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Epigenome-wide association study for lifetime estrogen exposure identifies an epigenetic signature associated with breast cancer risk.

ABSTRACT: BACKGROUND:It is well established that estrogens and other hormonal factors influence breast cancer susceptibility. We hypothesized that a woman's total lifetime estrogen exposure accumulates changes in DNA methylation, detectable in the blood, which could be used in risk assessment for breast cancer. METHODS:An estimated lifetime estrogen exposure (ELEE) model was defined using epidemiological data from EPIC-Italy (n?=?31,864). An epigenome-wide association study (EWAS) of ELEE was performed using existing Illumina HumanMethylation450K Beadchip (HM450K) methylation data obtained from EPIC-Italy blood DNA samples (n?=?216). A methylation index (MI) of ELEE based on 31 CpG sites was developed using HM450K data from EPIC-Italy and the Generations Study and evaluated for association with breast cancer risk in an independent dataset from the Generations Study (n?=?440 incident breast cancer cases matched to 440 healthy controls) using targeted bisulfite sequencing. Lastly, a meta-analysis was conducted including three additional cohorts, consisting of 1187 case-control pairs. RESULTS:We observed an estimated 5% increase in breast cancer risk per 1-year longer ELEE (OR?=?1.05, 95% CI 1.04-1.07, P =?3?×?10-12) in EPIC-Italy. The EWAS identified 694 CpG sites associated with ELEE (FDR Q

SUBMITTER: Johansson A

PROVIDER: S-EPMC6492393 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Epigenome-wide association study for lifetime estrogen exposure identifies an epigenetic signature associated with breast cancer risk.

Johansson Annelie A Palli Domenico D Masala Giovanna G Grioni Sara S Agnoli Claudia C Tumino Rosario R Giurdanella Maria Concetta MC Fasanelli Francesca F Sacerdote Carlotta C Panico Salvatore S Mattiello Amalia A Polidoro Silvia S Jones Michael E ME Schoemaker Minouk J MJ Orr Nick N Tomczyk Katarzyna K Johnson Nichola N Fletcher Olivia O Perduca Vittorio V Baglietto Laura L Dugué Pierre-Antoine PA Southey Melissa C MC Giles Graham G GG English Dallas R DR Milne Roger L RL Severi Gianluca G Ambatipudi Srikant S Cuenin Cyrille C Chajès Veronique V Romieu Isabelle I Herceg Zdenko Z Swerdlow Anthony J AJ Vineis Paolo P Flanagan James M JM

Clinical epigenetics 20190430 1

<h4>Background</h4>It is well established that estrogens and other hormonal factors influence breast cancer susceptibility. We hypothesized that a woman's total lifetime estrogen exposure accumulates changes in DNA methylation, detectable in the blood, which could be used in risk assessment for breast cancer.<h4>Methods</h4>An estimated lifetime estrogen exposure (ELEE) model was defined using epidemiological data from EPIC-Italy (n = 31,864). An epigenome-wide association study (EWAS) of ELEE w ...[more]

PMID: 31039828

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Project description:Genome-wide association studies (GWAS) have identified more than 90 susceptibility loci for breast cancer, but the underlying biology of those associations needs to be further elucidated. More genetic factors for breast cancer are yet to be identified but sample size constraints preclude the identification of individual genetic variants with weak effects using traditional GWAS methods. To address this challenge, we utilized a gene-level expression-based method, implemented in the MetaXcan software, to predict gene expression levels for 11,536 genes using expression quantitative trait loci and examine the genetically-predicted expression of specific genes for association with overall breast cancer risk and estrogen receptor (ER)-negative breast cancer risk. Using GWAS datasets from a Challenge launched by National Cancer Institute, we identified TP53INP2 (tumor protein p53-inducible nuclear protein 2) at 20q11.22 to be significantly associated with ER-negative breast cancer (Z = -5.013, p = 5.35×10-7, Bonferroni threshold = 4.33×10-6). The association was consistent across four GWAS datasets, representing European, African and Asian ancestry populations. There are 6 single nucleotide polymorphisms (SNPs) included in the prediction of TP53INP2 expression and five of them were associated with estrogen-receptor negative breast cancer, although none of the SNP-level associations reached genome-wide significance. We conducted a replication study using a dataset outside of the Challenge, and found the association between TP53INP2 and ER-negative breast cancer was significant (p = 5.07x10-3). Expression of HP (16q22.2) showed a suggestive association with ER-negative breast cancer in the discovery phase (Z = 4.30, p = 1.70x10-5) although the association was not significant after Bonferroni adjustment. Of the 249 genes that are 250 kb within known breast cancer susceptibility loci identified from previous GWAS, 20 genes (8.0%) were statistically significant associated with ER-negative breast cancer (p<0.05), compared to 582 (5.2%) of 11,287 genes that are not close to previous GWAS loci. This study demonstrated that expression-based gene mapping is a promising approach for identifying cancer susceptibility genes.

Dataset Information

Epigenome-wide association study for lifetime estrogen exposure identifies an epigenetic signature associated with breast cancer risk.

Publications

Epigenome-wide association study for lifetime estrogen exposure identifies an epigenetic signature associated with breast cancer risk.

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