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<p>Chronic cadmium chloride (CC) exposure is associated with diverse toxicological outcomes, yet its potential role in the pathogenesis of ankylosing spondylitis (AS) remains unclear. This study employed a network toxicology framework to computationally elucidate the potential molecular mechanisms linking CC exposure to AS. AS-associated differentially expressed genes (DEGs) were identified from the GSE73754 dataset. Potential CC toxicity targets were retrieved from the Comparative Toxicogenomics Database (CTD). Overlapping genes were subjected to functional enrichment analysis, protein–protein interaction (PPI) network construction, and identification of core targets using multiple machine learning algorithms (LASSO, SVM, random forest, and XGBoost). A predictive nomogram was developed. Pathway activity dysregulation was assessed via Gene Set Variation Analysis (GSVA), and immune cell infiltration patterns were evaluated using the MCPcounter method. Additionally, two-sample Mendelian randomization (MR) analysis was performed to evaluate the causal relationship between the core target ETFA and AS, and in silico knockout of ETFA was conducted using single-cell RNA-seq data (GSE194315) to assess its regulatory impact. We identified 45 shared targets between putative CC toxicity and AS-associated DEGs. Enrichment analysis revealed their significant involvement in cytokine-mediated signaling, immune response, necroptosis, and the HIF-1 signaling pathway. PPI network analysis highlighted key hub proteins, including TNF, STAT3, and CXCL8. Machine learning models prioritized ZFC3H1, SCRN1, and ETFA as core toxicity-related targets, and the constructed nomogram demonstrated high predictive accuracy. In vitro validation in a HFLS chronic CC exposure model confirmed significant dysregulation of these core targets, with ZFC3H1 expression suppressed and SCRN1 and ETFA markedly upregulated. GSVA indicated a downregulation of several immune-related pathways in AS. Immune infiltration analysis showed altered abundances of cytotoxic lymphocytes, monocytes, and neutrophils. Correlation analysis linked the core targets to dysregulated pathways, particularly associating ZFC3H1 with humoral immune response and osteoclast differentiation. MR analysis indicated that ETFA is a potential risk factor for AS, with the inverse variance weighted method showing a nominally significant association. Virtual knockout of ETFA in AS single‑cell data led to substantial upregulation of immune-related genes, including S100A8, S100A9, S100A12, and multiple HLA class II genes, and enriched pathways such as antigen processing and presentation and phagosome. This study suggests that chronic CC exposure may exacerbate AS pathogenesis by perturbing immune-inflammatory pathways and altering immune cell infiltration. The core targets identified (ZFC3H1, SCRN1, ETFA) offer novel mechanistic insights into this link, with MR and knockout analyses further supporting ETFA as a causal risk factor involved in immune dysregulation, thereby highlighting the need for further experimental validation.</p>

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Molecular mechanisms linking cadmium chloride exposure to ankylosing spondylitis: an integrative network-based study

  • 期刊论文

  • 发表日期：

    2026年5月11日

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  • Zhuchen Liu,
  • Zhirui Xue,
  • Hanbing Song,
  • Qipeng Chen,
  • Jingwen Zhang,
  • Geqiang Wang

摘要

Chronic cadmium chloride (CC) exposure is associated with diverse toxicological outcomes, yet its potential role in the pathogenesis of ankylosing spondylitis (AS) remains unclear. This study employed a network toxicology framework to computationally elucidate the potential molecular mechanisms linking CC exposure to AS. AS-associated differentially expressed genes (DEGs) were identified from the GSE73754 dataset. Potential CC toxicity targets were retrieved from the Comparative Toxicogenomics Database (CTD). Overlapping genes were subjected to functional enrichment analysis, protein–protein interaction (PPI) network construction, and identification of core targets using multiple machine learning algorithms (LASSO, SVM, random forest, and XGBoost). A predictive nomogram was developed. Pathway activity dysregulation was assessed via Gene Set Variation Analysis (GSVA), and immune cell infiltration patterns were evaluated using the MCPcounter method. Additionally, two-sample Mendelian randomization (MR) analysis was performed to evaluate the causal relationship between the core target ETFA and AS, and in silico knockout of ETFA was conducted using single-cell RNA-seq data (GSE194315) to assess its regulatory impact. We identified 45 shared targets between putative CC toxicity and AS-associated DEGs. Enrichment analysis revealed their significant involvement in cytokine-mediated signaling, immune response, necroptosis, and the HIF-1 signaling pathway. PPI network analysis highlighted key hub proteins, including TNF, STAT3, and CXCL8. Machine learning models prioritized ZFC3H1, SCRN1, and ETFA as core toxicity-related targets, and the constructed nomogram demonstrated high predictive accuracy. In vitro validation in a HFLS chronic CC exposure model confirmed significant dysregulation of these core targets, with ZFC3H1 expression suppressed and SCRN1 and ETFA markedly upregulated. GSVA indicated a downregulation of several immune-related pathways in AS. Immune infiltration analysis showed altered abundances of cytotoxic lymphocytes, monocytes, and neutrophils. Correlation analysis linked the core targets to dysregulated pathways, particularly associating ZFC3H1 with humoral immune response and osteoclast differentiation. MR analysis indicated that ETFA is a potential risk factor for AS, with the inverse variance weighted method showing a nominally significant association. Virtual knockout of ETFA in AS single‑cell data led to substantial upregulation of immune-related genes, including S100A8, S100A9, S100A12, and multiple HLA class II genes, and enriched pathways such as antigen processing and presentation and phagosome. This study suggests that chronic CC exposure may exacerbate AS pathogenesis by perturbing immune-inflammatory pathways and altering immune cell infiltration. The core targets identified (ZFC3H1, SCRN1, ETFA) offer novel mechanistic insights into this link, with MR and knockout analyses further supporting ETFA as a causal risk factor involved in immune dysregulation, thereby highlighting the need for further experimental validation.