Tao Wang, Albert Einstein College of Medicine
Jee-Young Moon, Albert Einstein College of Medicine
Yiqun Wu, Albert Einstein College of Medicine
Christopher I. Amos, Dartmouth College
Rayjean J. Hung, University of Toronto, Canada
Adonina Tardon, University of Oviedo, Spain
Angeline Andrew, Norris Cotton Cancer Center
Chu Chen, Fred Hutchinson Cancer Research Center
David C. Christiani, Harvard University
Demetrios Albanes, National Cancer Institute
Erik H. F. M. van der Heijden, Radboud University, The Netherlands
Eric Duell, Catalan Institute of Oncology, Spain
Gadi Rennert, Carmel Medical Center, Israel
Gary Goodman, Fred Hutchinson Cancer Research Center
Geoffrey Liu, University of Toronto, Canada
James D. Mckay, International Agency for Research on Cancer, France
Jian-Min Yuan, University of Pittsburgh
John K. Field, University of Liverpool, UK
Jonas Manjer, Lund University, Sweden
Kjell Grankvist, Umeå University , Sweden
Lambertus A. Kiemeney, Radboud University, The Netherlands
Loic Le Marchand, University of Hawaii
M. Dawn Teare, University Of Sheffield, UK
Matthew B. Schabath, H. Lee Moffitt Cancer Center and Research Institute
Mattias Johansson, International Agency for Research on Cancer, France
Melinda C. Aldrich, Vanderbilt University
Michael Davies, University of Liverpool, UK
Mikael Johansson, Umeå University , Sweden
Ming-Sound Tsao, Princess Margaret Cancer Center, Canada
Neil Caporaso, National Cancer Institute
Susanne Arnold, University of KentuckyFollow


Obesity and cigarette smoking are correlated through complex relationships. Common genetic causes may contribute to these correlations. In this study, we selected 241 loci potentially associated with body mass index (BMI) based on the Genetic Investigation of ANthropometric Traits (GIANT) consortium data and calculated a BMI genetic risk score (BMI-GRS) for 17,037 individuals of European descent from the Oncoarray Project of the International Lung Cancer Consortium (ILCCO). Smokers had a significantly higher BMI-GRS than never-smokers (p = 0.016 and 0.010 before and after adjustment for BMI, respectively). The BMI-GRS was also positively correlated with pack-years of smoking (p < 0.001) in smokers. Based on causal network inference analyses, seven and five of 241 SNPs were classified to pleiotropic models for BMI/smoking status and BMI/pack-years, respectively. Among them, three and four SNPs associated with smoking status and pack-years (p < 0.05), respectively, were followed up in the ever-smoking data of the Tobacco, Alcohol and Genetics (TAG) consortium. Among these seven candidate SNPs, one SNP (rs11030104, BDNF) achieved statistical significance after Bonferroni correction for multiple testing, and three suggestive SNPs (rs13021737, TMEM18; rs11583200, ELAVL4; and rs6990042, SGCZ) achieved a nominal statistical significance. Our results suggest that there is a common genetic component between BMI and smoking, and pleiotropy analysis can be useful to identify novel genetic loci of complex phenotypes.

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Notes/Citation Information

Published in PLOS ONE, v. 12, 9, e0185660, p. 1-17.

This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

Due to the large number of authors, only the first 30 and the authors affiliated with the University of Kentucky are listed in the author section above. For the complete list of authors, please download this article or visit:

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Funding Information

This study was funded by National Cancer Institution (, R21 CA202529, TWG YFH).

Related Content

Genotype data analyzed in this study are available through dbGAP. The accession number is phs001273.v2.p1.

journal.pone.0185660.s001.docx (98 kB)
S1 Table. 241 selected SNPs and the AIC values of different DAGs and minimum AIC values of different categories.

journal.pone.0185660.s002.docx (15 kB)
S2 Table. The comparison of associations between different BMI-GRSs and smoking categories (n = 17,037).

journal.pone.0185660.s003.docx (15 kB)
S3 Table. The comparison of partial correlations between different BMI-GRSs and pack-years of smoking in smokers.

journal.pone.0185660.s004.docx (15 kB)
S4 Table. The comparison of associations between seven candidate pleiotropic SNPs and BMI before and after adjustment for smoking phenotypes.