[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-detail-420365-en":59,"doc-seo-420365-105":80},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":5,"data":60},{"doc_id":61,"user_id":62,"nickname":63,"user_avatar":64,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":66,"doc_content":67,"file_id":68,"file_url":69,"file_type":70,"file_size":71,"view_count":8,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":72,"language":73,"language_code":74,"site_id":75,"html_lang":74,"table_of_contents":76,"faqs":77,"seo_title":78,"seo_description":66,"update_tm":79,"read_time":41},420365,962090893581,"OmBimo","https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c","Comprehensive Analysis of Vaginal and Gut Microbiome Alterations in Endometriosis Patients","Endometriosis (EMS) is a chronic gynecological disorder with unclear pathogenesis. This study investigates how vaginal and gut microbiomes jointly relate to EMS by integrating metagenomic evidence. Metagenomic sequencing was performed on 22 paired vaginal and fecal samples from EMS patients and controls, assessing microbial composition, diversity, and metabolic pathways. Machine learning models evaluated diagnostic predictive performance, showing gut features outperforming vaginal microbiome and hormonal indices.","International Journal of Women’s Health  \n Open Access Full Text Article  \nORIGINAL RESEARCH  \nComprehensive Analysis of Vaginal and Gut Microbiome Alterations in Endometriosis Patients  \nYiming Zhao 1 , 2 , *, Xinyu Hu 1 , *, Chunyan Li2 , Jing Huang 3 , Ke Guo4 , Qiong Pan 1 , Zheng Yu2  \n1Department of Obstetrics and Gynecology, the Third Xiangya Hospital of Central South University, Changsha, People’s Republic of China; 2Human Microbiome and Health Group, Department of Microbiology, Xiangya School of Basic Medical Sciences, Central South University, Changsha, Hunan, People’s Republic of China; 3Department of Parasitology, Xiangya School of Basic Medical Sciences, Central South University, Changsha, Hunan,  \nPeople’s Republic of China; 4Department of Neurology, the Third Xiangya Hospital of Central South University, Changsha, People’s Republic of China *These authors contributed equally to this work  \nCorrespondence: Qiong Pan; Zheng Yu, [Email panqiong1979@163.com](Email panqiong1979@163.com); [yuzheng@csu.edu.cn](yuzheng@csu.edu.cn)  \n\n| Purpose: Endometriosis (EMS) is a chronic gynecological disorder with unclear pathogenesis. While the vaginal and gut microbiomes are known to influence EMS, few studies have analyzed both microbiomes integrally. This study aims to characterize the vaginal and gut microbiome profiles in EMS patients and evaluate their diagnostic potential.\u003Cbr>Patients and Methods: We conducted metagenomic sequencing on 22 paired vaginal and fecal samples from EMS patients and controls. Microbial composition, diversity, and metabolic pathways were analyzed. Machine learning models were employed to assess the predictive performance of microbiome features in EMS diagnosis.\u003Cbr>Results: EMS patients exhibited pronounced shifts in the vaginal microbiome, characterized by reduced Lactobacillus and increased Bifidobacterium and Gardnerella, which correlated with elevated luteinizing hormone (LH) and follicle-stimulating hormone (FSH) levels. The gut microbiome displayed decreased diversity, with a depletion of beneficial taxa such as Ruminococcus and Prevotella, alongside an enrichment of Dialister. Metabolic pathways in both microbial communities were significantly altered. Machine learning analyses demonstrated that gut microbiome features outperformed both vaginal microbiome and hormonal indices in predicting EMS, highlighting their strong diagnostic potential.\u003Cbr>Conclusion: This study underscores the pivotal role of the gut microbiota in EMS and elucidates the complex interplay between microbial dysbiosis and disease pathogenesis. Our findings indicate that gut microbiome signatures may serve as superior diagnostic biomarkers for EMS, thereby paving the way for microbiome-based diagnostic and therapeutic strategies.\u003Cbr>Keywords: vaginal microbiome, gut microbiome, endometriosis, metagenomic sequencing |\n| --- |\n| Introduction\u003Cbr>Endometriosis (EMS) is a chronic gynecological disorder which can lead to pelvic pain, dysmenorrhea, and infertility.1 Despite its significant impact on women’s health, the pathogenesis of endometriosis remains poorly understood. The retrograde menstruation theory, which posits that viable endometrial cells are transported to the pelvic cavity, is widely regarded as the most plausible explanation for the development of EMS.2 However, the fact that only a small part of women develop EMS despite the near-universal occurrence of retrograde menstruation to some degree, implies that additional factors are at play.3 Recent studies have reported that genetic,4 immunological,5 hormonal,6 and environmental7 factors can influence the development of EMS.\u003Cbr>More and more studies have highlighted the potential role of the human microbiome,8 particularly the vaginal and gut microbiota.9 Alterations in the composition and function of these microbial communities, known as dysbiosis, have been associated with the development and progression of numerous health conditions. Emerging evidence suggests t","cbCaipAE23rAW09J","https://ap.wps.com/l/cbCaipAE23rAW09J","pdf",4734516,12,"English","en",105,"# Introduction\n## Patients and Methods\n## Results\n## Conclusion\n## Keywords","[{\"question\":\"What is the main goal of this study on endometriosis?\",\"answer\":\"To characterize both vaginal and gut microbiome profiles in endometriosis patients and to evaluate their diagnostic potential using metagenomic and machine learning analyses.\"},{\"question\":\"How were the microbiome data collected and analyzed?\",\"answer\":\"Metagenomic sequencing was conducted on 22 paired vaginal and fecal samples, followed by analysis of microbial composition, diversity, metabolic pathways, and machine learning-based prediction of EMS.\"},{\"question\":\"Which microbiome source performed best for diagnosing endometriosis?\",\"answer\":\"Gut microbiome features outperformed both vaginal microbiome features and hormonal indices in predicting EMS, indicating stronger diagnostic potential.\"}]","Comprehensive Analysis of Vaginal and Gut Microbiome Alterations in Endometriosis Patients | PDF",1790620682,{"code":4,"msg":81,"data":82},"ok",{"site_id":75,"language":74,"slug":83,"title":65,"keywords":84,"description":66,"schema_data":85,"social_meta":139,"head_meta":141,"extra_data":143,"updated_unix":144},"comprehensive-analysis-of-vaginal-and-gut-microbiome-alterations-in-endometriosis-patients","",{"@graph":86,"@context":138},[87,101,121],{"@type":88,"itemListElement":89},"BreadcrumbList",[90,94,96,99],{"item":91,"name":92,"@type":93,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":95,"name":9,"@type":93,"position":14},"https://docshare.wps.com/document/",{"item":97,"name":40,"@type":93,"position":98},"https://docshare.wps.com/document/research-report/",3,{"item":100,"name":65,"@type":93,"position":19},"https://docshare.wps.com/document/comprehensive-analysis-of-vaginal-and-gut-microbiome-alterations-in-endometriosis-patients/420365/",{"url":100,"name":65,"@type":102,"image":103,"author":108,"headline":65,"publisher":110,"fileFormat":113,"inLanguage":74,"description":66,"dateModified":114,"datePublished":115,"encodingFormat":113,"isAccessibleForFree":116,"interactionStatistic":117},"DigitalDocument",{"url":104,"@type":105,"width":106,"height":107},"https://docshare.wps.com/thumbnails/comprehensive-analysis-of-vaginal-and-gut-microbiome-alterations-in-endometriosis-patients/420365.png","ImageObject",300,407,{"name":63,"@type":109},"Person",{"url":91,"name":111,"@type":112},"DocShare","Organization","application/pdf","2026-09-29","2026-09-28",true,{"@type":118,"interactionType":119,"userInteractionCount":8},"InteractionCounter",{"@type":120},"ViewAction",{"@type":122,"mainEntity":123},"FAQPage",[124,130,134],{"name":125,"@type":126,"acceptedAnswer":127},"What is the main goal of this study on endometriosis?","Question",{"text":128,"@type":129},"To characterize both vaginal and gut microbiome profiles in endometriosis patients and to evaluate their diagnostic potential using metagenomic and machine learning analyses.","Answer",{"name":131,"@type":126,"acceptedAnswer":132},"How were the microbiome data collected and analyzed?",{"text":133,"@type":129},"Metagenomic sequencing was conducted on 22 paired vaginal and fecal samples, followed by analysis of microbial composition, diversity, metabolic pathways, and machine learning-based prediction of EMS.",{"name":135,"@type":126,"acceptedAnswer":136},"Which microbiome source performed best for diagnosing endometriosis?",{"text":137,"@type":129},"Gut microbiome features outperformed both vaginal microbiome features and hormonal indices in predicting EMS, indicating stronger diagnostic potential.","https://schema.org",{"og:url":100,"og:type":140,"og:title":65,"og:site_name":111,"og:description":66},"article",{"robots":142,"canonical":100},"index,follow",{"doc_id":61,"site_id":75},1790708961]