[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-122643-en":3,"doc-seo-122643-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},122643,687197100911,"Himbo","https://ap-avatar.wpscdn.com/avatar/a000239b6f1da00475?x-image-process=image/resize,m_fixed,w_180,h_180&k=1785132997149421697",8,"Research & Report","Machine learning and integrative analysis identify the common pathogenesis of azoospermia complicated with COVID-19","Study goal focuses on clarifying the common molecular mechanism linking COVID-19 with azoospermia, given evidence that SARS-CoV-2 is prone to induce azoospermia. Integrated weighted co-expression network analysis, multiple machine learning workflows, and single-cell RNA sequencing were used to identify shared differentially expressed genes, key network modules, IL-17 signaling enrichment, hub genes, and transcriptomic subtypes. Predicted drug candidates and single-cell validation were applied to characterize impaired spermatogenesis patterns in cryptozoospermia.","TYPE Original Research PUBLISHED 22 May 2023  \nDOI 10.3389/fimmu.2023.1114870  \nOPEN ACCESS  \nEDITED BY  \nAlan Landay,  \nRush University, United States  \nREVIEWED BY  \nSudhanshu Bhushan,  \nUniversity of Giessen, Germany Ruben Blachman-Braun, University of Miami Health System, United States  \n*CORRESPONDENCE Mingming Zhang  \n [zhangmm@csu.edu.cn](zhangmm@csu.edu.cn)  \n†These authors have contributed equally to this work  \nRECEIVED 05 December 2022  \nACCEPTED 05 May 2023  \nPUBLISHED 22 May 2023  \nCITATION  \nHe J, Zhao Y, Zhou Z and Zhang M (2023) Machine learning and integrative analysis identify the common pathogenesis of azoospermia complicated with COVID-19 . Front. Immunol. 14:1114870 .  \ndoi: 10.3389/fimmu.2023.1114870  \nCOPYRIGHT  \n© 2023 He, Zhao, Zhou and Zhang. This isan open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.  \nMachine learning and integrative analysis identify the common pathogenesis of azoospermia complicated with COVID-19  \nJiarong He 1†, Yuanqiao Zhao 2†, Zhixian Zhou 3 and Mingming Zhang 1*  \n1 Department of Neurosurgery, The Second Xiangya Hospital, Central South University, Changsha, Hunan, PR, China, 2 Department of Urology, The Second Xiangya Hospital, Central South University, Changsha, Hunan, PR, China, 3 Department of Obstetrics and Gynecology, The Second Xiangya Hospital, Central South University, Changsha, Hunan, PR, China  \nBackground: Although more recent evidence has indicated COVID-19 is prone to azoospermia, the common molecular mechanism of its occurrence remains to be elucidated. The aim of the present study is to further investigate the mechanism of this complication.  \nMethods: To discover the common differentially expressed genes (DEGs) and pathways of azoospermia and COVID-19, integrated weighted co-expression network (WGCNA), multiple machine learning analyses, and single-cell RNAsequencing (scRNA-seq) were performed.  \nResults: Therefore, we screened two key network modules in the obstructive azoospermia (OA) and non-obstructive azoospermia (NOA) samples. The differentially expressed genes were mainly related to the immune system and infectious virus diseases. We then used multiple machine learning methods to detect biomarkers that differentiated OA from NOA. Enrichment analysis showed that azoospermia patients and COVID-19 patients shared a common IL-17 signaling pathway. In addition, GLO1, GPR135, DYNLL2, and EPB41L3 were identiﬁed as signiﬁcant hub genes in these two diseases. Screening of two different molecular subtypes revealed that azoospermia-related genes were associated with clinicopathological characteristics of age, hospital-free-days, ventilator-free-days, charlson score, and d-dimer of patients with COVID-19 (P \u003C 0. 05) . Finally, we used the Xsum method to predict potential drugs and singlecell sequencing data to further characterize whether azoospermia-related genes could validate the biological patterns of impaired spermatogenesis in cryptozoospermia patients.  \nConclusion: Our study performs a comprehensive and integrated bioinformatics analysis of azoospermia and COVID-19 . These hub genes and common pathways may provide new insights for further mechanism research.  \nKEYWORDS  \nazoospermia, COVID-19, single-cell sequencing, machine learning, WGCNA  \nFrontiers in Immunology 01 [frontiersin.org](frontiersin.org)  \nIntroduction  \nInfertility affects 10-15% of couples worldwide, and nearly half of these are due to male factors. Despite the high prevalence of male infertility, approximately 70% of patients do not receive a timely clinical diagnosis (1) . This knowledge gap prevents clini","cbCaibDNWnyBGUBX","https://ap.wps.com/l/cbCaibDNWnyBGUBX","pdf",22241684,1,17,"English","en",105,"# Introduction\n# Methods\n# Results\n## Network modules and differential genes\n## Shared pathways and hub genes\n## Molecular subtypes and clinical associations\n## Drug prediction and single-cell validation\n# Conclusion","[{\"question\":\"What is the main research aim of the study?\",\"answer\":\"To investigate the common molecular mechanism of azoospermia caused by or complicated with COVID-19 and identify shared genes, pathways, and biomarkers.\"},{\"question\":\"Which analytical approaches were used to identify key biomarkers?\",\"answer\":\"Integrated weighted co-expression network analysis (WGCNA), multiple machine learning analyses, enrichment analyses, and single-cell RNA sequencing.\"},{\"question\":\"What common biological pathway and hub genes were found?\",\"answer\":\"A shared IL-17 signaling pathway was enriched between azoospermia and COVID-19. Hub genes identified include GLO1, GPR135, DYNLL2, and EPB41L3.\"}]","Machine learning and integrative analysis identify the common pathogenesis of azoospermia complicated with COVID-19 | PDF",1785811888,43,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"machine-learning-and-integrative-analysis-identify-the-common-pathogenesis-of-azoospermia-complicated-with-covid-19","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/machine-learning-and-integrative-analysis-identify-the-common-pathogenesis-of-azoospermia-complicated-with-covid-19/122643/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-04",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What is the main research aim of the study?","Question",{"text":75,"@type":76},"To investigate the common molecular mechanism of azoospermia caused by or complicated with COVID-19 and identify shared genes, pathways, and biomarkers.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Which analytical approaches were used to identify key biomarkers?",{"text":80,"@type":76},"Integrated weighted co-expression network analysis (WGCNA), multiple machine learning analyses, enrichment analyses, and single-cell RNA sequencing.",{"name":82,"@type":73,"acceptedAnswer":83},"What common biological pathway and hub genes were found?",{"text":84,"@type":76},"A shared IL-17 signaling pathway was enriched between azoospermia and COVID-19. 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