medRxivGenetic & Genomic MedicinePreprint
Integrating genome and epigenome data to identify tissue-specific DNA methylation biomarkers for cancer risk
Yaohua YangiD, Yaxin CheniD, Shuai XuiD, Xingyi GuoiD, Guochong JiaiD, Jie PingiD, Xiang ShuiD, Tianying ZhaoiD, Fangcheng YuaniD, Gang WangiD, Yufang XieiD, Hang Ci, Dan LiuiD, Fei YeiD, Xiao‐Ou ShuiD, Wei ZhengiD, Li LiiD, Qiuyin CaiiD, Jirong LongiD
Abstract
The relationship between tissue-specific DNA methylation and cancer risk remains inadequately elucidated. Leveraging the Genotype-Tissue Expression (GTEx) consortium, we developed genetic models to predict DNA methylation at CpG sites (CpGs) across the genome for seven tissues and applied these models to genome-wide association study (GWAS) data of corresponding cancers, namely breast, colorectal, renal cell, lung, ovarian, prostate, and testicular germ cell cancers. At Bonferroni-corrected P<0.05, we identified 2,776 CpGs significantly associated with cancer risk, of which 92.7% (2,572) were specific to a particular cancer type. Notably, 57 CpGs within 35 putative novel loci retained significant associations with cancer risk after conditioning on proximal GWAS-identified signals. Further integrative multi-omics analyses revealed 791 CpG-gene-cancer trios, suggesting that DNA methylation at 248 distinct CpGs might influence cancer risk through regulating expression of 145 unique cis-genes. These findings substantially advance our understanding of the interplay between genetics, epigenetics, and gene expression in cancer etiology.
- organism: human
- assay: DNA methylation
- research focus: GWAS / association mapping
- approach: statistical model
- approach: benchmark study
- Citations
- 2
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