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Integrative multi-omics analyses identify 854 CpG-gene-cancer trios, implicating 309 CpGs acting through 205 cis-genes and advancing links among genetics, epigenetics, and cancer etiology.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/research-report/","Research & 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[https://doi.org/10.1038/s41467-024-50404-y](https://doi.org/10.1038/s41467-024-50404-y)  \nIntegrating muti-omics data to identify tissue-specific DNA methylation biomarkers for cancer risk  \nReceived: 6 September 2023  \n\n| Accepted: 10 July 2024 |\n| --- |\n| |\n| Check for updates |\n\nYaohua Yang 1,8 , Yaxin Chen2,8, Shuai Xu 3, Xingyi Guo 3, Guochong Jia 3, Jie Ping 3, Xiang Shu4, Tianying Zhao 3, FangchengYuan 3, Gang Wang2, Yufang Xie2, Hang Ci2, Hongmo Liu2, Yawen Qi2, Yongjun Liu5, Dan Liu2, Weimin Li 2, Fei Ye 6, Xiao-Ou Shu3, Wei Zheng 3, Li Li7,  \nQiuyin Cai 3  & Jirong Long 3   \nThe relationship between tissue-specific DNA methylation and cancer risk remains inadequately elucidated. Leveraging resources from the GenotypeTissue Expression consortium, here we develop genetic models to predict DNA methylation at CpG sites across the genome for seven tissues and apply these models to genome-wide association study data of corresponding cancers, namely breast, colorectal, renal cell, lung, ovarian, prostate, and testicular germ cell cancers. At Bonferroni-corrected P \u003C 0.05, we identify 4248 CpGs that are significantly associated with cancer risk, of which 95.4%(4052) arespecific to a particular cancer type. Notably, 92 CpGs within 55 putative novel loci retain significant associations with cancer risk after conditioning on proximal signals identified by genome-wide association studies. Integrative multi-omics analyses reveal 854 CpG-gene-cancer trios, suggesting that DNA methylation at 309 distinct CpGs might influence cancer risk through regulating the expression of 205 unique cis-genes. These findings substantially advance our understanding of the interplay between genetics, epigenetics, and gene expression in cancer etiology.  \nCancer is a complex disease with an estimated overall heritability of 33%1. Genome-wide association studies (GWAS) have identified over 1000 common variants associated with cancer risk2–9. However, these variants are mainly situated in non-coding regions, posing challenges in identifying target genes and mechanisms2–9. While expression quantitative trait loci (eQTL) studies have uncovered many genes associated with GWAS-identified variants, most of them  \nwere limited by the small proportion of gene expression variation captured by individual eQTL variants10. Transcriptome-wide association studies (TWAS) made strides in addressing this by incorporating multiple cis-variants to predict gene expression, unveiling hundreds of candidate cancer susceptibility genes11. However, over half of GWAS loci lacked TWAS-identified genes, implying the possible existence of additional mechanisms contributing to the  \n1Center for Public Health Genomics, Department of Public Health Sciences, UVA Comprehensive Cancer Center, School of Medicine, University of Virginia, Charlottesville, VA, USA. 2Institute of Respiratory Health, Frontiers Science Center for Disease‑Related Molecular Network, State Key Laboratory of Respiratory Health and Multimorbidity, Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, China. 3Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA. 4Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA. 5Department of Laboratory Medicine and Pathology, University of Washington Medical Center, Seattle, WA, USA. 6Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA. 7Department of Family Medicine, UVA Comprehensive Cancer Center, School of Medicine, University of Virginia, Charlottesville, VA, USA. 8These authors contributed equally: Yaohua Yang, Yaxin Chen. e-mail: [vta8we@virginia.edu](vta8we@virginia.edu); [qiuyin.cai@vumc.org](qiuyin.cai@vumc.org); [jirong.long@vumc.org](jirong.long@vumc.org)  \nA B  \n~5 million SNPs ~~ ~~  \nSingle-/cross-tissue ","cbCaiieV8HJS2zGs","https://ap.wps.com/l/cbCaiieV8HJS2zGs","pdf",1522408,13,"English","# Overview\n## DNA methylation prediction using genetic models\n## Association with cancer GWAS across seven cancers\n## Conditional signals and novel loci\n## Integrative multi-omics and CpG-gene-cancer trios\n## Implications for cancer etiology","[{\"question\":\"How are DNA methylation prediction models constructed for different tissues?\",\"answer\":\"The study develops genetic models to predict DNA methylation at CpG sites across the genome for seven tissues using resources from the Genotype-Tissue Expression consortium.\"},{\"question\":\"What is the main result linking CpG methylation to cancer risk?\",\"answer\":\"Across the analyzed cancers, the authors identify 4248 CpGs significantly associated with cancer risk at Bonferroni-corrected P\\u003c0.05, with 95.4% corresponding to a specific cancer type.\"},{\"question\":\"How do integrative multi-omics analyses connect CpG methylation to gene regulation and cancer?\",\"answer\":\"The authors integrate multi-omics data to identify 854 CpG-gene-cancer trios, suggesting 309 distinct CpGs may influence cancer risk by regulating 205 unique cis-genes.\"}]","Integrating muti-omics data to identify tissue-specific DNA methylation biomarkers for cancer risk | PDF",1790002944,33]