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Published in: Breast Cancer Research 1/2019

Open Access 01-12-2019 | Breast Cancer | Research article

Blood DNA methylation and breast cancer risk: a meta-analysis of four prospective cohort studies

Authors: Clara Bodelon, Srikant Ambatipudi, Pierre-Antoine Dugué, Annelie Johansson, Joshua N. Sampson, Belynda Hicks, Eric Karlins, Amy Hutchinson, Cyrille Cuenin, Veronique Chajès, Melissa C. Southey, Isabelle Romieu, Graham G. Giles, Dallas English, Silvia Polidoro, Manuela Assumma, Laura Baglietto, Paolo Vineis, Gianluca Severi, Zdenko Herceg, James M. Flanagan, Roger L. Milne, Montserrat Garcia-Closas

Published in: Breast Cancer Research | Issue 1/2019

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Abstract

Background

Environmental and genetic factors play an important role in the etiology of breast cancer. Several small blood-based DNA methylation studies have reported risk associations with methylation at individual CpGs and average methylation levels; however, these findings require validation in larger prospective cohort studies. To investigate the role of blood DNA methylation on breast cancer risk, we conducted a meta-analysis of four prospective cohort studies, including a total of 1663 incident cases and 1885 controls, the largest study of blood DNA methylation and breast cancer risk to date.

Methods

We assessed associations with methylation at 365,145 CpGs present in the HumanMethylation450 (HM450K) Beadchip, after excluding CpGs that did not pass quality controls in all studies. Each of the four cohorts estimated odds ratios (ORs) and 95% confidence intervals (CI) for the association between each individual CpG and breast cancer risk. In addition, each study assessed the association between average methylation measures and breast cancer risk, adjusted and unadjusted for cell-type composition. Study-specific ORs were combined using fixed-effect meta-analysis with inverse variance weights. Stratified analyses were conducted by age at diagnosis (< 50, ≥ 50), estrogen receptor (ER) status (+/−), and time since blood collection (< 5, 5–10, > 10 years). The false discovery rate (q value) was used to account for multiple testing.

Results

The average age at blood draw ranged from 52.2 to 62.2 years across the four cohorts. Median follow-up time ranged from 6.6 to 8.4 years. The methylation measured at individual CpGs was not associated with breast cancer risk (q value > 0.59). In addition, higher average methylation level was not associated with risk of breast cancer (OR = 0.94, 95% CI = 0.85, 1.05; P = 0.26; P for study heterogeneity = 0.86). We found no evidence of modification of this association by age at diagnosis (P = 0.17), ER status (P = 0.88), time since blood collection (P = 0.98), or CpG location (P = 0.98).

Conclusions

Our data indicate that DNA methylation measured in the blood prior to breast cancer diagnosis in predominantly postmenopausal women is unlikely to be associated with substantial breast cancer risk on the HM450K array. Larger studies or with greater methylation coverage are needed to determine if associations exist between blood DNA methylation and breast cancer risk.
Appendix
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Metadata
Title
Blood DNA methylation and breast cancer risk: a meta-analysis of four prospective cohort studies
Authors
Clara Bodelon
Srikant Ambatipudi
Pierre-Antoine Dugué
Annelie Johansson
Joshua N. Sampson
Belynda Hicks
Eric Karlins
Amy Hutchinson
Cyrille Cuenin
Veronique Chajès
Melissa C. Southey
Isabelle Romieu
Graham G. Giles
Dallas English
Silvia Polidoro
Manuela Assumma
Laura Baglietto
Paolo Vineis
Gianluca Severi
Zdenko Herceg
James M. Flanagan
Roger L. Milne
Montserrat Garcia-Closas
Publication date
01-12-2019
Publisher
BioMed Central
Published in
Breast Cancer Research / Issue 1/2019
Electronic ISSN: 1465-542X
DOI
https://doi.org/10.1186/s13058-019-1145-9

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Webinar | 19-02-2024 | 17:30 (CET)

Keynote webinar | Spotlight on antibody–drug conjugates in cancer

Antibody–drug conjugates (ADCs) are novel agents that have shown promise across multiple tumor types. Explore the current landscape of ADCs in breast and lung cancer with our experts, and gain insights into the mechanism of action, key clinical trials data, existing challenges, and future directions.

Dr. Véronique Diéras
Prof. Fabrice Barlesi
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