{"title":"Evaluation of the diagnostic utility of immune microenvironment-related biomarkers in endometriosis using multidimensional transcriptomic data.","authors":"Qing Tu, Ruiheng Zhao, Ning Lu","doi":"10.1007/s10815-024-03261-z","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>Endometriosis (EMS) is a relatively common gynecological disorder and almost fifty percent of women with EMS suffer from infertility. There are few treatment options for endometriosis, and often recurrences occur following surgery and medication. We aimed to identify potential diagnostic biomarkers for EMS to improve its diagnostic efficiency.</p><p><strong>Methods: </strong>Differential analysis was utilized to choose EMS-associated abnormal miRNAs (DEMIs) and mRNAs (DEMs). ImmuneAI analysis was to evaluate the levels of immune cells in EMS. Next, the weighted gene co-expression network analysis (WGCNA) was utilized to identify the co-expression modules. Random forest and SVM analyses were used to filter the candidate biomarkers and construct the diagnostic model. qRT-PCR was used to test the expression level of the biomarkers.</p><p><strong>Results: </strong>Based on the different analyses, we obtained 32 DEMIs and 516 DEMs and selected 9 abnormal immune cells whose abundance is abnormal in EMS. Next, we identified five co-expression modules associated with these abnormal immune cells. Then, 176 candidate genes which are both miRNA targets and associated with immune cells and aberrantly expressed in EMS were filtered. Subsequently, random forest analysis selected 11 genes as the diagnostic biomarkers and constructed a diagnostic model by SVM. Finally, we demonstrated that 8 of the 11 genes aberrantly expressed and with better diagnostic efficiency in EMS.</p><p><strong>Conclusions: </strong>In total, we identified 11 crucial genes regulated by 8 miRNAs that could serve as promising diagnostic biomarkers for EMS, potentially enhancing disease diagnosis with novel factors.</p>","PeriodicalId":15246,"journal":{"name":"Journal of Assisted Reproduction and Genetics","volume":null,"pages":null},"PeriodicalIF":3.2000,"publicationDate":"2024-09-24","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/s10815-024-03261-z","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose: Endometriosis (EMS) is a relatively common gynecological disorder and almost fifty percent of women with EMS suffer from infertility. There are few treatment options for endometriosis, and often recurrences occur following surgery and medication. We aimed to identify potential diagnostic biomarkers for EMS to improve its diagnostic efficiency.
Methods: Differential analysis was utilized to choose EMS-associated abnormal miRNAs (DEMIs) and mRNAs (DEMs). ImmuneAI analysis was to evaluate the levels of immune cells in EMS. Next, the weighted gene co-expression network analysis (WGCNA) was utilized to identify the co-expression modules. Random forest and SVM analyses were used to filter the candidate biomarkers and construct the diagnostic model. qRT-PCR was used to test the expression level of the biomarkers.
Results: Based on the different analyses, we obtained 32 DEMIs and 516 DEMs and selected 9 abnormal immune cells whose abundance is abnormal in EMS. Next, we identified five co-expression modules associated with these abnormal immune cells. Then, 176 candidate genes which are both miRNA targets and associated with immune cells and aberrantly expressed in EMS were filtered. Subsequently, random forest analysis selected 11 genes as the diagnostic biomarkers and constructed a diagnostic model by SVM. Finally, we demonstrated that 8 of the 11 genes aberrantly expressed and with better diagnostic efficiency in EMS.
Conclusions: In total, we identified 11 crucial genes regulated by 8 miRNAs that could serve as promising diagnostic biomarkers for EMS, potentially enhancing disease diagnosis with novel factors.
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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