Genetically predicted levels of DNA methylation biomarkers and breast cancer risk: data from 228,951 women of European descent.

BACKGROUND DNA methylation plays a critical role in breast cancer development. Previous studies have identified DNA methylation marks in white blood cells as promising biomarkers for breast cancer. However, these studies were limited by low statistical power and potential biases. Utilizing a new methodology, we investigated DNA methylation marks for their associations with breast cancer risk. METHODS Statistical models were built to predict levels of DNA methylation marks using genetic data and DNA methylation data from HumanMethylation450 BeadChip from the Framingham Heart Study (N=1,595). The prediction models were validated using data from the Women's Health Initiative (N=883). We applied these models to genome-wide association study (GWAS) data of 122,977 breast cancer cases and 105,974 controls to evaluate if the genetically predicted DNA methylation levels at CpGs are associated with breast cancer risk. All statistical tests were two-sided. RESULTS Of the 62,938 CpG sites (CpGs) investigated, statistically significant associations with breast cancer risk were observed for 450 CpGs at a Bonferroni-corrected threshold of P<7.94 × 10-7, including 45 CpGs residing in 18 genomic regions which have not previously been associated with breast cancer risk. Of the remaining 405 CpGs located within 500 kilobase flaking regions of 70 GWAS-identified breast cancer risk variants, the associations for 11 CpGs were independent of GWAS-identified variants. Integrative analyses of genetic, DNA methylation and gene expression data found that 38 CpGs may affect breast cancer risk through regulating expression of 21 genes. CONCLUSION Our new methodology can identify novel DNA methylation biomarkers for breast cancer risk and can be applied to other diseases.

[1]  H. Brenner,et al.  Individual and joint performance of DNA methylation profiles, genetic risk score and environmental risk scores for predicting breast cancer risk , 2019, Molecular oncology.

[2]  S. Sinha,et al.  Coupled Genome-Wide DNA Methylation and Transcription Analysis Identified Rich Biomarkers and Drug Targets in Triple-Negative Breast Cancer , 2019, Cancers.

[3]  T. Tollefsbol,et al.  MicroRNAs and Epigenetics Strategies to Reverse Breast Cancer , 2019, Cells.

[4]  Javier Santoyo-Lopez,et al.  A Dominantly Inherited 5′ UTR Variant Causing Methylation-Associated Silencing of BRCA1 as a Cause of Breast and Ovarian Cancer , 2018, American journal of human genetics.

[5]  A. Prentice,et al.  Establishment of environmentally sensitive DNA methylation states in the very early human embryo , 2018, Science Advances.

[6]  Jeffery M. Meyer,et al.  A transcriptome-wide association study of 229,000 women identifies new candidate susceptibility genes for breast cancer , 2018, Nature Genetics.

[7]  Tom R. Gaunt,et al.  Systematic Mendelian randomization framework elucidates hundreds of CpG sites which may mediate the influence of genetic variants on disease , 2018, Human molecular genetics.

[8]  D. English,et al.  Heritable DNA methylation marks associated with susceptibility to breast cancer , 2018, Nature Communications.

[9]  Fan Yang,et al.  Knockdown of LncRNA MAPT-AS1 inhibites proliferation and migration and sensitizes cancer cells to paclitaxel by regulating MAPT expression in ER-negative breast cancers , 2018, Cell & Bioscience.

[10]  P. Vineis,et al.  Epigenetic supersimilarity of monozygotic twin pairs , 2018, Genome Biology.

[11]  Gary D Bader,et al.  Association analysis identifies 65 new breast cancer risk loci , 2017, Nature.

[12]  Tom R. Gaunt,et al.  Mendelian Randomization Analysis Identifies CpG Sites as Putative Mediators for Genetic Influences on Cardiovascular Disease Risk , 2017, American journal of human genetics.

[13]  Mary Goldman,et al.  Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics , 2016, Nature Communications.

[14]  X. Hua,et al.  Epigenome-wide analysis of DNA methylation in lung tissue shows concordance with blood studies and identifies tobacco smoke-inducible enhancers , 2017, Human molecular genetics.

[15]  R. Marioni,et al.  Identification of 55,000 Replicated DNA Methylation QTL , 2017, bioRxiv.

[16]  J. Leitner,et al.  PD-1 Blockade Promotes Emerging Checkpoint Inhibitors in Enhancing T Cell Responses to Allogeneic Dendritic Cells , 2017, Front. Immunol..

[17]  M. O’Donovan,et al.  Pleiotropic effects of trait-associated genetic variation on DNA methylation: utility for refining , 2018 .

[18]  E. Birney,et al.  eFORGE: A Tool for Identifying Cell Type-Specific Signal in Epigenomic Data , 2016, Cell reports.

[19]  Xing-Ming Zhao,et al.  Integrative analysis of mutational and transcriptional profiles reveals driver mutations of metastatic breast cancers , 2016, Cell Discovery.

[20]  Tom R. Gaunt,et al.  Systematic identification of genetic influences on methylation across the human life course , 2016, Genome Biology.

[21]  A. Neugut,et al.  DNA methylation modifies the association between obesity and survival after breast cancer diagnosis , 2016, Breast Cancer Research and Treatment.

[22]  S. Bose,et al.  BRCA‐mutated Invasive Breast Carcinomas: Immunohistochemical Analysis of Insulin‐like Growth Factor II mRNA‐binding Protein (IMP3), Cytokeratin 8/18, and Cytokeratin 14 , 2015, The breast journal.

[23]  A. Ashworth,et al.  Epigenome-wide association study reveals decreased average methylation levels years before breast cancer diagnosis , 2015, Clinical Epigenetics.

[24]  D. English,et al.  The repeatability of DNA methylation measures may also affect the power of epigenome-wide association studies. , 2015, International journal of epidemiology.

[25]  Z. Herceg,et al.  Independent genomewide screens identify the tumor suppressor VTRNA2-1 as a human epiallele responsive to periconceptional environment , 2015, Genome Biology.

[26]  Jun S. Liu,et al.  The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans , 2015, Science.

[27]  Michael Q. Zhang,et al.  Integrative analysis of 111 reference human epigenomes , 2015, Nature.

[28]  Andrew Lonie,et al.  Epigenome-wide methylation in DNA from peripheral blood as a marker of risk for breast cancer , 2014, Breast Cancer Research and Treatment.

[29]  Rafael A. Irizarry,et al.  Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays , 2014, Bioinform..

[30]  William Wheeler,et al.  Characterizing the genetic basis of methylome diversity in histologically normal human lung tissue , 2014, Nature Communications.

[31]  Lynn M Almli,et al.  Methylation quantitative trait loci (meQTLs) are consistently detected across ancestry, developmental stage, and tissue type , 2014, BMC Genomics.

[32]  S. Sarkar,et al.  Cancer Development, Progression, and Therapy: An Epigenetic Overview , 2013, International journal of molecular sciences.

[33]  A. Butterworth,et al.  Mendelian Randomization Analysis With Multiple Genetic Variants Using Summarized Data , 2013, Genetic epidemiology.

[34]  Clarice R Weinberg,et al.  Epigenome-wide association study of breast cancer using prospectively collected sister study samples. , 2013, Journal of the National Cancer Institute.

[35]  Conceição Santos,et al.  The Redox State of Cytochrome C Modulates Resistance to Methotrexate in Human MCF7 Breast Cancer Cells , 2013, PloS one.

[36]  R. Harris,et al.  Human metastable epiallele candidates link to common disorders , 2013, Epigenetics.

[37]  T. Haaf,et al.  Constitutive promoter methylation of BRCA1 and RAD51C in patients with familial ovarian cancer and early-onset sporadic breast cancer , 2012, Human Molecular Genetics.

[38]  Steven J. M. Jones,et al.  Comprehensive molecular portraits of human breast tumors , 2012, Nature.

[39]  P. Visscher,et al.  Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits , 2012, Nature Genetics.

[40]  Graham G. Giles,et al.  Constitutional Methylation of the BRCA1 Promoter Is Specifically Associated with BRCA1 Mutation-Associated Pathology in Early-Onset Breast Cancer , 2010, Cancer Prevention Research.

[41]  H. Hakonarson,et al.  ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data , 2010, Nucleic acids research.

[42]  M. Vitolo,et al.  Metastatic breast tumors express increased tau, which promotes microtentacle formation and the reattachment of detached breast tumor cells , 2010, Oncogene.

[43]  J. Peto,et al.  Gene-body hypermethylation of ATM in peripheral blood DNA of bilateral breast cancer patients , 2009, Human molecular genetics.

[44]  Maurice B Loughrey,et al.  BRCA1 promoter methylation in peripheral blood DNA of mutation negative familial breast cancer patients with a BRCA1 tumour phenotype , 2008, Breast Cancer Research.

[45]  A. Jemal,et al.  Breast cancer statistics, 2015: Convergence of incidence rates between black and white women , 2016, CA: a cancer journal for clinicians.

[46]  Steven J. M. Jones,et al.  Comprehensive molecular portraits of human breast tumours , 2013 .

[47]  A. Jemal,et al.  Breast Cancer Statistics , 2013 .