Huanmin Luo, Shuqing Li, Yuming Cao, Jinfeng Xu, Li Wang
{"title":"复发性流产中m5c相关基因和亚群的鉴定。","authors":"Huanmin Luo, Shuqing Li, Yuming Cao, Jinfeng Xu, Li Wang","doi":"10.1007/s10815-025-03580-9","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>Recurrent pregnancy loss (RPL), which occurs in 1-5% of couples and nearly half of the cases remain unexplained, is a complex condition influenced by multiple factors. Previous investigations have demonstrated the role of m5C-related genes (MRGs) in cancer prognosis and the significance of epigenetic modifications during pregnancy. However, the connection between MRGs and the pathogenesis of RPL remains elusive. This study endeavors to elucidate this relationship through bioinformatics approaches.</p><p><strong>Methods: </strong>Data of 48 endometrial tissue samples were obtained through GEO query. Twenty-one MRGs were analyzed. Multiple machine learning (ML) methods were applied to identify biomarkers. A nomogram was constructed, and further analyses like GSEA and scRNA-seq were carried out using the R software.</p><p><strong>Results: </strong>Five core biomarkers (DNMT1, SMUG1, ZBTB38, MBD4, and TDG) were pinpointed by ML methods, with the prediction model achieving an AUC of 0.953. Based on hub genes, 24 RPL samples were grouped into cluster A (n = 9) and cluster B (n = 15). The study revealed differences in immune cells and microenvironments, and the scRNA-seq analysis confirmed the connection between immune cells and m5C.</p><p><strong>Conclusion: </strong>This study identified five key m5C-related genes, unraveled their link to immune cells, and developed an accurate RPL diagnostic model. The RPL patients are innovatively divided into two clusters, and the difference of their immune microenvironment is analyzed. This study offers a fresh perspective for examining biomarkers and potential therapeutic targets for RPL.</p>","PeriodicalId":15246,"journal":{"name":"Journal of Assisted Reproduction and Genetics","volume":" ","pages":""},"PeriodicalIF":2.7000,"publicationDate":"2025-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Identification of m5C-related genes and subclusters in recurrent pregnancy loss.\",\"authors\":\"Huanmin Luo, Shuqing Li, Yuming Cao, Jinfeng Xu, Li Wang\",\"doi\":\"10.1007/s10815-025-03580-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>Recurrent pregnancy loss (RPL), which occurs in 1-5% of couples and nearly half of the cases remain unexplained, is a complex condition influenced by multiple factors. Previous investigations have demonstrated the role of m5C-related genes (MRGs) in cancer prognosis and the significance of epigenetic modifications during pregnancy. However, the connection between MRGs and the pathogenesis of RPL remains elusive. This study endeavors to elucidate this relationship through bioinformatics approaches.</p><p><strong>Methods: </strong>Data of 48 endometrial tissue samples were obtained through GEO query. Twenty-one MRGs were analyzed. Multiple machine learning (ML) methods were applied to identify biomarkers. A nomogram was constructed, and further analyses like GSEA and scRNA-seq were carried out using the R software.</p><p><strong>Results: </strong>Five core biomarkers (DNMT1, SMUG1, ZBTB38, MBD4, and TDG) were pinpointed by ML methods, with the prediction model achieving an AUC of 0.953. Based on hub genes, 24 RPL samples were grouped into cluster A (n = 9) and cluster B (n = 15). The study revealed differences in immune cells and microenvironments, and the scRNA-seq analysis confirmed the connection between immune cells and m5C.</p><p><strong>Conclusion: </strong>This study identified five key m5C-related genes, unraveled their link to immune cells, and developed an accurate RPL diagnostic model. The RPL patients are innovatively divided into two clusters, and the difference of their immune microenvironment is analyzed. This study offers a fresh perspective for examining biomarkers and potential therapeutic targets for RPL.</p>\",\"PeriodicalId\":15246,\"journal\":{\"name\":\"Journal of Assisted Reproduction and Genetics\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2025-08-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Assisted Reproduction and Genetics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s10815-025-03580-9\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"GENETICS & HEREDITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Assisted Reproduction and Genetics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s10815-025-03580-9","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
Identification of m5C-related genes and subclusters in recurrent pregnancy loss.
Purpose: Recurrent pregnancy loss (RPL), which occurs in 1-5% of couples and nearly half of the cases remain unexplained, is a complex condition influenced by multiple factors. Previous investigations have demonstrated the role of m5C-related genes (MRGs) in cancer prognosis and the significance of epigenetic modifications during pregnancy. However, the connection between MRGs and the pathogenesis of RPL remains elusive. This study endeavors to elucidate this relationship through bioinformatics approaches.
Methods: Data of 48 endometrial tissue samples were obtained through GEO query. Twenty-one MRGs were analyzed. Multiple machine learning (ML) methods were applied to identify biomarkers. A nomogram was constructed, and further analyses like GSEA and scRNA-seq were carried out using the R software.
Results: Five core biomarkers (DNMT1, SMUG1, ZBTB38, MBD4, and TDG) were pinpointed by ML methods, with the prediction model achieving an AUC of 0.953. Based on hub genes, 24 RPL samples were grouped into cluster A (n = 9) and cluster B (n = 15). The study revealed differences in immune cells and microenvironments, and the scRNA-seq analysis confirmed the connection between immune cells and m5C.
Conclusion: This study identified five key m5C-related genes, unraveled their link to immune cells, and developed an accurate RPL diagnostic model. The RPL patients are innovatively divided into two clusters, and the difference of their immune microenvironment is analyzed. This study offers a fresh perspective for examining biomarkers and potential therapeutic targets for RPL.
期刊介绍：
The Journal of Assisted Reproduction and Genetics publishes cellular, molecular, genetic, and epigenetic discoveries advancing our understanding of the biology and underlying mechanisms from gametogenesis to offspring health. Special emphasis is placed on the practice and evolution of assisted reproduction technologies (ARTs) with reference to the diagnosis and management of diseases affecting fertility. Our goal is to educate our readership in the translation of basic and clinical discoveries made from human or relevant animal models to the safe and efficacious practice of human ARTs. The scientific rigor and ethical standards embraced by the JARG editorial team ensures a broad international base of expertise guiding the marriage of contemporary clinical research paradigms with basic science discovery. JARG publishes original papers, minireviews, case reports, and opinion pieces often combined into special topic issues that will educate clinicians and scientists with interests in the mechanisms of human development that bear on the treatment of infertility and emerging innovations in human ARTs. The guiding principles of male and female reproductive health impacting pre- and post-conceptional viability and developmental potential are emphasized within the purview of human reproductive health in current and future generations of our species.
The journal is published in cooperation with the American Society for Reproductive Medicine, an organization of more than 8,000 physicians, researchers, nurses, technicians and other professionals dedicated to advancing knowledge and expertise in reproductive biology.
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