ArticlePloS one2023
Screening of potential biomarkers for polycystic ovary syndrome and identification of expression and immune characteristics.
Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 13 citations in OpenAlex.
- Heme oxygenase-1 emerges as a critical regulator linking autophagy dysregulation, immune infiltration, and NOD-Like receptor signaling in PCOS pathogenesis.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2026Article
- Screening of Oxidative Stress-related Biomarkers and Antioxidant Drugs for Polycystic Ovary Syndrome Based on Bioinformatics and Molecular Docking.Reproductive sciences (Thousand Oaks, Calif.) · 2025Article
- Development of machine learning models for diagnostic biomarker identification and immune cell infiltration analysis in PCOS.Journal of ovarian research · 2025Article
- Mendelian Randomization and Transcriptomics Analysis Reveal Potential Relationships Between Lipids, Immune Cells and PCOS.International journal of women's health · 2025Article
- Article
- The promoter T-413A variant and elevated enzyme levels of heme oxygenase-1 associated with an increased risk of polycystic ovarian syndrome.Frontiers in endocrinology · 2025Article
- The shared genetic landscape of polycystic ovary syndrome and breast cancer: convergence on ER + breast cancer but not ER- breast cancer.Breast cancer research : BCR · 2024Article
- Kallistatin as a Potential Biomarker in Polycystic Ovary Syndrome: A Prospective Cohort Study.Diagnostics (Basel, Switzerland) · 2024Article
- Identification of crucial pathways and genes linked to endoplasmic reticulum stress in PCOS through combined bioinformatic analysis.Frontiers in molecular biosciences · 2024Article
Corrections and comments
- Retraction · 2025-08-12Concerns/Issues about Methods · Unreliable Results and/or Conclusions ·
- Retracted
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPolycystic ovary syndrome (PCOS) seriously affects the fertility and health of women of childbearing age. We look forward to finding potential biomarkers for PCOS that can aid clinical diagnosis.
methodsWe acquired PCOS and normal granulosa cell (GC) expression profiles from the Gene Expression Omnibus (GEO) database. After data preprocessing, differentially expressed genes (DEGs) were screened by limma package, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and Gene Set Enrichment Analysis (GSEA) were performed. Recursive feature elimination (RFE) algorithm and the least absolute shrinkage and selection operator (LASSO) Cox regression analysis were used to acquire feature genes as potential biomarkers. Time-dependent receiver operator characteristic curve (ROC curve) and Confusion matrix were used to verify the classification performance of biomarkers. Then, the expression characteristics of biomarkers in PCOS and normal cells were analyzed, and the insulin resistance (IR) score of samples was computed by ssGSEA. Immune characterization of biomarkers was evaluated using MCP counter and single sample gene set enrichment analysis (ssGSEA). Finally, the correlation between biomarkers and the scores of each pathway was assessed.
resultsWe acquired 93 DEGs, and the enrichment results indicated that most of DEGs in PCOS group were significantly enriched in immune-related biological pathways. Further screening results indicated that JDP2 and HMOX1 were potential biomarkers. The area under ROC curve (AUC) value and Confusion matrix of the two biomarkers were ideal when separated and combined. In the combination, the training set AUC = 0.929 and the test set AUC = 0.917 indicated good diagnostic performance of the two biomarkers. Both biomarkers were highly expressed in the PCOS group, and both biomarkers, which should be suppressed in the preovulation phase, were elevated in PCOS tissues. The IR score of PCOS group was higher, and the expression of JDP2 and HMOX1 showed a significant positive correlation with IR score. Most immune cell scores and immune infiltration results were significantly higher in PCOS. Comprehensive analysis indicated that the two biomarkers had strong correlation with immune-related pathways.
conclusionWe acquired two potential biomarkers, JDP2 and HMOX1. We found that they were highly expressed in the PCOS and had a strong positive correlation with immune-related pathways.
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