{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T10:19:51Z","timestamp":1788949191669,"version":"build-2803163510"},"reference-count":85,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2024,9,11]],"date-time":"2024-09-11T00:00:00Z","timestamp":1726012800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Med."],"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>Polycystic ovary syndrome (PCOS) can lead to infertility and increase the risk of endometrial cancer. Analyzing the macrophage polarization characteristics in ovarian tissues of PCOS is crucial for clinical treatment.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>We obtained 13 PCOS and nine control ovarian samples from the CEO database and analyzed differentially expressed genes (DEGs). Macrophage polarization-related genes (MPRGs) were sourced from the GeneCards and MSigDB databases. Intersection of DEGs with MPRGs identified DEGs associated with macrophage polarization (MPRDEGs). Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Protein\u2013protein interaction (PPI) Network analysis were conducted on MPRDEGs. Moreover, the top 10 genes from three algorithms were identified as the hub genes of MPRGs. In addition, miRNAs, transcription factors (TFs), and drugs were retrieved from relevant databases for regulatory network analysis of mRNA-miRNA, mRNA-TF, and mRNA-Drug interactions. Immune cell composition analysis between the PCOS and control groups was performed using the CIBERSORT algorithm to calculate correlations across 22 immune cell types.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>A total of 13 PCOS samples and nine control ovarian samples were obtained in this study. We identified 714 DEGs between the two groups, with 394 up-regulated and 320 down-regulated. Additionally, we identified 774 MPRGs, from which we derived 30 MPRDEGs by intersecting with DEGs, among which 21 exhibited interaction relationships. GO and KEGG analyses revealed the enrichment of MPRDEGs in five biological processes, five cell components, five molecular functions, and three biological pathways. Immune infiltration analysis indicated a strong positive correlation between activated nature killer (NK) cells and memory B cells, while neutrophils and monocytes showed the strongest negative correlation. Further investigation of MPRDEGs identified nine hub genes associated with 41 TFs, 82 miRNAs, and 44 drugs or molecular compounds. Additionally, qRT-PCR results demonstrated overexpression of the CD163, TREM1, and TREM2 genes in ovarian tissues from the PCOS group.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>This study elucidated the polarization status and regulatory characteristics of macrophages in ovarian tissues of the PCOS subjects, confirming significant overexpression of CD163, TREM1, and TREM2. These findings contribute to a deeper understanding of the pathogenesis of PCOS.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fmed.2024.1417983","type":"journal-article","created":{"date-parts":[[2024,9,11]],"date-time":"2024-09-11T04:13:56Z","timestamp":1726028036000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["Analysis of macrophage polarization and regulation characteristics in ovarian tissues of polycystic ovary syndrome"],"prefix":"10.3389","volume":"11","author":[{"given":"Yue","family":"Yuan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yan","family":"Mao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liu","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yilin","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xuehong","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2024,9,11]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"219","DOI":"10.1038\/nrendo.2010.217","article-title":"Polycystic ovary syndrome: etiology, pathogenesis and diagnosis","volume":"7","author":"Goodarzi","year":"2011","journal-title":"Nat Rev Endocrinol"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1097\/AOG.0000000000002698","article-title":"Polycystic ovary syndrome","volume":"132","author":"Azziz","year":"2018","journal-title":"Obstet Gynecol"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1093\/aje\/kwae061","article-title":"Polycystic ovary syndrome and endometrial cancer risk: results from a nationwide cohort study","author":"Frandsen","year":"2024","journal-title":"Am J Epidemiol"},{"key":"ref4","doi-asserted-by":"publisher","first-page":"314","DOI":"10.1016\/j.cjco.2023.12.010","article-title":"Increased prevalence of adverse health outcomes across the lifespan in those affected by polycystic ovary syndrome: a Canadian population cohort","volume":"6","author":"Vine","year":"2024","journal-title":"CJC Open"},{"key":"ref5","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1056\/NEJMcp1514916","article-title":"CLINICAL PRACTICE. 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