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Backgrounds <p>Osteoarthritis (OA) is a chronic degenerative joint disease increasingly recognized as an immunopathological condition. While immune responses and programmed cell death (PCD) are both implicated in OA progression, the molecular crosstalk between these processes and their key mediators remain poorly defined.</p> Methods <p>Candidate OA-associated PCD genes were obtained by using single-sample gene set enrichment analysis, weighted gene co-expression network analysis, and differentially expressed genes (DEGs). Function annotation of candidates was performed using ClueGO. Four machine learning algorithms were employed to identify key molecules. Their expressions and distributions were characterized at the single-cell level. Finally, key gene expressions were validated by quantitative real-time PCR (qRT-PCR).</p> Results <p>A total of 44 candidate genes were obtained, involving in antigen presentation, TNF superfamily cytokine production and immune-regulating signaling pathways. XGBoost and random forest models exhibited superior performance, revealing <i>VAV1</i>, <i>HLA-DMB</i>, <i>TYROBP</i>, <i>S100A11</i>, <i>CD74</i>, and <i>MR1</i> as key genes. Subsequently, T cells CD4 memory resting showed a substantial negative correlation with <i>CD74</i>, <i>HLA-DMB</i>, <i>MR1</i>, <i>S100A11</i>, and <i>TYROBP</i>, whereas activated dendritic cells were significantly positively correlated with <i>HLA-DMB</i>, <i>TYROBP</i>, and <i>VAV1</i>. The scRNA-seq further localized the expressions of key genes in myeloid cells and dendritic cells. Finally, qRT-PCR results validated the upregulation of <i>TYROBP</i>, <i>HLA-DMB</i>, and <i>S100A11</i> in OA tissues.</p> Conclusion <p>This study identifies six netotic cell death-related immune genes with diagnostic and mechanistic relevance in OA. These findings provide new insight into the immune-cell death interface in OA and offer a molecular basis for the development of targeted therapeutic strategies.</p>

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Identification and validation of NETotic cell death-related immune biomarkers in osteoarthritis

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年8月1日

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  • Hao Tang,
  • Gangyi Sun,
  • Shuwen Mao

摘要

Backgrounds

Osteoarthritis (OA) is a chronic degenerative joint disease increasingly recognized as an immunopathological condition. While immune responses and programmed cell death (PCD) are both implicated in OA progression, the molecular crosstalk between these processes and their key mediators remain poorly defined.

Methods

Candidate OA-associated PCD genes were obtained by using single-sample gene set enrichment analysis, weighted gene co-expression network analysis, and differentially expressed genes (DEGs). Function annotation of candidates was performed using ClueGO. Four machine learning algorithms were employed to identify key molecules. Their expressions and distributions were characterized at the single-cell level. Finally, key gene expressions were validated by quantitative real-time PCR (qRT-PCR).

Results

A total of 44 candidate genes were obtained, involving in antigen presentation, TNF superfamily cytokine production and immune-regulating signaling pathways. XGBoost and random forest models exhibited superior performance, revealing VAV1, HLA-DMB, TYROBP, S100A11, CD74, and MR1 as key genes. Subsequently, T cells CD4 memory resting showed a substantial negative correlation with CD74, HLA-DMB, MR1, S100A11, and TYROBP, whereas activated dendritic cells were significantly positively correlated with HLA-DMB, TYROBP, and VAV1. The scRNA-seq further localized the expressions of key genes in myeloid cells and dendritic cells. Finally, qRT-PCR results validated the upregulation of TYROBP, HLA-DMB, and S100A11 in OA tissues.

Conclusion

This study identifies six netotic cell death-related immune genes with diagnostic and mechanistic relevance in OA. These findings provide new insight into the immune-cell death interface in OA and offer a molecular basis for the development of targeted therapeutic strategies.