Multi-ancestry GWAS meta-analyses of lung cancer reveal susceptibility loci and elucidate smoking-independent genetic risk
Lung cancer remains the leading cause of cancer mortality, despite declining smoking rates. Previous lung cancer GWAS have identified numerous loci, but separating the genetic risks of lung cancer and smoking behavioral susceptibility remains challenging. Here, we perform multi-ancestry GWAS meta-an...
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| Vydáno v: | Nature communications Ročník 15; číslo 1; s. 8629 - 13 |
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| Hlavní autoři: | , , , , , , , , , , , , , , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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London
Nature Publishing Group UK
04.10.2024
Nature Publishing Group Nature Portfolio |
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| ISSN: | 2041-1723, 2041-1723 |
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| Abstract | Lung cancer remains the leading cause of cancer mortality, despite declining smoking rates. Previous lung cancer GWAS have identified numerous loci, but separating the genetic risks of lung cancer and smoking behavioral susceptibility remains challenging. Here, we perform multi-ancestry GWAS meta-analyses of lung cancer using the Million Veteran Program cohort (approximately 95% male cases) and a previous study of European-ancestry individuals, jointly comprising 42,102 cases and 181,270 controls, followed by replication in an independent cohort of 19,404 cases and 17,378 controls. We then carry out conditional meta-analyses on cigarettes per day and identify two novel, replicated loci, including the 19p13.11 pleiotropic cancer locus in squamous cell lung carcinoma. Overall, we report twelve novel risk loci for overall lung cancer, lung adenocarcinoma, and squamous cell lung carcinoma, nine of which are externally replicated. Finally, we perform PheWAS on polygenic risk scores for lung cancer, with and without conditioning on smoking. The unconditioned lung cancer polygenic risk score is associated with smoking status in controls, illustrating a reduced predictive utility in non-smokers. Additionally, our polygenic risk score demonstrates smoking-independent pleiotropy of lung cancer risk across neoplasms and metabolic traits.
Lung cancer is the leading cause of cancer mortality, despite declining smoking rates. Gorman et al. report multi-ancestry GWAS meta-analyses of lung cancer providing insights into smoking-independent genetic predisposition to the disease. |
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| AbstractList | Lung cancer remains the leading cause of cancer mortality, despite declining smoking rates. Previous lung cancer GWAS have identified numerous loci, but separating the genetic risks of lung cancer and smoking behavioral susceptibility remains challenging. Here, we perform multi-ancestry GWAS meta-analyses of lung cancer using the Million Veteran Program cohort (approximately 95% male cases) and a previous study of European-ancestry individuals, jointly comprising 42,102 cases and 181,270 controls, followed by replication in an independent cohort of 19,404 cases and 17,378 controls. We then carry out conditional meta-analyses on cigarettes per day and identify two novel, replicated loci, including the 19p13.11 pleiotropic cancer locus in squamous cell lung carcinoma. Overall, we report twelve novel risk loci for overall lung cancer, lung adenocarcinoma, and squamous cell lung carcinoma, nine of which are externally replicated. Finally, we perform PheWAS on polygenic risk scores for lung cancer, with and without conditioning on smoking. The unconditioned lung cancer polygenic risk score is associated with smoking status in controls, illustrating a reduced predictive utility in non-smokers. Additionally, our polygenic risk score demonstrates smoking-independent pleiotropy of lung cancer risk across neoplasms and metabolic traits.
Lung cancer is the leading cause of cancer mortality, despite declining smoking rates. Gorman et al. report multi-ancestry GWAS meta-analyses of lung cancer providing insights into smoking-independent genetic predisposition to the disease. Lung cancer remains the leading cause of cancer mortality, despite declining smoking rates. Previous lung cancer GWAS have identified numerous loci, but separating the genetic risks of lung cancer and smoking behavioral susceptibility remains challenging. Here, we perform multi-ancestry GWAS meta-analyses of lung cancer using the Million Veteran Program cohort (approximately 95% male cases) and a previous study of European-ancestry individuals, jointly comprising 42,102 cases and 181,270 controls, followed by replication in an independent cohort of 19,404 cases and 17,378 controls. We then carry out conditional meta-analyses on cigarettes per day and identify two novel, replicated loci, including the 19p13.11 pleiotropic cancer locus in squamous cell lung carcinoma. Overall, we report twelve novel risk loci for overall lung cancer, lung adenocarcinoma, and squamous cell lung carcinoma, nine of which are externally replicated. Finally, we perform PheWAS on polygenic risk scores for lung cancer, with and without conditioning on smoking. The unconditioned lung cancer polygenic risk score is associated with smoking status in controls, illustrating a reduced predictive utility in non-smokers. Additionally, our polygenic risk score demonstrates smoking-independent pleiotropy of lung cancer risk across neoplasms and metabolic traits. Lung cancer is the leading cause of cancer mortality, despite declining smoking rates. Gorman et al. report multi-ancestry GWAS meta-analyses of lung cancer providing insights into smoking-independent genetic predisposition to the disease. Abstract Lung cancer remains the leading cause of cancer mortality, despite declining smoking rates. Previous lung cancer GWAS have identified numerous loci, but separating the genetic risks of lung cancer and smoking behavioral susceptibility remains challenging. Here, we perform multi-ancestry GWAS meta-analyses of lung cancer using the Million Veteran Program cohort (approximately 95% male cases) and a previous study of European-ancestry individuals, jointly comprising 42,102 cases and 181,270 controls, followed by replication in an independent cohort of 19,404 cases and 17,378 controls. We then carry out conditional meta-analyses on cigarettes per day and identify two novel, replicated loci, including the 19p13.11 pleiotropic cancer locus in squamous cell lung carcinoma. Overall, we report twelve novel risk loci for overall lung cancer, lung adenocarcinoma, and squamous cell lung carcinoma, nine of which are externally replicated. Finally, we perform PheWAS on polygenic risk scores for lung cancer, with and without conditioning on smoking. The unconditioned lung cancer polygenic risk score is associated with smoking status in controls, illustrating a reduced predictive utility in non-smokers. Additionally, our polygenic risk score demonstrates smoking-independent pleiotropy of lung cancer risk across neoplasms and metabolic traits. Lung cancer remains the leading cause of cancer mortality, despite declining smoking rates. Previous lung cancer GWAS have identified numerous loci, but separating the genetic risks of lung cancer and smoking behavioral susceptibility remains challenging. Here, we perform multi-ancestry GWAS meta-analyses of lung cancer using the Million Veteran Program cohort (approximately 95% male cases) and a previous study of European-ancestry individuals, jointly comprising 42,102 cases and 181,270 controls, followed by replication in an independent cohort of 19,404 cases and 17,378 controls. We then carry out conditional meta-analyses on cigarettes per day and identify two novel, replicated loci, including the 19p13.11 pleiotropic cancer locus in squamous cell lung carcinoma. Overall, we report twelve novel risk loci for overall lung cancer, lung adenocarcinoma, and squamous cell lung carcinoma, nine of which are externally replicated. Finally, we perform PheWAS on polygenic risk scores for lung cancer, with and without conditioning on smoking. The unconditioned lung cancer polygenic risk score is associated with smoking status in controls, illustrating a reduced predictive utility in non-smokers. Additionally, our polygenic risk score demonstrates smoking-independent pleiotropy of lung cancer risk across neoplasms and metabolic traits.Lung cancer is the leading cause of cancer mortality, despite declining smoking rates. Gorman et al. report multi-ancestry GWAS meta-analyses of lung cancer providing insights into smoking-independent genetic predisposition to the disease. Lung cancer remains the leading cause of cancer mortality, despite declining smoking rates. Previous lung cancer GWAS have identified numerous loci, but separating the genetic risks of lung cancer and smoking behavioral susceptibility remains challenging. Here, we perform multi-ancestry GWAS meta-analyses of lung cancer using the Million Veteran Program cohort (approximately 95% male cases) and a previous study of European-ancestry individuals, jointly comprising 42,102 cases and 181,270 controls, followed by replication in an independent cohort of 19,404 cases and 17,378 controls. We then carry out conditional meta-analyses on cigarettes per day and identify two novel, replicated loci, including the 19p13.11 pleiotropic cancer locus in squamous cell lung carcinoma. Overall, we report twelve novel risk loci for overall lung cancer, lung adenocarcinoma, and squamous cell lung carcinoma, nine of which are externally replicated. Finally, we perform PheWAS on polygenic risk scores for lung cancer, with and without conditioning on smoking. The unconditioned lung cancer polygenic risk score is associated with smoking status in controls, illustrating a reduced predictive utility in non-smokers. Additionally, our polygenic risk score demonstrates smoking-independent pleiotropy of lung cancer risk across neoplasms and metabolic traits. Lung cancer remains the leading cause of cancer mortality, despite declining smoking rates. Previous lung cancer GWAS have identified numerous loci, but separating the genetic risks of lung cancer and smoking behavioral susceptibility remains challenging. Here, we perform multi-ancestry GWAS meta-analyses of lung cancer using the Million Veteran Program cohort (approximately 95% male cases) and a previous study of European-ancestry individuals, jointly comprising 42,102 cases and 181,270 controls, followed by replication in an independent cohort of 19,404 cases and 17,378 controls. We then carry out conditional meta-analyses on cigarettes per day and identify two novel, replicated loci, including the 19p13.11 pleiotropic cancer locus in squamous cell lung carcinoma. Overall, we report twelve novel risk loci for overall lung cancer, lung adenocarcinoma, and squamous cell lung carcinoma, nine of which are externally replicated. Finally, we perform PheWAS on polygenic risk scores for lung cancer, with and without conditioning on smoking. The unconditioned lung cancer polygenic risk score is associated with smoking status in controls, illustrating a reduced predictive utility in non-smokers. Additionally, our polygenic risk score demonstrates smoking-independent pleiotropy of lung cancer risk across neoplasms and metabolic traits.Lung cancer remains the leading cause of cancer mortality, despite declining smoking rates. Previous lung cancer GWAS have identified numerous loci, but separating the genetic risks of lung cancer and smoking behavioral susceptibility remains challenging. Here, we perform multi-ancestry GWAS meta-analyses of lung cancer using the Million Veteran Program cohort (approximately 95% male cases) and a previous study of European-ancestry individuals, jointly comprising 42,102 cases and 181,270 controls, followed by replication in an independent cohort of 19,404 cases and 17,378 controls. We then carry out conditional meta-analyses on cigarettes per day and identify two novel, replicated loci, including the 19p13.11 pleiotropic cancer locus in squamous cell lung carcinoma. Overall, we report twelve novel risk loci for overall lung cancer, lung adenocarcinoma, and squamous cell lung carcinoma, nine of which are externally replicated. Finally, we perform PheWAS on polygenic risk scores for lung cancer, with and without conditioning on smoking. The unconditioned lung cancer polygenic risk score is associated with smoking status in controls, illustrating a reduced predictive utility in non-smokers. Additionally, our polygenic risk score demonstrates smoking-independent pleiotropy of lung cancer risk across neoplasms and metabolic traits. |
| ArticleNumber | 8629 |
| Author | Bossé, Yohan Hung, Rayjean J. Devineni, Poornima Ji, Sun-Gou Amos, Christopher I. Sendamarai, Anoop K. Han, Younghun Ramoni, Rachel Pyarajan, Saiju Muralidhar, Sumitra Sun, Ryan Sin, Don D. McKay, James D. Gorman, Bryan R. Saxena, Uma Partan, Elizabeth Xiao, Xiangjun Moser, Jennifer DeVito, Andrea K. Francis, Michael Shi, Yunling Byun, Jinyoung Timens, Wim |
| Author_xml | – sequence: 1 givenname: Bryan R. orcidid: 0000-0002-4239-4672 surname: Gorman fullname: Gorman, Bryan R. organization: Center for Data and Computational Sciences (C-DACS), VA Boston Healthcare System, Booz Allen Hamilton – sequence: 2 givenname: Sun-Gou orcidid: 0000-0001-8652-6318 surname: Ji fullname: Ji, Sun-Gou organization: Center for Data and Computational Sciences (C-DACS), VA Boston Healthcare System, BridgeBio Pharma – sequence: 3 givenname: Michael orcidid: 0000-0002-1320-7161 surname: Francis fullname: Francis, Michael organization: Center for Data and Computational Sciences (C-DACS), VA Boston Healthcare System, Booz Allen Hamilton – sequence: 4 givenname: Anoop K. orcidid: 0000-0002-0476-5428 surname: Sendamarai fullname: Sendamarai, Anoop K. organization: Center for Data and Computational Sciences (C-DACS), VA Boston Healthcare System, Carbone Cancer Center, University of Wisconsin – sequence: 5 givenname: Yunling surname: Shi fullname: Shi, Yunling organization: Center for Data and Computational Sciences (C-DACS), VA Boston Healthcare System – sequence: 6 givenname: Poornima surname: Devineni fullname: Devineni, Poornima organization: Center for Data and Computational Sciences (C-DACS), VA Boston Healthcare System – sequence: 7 givenname: Uma surname: Saxena fullname: Saxena, Uma organization: Center for Data and Computational Sciences (C-DACS), VA Boston Healthcare System – sequence: 8 givenname: Elizabeth orcidid: 0000-0002-3995-6742 surname: Partan fullname: Partan, Elizabeth organization: Center for Data and Computational Sciences (C-DACS), VA Boston Healthcare System – sequence: 9 givenname: Andrea K. surname: DeVito fullname: DeVito, Andrea K. organization: Center for Data and Computational Sciences (C-DACS), VA Boston Healthcare System, Booz Allen Hamilton – sequence: 10 givenname: Jinyoung orcidid: 0000-0001-8579-1435 surname: Byun fullname: Byun, Jinyoung organization: Institute for Clinical and Translational Research, Baylor College of Medicine, Department of Medicine, Section of Epidemiology and Population Sciences, Baylor College of Medicine – sequence: 11 givenname: Younghun orcidid: 0000-0001-5048-8479 surname: Han fullname: Han, Younghun organization: Institute for Clinical and Translational Research, Baylor College of Medicine, Department of Medicine, Section of Epidemiology and Population Sciences, Baylor College of Medicine – sequence: 12 givenname: Xiangjun surname: Xiao fullname: Xiao, Xiangjun organization: Institute for Clinical and Translational Research, Baylor College of Medicine, Department of Medicine, Section of Epidemiology and Population Sciences, Baylor College of Medicine – sequence: 13 givenname: Don D. orcidid: 0000-0002-0756-6643 surname: Sin fullname: Sin, Don D. organization: The University of British Columbia Centre for Heart Lung Innovation, St Paul’s Hospital – sequence: 14 givenname: Wim orcidid: 0000-0002-4146-6363 surname: Timens fullname: Timens, Wim organization: University Medical Centre Groningen, GRIAC (Groningen Research Institute for Asthma and COPD), University of Groningen, Department of Pathology & Medical Biology, University Medical Centre Groningen, University of Groningen – sequence: 15 givenname: Jennifer surname: Moser fullname: Moser, Jennifer organization: Office of Research and Development, Department of Veterans Affairs – sequence: 16 givenname: Sumitra orcidid: 0000-0001-8417-9068 surname: Muralidhar fullname: Muralidhar, Sumitra organization: Office of Research and Development, Department of Veterans Affairs – sequence: 17 givenname: Rachel surname: Ramoni fullname: Ramoni, Rachel organization: Office of Research and Development, Department of Veterans Affairs – sequence: 18 givenname: Rayjean J. surname: Hung fullname: Hung, Rayjean J. organization: Lunenfeld-Tanenbaum Research Institute, Sinai Health System, University of Toronto – sequence: 19 givenname: James D. surname: McKay fullname: McKay, James D. organization: Section of Genetics, International Agency for Research on Cancer, World Health Organization – sequence: 20 givenname: Yohan orcidid: 0000-0002-3067-3711 surname: Bossé fullname: Bossé, Yohan organization: Institut universitaire de cardiologie et de pneumologie de Québec, Department of Molecular Medicine, Laval University – sequence: 21 givenname: Ryan surname: Sun fullname: Sun, Ryan organization: Department of Biostatistics, University of Texas MD Anderson Cancer Center – sequence: 22 givenname: Christopher I. orcidid: 0000-0002-8540-7023 surname: Amos fullname: Amos, Christopher I. organization: Institute for Clinical and Translational Research, Baylor College of Medicine, Department of Medicine, Section of Epidemiology and Population Sciences, Baylor College of Medicine, Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine – sequence: 24 givenname: Saiju orcidid: 0000-0002-9047-3762 surname: Pyarajan fullname: Pyarajan, Saiju email: saiju.pyarajan@va.gov organization: Center for Data and Computational Sciences (C-DACS), VA Boston Healthcare System, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/39366959$$D View this record in MEDLINE/PubMed |
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| Snippet | Lung cancer remains the leading cause of cancer mortality, despite declining smoking rates. Previous lung cancer GWAS have identified numerous loci, but... Abstract Lung cancer remains the leading cause of cancer mortality, despite declining smoking rates. Previous lung cancer GWAS have identified numerous loci,... |
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| SubjectTerms | 45/43 631/208/205/2138 631/208/68 692/699/67/1612 Adenocarcinoma Adenocarcinoma of Lung - genetics Aged Carcinoma, Squamous Cell - genetics Case-Control Studies Chromosome 19 Cigarettes Ethnicity - genetics Female Genetic analysis Genetic Loci Genetic Predisposition to Disease Genetic Risk Score Genome-Wide Association Study Health risks Humanities and Social Sciences Humans Lung cancer Lung carcinoma Lung diseases Lung Neoplasms - genetics Lung Neoplasms - mortality Male Meta-analysis Middle Aged Mortality multidisciplinary Neoplasms Performance prediction Pleiotropy Polygenic inheritance Polymorphism, Single Nucleotide Predictive control Risk Factors Science Science (multidisciplinary) Smoking Smoking - genetics Squamous cell carcinoma White |
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| Title | Multi-ancestry GWAS meta-analyses of lung cancer reveal susceptibility loci and elucidate smoking-independent genetic risk |
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