Y Yang, L Wu, X Shu, Y Lu, X-O Shu, Q Cai, A Beeghly-Fadiel, B Li, F Ye, A Berchuck, H Anton-Culver, S Banerjee, J Benitez, L Bjørge, JD Brenton, R Butzow, IG Campbell, J Chang-Claude, K Chen, LS Cook, DW Cramer, A DeFazio, J Dennis, JA Doherty, T Dork, DM Eccles, D Velez Edwards, PA Fasching, RT Fortner, SA Gayther, GG Giles, RM Glasspool, EL Goode, MT Goodman, J Gronwald, HR Harris, F Heitz, MAT Hildebrandt, E Høgdall, CK Høgdall, DG Huntsman, SP Kar, BY Karlan, LE Kelemen, LA Kiemeney, SK Kjaer, A Koushik, D Lambrechts, ND Le, DA Levine, LFAG Massuger, K Matsuo, T May, IA McNeish, U Menon, F Modugno, AN Monteiro, PG Moorman, KB Moysich, RB Ness, H Nevanlinna, H Olsson, NC Onland-Moret, SK Park, J Paul, CL Pearce, T Pejovic, CM Phelan, MC Pike, SJ Ramus, E Riboli, C Rodríguez-Antona, I Romieu, DP Sandler, JM Schildkraut, VW Setiawan, K Shan, N Siddiqui, W Sieh, MJ Stampfer, R Sutphen, AJ Swerdlow, LM Szafron, SH Teo, SS Tworoger, JP Tyrer, PM Webb, N Wentzensen, E White, WC Willett, A Wolk, YL Woo, AH Wu, L Yan, D Yannoukakos, G Chenevix-Trench, TA Sellers, PDP Pharoah, W Zheng, J Long
DNA methylation is instrumental for gene regulation. Global changes in the epigenetic landscape have been recognized as a hallmark of cancer. However, the role of DNA methylation in epithelial ovarian cancer (EOC) remains unclear. In this study, high density genetic and DNA methylation data in white blood cells from the Framingham Heart Study (N=1,595) were used to build genetic models to predict DNA methylation levels. These prediction models were then applied to the summary statistics of a genome-wide association study (GWAS) of ovarian cancer including 22,406 EOC cases and 40,941 controls to investigate genetically predicted DNA methylation levels in association with EOC risk. Among 62,938 CpG sites investigated, genetically predicted methylation levels at 89 CpG were significantly associated with EOC risk at a Bonferroni-corrected threshold of P<7.94×10-7. Of them, 87 were located at GWAS-identified EOC susceptibility regions and two resided in a genomic region not previously reported to be associated with EOC risk. Integrative analyses of genetic, methylation, and gene expression data identified consistent directions of associations across 12 CpG, five genes, and EOC risk, suggesting that methylation at these 12 CpG may influence EOC risk by regulating expression of these five genes, namely MAPT, HOXB3, ABHD8, ARHGAP27 and SKAP1. We identified novel DNA methylation markers associated with EOC risk and propose that methylation at multiple CpG may affect EOC risk via regulation of gene expression.