Multi-ancestry GWAS meta-analyses of lung cancer reveal susceptibility loci and elucidate smoking-independent genetic risk

Bryan R. Gorman, Sun-Gou Ji, Michael Francis, Anoop K. Sendamarai, Yunling Shi, Poornima Devineni, Uma Saxena, Elizabeth Partan, Andrea K. DeVito, Jinyoung Byun, Younghun Han, Xiangjun Xiao, Don D. Sin, Wim Timens, Jennifer Moser, Sumitra Muralidhar, Rachel Ramoni, Rayjean J. Hung, James D. McKay, Yohan Bossé, Ryan Sun, Christopher I. Amos and Saiju Pyarajan ()
Additional contact information
Bryan R. Gorman: VA Boston Healthcare System
Sun-Gou Ji: VA Boston Healthcare System
Michael Francis: VA Boston Healthcare System
Anoop K. Sendamarai: VA Boston Healthcare System
Yunling Shi: VA Boston Healthcare System
Poornima Devineni: VA Boston Healthcare System
Uma Saxena: VA Boston Healthcare System
Elizabeth Partan: VA Boston Healthcare System
Andrea K. DeVito: VA Boston Healthcare System
Jinyoung Byun: Baylor College of Medicine
Younghun Han: Baylor College of Medicine
Xiangjun Xiao: Baylor College of Medicine
Don D. Sin: St Paul’s Hospital
Wim Timens: University of Groningen
Jennifer Moser: Department of Veterans Affairs
Sumitra Muralidhar: Department of Veterans Affairs
Rachel Ramoni: Department of Veterans Affairs
Rayjean J. Hung: University of Toronto
James D. McKay: World Health Organization
Yohan Bossé: Laval University
Ryan Sun: University of Texas MD Anderson Cancer Center
Christopher I. Amos: Baylor College of Medicine
Saiju Pyarajan: VA Boston Healthcare System

Nature Communications, 2024, vol. 15, issue 1, 1-13

Abstract: 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.

Date: 2024
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DOI: 10.1038/s41467-024-52129-4

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