{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T15:54:23Z","timestamp":1792079663063,"version":"4.4.0"},"reference-count":78,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2024,11,21]],"date-time":"2024-11-21T00:00:00Z","timestamp":1732147200000},"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. Endocrinol."],"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>Oxidative stress has been implicated in the pathogenesis of uterine leiomyoma (ULM) with an increasing incidence. This study aimed to identify potential oxidative stress-related biomarkers in ULM using transcriptome data integrated with Mendelian randomization (MR) analysis.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Data from GSE64763 and GSE31699 in the Gene Expression Omnibus (GEO) were included in the analysis. Oxidative stress-related genes (OSRGs) were identified, and the intersection of differentially expressed genes (DEGs), Weighted Gene Co-expression Network Analysis (WGCNA) genes, and OSRGs was used to derive differentially expressed oxidative stress-related genes (DE-OSRGs). Biomarkers were subsequently identified <jats:italic>via<\/jats:italic> MR analysis, followed by Gene Set Enrichment Analysis (GSEA) and immune infiltration analysis. Nomograms, regulatory networks, and gene-drug interaction networks were constructed based on the identified biomarkers.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>A total of 883 DEGs were identified between ULM and control samples, from which 42 DE-OSRGs were screened. MR analysis revealed four biomarkers: <jats:italic>ANXA1<\/jats:italic>, <jats:italic>CD36<\/jats:italic>, <jats:italic>MICB<\/jats:italic>, and <jats:italic>PRDX6<\/jats:italic>. Predictive nomograms were generated based on these biomarkers. <jats:italic>ANXA1<\/jats:italic>, <jats:italic>CD36<\/jats:italic>, and <jats:italic>MICB<\/jats:italic> were significantly enriched in chemokine signaling and other pathways. Notably, <jats:italic>ANXA1<\/jats:italic> showed strong associations with follicular helper T cells, resting mast cells, and M0 macrophages. <jats:italic>CD36<\/jats:italic> was positively correlated with resting mast cells, while <jats:italic>MICB<\/jats:italic> was negatively correlated with macrophages. Additionally, <jats:italic>ANXA1<\/jats:italic> displayed strong binding energy with amcinonide, and <jats:italic>MICB<\/jats:italic> with ribavirin.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>This study identified oxidative stress-related biomarkers (ANXA1, CD36, MICB, and PRDX6) in ULM through transcriptomic and MR analysis, providing valuable insights for ULM therapeutic research.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fendo.2024.1373011","type":"journal-article","created":{"date-parts":[[2024,11,21]],"date-time":"2024-11-21T04:33:50Z","timestamp":1732163630000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":9,"title":["Identification of oxidative stress-related biomarkers in uterine leiomyoma: a transcriptome-combined Mendelian randomization analysis"],"prefix":"10.3389","volume":"15","author":[{"given":"Yingxiao","family":"Li","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haoyue","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hao","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhaochen","family":"Lin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liang","family":"Song","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chuanliang","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2024,11,21]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"102861","DOI":"10.1016\/j.redox.2023.102861","article-title":"Oxidative stress mediates the inhibitory effects of Manzamine A on uterine leiomyoma cell proliferation and extracellular matrix deposition via SOAT inhibition","volume":"66","author":"Lin","year":"2023","journal-title":"Redox Biol"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.1016\/j.fertnstert.2023.01.022","article-title":"Racial disparities in uterine fibroids and endometriosis: a systematic review and application of social, structural, and political context","volume":"119","author":"Katon","year":"2023","journal-title":"Fertil Steril"},{"key":"B3","doi-asserted-by":"publisher","first-page":"1117","DOI":"10.3390\/cells12081117","article-title":"Progesterone signaling and uterine fibroid pathogenesis; molecular mechanisms and potential therapeutics","volume":"12","author":"Ali","year":"2023","journal-title":"Cells"},{"key":"B4","doi-asserted-by":"publisher","DOI":"10.3389\/fendo.2023.1133260","article-title":"Genetic liability to multiple factors and uterine leiomyoma risk: a Mendelian randomization study","volume":"14","author":"Qu","year":"2023","journal-title":"Front Endocrinol (Lausanne)"},{"key":"B5","doi-asserted-by":"publisher","DOI":"10.1007\/s00011-022-01621-y","article-title":"Lipoxin alleviates oxidative stress: a state-of-the-art review","volume":"71","author":"Zhou","year":"2022","journal-title":"Inflammation Res"},{"key":"B6","doi-asserted-by":"publisher","first-page":"4105","DOI":"10.3390\/cells11244105","article-title":"To be or not to be? 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