{
  "abstract": "Non-obstructive azoospermia (NOA) is a severe male infertility disorder. This study aims to identify immune-related biomarkers for explore immune-related molecular signatures associated with NOA. Here, we integrated transcriptomic data from four independent cohorts (GSE145467, GSE45885, GSE45887, GSE9210) using an integrative pipeline combining differential expression analysis, weighted gene co-expression network analysis (WGCNA), and consensus-based multi-machine learning to identify an immune-related gene signature associated with NOA. We identified 16 immune-related differentially expressed genes through WGCNA, which were refined into a 12-gene panel—Hub NOA.Sig (CD14, CD19, CMTM2, CXCL16, HSPA1L, HSPA2, IGF1, IL13, POMC, RBP1, STAB2, TYROBP)—using five feature selection algorithms (Bagged Trees, Bayesian, Boruta, LASSO, LVQ). A Random Forest classifier based on Hub NOA.Sig yielded good classification performance with an AUC of 0.87. This signature offers a transcriptomic reference for characterizing NOA heterogeneity and exploring immune-related molecular features. Single-sample gene set enrichment analysis (ssGSEA) revealed significant alterations in six immune cell populations—including effector memory CD4 ⁺ /CD8 ⁺ T cells, regulatory T cells, and plasmacytoid dendritic cells—and demonstrated strong correlations between hub genes and specific immune infiltrates. Furthermore, drug-gene interaction screening and molecular docking predicted loperamide-POMC, acitretin-RBP1, and retinol-RBP1 as candidate drug-gene pairs for subsequent experimental validation. This work provides transcriptomic clues and candidate molecular targets for future mechanistic investigations into NOA-related male infertility.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Urology, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China",
    "Assisted Reproductive Technology Center, The Affiliated Foshan Women and Children Hospital, Guangdong Medical University, Foshan, China",
    "Department of Urology, Affiliated Hospital Group of Guangdong Medical University Shenzhen Baoan Central Hospital, Shenzhen, Guangdong, China"
  ],
  "article_type": "Research Article",
  "arxiv": null,
  "author_total": 6,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Yucheng Zhong"
    },
    {
      "affs": [
        1
      ],
      "name": "Songqing Ye"
    },
    {
      "affs": [
        2
      ],
      "name": "Hongshen Lai"
    },
    {
      "name": "Xiangyu Zeng"
    },
    {
      "name": "Ge Song"
    },
    {
      "name": "Xiaofu Qiu"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/4y1y929n0j0mp.bib",
  "cited_by": 0,
  "doi": "10.1371/journal.pone.0360305",
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  "id": "4y1y929n0j0mp",
  "issns": [
    "1932-6203"
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  "landing_url": "https://doi.org/10.1371/journal.pone.0360305",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
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  "native_subjects": [
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      "2743|Sperm and Testicular Function"
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      "plos",
      "/Biology and life sciences/Cell biology/Cellular types/Animal cells/Immune cells"
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      "/Biology and life sciences/Genetics/Genomics/Genome analysis/Transcriptome analysis"
    ],
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      "/Biology and life sciences/Immunology/Immune cells"
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      "/Biology and life sciences/Immunology/Immune cells/Antigen-presenting cells/Dendritic cells"
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      "plos",
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      "/Medicine and health sciences/Immunology/Immune cells"
    ],
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      "plos",
      "/Medicine and health sciences/Immunology/Immune cells/Antigen-presenting cells/Dendritic cells"
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      "/Research and analysis methods/Mathematical and statistical techniques/Statistical methods/Forecasting"
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      "plos",
      "/Research and analysis methods/Simulation and modeling/Algorithms/Machine learning algorithms"
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  "pdf_url": "https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0360305&type=printable",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-12",
  "publisher": "Public Library of Science",
  "ris": "https://research.draconitic.com/paper/4y1y929n0j0mp.ris",
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    {
      "first_seen": "2026-10-30T12:17:30Z",
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      "url": "https://doi.org/10.1371/journal.pone.0360305"
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  "subjects": [
    {
      "field": "biology",
      "origin": "plos:cell biology",
      "subfield": "cell-biology"
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      "origin": "plos:immunology",
      "subfield": "immunology"
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  "title": "Integrated bioinformatics analysis identifies an immune-related gene signature associated with non-obstructive azoospermia",
  "title_text": "Integrated bioinformatics analysis identifies an immune-related gene signature associated with non-obstructive azoospermia",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:17:30Z",
  "url": "https://research.draconitic.com/paper/4y1y929n0j0mp",
  "venue": "PLOS One",
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}