[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-125572-en":3,"doc-seo-125572-105":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},125572,687197100911,"Himbo","https://ap-avatar.wpscdn.com/avatar/a000239b6f1da00475?x-image-process=image/resize,m_fixed,w_180,h_180&k=1785132997149421697",8,"Research & Report","Identification of immune-associated genes in diagnosing osteoarthritis with metabolic syndrome by integrated bioinformatics analysis and machine learning","Osteoarthritis (OA) and metabolic syndrome (MetS) share overlapping pathological processes, and immune dysregulation may influence disease onset and progression. This study integrates gene-expression data from public GEO resources and applies differential-expression analysis, weighted gene co-expression network analysis, enrichment assessment, immune infiltration profiling, and machine-learning feature screening to uncover immune-related diagnostic candidates. Key immune genes were validated through nomograms and receiver operating characteristic evaluation, supporting their diagnostic utility for identifying OA in patients with MetS.","TYPE Original Research PUBLISHED 17 April 2023  \nDOI 10.3389/fimmu.2023.1134412  \nOPEN ACCESS  \nEDITED BY  \nMichael V. Volin,  \nMidwestern University, United States  \nREVIEWED BY Ming Lu,  \nAnhui Medical University, China Maria Andersson,  \nLund University, Sweden  \n*CORRESPONDENCE Xiaofeng Zhang  \n [zxfenghlj@163.com](zxfenghlj@163.com)  \n†These authors have contributed equally to this work and share first authorship  \nSPECIALTY SECTION  \nThis article was submitted to Inflammation,  \na section of the journal Frontiers in Immunology  \nRECEIVED 30 December 2022  \nACCEPTED 27 March 2023  \nPUBLISHED 17 April 2023  \nCITATION  \nLi J, Wang G, Xv X, Li Z, Shen Y, Zhang Cand Zhang X (2023) Identification of immune-associated genes in diagnosing osteoarthritis with metabolic syndrome by integrated bioinformatics analysis and machine learning.  \nFront. Immunol. 14:1134412 .  \ndoi: 10.3389/fimmu.2023.1134412  \nCOPYRIGHT  \n© 2023 Li, Wang, Xv, Li, Shen, Zhang and Zhang. This is an 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.  \nIdentification of immuneassociated genes in diagnosing osteoarthritis with metabolic syndrome by integrated bioinformatics analysis and machine learning  \nJunchen Li 1†, Genghong Wang 1†, Xilin Xv 2,3, Zhigang Li 4, Yiwei Shen 1, Cheng Zhang 1 and Xiaofeng Zhang 3,5*  \n1The Graduate School, Heilongjiang University of Chinese Medicine, Harbin, China, 2The Third Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, China, 3Teaching and Research Section of Orthopedics and Traumatology, Heilongjiang University of Chinese Medicine, Harbin, China, 4The Second Department of Orthopedics and Traumatology, The Second Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, China, 5The Bone Injury Teaching Laboratory, Heilongjiang University of Chinese Medicine, Harbin, China  \nBackground: In the pathogenesis of osteoarthritis (OA) and metabolic syndrome (MetS), the immune system plays a particularly important role. The purpose of this study was to find key diagnostic candidate genes in OA patients who also had metabolic syndrome.  \nMethods: We searched the Gene Expression Omnibus (GEO) database for three OA and one MetS dataset. Limma, weighted gene co-expression network analysis (WGCNA), and machine learning algorithms were used to identify and analyze the immune genes associated with OA and MetS. They were evaluated using nomograms and receiver operating characteristic (ROC) curves, and finally, immune cells dysregulated in OA were investigated using immune infiltration analysis.  \nResults: After Limma analysis, the integrated OA dataset yielded 2263 DEGs, and the MetS dataset yielded the most relevant module containing 691 genes after WGCNA, with a total of 82 intersections between the two. The immune-related genes were mostly enriched in the enrichment analysis, and the immune infiltration analysis revealed an imbalance in multiple immune cells. Further machine learning screening yielded eight core genes that were evaluated by nomogram and diagnostic value and found to have a high diagnostic value (area under the curve from 0 .82 to 0 .96) .  \nConclusion: Eight immune-related core genes were identified (FZD7, IRAK3, KDELR3, PHC2, RHOB, RNF170, SOX13, and ZKSCAN4), and a nomogram for the diagnosis of OA and MetS was established. This research could lead to the identification of potential peripheral blood diagnostic candidate genes for MetS patients who also suffer from OA.  \nKEYWORDS  \ndifferentially expressed genes, osteoarthritis, metabolic syndrome, machine learning, immune infiltration  \nFrontiers in Immu","cbCaituH9wdTtd5s","https://ap.wps.com/l/cbCaituH9wdTtd5s","pdf",3860838,1,13,"English","en",105,"# Introduction\n# Methods\n# Results\n# Conclusion","[{\"question\":\"What was the main objective of this study?\",\"answer\":\"To identify immune-associated key candidate genes that could help diagnose osteoarthritis in patients with metabolic syndrome.\"},{\"question\":\"Which data and analytical methods were used to discover candidate immune genes?\",\"answer\":\"The study mined three OA and one MetS datasets from the GEO database, then used limma, WGCNA, enrichment analysis, immune infiltration analysis, and machine-learning algorithms.\"},{\"question\":\"How were the identified genes evaluated for diagnostic performance?\",\"answer\":\"Candidate genes were assessed using nomograms and receiver operating characteristic (ROC) curves, showing high diagnostic value across the reported AUC range.\"}]","Identification of immune-associated genes in diagnosing osteoarthritis with metabolic syndrome by integrated bioinformatics analysis and machine learning | PDF",1785899954,33,{"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},"identification-of-immune-associated-genes-in-diagnosing-osteoarthritis-with-metabolic-syndrome-by-integrated-bioinformatics-analysis-and-machine-learning","",{"@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/identification-of-immune-associated-genes-in-diagnosing-osteoarthritis-with-metabolic-syndrome-by-integrated-bioinformatics-analysis-and-machine-learning/125572/",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","2026-08-05",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 was the main objective of this study?","Question",{"text":75,"@type":76},"To identify immune-associated key candidate genes that could help diagnose osteoarthritis in patients with metabolic syndrome.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Which data and analytical methods were used to discover candidate immune genes?",{"text":80,"@type":76},"The study mined three OA and one MetS datasets from the GEO database, then used limma, WGCNA, enrichment analysis, immune infiltration analysis, and machine-learning algorithms.",{"name":82,"@type":73,"acceptedAnswer":83},"How were the identified genes evaluated for diagnostic performance?",{"text":84,"@type":76},"Candidate genes were assessed using nomograms and receiver operating characteristic (ROC) curves, showing high diagnostic value across the reported AUC range.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]