Smoking Modifies Pancreatic Cancer Risk Loci on 2q21.3

This large genome-wide interaction study identifies a susceptibility locus on 2q21.3 that significantly modified PDAC risk by smoking status, providing insight into smoking-associated PDAC, with implications for prevention. Germline variation and smoking are independently associated with pancreatic ductal adenocarcinoma (PDAC). We conducted genome-wide smoking interaction analysis of PDAC using genotype data from four previous genome-wide association studies in individuals of European ancestry (7,937 cases and 11,774 controls). Examination of expression quantitative trait loci data from the Genotype-Tissue Expression Project followed by colocalization analysis was conducted to determine whether there was support for common SNP(s) underlying the observed associations. Statistical tests were two sided and P < 5 × 10–8 was considered statistically significant. Genome-wide significant evidence of qualitative interaction was identified on chr2q21.3 in intron 5 of the transmembrane protein 163 (TMEM163) and upstream of the cyclin T2 (CCNT2). The most significant SNP using the Empirical Bayes method, in this region that included 45 significantly associated SNPs, was rs1818613 [per allele OR in never smokers 0.87, 95% confidence interval (CI), 0.82–0.93; former smokers 1.00, 95% CI, 0.91–1.07; current smokers 1.25, 95% CI 1.12–1.40, Pinteraction = 3.08 × 10–9). Examination of the Genotype-Tissue Expression Project data demonstrated an expression quantitative trait locus in this region for TMEM163 and CCNT2 in several tissue types. Colocalization analysis supported a shared SNP, rs842357, in high linkage disequilibrium with rs1818613 (r2 = 0. 94) driving both the observed interaction and the expression quantitative trait loci signals. Future studies are needed to confirm and understand the differential biologic mechanisms by smoking status that contribute to our PDAC findings. Significance: This large genome-wide interaction study identifies a susceptibility locus on 2q21.3 that significantly modified PDAC risk by smoking status, providing insight into smoking-associated PDAC, with implications for prevention.

[1]  Yousheng Shu,et al.  Hypothalamic proteome changes in response to nicotine and its withdrawal are potentially associated with alteration in body weight. , 2020, Journal of proteomics.

[2]  R. Cormier,et al.  Role of ion channels in gastrointestinal cancer , 2019, World journal of gastroenterology.

[3]  D. Sumi,et al.  Toxicometallomics of Cadmium, Manganese and Arsenic with Special Reference to the Roles of Metal Transporters , 2019, Toxicological research.

[4]  W. Bamlet,et al.  Analysis of Heritability and Genetic Architecture of Pancreatic Cancer: A PanC4 Study , 2019, Cancer Epidemiology, Biomarkers & Prevention.

[5]  M. Kanai,et al.  GWAS of smoking behaviour in 165,436 Japanese people reveals seven new loci and shared genetic architecture , 2019, Nature Human Behaviour.

[6]  Prashanth Rawla,et al.  Epidemiology of Pancreatic Cancer: Global Trends, Etiology and Risk Factors , 2019, World journal of oncology.

[7]  Ganfeng Luo,et al.  Global Patterns and Trends in Pancreatic Cancer Incidence: Age, Period, and Birth Cohort Analysis , 2019, Pancreas.

[8]  Dajiang J. Liu,et al.  Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use , 2018, Nature Genetics.

[9]  J. Kaprio,et al.  Genome‐wide association study in Finnish twins highlights the connection between nicotine addiction and neurotrophin signaling pathway , 2018, Addiction biology.

[10]  W. Hahn,et al.  Germline cancer susceptibility gene variants, somatic second hits, and survival outcomes in patients with resected pancreatic cancer , 2018, Genetics in Medicine.

[11]  Raymond M. Moore,et al.  Association Between Inherited Germline Mutations in Cancer Predisposition Genes and Risk of Pancreatic Cancer , 2018, JAMA.

[12]  K. Krüger,et al.  Immune-regulating effects of exercise on cigarette smoke-induced inflammation , 2018, Journal of inflammation research.

[13]  S. Devesa,et al.  Pancreatic cancer incidence trends: evidence from the Surveillance, Epidemiology and End Results (SEER) population-based data. , 2018, International journal of epidemiology.

[14]  Nilanjan Chatterjee,et al.  Using imputed genotype data in the joint score tests for genetic association and gene–environment interactions in case‐control studies , 2018, Genetic epidemiology.

[15]  A. Kulminski,et al.  Strong impact of natural-selection–free heterogeneity in genetics of age-related phenotypes , 2018, Aging.

[16]  Peter Kraft,et al.  Genome-wide meta-analysis identifies five new susceptibility loci for pancreatic cancer , 2018, Nature Communications.

[17]  Erdogan Taskesen,et al.  Functional mapping and annotation of genetic associations with FUMA , 2017, Nature Communications.

[18]  K. Kiselyov,et al.  The mucolipin-1 (TRPML1) ion channel, transmembrane-163 (TMEM163) protein, and lysosomal zinc handling. , 2017, Frontiers in bioscience.

[19]  D. Silverman,et al.  Serum C-peptide, Total and High Molecular Weight Adiponectin, and Pancreatic Cancer: Do Associations Differ by Smoking? , 2017, Cancer Epidemiology, Biomarkers & Prevention.

[20]  Ayellet V. Segrè,et al.  Colocalization of GWAS and eQTL Signals Detects Target Genes , 2016, bioRxiv.

[21]  Alison P. Klein,et al.  Three new pancreatic cancer susceptibility signals identified on chromosomes 1q32.1, 5p15.33 and 8q24.21 , 2016, Oncotarget.

[22]  Benjamin Y Hayden,et al.  Dorsal Anterior Cingulate Cortex: A Bottom-Up View. , 2016, Annual review of neuroscience.

[23]  Ming D. Li,et al.  Converging Findings from Linkage and Association Analyses on Susceptibility Genes for Smoking and Other Addictions , 2016, Molecular Psychiatry.

[24]  Gabor T. Marth,et al.  A global reference for human genetic variation , 2015, Nature.

[25]  A. Jemal,et al.  Deaths Due to Cigarette Smoking for 12 Smoking-Related Cancers in the United States. , 2015, JAMA internal medicine.

[26]  Y. Orlov,et al.  Association Analysis of Genetic Variants with Type 2 Diabetes in a Mongolian Population in China , 2015, Journal of diabetes research.

[27]  Raffaele Pezzilli,et al.  Common variation at 2 p 13 . 3 , 3 q 29 , 7 p 13 and 17 q 25 . 1 associated with susceptibility to pancreatic cancer , 2022 .

[28]  G. Petersen,et al.  Gene-by-Environment Interactions in Pancreatic Cancer: Implications for Prevention , 2015, The Yale journal of biology and medicine.

[29]  G. Kempermann.  Faculty Opinions recommendation of Human genomics. The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans. , 2015 .

[30]  Michael Q. Zhang,et al.  Integrative analysis of 111 reference human epigenomes , 2015, Nature.

[31]  S. Lukas,et al.  Insula–Dorsal Anterior Cingulate Cortex Coupling is Associated with Enhanced Brain Reactivity to Smoking Cues , 2015, Neuropsychopharmacology.

[32]  Yusuke Nakamura,et al.  Genome-wide association study identifies multiple susceptibility loci for pancreatic cancer , 2014, Nature Genetics.

[33]  Chuong B. Do,et al.  Large-scale meta-analysis of genome-wide association data identifies six new risk loci for Parkinson’s disease , 2014, Nature Genetics.

[34]  Olivier Delaneau,et al.  Integrating sequence and array data to create an improved 1000 Genomes Project haplotype reference panel , 2014, Nature Communications.

[35]  Salvatore Panico,et al.  Axonal guidance signaling pathway interacting with smoking in modifying the risk of pancreatic cancer: a gene- and pathway-based interaction analysis of GWAS data. , 2014, Carcinogenesis.

[36]  C. Wallace,et al.  Bayesian Test for Colocalisation between Pairs of Genetic Association Studies Using Summary Statistics , 2013, PLoS genetics.

[37]  R. Bretzel,et al.  Diabetes mellitus secondary to pancreatic diseases (Type 3c)--are we neglecting an important disease? , 2013, European journal of internal medicine.

[38]  S. K. Aggarwal,et al.  Genome-Wide Association Study for Type 2 Diabetes in Indians Identifies a New Susceptibility Locus at 2q21 , 2013, Diabetes.

[39]  Nilanjan Chatterjee,et al.  Likelihood ratio test for detecting gene (G)-environment (E) interactions under an additive risk model exploiting G-E independence for case-control data. , 2012, American journal of epidemiology.

[40]  A. Miller,et al.  Cigarette smoking and pancreatic cancer: an analysis from the International Pancreatic Cancer Case-Control Consortium (Panc4). , 2012, Annals of oncology : official journal of the European Society for Medical Oncology.

[41]  Jaeil Ahn,et al.  Testing gene-environment interaction in large-scale case-control association studies: possible choices and comparisons. , 2012, American journal of epidemiology.

[42]  Manolis Kellis,et al.  HaploReg: a resource for exploring chromatin states, conservation, and regulatory motif alterations within sets of genetically linked variants , 2011, Nucleic Acids Res..

[43]  J. Marchini,et al.  Genotype imputation for genome-wide association studies , 2010, Nature Reviews Genetics.

[44]  Wei Zheng,et al.  A genome-wide association study identifies pancreatic cancer susceptibility loci on chromosomes 13q22.1, 1q32.1 and 5p15.33 , 2010, Nature Genetics.

[45]  J. Boardman,et al.  Trends in the Genetic Influences on Smoking , 2010, Journal of health and social behavior.

[46]  B. Lau,et al.  Importance of Age of Onset in Pancreatic Cancer Kindreds , 2010, Journal of the National Cancer Institute.

[47]  Geoffrey S. Tobias,et al.  Genome-wide association study identifies variants in the ABO locus associated with susceptibility to pancreatic cancer , 2009, Nature Genetics.

[48]  Geoffrey S. Tobias,et al.  Cigarette smoking and pancreatic cancer: a pooled analysis from the pancreatic cancer cohort consortium. , 2009, American journal of epidemiology.

[49]  Bhramar Mukherjee,et al.  Exploiting Gene‐Environment Independence for Analysis of Case–Control Studies: An Empirical Bayes‐Type Shrinkage Estimator to Trade‐Off between Bias and Efficiency , 2008, Biometrics.

[50]  S. Batra,et al.  Cigarette smoke-induced pancreatic damage—experimental data , 2008, Langenbeck's Archives of Surgery.

[51]  Jacqueline Burré,et al.  Identification and characterization of SV31, a novel synaptic vesicle membrane protein and potential transporter , 2007, Journal of neurochemistry.

[52]  Manuel A. R. Ferreira,et al.  PLINK: a tool set for whole-genome association and population-based linkage analyses. , 2007, American journal of human genetics.

[53]  Peter Kraft,et al.  Exploiting Gene-Environment Interaction to Detect Genetic Associations , 2007, Human Heredity.

[54]  Nilanjan Chatterjee,et al.  Semiparametric maximum likelihood estimation exploiting gene-environment independence in case-control studies , 2005 .

[55]  Jack A. Taylor,et al.  Non-hierarchical logistic models and case-only designs for assessing susceptibility in population-based case-control studies. , 1994, Statistics in medicine.