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Eur J Cancer. 2017 Apr;75:299-307. doi: 10.1016/j.ejca.2017.01.014. Epub 2017 Feb 28.

DNA methylome analysis identifies accelerated epigenetic ageing associated with postmenopausal breast cancer susceptibility.

Author information

1
International Agency for Research on Cancer (IARC), Lyon, France.
2
Human Genetics and Biostatistics, University of California Los Angeles, Los Angeles, CA 90095-7088, USA.
3
Section for Epidemiology, Department of Public Health, Aarhus University, Aarhus, Denmark.
4
Inserm, Centre de Recherche en Epidémiologie et Santé des Populations (CESP, U1018), Université Paris-Saclay, Université Paris-Sud, UVSQ, Institut Gustave Roussy, Villejuif, France; Human Genetics Foundation (HuGeF), Torino, Italy; Cancer Epidemiology Centre, Cancer Council Victoria and Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourn, Australia.
5
Inserm, Centre de Recherche en Epidémiologie et Santé des Populations (CESP, U1018), Université Paris-Saclay, Université Paris-Sud, UVSQ, Institut Gustave Roussy, Villejuif, France; Cancer Epidemiology Centre, Cancer Council Victoria and Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourn, Australia.
6
Inserm, Centre de Recherche en Epidémiologie et Santé des Populations (CESP, U1018), Université Paris-Saclay, Université Paris-Sud, UVSQ, Institut Gustave Roussy, Villejuif, France.
7
Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
8
Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal, Germany.
9
Hellenic Health Foundation, Athens, Greece; 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.
10
Hellenic Health Foundation, Athens, Greece; 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; Department of Epidemiology, Harvard School of Public Health, Boston, USA.
11
Molecular and Nutritional Epidemiology Unit, Cancer Research and Prevention Institute - ISPO, Florence, Italy.
12
Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale Tumori, Milano, Italy.
13
Human Genetics Foundation (HuGeF), Torino, Italy.
14
Cancer Registry and Histopathology Unit, "Civic M.P. Arezzo" Hospital, ASP Ragusa, Italy.
15
Dipartimento di Medicina Clinica e Chirurgia, Federico II University, Naples, Italy.
16
Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands.
17
Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands; MRC-PHE Centre for Environment and Health, Dept of Epidemiology and Biostatistics, School of Public Health, Imperial College, London, UK.
18
Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands.
19
Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, The Arctic University of Norway, Tromsø, Norway.
20
Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, The Arctic University of Norway, Tromsø, Norway; Department of Research, Cancer Registry of Norway, Institute of Population-Based Cancer Research, Oslo, Norway; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Genetic Epidemiology Group, Folkhälsan Research Center, Helsinki, Finland.
21
Public Health Directorate, Asturias, Spain.
22
Unit of Nutrition and Cancer, Cancer Epidemiology Research Program, Catalan Institute of Oncology-IDIBELL, L'Hospitalet de Llobregat, Barcelona, Spain.
23
Escuela Andaluza de Salud Pública, Instituto de Investigación Biosanitaria ibsn Granada, Hospitales Universitarios de Granada/Universidad de Granada, Granada, Spain; CIBER de Epidemiología y Salud Pública (CIBERESP), Spain.
24
Department of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, Murcia, Spain; CIBER de Epidemiología y Salud Pública (CIBERESP), Spain.
25
Navarra Public Health Institute, Pamplona, Spain; Navarra Institute for Health Research (IdiSNA) Pamplona, Spain; CIBER de Epidemiología y Salud Pública (CIBERESP), Spain.
26
Cellular Oncology Group, Biodonostia Health Research Institute, Paseo Dr. Beguiristain s/n, San Sebastian, Spain; IKERBASQUE, Basque Foundation, Spain.
27
Cancer Epidemiology Unit, Nuffield Department of Population Health University of Oxford, Oxford UK.
28
School of Public Health, Imperial College London, London, UK.
29
International Agency for Research on Cancer (IARC), Lyon, France. Electronic address: herceg@iarc.fr.

Abstract

AIM OF THE STUDY:

A 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.

METHODS:

Here, 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.

RESULTS:

We 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.

CONCLUSION:

Epigenetic age acceleration and CpG island methylation have a weak, but statistically significant, association with breast cancer susceptibility.

KEYWORDS:

Age acceleration; Biomarkers; Breast cancer; DNA methylation; Epigenomics; Prospective studies

PMID:
28259012
PMCID:
PMC5512160
DOI:
10.1016/j.ejca.2017.01.014
[Indexed for MEDLINE]
Free PMC Article

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