Juncheng Dai1, Jun Lv2, Meng Zhu3, Yuzhuo Wang4, Na Qin4, Hongxia Ma5, Yong-Qiao He6, Ruoxin Zhang7, Wen Tan8, Jingyi Fan4, Tianpei Wang4, Hong Zheng9, Qi Sun4, Lijuan Wang4, Mingtao Huang4, Zijun Ge4, Canqing Yu2, Yu Guo10, Tong-Min Wang6, Jie Wang11, Lin Xu11, Weibing Wu12, Liang Chen12, Zheng Bian10, Robin Walters13, Iona Y Millwood13, Xi-Zhao Li6, Xin Wang14, Rayjean J Hung15, David C Christiani16, Haiquan Chen17, Mengyun Wang7, Cheng Wang18, Yue Jiang3, Kexin Chen9, Zhengming Chen13, Guangfu Jin5, Tangchun Wu19, Dongxin Lin8, Zhibin Hu5, Christopher I Amos20, Chen Wu8, Qingyi Wei21, Wei-Hua Jia6, Liming Li2, Hongbing Shen22. 1. Department of Epidemiology and Biostatistics, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China; State Key Laboratory of Reproductive Medicine, Center for Global Health, Nanjing Medical University, Nanjing, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China. 2. Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China. 3. Department of Epidemiology and Biostatistics, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China. 4. Department of Epidemiology and Biostatistics, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China. 5. Department of Epidemiology and Biostatistics, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China; State Key Laboratory of Reproductive Medicine, Center for Global Health, Nanjing Medical University, Nanjing, China. 6. State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China. 7. Cancer Institute, Fudan University Shanghai Cancer Center, Shanghai, China; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China. 8. Department of Etiology and Carcinogenesis, National Cancer Center and Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. 9. Department of Epidemiology and Biostatistics, Key Laboratory of Cancer Prevention and Therapy, Tianjin Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China. 10. Chinese Academy of Medical Sciences, Beijing, China. 11. Jiangsu Key Laboratory of Molecular and Translational Cancer Research, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer Hospital, Nanjing, China; Department of Thoracic Surgery, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer Hospital, Nanjing, China. 12. Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China. 13. Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK. 14. Department of Thoracic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China. 15. Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada. 16. Department of Environmental Health, Harvard School of Public Health, Department of Medicine, Harvard Medical School, Boston, MA, USA. 17. Department of Thoracic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China. 18. Department of Epidemiology and Biostatistics, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China; Department of Bioinformatics, School of Basic Medical Sciences, Nanjing Medical University, Nanjing, China. 19. Department of Occupational and Environmental Health and Ministry of Education Key Lab for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. 20. Baylor College of Medicine, Institute for Clinical and Translational Research, Houston, TX, USA. 21. Cancer Institute, Fudan University Shanghai Cancer Center, Shanghai, China; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China; Duke Cancer Institute, Duke University Medical Center, Durham, NC, USA; Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, USA. 22. Department of Epidemiology and Biostatistics, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China. Electronic address: hbshen@njmu.edu.cn.
Abstract
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.
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.
Authors: P Lichtenstein; N V Holm; P K Verkasalo; A Iliadou; J Kaprio; M Koskenvuo; E Pukkala; A Skytthe; K Hemminki Journal: N Engl J Med Date: 2000-07-13 Impact factor: 91.245
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Authors: Na Qin; Yuancheng Li; Cheng Wang; Meng Zhu; Juncheng Dai; Tongtong Hong; Demetrius Albanes; Stephen Lam; Adonina Tardon; Chu Chen; Gary Goodman; Stig E Bojesen; Maria Teresa Landi; Mattias Johansson; Angela Risch; H-Erich Wichmann; Heike Bickeboller; Gadi Rennert; Susanne Arnold; Paul Brennan; John K Field; Sanjay Shete; Loic Le Marchand; Olle Melander; Hans Brunnstrom; Geoffrey Liu; Rayjean J Hung; Angeline Andrew; Lambertus A Kiemeney; Shan Zienolddiny; Kjell Grankvist; Mikael Johansson; Neil Caporaso; Penella Woll; Philip Lazarus; Matthew B Schabath; Melinda C Aldrich; Victoria L Stevens; Guangfu Jin; David C Christiani; Zhibin Hu; Christopher I Amos; Hongxia Ma; Hongbing Shen Journal: Front Med Date: 2020-09-05 Impact factor: 4.592
Authors: Yuzhuo Wang; Olga Y Gorlova; Ivan P Gorlov; Meng Zhu; Juncheng Dai; Demetrius Albanes; Stephen Lam; Adonina Tardon; Chu Chen; Gary E Goodman; Stig E Bojesen; Maria Teresa Landi; Mattias Johansson; Angela Risch; Heunz-Erich Wichmann; Heike Bickeboller; David C Christiani; Gad Rennert; Susanne M Arnold; Paul Brennan; John K Field; Sanjay Shete; Loïc Le Marchand; Olle Melander; Hans Brunnstrom; Geoffrey Liu; Rayjean J Hung; Angeline S Andrew; Lambertus A Kiemeney; Shanbeh Zienolddiny; Kjell Grankvist; Mikael Johansson; Neil E Caporaso; Penella J Woll; Philip Lazarus; Matthew B Schabath; Melinda C Aldrich; Victoria L Stevens; Hongxia Ma; Guangfu Jin; Zhibin Hu; Christopher I Amos; Hongbing Shen Journal: Cancer Epidemiol Biomarkers Prev Date: 2020-04-10 Impact factor: 4.254
Authors: Jinyoung Byun; Younghun Han; Yafang Li; Jun Xia; Erping Long; Jiyeon Choi; Xiangjun Xiao; Meng Zhu; Wen Zhou; Ryan Sun; Yohan Bossé; Zhuoyi Song; Ann Schwartz; Christine Lusk; Thorunn Rafnar; Kari Stefansson; Tongwu Zhang; Wei Zhao; Rowland W Pettit; Yanhong Liu; Xihao Li; Hufeng Zhou; Kyle M Walsh; Ivan Gorlov; Olga Gorlova; Dakai Zhu; Susan M Rosenberg; Susan Pinney; Joan E Bailey-Wilson; Diptasri Mandal; Mariza de Andrade; Colette Gaba; James C Willey; Ming You; Marshall Anderson; John K Wiencke; Demetrius Albanes; Stephan Lam; Adonina Tardon; Chu Chen; Gary Goodman; Stig Bojeson; Hermann Brenner; Maria Teresa Landi; Stephen J Chanock; Mattias Johansson; Thomas Muley; Angela Risch; H-Erich Wichmann; Heike Bickeböller; David C Christiani; Gad Rennert; Susanne Arnold; John K Field; Sanjay Shete; Loic Le Marchand; Olle Melander; Hans Brunnstrom; Geoffrey Liu; Angeline S Andrew; Lambertus A Kiemeney; Hongbing Shen; Shanbeh Zienolddiny; Kjell Grankvist; Mikael Johansson; Neil Caporaso; Angela Cox; Yun-Chul Hong; Jian-Min Yuan; Philip Lazarus; Matthew B Schabath; Melinda C Aldrich; Alpa Patel; Qing Lan; Nathaniel Rothman; Fiona Taylor; Linda Kachuri; John S Witte; Lori C Sakoda; Margaret Spitz; Paul Brennan; Xihong Lin; James McKay; Rayjean J Hung; Christopher I Amos Journal: Nat Genet Date: 2022-08-01 Impact factor: 41.307