DNA methylome analysis identifies accelerated epigenetic ageing associated with postmenopausal breast cancer susceptibility |
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| Affiliation: | 1. Nutrition and Metabolism Section, International Agency for Research on Cancer, Lyon;2. Institut Gustave Roussy, Villejuif;3. Université Paris-Saclay, Université Paris-Sud, UVSQ, CESP, INSERM, Villejuif, France;4. Hellenic Health Foundation, Athens;5. WHO Collaborating Center for Nutrition and Health, Unit of Nutritional Epidemiology and Nutrition in Public Health, Department of Hygiene, Epidemiology and Medical Statistics, University of Athens Medical School, Athens, Greece;6. Department of Epidemiology, Harvard School of Public Health, Boston, USA;7. The German Cancer Research Center (DKFZ), Heidelberg, Germany;8. Dipartimento Di Medicina Clinica E Chirurgia, Federico II University, Naples;9. Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan;10. Cancer Risk Factors and Life-Style Epidemiology Unit, Cancer Research and Prevention Institute – ISPO, Florence, Italy;11. Department for Determinants of Chronic Diseases (DCD), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands;12. Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London, UK;13. Department of Social & Preventive Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia;14. Julius Center for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, The Netherlands;15. Department of Nutrition, Institute of Basic Medical Sciences, University of Oslo, Oslo;16. Department of Community Medicine, University of Tromsø-UiT—The Artic University of Norway, Tromsø, Norway;17. Navarra Public Health Institute, Pamplona;18. Navarra Institute for Health Research (IdiSNA), Pamplona;19. CIBER Epidemiology and Public Health CIBERESP, Madrid;20. Escuela Andaluza de Salud Pública, Instituto de Investigación Biosanitaria ibs.Granada, Hospitales Universitarios de Granada, Granada;21. Universidad de Granada, Granada;22. Public Health Directorate, Asturias;23. Public Health Division of Gipuzkoa, Health Department, Basque Region, San Sebastian, Spain;24. Public Health and Clinical Medicine, Nutritional Research, Umeå University, Umeå, Sweden;25. The Cancer Epidemiology Unit, University of Oxford, Oxford;26. University of Cambridge School of Clinical Medicine, Cambridge, UK;2. Emory University School of Medicine, Atlanta, Georgia;3. Yale University School of Medicine, New Haven, Connecticut;4. Yale University School of Nursing, Orange, Connecticut;1. Genetic Epidemiology Laboratory, Department of Clinical Pathology, The University of Melbourne, VIC 3010, Australia;2. Olivia Newton-John Cancer Research Institute, School of Cancer Medicine, La Trobe University, Heidelberg, VIC 3084, Australia;3. Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton 3168, Australia;4. Colorectal Oncogenomics Group, Department of Clinical Pathology, University of Melbourne Centre for Cancer Research, The University of Melbourne, Australia;5. Centre for Epidemiology and Biostatistics, The University of Melbourne, VIC 3010, Australia;6. Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, VIC 3004, Australia;7. Melbourne Bioinformatics, The University of Melbourne, Parkville, VIC, Australia |
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| Abstract: | 
Aim of the studyA vast majority of human malignancies are associated with ageing, and age is a strong predictor of cancer risk. Recently, DNA methylation-based marker of ageing, known as ‘epigenetic clock’, has been linked with cancer risk factors. This study aimed to evaluate whether the epigenetic clock is associated with breast cancer risk susceptibility and to identify potential epigenetics-based biomarkers for risk stratification.MethodsHere, we profiled DNA methylation changes in a nested case–control study embedded in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort (n = 960) using the Illumina HumanMethylation 450K BeadChip arrays and used the Horvath age estimation method to calculate epigenetic age for these samples. Intrinsic epigenetic age acceleration (IEAA) was estimated as the residuals by regressing epigenetic age on chronological age.ResultsWe observed an association between IEAA and breast cancer risk (OR, 1.04; 95% CI, 1.007–1.076, P = 0.016). One unit increase in IEAA was associated with a 4% increased odds of developing breast cancer (OR, 1.04; 95% CI, 1.007–1.076). Stratified analysis based on menopausal status revealed that IEAA was associated with development of postmenopausal breast cancers (OR, 1.07; 95% CI, 1.020–1.11, P = 0.003). In addition, methylome-wide analyses revealed that a higher mean DNA methylation at cytosine-phosphate-guanine (CpG) islands was associated with increased risk of breast cancer development (OR per 1 SD = 1.20; 95 %CI: 1.03–1.40, P = 0.02) whereas mean methylation levels at non-island CpGs were indistinguishable between cancer cases and controls.ConclusionEpigenetic age acceleration and CpG island methylation have a weak, but statistically significant, association with breast cancer susceptibility. |
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| Keywords: | DNA methylation Epigenomics Age acceleration Breast cancer Biomarkers Prospective studies |
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