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<p>The association between oxidative stress and osteoporosis (OP) has been substantiated by numerous studies; however, the precise underlying mechanism remains elusive. Hence, we employed bioinformatics methodologies to investigate this phenomenon. OP-related datasets (GSE56815 and GSE7158) were utilized in this study. Key module genes linked to oxidative stress-related genes (OS-RGs) were acquired through weighted gene coexpression network analysis (WGCNA). By crossing key module genes and differentially expressed genes (DEGs) from differential expression analysis, candidate genes were obtained. Subsequently, diagnostic genes were obtained through receiver operating characteristic (ROC) curve analysis and expression evaluation. Furthermore, a nomogram model was developed utilizing these genes to assess the collective predictive capacity of the diagnostic genes for OP comprehensively. Additionally, gene set variation analysis (GSVA), immune analysis, and construction of a molecular regulatory network were implemented to further understand the mechanism of the diagnostic genes in OP. We also preliminarily verified the effect of NAPG on osteogenic differentiation through experiments such as ALP, ARS and Western Blot. A total of 101 candidate genes were identified by crossing 395 DEGs and 1,730 key module genes. Importantly, NAPG, NCOA1, and TRIM44 were identified as diagnostic genes associated with oxidative stress in OP. The nomogram model showed the potential predictive ability of OP. Moreover, the GSVA results demonstrated that low expression of NAPG, NCOA1, and TRIM44 was enriched in the oestrogen response early signalling pathway. Moreover, these diagnostic genes were strongly correlated with multiple immune-related genes in the two datasets. Additionally, we identified several important factors that have regulatory relationships with diagnostic genes, such as MEF2A, STAT3, YY1, CREB1, hsa-mir-132-3p, and hsa-mir-148a-3p. Finally, it was verified at the protein and cellular levels that NAPG inhibits osteogenic differentiation and may play a crucial role in osteoporosis. NAPG, NCOA1, and TRIM44 were found to be associated with the diagnosis of OP, suggesting novel opportunities for diagnosing and treating OP.</p>

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Identification and verification of oxidative stress-related genes in the diagnosis of osteoporosis

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月2日

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  • Zhenchuan Liu,
  • Xu Yang,
  • Zexin Wang,
  • Qi Li,
  • Hanwen Gu,
  • Qunbo Meng,
  • Yuanqiang Zhang

摘要

The association between oxidative stress and osteoporosis (OP) has been substantiated by numerous studies; however, the precise underlying mechanism remains elusive. Hence, we employed bioinformatics methodologies to investigate this phenomenon. OP-related datasets (GSE56815 and GSE7158) were utilized in this study. Key module genes linked to oxidative stress-related genes (OS-RGs) were acquired through weighted gene coexpression network analysis (WGCNA). By crossing key module genes and differentially expressed genes (DEGs) from differential expression analysis, candidate genes were obtained. Subsequently, diagnostic genes were obtained through receiver operating characteristic (ROC) curve analysis and expression evaluation. Furthermore, a nomogram model was developed utilizing these genes to assess the collective predictive capacity of the diagnostic genes for OP comprehensively. Additionally, gene set variation analysis (GSVA), immune analysis, and construction of a molecular regulatory network were implemented to further understand the mechanism of the diagnostic genes in OP. We also preliminarily verified the effect of NAPG on osteogenic differentiation through experiments such as ALP, ARS and Western Blot. A total of 101 candidate genes were identified by crossing 395 DEGs and 1,730 key module genes. Importantly, NAPG, NCOA1, and TRIM44 were identified as diagnostic genes associated with oxidative stress in OP. The nomogram model showed the potential predictive ability of OP. Moreover, the GSVA results demonstrated that low expression of NAPG, NCOA1, and TRIM44 was enriched in the oestrogen response early signalling pathway. Moreover, these diagnostic genes were strongly correlated with multiple immune-related genes in the two datasets. Additionally, we identified several important factors that have regulatory relationships with diagnostic genes, such as MEF2A, STAT3, YY1, CREB1, hsa-mir-132-3p, and hsa-mir-148a-3p. Finally, it was verified at the protein and cellular levels that NAPG inhibits osteogenic differentiation and may play a crucial role in osteoporosis. NAPG, NCOA1, and TRIM44 were found to be associated with the diagnosis of OP, suggesting novel opportunities for diagnosing and treating OP.