Obesity, metabolic factors and risk of different histological types of lung cancer: A Mendelian randomization study
Carreras-Torres, Robert; Johansson, Mattias; Haycock, Philip C.; Wade, Kaitlin H.; Relton, Caroline L.; Martin, Richard M.; Davey Smith, George; Albanes, Demetrius; Aldrich, Melinda C.; Andrew, Angeline; Arnold, Susanne M.; Bickeböller, Heike; Bojesen, Stig E.; Brunnström, Hans; Manjer, Jonas; Brüske, Irene; Caporaso, Neil E.; Chen, Chu; Christiani, David C.; Christian, W. Jay; Doherty, Jennifer A.; Duell, Eric J.; Field, John K.; Davies, Michael P. A.; Marcus, Michael W.; Goodman, Gary E.; Grankvist, Kjell; Haugen, Aage; Hong, Yun-Chul; Kiemeney, Lambertus A.; van der Heijden, Erik H. F. M.; Kraft, Peter; Johansson, Mikael B.; Lam, Stephen; Landi, Maria Teresa; Lazarus, Philip; Le Marchand, Loïc; Liu, Geoffrey; Melander, Olle; Park, Sungshim L.; Rennert, Gad; Risch, Angela; Haura, Eric B.; Scelo, Ghislaine; Zaridze, David; Mukeriya, Anush; Savić, Milan; Lissowska, Jolanta; Swiatkowska, Beata; Janout, Vladimir; Holcatova, Ivana; Mates, Dana; Schabath, Matthew B.; Shen, Hongbing; Tardon, Adonina; Teare, M Dawn; Woll, Penella; Tsao, Ming-Sound; Wu, Xifeng; Yuan, Jian-Min; Hung, Rayjean J.; Amos, Christopher I.; McKay, James; Brennan, Paul
Background: Assessing the relationship between lung cancer and metabolic conditions is challenging because of the confounding effect of tobacco. Mendelian randomization (MR), or the use of genetic instrumental variables to assess causality, may help to identify the metabolic drivers of lung cancer. Methods and findings We identified genetic instruments for potential metabolic risk factors and evaluated these in relation to risk using 29,266 lung cancer cases (including 11,273 adenocarcinomas, 7,426 squamous cell and 2,664 small cell cases) and 56,450 controls. The MR risk analysis suggested a causal effect of body mass index (BMI) on lung cancer risk for two of the three major histological subtypes, with evidence of a risk increase for squamous cell carcinoma (odds ratio (OR) [95% confidence interval (CI)] = 1.20 [1.01–1.43] and for small cell lung cancer (OR [95%CI] = 1.52 [1.15–2.00]) for each standard deviation (SD) increase in BMI [4.6 kg/m2]), but not for adenocarcinoma (OR [95%CI] = 0.93 [0.79–1.08]) (Pheterogeneity = 4.3x10-3). Additional analysis using a genetic instrument for BMI showed that each SD increase in BMI increased cigarette consumption by 1.27 cigarettes per day (P = 2.1x10-3), providing novel evidence that a genetic susceptibility to obesity influences smoking patterns. There was also evidence that low-density lipoprotein cholesterol was inversely associated with lung cancer overall risk (OR [95%CI] = 0.90 [0.84–0.97] per SD of 38 mg/dl), while fasting insulin was positively associated (OR [95%CI] = 1.63 [1.25–2.13] per SD of 44.4 pmol/l). Sensitivity analyses including a weighted-median approach and MR-Egger test did not detect other pleiotropic effects biasing the main results. Conclusions: Our results are consistent with a causal role of fasting insulin and low-density lipoprotein cholesterol in lung cancer etiology, as well as for BMI in squamous cell and small cell carcinoma. The latter relation may be mediated by a previously unrecognized effect of obesity on smoking behavior.
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Medicine and Health Sciences; Oncology; Cancers and Neoplasms; Lung and Intrathoracic Tumors; Small Cell Lung Cancer; Biology and Life Sciences; Behavior; Habits; Smoking Habits; Biochemistry; Lipids; Cholesterol; Endocrinology; Diabetic Endocrinology; Insulin; Hormones; Physiology; Physiological Parameters; Body Weight; Body Mass Index; Physical Sciences; Mathematics; Statistics (Mathematics); Confidence Intervals; Anatomy; Histology