{"title":"Identification of candidate genes for endometrial cancer in multi-omics: a Mendelian randomization analysis.","authors":"Lan-Hui Qin, Chongze Yang, Rui Song, Pei-Yin Chen, Zijian Jiang, Weihui Xu, Guanzhen Zeng, Jin-Yuan Liao, Liling Long","doi":"10.1080/19396368.2024.2411458","DOIUrl":null,"url":null,"abstract":"<p><p>Endometrial cancer is the most common malignant tumor of the uterus, but the underlying genetic mechanisms of EC remain unclear. To identify candidate genes and investigate genetic mechanisms for endometrial cancer, we utilized the summary-data-based Mendelian randomization (SMR) method to investigate causal associations between genetic variants, gene expression, DNA methylation, and endometrial cancer. Three main analyses were conducted utilizing cis-expression and methylation quantitative trait loci (eQTLs and mQTLs) as instrumental variables to examine causal relationships with endometrial cancer, and assessing the causal relationship between DNA methylation and gene expression. Data sources included genetic association data from O'Mara et al. eQTL data from the GTEx database, and mQTL data from McRae et al. Analysis involved the HEIDI test to distinguish pleiotropy, SMR analysis with multiple testing correction, and colocalization analysis to assess associations driven by linkage disequilibrium. Functional enrichment analysis was performed by the Metascape tool. Our study showed that three genes, SNX11, LINC00243, and EVI2A, were identified as causally related to endometrial cancer. SNX11 exhibited a positive causal relationship, while LINC00243 and EVI2A showed negative ones. Furthermore, 24 CpG sites were identified as causally related to endometrial cancer, with cg14424631 (CYP19A1) being the most significant. The study revealed common genes implicated in endometrial cancer, gene expression, and methylation sites, with LINC00243 playing a key role. Colocalization analysis confirmed significant causal relationships between LINC00243, SNX11, and endometrial cancer. Enrichment analysis uncovered pathways like interferon gamma signaling enriched in both endometrial cancer GWAS and e/mQTL. These findings shed light on the molecular mechanisms underlying endometrial cancer development. The study identified candidate genes and DNA methylation loci causally associated with endometrial cancer, which are expected to serve as potential targets for treatment.</p>","PeriodicalId":22184,"journal":{"name":"Systems Biology in Reproductive Medicine","volume":"70 1","pages":"299-311"},"PeriodicalIF":2.1000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Systems Biology in Reproductive Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/19396368.2024.2411458","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/10/14 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"ANDROLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Endometrial cancer is the most common malignant tumor of the uterus, but the underlying genetic mechanisms of EC remain unclear. To identify candidate genes and investigate genetic mechanisms for endometrial cancer, we utilized the summary-data-based Mendelian randomization (SMR) method to investigate causal associations between genetic variants, gene expression, DNA methylation, and endometrial cancer. Three main analyses were conducted utilizing cis-expression and methylation quantitative trait loci (eQTLs and mQTLs) as instrumental variables to examine causal relationships with endometrial cancer, and assessing the causal relationship between DNA methylation and gene expression. Data sources included genetic association data from O'Mara et al. eQTL data from the GTEx database, and mQTL data from McRae et al. Analysis involved the HEIDI test to distinguish pleiotropy, SMR analysis with multiple testing correction, and colocalization analysis to assess associations driven by linkage disequilibrium. Functional enrichment analysis was performed by the Metascape tool. Our study showed that three genes, SNX11, LINC00243, and EVI2A, were identified as causally related to endometrial cancer. SNX11 exhibited a positive causal relationship, while LINC00243 and EVI2A showed negative ones. Furthermore, 24 CpG sites were identified as causally related to endometrial cancer, with cg14424631 (CYP19A1) being the most significant. The study revealed common genes implicated in endometrial cancer, gene expression, and methylation sites, with LINC00243 playing a key role. Colocalization analysis confirmed significant causal relationships between LINC00243, SNX11, and endometrial cancer. Enrichment analysis uncovered pathways like interferon gamma signaling enriched in both endometrial cancer GWAS and e/mQTL. These findings shed light on the molecular mechanisms underlying endometrial cancer development. The study identified candidate genes and DNA methylation loci causally associated with endometrial cancer, which are expected to serve as potential targets for treatment.
期刊介绍:
Systems Biology in Reproductive Medicine, SBiRM, publishes Research Articles, Communications, Applications Notes that include protocols a Clinical Corner that includes case reports, Review Articles and Hypotheses and Letters to the Editor on human and animal reproduction. The journal will highlight the use of systems approaches including genomic, cellular, proteomic, metabolomic, bioinformatic, molecular, and biochemical, to address fundamental questions in reproductive biology, reproductive medicine, and translational research. The journal publishes research involving human and animal gametes, stem cells, developmental biology and toxicology, and clinical care in reproductive medicine. Specific areas of interest to the journal include: male factor infertility and germ cell biology, reproductive technologies (gamete micro-manipulation and cryopreservation, in vitro fertilization/embryo transfer (IVF/ET) and contraception. Research that is directed towards developing new or enhanced technologies for clinical medicine or scientific research in reproduction is of significant interest to the journal.