Multi-ancestry meta-analyses of lung cancer in the Million Veteran Program reveal novel risk loci and elucidate smoking-independent genetic risk
Bryan R. GormaniD, Sun‐Gou JiiD, Michael FrancisiD, Anoop K. SendamaraiiD, Yunling ShiiD, Poornima Devineni, Uma SaxenaiD, Elizabeth S. PartaniD, Andrea K. DeVitoiD, Jinyoung ByuniD, Younghun HaniD, Xiangjun XiaoiD, Don D. SiniD, Wim TimensiD, Jennifer MoseriD, Sumitra MuralidhariD, Rachel Badovinac RamoniiD, Rayjean J. HungiD, James McKayiD, Yohan BosséiD, Ryan SuniD, Christopher Ian AmosiD, VA Million Veteran Program, Saiju PyarajaniD
Abstract
Lung cancer remains the leading cause of cancer mortality, despite declines in smoking rates. Previous lung cancer genome-wide association studies (GWAS) have identified numerous loci, but separating the genetic risks of lung cancer and smoking behavioral susceptibility remains challenging. We performed multi-ancestry GWAS meta-analyses of lung cancer using the Million Veteran Program (MVP) cohort and a previous study of European-ancestry individuals, comprising 42,102 cases and 181,270 controls, followed by replication in an independent cohort of 19,404 cases and 17,378 controls. We further performed conditional meta-analyses on cigarettes per day and identified two novel, replicated loci, including the 19p13.11 pleiotropic cancer locus in LUSC. Overall, we report twelve novel risk loci for overall lung cancer, lung adenocarcinoma (LUAD), and squamous cell lung carcinoma (LUSC), nine of which were externally replicated. Finally, we performed phenome-wide association studies (PheWAS) on polygenic risk scores (PRS) for lung cancer, with and without conditioning on smoking. The unconditioned lung cancer PRS was associated with smoking status in controls, illustrating reduced predictive utility in non-smokers. Additionally, our PRS demonstrates smoking-independent pleiotropy of lung cancer risk across neoplasms and metabolic traits.
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