Amos, C. I., Wu, X., Broderick, P., Gorlov, I. P., Gu, J., Eisen, T. et al. Genome-wide association scan of tag SNPs identifies a susceptibility locus for lung cancer at 15q25.1. Nat. Genet. 40, 616-622

Department of Epidemiology, The University of Texas M.D. Anderson Cancer Center, Houston, Texas 77030, USA.
Nature Genetics (Impact Factor: 29.35). 06/2008; 40(5):616-22. DOI: 10.1038/ng.109
Source: PubMed


To identify risk variants for lung cancer, we conducted a multistage genome-wide association study. In the discovery phase, we analyzed 315,450 tagging SNPs in 1,154 current and former (ever) smoking cases of European ancestry and 1,137 frequency-matched, ever-smoking controls from Houston, Texas. For replication, we evaluated the ten SNPs most significantly associated with lung cancer in an additional 711 cases and 632 controls from Texas and 2,013 cases and 3,062 controls from the UK. Two SNPs, rs1051730 and rs8034191, mapping to a region of strong linkage disequilibrium within 15q25.1 containing PSMA4 and the nicotinic acetylcholine receptor subunit genes CHRNA3 and CHRNA5, were significantly associated with risk in both replication sets. Combined analysis yielded odds ratios of 1.32 (P < 1 10-
17) for both SNPs. Haplotype analysis was consistent with there being a single risk variant in this region. We conclude that variation in a region of 15q25.1 containing nicotinic acetylcholine receptors genes contributes to lung cancer risk.

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    • "Large-scale multinational genome-wide association studies (GWAS) of the genetic variation associated with lung cancer initially found that the 5p15.33, 6p21.33, and 15q25 regions were associated with risk of lung cancer among smokers (Amos et al., 2008; Hung et al., 2008). Interestingly, unique regions including 10q25.2, 6q22.2 and 6p21.32 were associated with lung cancer risk in those who had never smoked (Lan et al., 2012), suggesting that the risk variants for non-smoking related lung cancer were distinct from those for smoking related lung cancer. "

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    • "In Section 4, we first show the ability of the proposed methodology to detect relevant biomarkers using simulated data and also compare results to existing approaches. We then illustrate an application of the method to the lung cancer data of [2]. We conclude the paper with a brief discussion in Section 5. "
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    • "These variants may have played a small role in the genetic etiology of weight throughout the history of our species, but may explain a larger proportion of the individual susceptibility to obesity in the modern environment of unrestricted access to processed food. A variety of other similar situations could be imagined, such as the interplay between addiction, tobacco use and lung cancer (Amos et al., 2008). In our simulations, we explore a range of parameter space in which the “modern” environment perturbs from 1 to 20% of the causal variants. "
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