Sachelly Julián-Serrano1, Fangcheng Yuan1, William Wheeler2, Beben Benyamin3,4, Mitchell J Machiela1, Alan A Arslan5, Laura E Beane-Freeman1, Paige M Bracci6, Eric J Duell7,8,9, Mengmeng Du10, Steven Gallinger11, Graham G Giles12,13,14, Phyllis J Goodman15, Charles Kooperberg16, Loic Le Marchand17, Rachel E Neale18, Xiao-Ou Shu19, Stephen K Van Den Eeden20, Kala Visvanathan21, Wei Zheng19, Demetrius Albanes1, Gabriella Andreotti1, Eva Ardanaz22,23,24, Ana Babic25, Sonja I Berndt1, Lauren K Brais25, Paul Brennan26, Bas Bueno-de-Mesquita27, Julie E Buring28, Stephen J Chanock1, Erica J Childs29, Charles C Chung1, Eleonora Fabiánová30, Lenka Foretová31, Charles S Fuchs32, J Michael Gaziano33, Manuel Gentiluomo34,35, Edward L Giovannucci25, Michael G Goggins36, Thilo Hackert37, Patricia Hartge1, Manal M Hassan38, Ivana Holcátová39, Elizabeth A Holly6, Rayjean I Hung11, Vladimir Janout40, Robert C Kurtz41, I-Min Lee28,42, Núria Malats43, David McKean29, Roger L Milne12,13,14, Christina C Newton44, Ann L Oberg45, Sandra Perdomo26, Ulrike Peters16, Miquel Porta46, Nathaniel Rothman1, Matthias B Schulze47,48, Howard D Sesso28, Debra T Silverman1, Ian M Thompson49, Jean Wactawski-Wende50, Elisabete Weiderpass16, Nicolas Wenstzensen1, Emily White16, Lynne R Wilkens17, Herbert Yu17, Anne Zeleniuch-Jacquotte51, Jun Zhong1, Peter Kraft42,52, Dounghui Li53, Peter T Campbell44, Gloria M Petersen45, Brian M Wolpin25, Harvey A Risch54, Laufey T Amundadottir1, Alison P Klein29,36, Kai Yu1, Rachael Z Stolzenberg-Solomon1. 1. Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA. 2. Information Management Services, Silver Spring, MD, USA. 3. Australian Centre for Precision Health, Allied Health and Human Performance, University of South Australia, Adelaide, Australia. 4. South Australian Health and Medical Research Institute, Adelaide, Australia. 5. Department of Obstetrics and Gynecology, New York University School of Medicine, New York, NY, USA. 6. Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA. 7. Unit of Biomarkers and Susceptibility, Oncology Data Analytics Program, Catalan Institute of Oncology, L'Hospitalet de Llobregat, Barcelona, Spain. 8. Colorectal Cancer Group, ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain. 9. Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain. 10. Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA. 11. Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Canada. 12. Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia. 13. Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia. 14. Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Australia. 15. SWOG Statistical Center, Fred Hutchinson Cancer Research Center, Seattle, WA, USA. 16. Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA. 17. Department of Epidemiology, University of Hawaii Cancer Center, Honolulu, HI, USA. 18. Population Health Department, QIMR Berghofer Medical Research Institute, Brisbane, Australia. 19. Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA. 20. Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA. 21. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA. 22. Navarra Public Health Institute, Pamplona, Spain. 23. IdiSNA, Navarra Institute for Health Research, Pamplona, Spain. 24. CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain. 25. Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA. 26. International Agency for Research on Cancer (IARC), Lyon, France. 27. Department for Determinants of Chronic Diseases, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands. 28. Division of Preventive Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. 29. Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD, USA. 30. Specialized Institute of Hygiene and Epidemiology, Banska Bystrica, Slovakia. 31. Department of Cancer Epidemiology and Genetics, Masaryk Memorial Cancer Institute, Brno, Czech Republic. 32. Yale Cancer Center and Smilow Cancer Hospital, New Haven, CT, USA. 33. Division of Aging, Brigham and Women's Hospital, Boston, MA, USA. 34. Department of Biology, University of Pisa, Italy. 35. Genomic Epidemiology Group, German Cancer Research Center, (DKFZ), Heidelberg, Germany. 36. Department of Pathology, Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins School of Medicine, Baltimore, MD, USA. 37. Department of General, Visceral and Transplantation Surgery, Heidelberg University Hospital, Heidelberg, Germany. 38. Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA. 39. Institute of Public Health and Preventive Medicine, Second Faculty of Medicine, Charles University, Prague, Czech Republic. 40. Faculty of Health Sciences, University of Olomouc, Olomouc, Czech Republic. 41. Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA. 42. Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA. 43. Genetic and Molecular Epidemiology Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain. 44. Department of Population Science, American Cancer Society, Atlanta, GA, USA. 45. Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN, USA. 46. Hospital del Mar Institute of Medical Research (IMIM), Universitat Autònoma de Barcelona, Barcelona, Spain. 47. Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany. 48. Institute of Nutritional Science, University of Potsdam, Nuthetal, Germany. 49. CHRISTUS Santa Rosa Hospital-Medical Center, San Antonio, TX, USA. 50. Department of Epidemiology and Environmental Health, University at Buffalo, Buffalo, NY, USA. 51. Department of Population Health and Perlmutter Cancer Center, New York University School of Medicine, New York, NY, USA. 52. Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA. 53. Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. 54. Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, CT, USA.
Abstract
BACKGROUND: Epidemiological studies have suggested positive associations for iron and red meat intake with risk of pancreatic ductal adenocarcinoma (PDAC). Inherited pathogenic variants in genes involved in the hepcidin-regulating iron metabolism pathway are known to cause iron overload and hemochromatosis. OBJECTIVES: The objective of this study was to determine whether common genetic variation in the hepcidin-regulating iron metabolism pathway is associated with PDAC. METHODS: We conducted a pathway analysis of the hepcidin-regulating genes using single nucleotide polymorphism (SNP) summary statistics generated from 4 genome-wide association studies in 2 large consortium studies using the summary data-based adaptive rank truncated product method. Our population consisted of 9253 PDAC cases and 12,525 controls of European descent. Our analysis included 11 hepcidin-regulating genes [bone morphogenetic protein 2 (BMP2), bone morphogenetic protein 6 (BMP6), ferritin heavy chain 1 (FTH1), ferritin light chain (FTL), hepcidin (HAMP), homeostatic iron regulator (HFE), hemojuvelin (HJV), nuclear factor erythroid 2-related factor 2 (NRF2), ferroportin 1 (SLC40A1), transferrin receptor 1 (TFR1), and transferrin receptor 2 (TFR2)] and their surrounding genomic regions (±20 kb) for a total of 412 SNPs. RESULTS: The hepcidin-regulating gene pathway was significantly associated with PDAC (P = 0.002), with the HJV, TFR2, TFR1, BMP6, and HAMP genes contributing the most to the association. CONCLUSIONS: Our results support that genetic susceptibility related to the hepcidin-regulating gene pathway is associated with PDAC risk and suggest a potential role of iron metabolism in pancreatic carcinogenesis. Further studies are needed to evaluate effect modification by intake of iron-rich foods on this association. Published by Oxford University Press on behalf of the American Society for Nutrition 2021.
BACKGROUND: Epidemiological studies have suggested positive associations for iron and red meat intake with risk of pancreatic ductal adenocarcinoma (PDAC). Inherited pathogenic variants in genes involved in the hepcidin-regulating iron metabolism pathway are known to cause iron overload and hemochromatosis. OBJECTIVES: The objective of this study was to determine whether common genetic variation in the hepcidin-regulating iron metabolism pathway is associated with PDAC. METHODS: We conducted a pathway analysis of the hepcidin-regulating genes using single nucleotide polymorphism (SNP) summary statistics generated from 4 genome-wide association studies in 2 large consortium studies using the summary data-based adaptive rank truncated product method. Our population consisted of 9253 PDAC cases and 12,525 controls of European descent. Our analysis included 11 hepcidin-regulating genes [bone morphogenetic protein 2 (BMP2), bone morphogenetic protein 6 (BMP6), ferritin heavy chain 1 (FTH1), ferritin light chain (FTL), hepcidin (HAMP), homeostatic iron regulator (HFE), hemojuvelin (HJV), nuclear factor erythroid 2-related factor 2 (NRF2), ferroportin 1 (SLC40A1), transferrin receptor 1 (TFR1), and transferrin receptor 2 (TFR2)] and their surrounding genomic regions (±20 kb) for a total of 412 SNPs. RESULTS: The hepcidin-regulating gene pathway was significantly associated with PDAC (P = 0.002), with the HJV, TFR2, TFR1, BMP6, and HAMP genes contributing the most to the association. CONCLUSIONS: Our results support that genetic susceptibility related to the hepcidin-regulating gene pathway is associated with PDAC risk and suggest a potential role of iron metabolism in pancreatic carcinogenesis. Further studies are needed to evaluate effect modification by intake of iron-rich foods on this association. Published by Oxford University Press on behalf of the American Society for Nutrition 2021.
Entities:
Keywords:
epidemiology; genetic susceptibility; hepcidin; iron metabolism pathway; pancreatic cancer
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