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Conditional analyses on cigarettes per day identify two novel loci, reporting twelve new risk loci across lung cancer subtypes. PheWAS of polygenic risk scores quantifies smoking-conditioned and smoking-independent pleiotropy, including reduced predictive utility in non-smokers and cross-neoplasm metabolic associations.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/research-report/","Research & 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[https://doi.org/10.1038/s41467-024-52129-4](https://doi.org/10.1038/s41467-024-52129-4)  \nMulti-ancestry GWAS meta-analyses of lung cancer reveal susceptibility loci and elucidate smoking-independent genetic risk  \nReceived: 8 April 2024  \n\n| Accepted: 27 August 2024 |\n| --- |\n| |\n| Check for updates |\n\nBryan R. Gorman 1,2, Sun-Gou Ji 1,15, Michael Francis 1,2,  \nAnoop K. Sendamarai 1,16, Yunling Shi1, Poornima Devineni1, Uma Saxena1, Elizabeth Partan 1, Andrea K. DeVito1,2, Jinyoung Byun 3,4, Younghun Han 3,4, Xiangjun Xiao3,4, Don D. Sin 5, Wim Timens 6,7, Jennifer Moser8,  \nSumitra Muralidhar 8, Rachel Ramoni8, Rayjean J. Hung9, James D. McKay10, Yohan Bossé 11, Ryan Sun12, Christopher I. Amos 3,4,13, VA Million Veteran Program* & Saiju Pyarajan 1,14   \nLung 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 metaanalyses 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 carryout 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.  \nLung cancer remains the leading cause of overall cancer mortality, as the most prevalent cancer type in men, and the second highest in women after breast cancer1–3. Despite declines in smoking rates in the US since the 1980s4, tobacco use is currently implicated in upwards of 80% of lung cancer diagnoses1. Even in those who have never smoked, nor had meaningful exposure to environmental carcinogens1,5, there exists a heritable risk component of lung cancer conferred by genetic factors6–8. Differentiating the mutations that directly predispose an individual to  \nlung cancer from those whose effect is mediated through environmental components remains challenging.  \nGenome-wide association studies (GWAS) have identified lung cancer risk variants associated with oncogenic processes such as immune response7, cell cycle regulation9, and those affecting DNA damage response and genomic stability8. Several lung cancer GWAShave also reported strong effects of genes such as CHRNA nicotine receptor genes which putatively increase the risk of lung cancer through behavioral predisposition towards smoking5. Characteristic  \nA full list of affiliations appears at the end of the paper. *A list of authors and their affiliations appears at the end of the paper. e-mail: [saiju.pyarajan@va.gov](saiju.pyarajan@va.gov)  \nmolecular markers and genetic risk factors in smokers and neversmokers have been identified10,11, though fewer variants have been found in GWAS performed exclusively in never-smokers12.  \nLung cancer has a heterogeneous genetic architecture across ancestral groups13,14. In the two most well-studied ancestries, European (EA) and East Asian (EAS), the majority of genome-wide significant loci are not shared15,16; this is in agreement with molecular studies showing differences in tumor characteristics between EA and EAS17. Smaller African ancestry (AA) cohort","cbCaiiTvFUhQgATi","https://ap.wps.com/l/cbCaiiTvFUhQgATi","pdf",1739857,13,"English","# Background\n## Smoking rates and genetic risk separation\n# Methods\n## Multi-ancestry GWAS meta-analyses\n## Conditional analyses and replication\n# Results\n## Novel susceptibility loci and subtype findings\n## PheWAS and smoking-conditioned vs smoking-independent effects","[{\"question\":\"Why is it challenging to distinguish lung cancer genetic risk from smoking-related susceptibility?\",\"answer\":\"Previous GWAS have identified many loci, but separating genetic risks for lung cancer from genetic influences on smoking behavior remains difficult.\"},{\"question\":\"What datasets and sample sizes were used for discovery and replication?\",\"answer\":\"Discovery used Million Veteran Program and a prior European-ancestry study (42,102 cases, 181,270 controls), followed by replication in an independent cohort (19,404 cases, 17,378 controls).\"},{\"question\":\"How do the polygenic risk scores differ when conditioned on smoking?\",\"answer\":\"The unconditioned lung cancer polygenic risk score associates with smoking status in controls, reducing predictive utility in non-smokers, while the polygenic risk score still shows smoking-independent pleiotropy across neoplasms and metabolic traits.\"}]","Multi-ancestry GWAS meta-analyses of lung cancer reveal susceptibility loci and elucidate smoking-independent genetic risk | PDF",1789998725,33]