective cohort study in Chinese populations. The Lancet Respiratory Medicine. https://doi.org/10.1016/s2213-2600(19)30144-4
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