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DNA甲基化组分析确定了与绝经后乳腺癌易感性相关的加速表观遗传衰老。

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

作者信息

Ambatipudi Srikant, Horvath Steve, Perrier Flavie, Cuenin Cyrille, Hernandez-Vargas Hector, Le Calvez-Kelm Florence, Durand Geoffroy, Byrnes Graham, Ferrari Pietro, Bouaoun Liacine, Sklias Athena, Chajes Véronique, Overvad Kim, Severi Gianluca, Baglietto Laura, Clavel-Chapelon Françoise, Kaaks Rudolf, Barrdahl Myrto, Boeing Heiner, Trichopoulou Antonia, Lagiou Pagona, Naska Androniki, Masala Giovanna, Agnoli Claudia, Polidoro Silvia, Tumino Rosario, Panico Salvatore, Dollé Martijn, Peeters Petra H M, Onland-Moret N Charlotte, Sandanger Torkjel M, Nøst Therese H, Weiderpass Elisabete, Quirós J Ramón, Agudo Antonio, Rodriguez-Barranco Miguel, Huerta Castaño José María, Barricarte Aurelio, Fernández Ander Matheu, Travis Ruth C, Vineis Paolo, Muller David C, Riboli Elio, Gunter Marc, Romieu Isabelle, Herceg Zdenko

机构信息

International Agency for Research on Cancer (IARC), Lyon, France.

Human Genetics and Biostatistics, University of California Los Angeles, Los Angeles, CA 90095-7088, USA.

出版信息

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

DOI:10.1016/j.ejca.2017.01.014
PMID:28259012
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5512160/
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.

摘要

研究目的

绝大多数人类恶性肿瘤都与衰老相关,年龄是癌症风险的有力预测指标。最近,基于DNA甲基化的衰老标志物,即“表观遗传时钟”,已与癌症风险因素相关联。本研究旨在评估表观遗传时钟是否与乳腺癌风险易感性相关,并确定潜在的基于表观遗传学的生物标志物用于风险分层。

方法

在此,我们在欧洲癌症与营养前瞻性调查(EPIC)队列(n = 960)中的一项巢式病例对照研究中,使用Illumina HumanMethylation 450K BeadChip阵列分析DNA甲基化变化,并使用Horvath年龄估计方法计算这些样本的表观遗传年龄。通过将表观遗传年龄对实足年龄进行回归,将内在表观遗传年龄加速(IEAA)估计为残差。

结果

我们观察到IEAA与乳腺癌风险之间存在关联(OR,1.04;95%CI,1.007 - 1.076,P = 0.016)。IEAA每增加一个单位,患乳腺癌的几率增加4%(OR,1.04;95%CI,1.007 - 1.076)。基于绝经状态的分层分析显示,IEAA与绝经后乳腺癌的发生相关(OR,1.07;95%CI,1.020 - 1.11,P = 0.003)。此外,全基因组甲基化分析显示,胞嘧啶 - 磷酸 - 鸟嘌呤(CpG)岛处较高的平均DNA甲基化与乳腺癌发生风险增加相关(每1个标准差的OR = 1.20;95%CI:1.03 - 1.40,P = 0.02),而非岛CpG处的平均甲基化水平在癌症病例和对照之间无差异。

结论

表观遗传年龄加速和CpG岛甲基化与乳腺癌易感性存在微弱但具有统计学意义的关联。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/452e/5512160/259f8664568a/nihms856074f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/452e/5512160/5f1b47a483fa/nihms856074f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/452e/5512160/259f8664568a/nihms856074f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/452e/5512160/5f1b47a483fa/nihms856074f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/452e/5512160/259f8664568a/nihms856074f2.jpg

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