Luo Yuwen, Liu Shizhen, Liu Xianyin, Zhong Shu, Wang Ye, Wan Zheng
Department of Orthopaedics, Dongguan Hospital Affiliated to Southern Medical University (Dongguan People's Hospital), Dongguan 523059, Guangdong, China.
Department of Geriatrics, Zhongshan Hospital Xiamen University, School of Medicine, Xiamen University, Xiamen 361000, Fujian, China.
Int J Endocrinol. 2025 Aug 30;2025:8816596. doi: 10.1155/ije/8816596. eCollection 2025.
Osteoporosis is a progressive bone disease characterized by reduced bone density and deterioration of bone microarchitecture, predominantly affecting the elderly population. The ongoing COVID-19 pandemic has introduced additional challenges in osteoporosis management, potentially due to systemic inflammation and direct viral impacts on bone metabolism. This study aims to identify common differentially expressed genes (DEGs) and key molecular pathways shared between osteoporosis and COVID-19, with the goal of uncovering potential therapeutic targets through bioinformatics analysis. Publicly available gene expression datasets GSE164805 (osteoporosis) and GSE230665 (COVID-19) were analyzed to identify overlapping DEGs. Functional enrichment analysis using Gene Ontology (GO), pathway analysis, protein-protein interaction (PPI) network construction, and transcription factor (TF)-hub gene regulatory network analysis were performed to explore the biological significance and regulatory mechanisms of these DEGs. A total of 325 common DEGs were identified between osteoporosis and COVID-19. GO enrichment analysis revealed significant involvement in signal transduction and plasma membrane components. Pathway analysis highlighted the "cytokine-cytokine receptor interaction" pathway as a central player. PPI network analysis identified a module of 193 genes with 397 interactions, from which 10 key hub genes were prioritized: ACTB, CDH1, RPS8, IFNG, RPL17, UBC, RPL36, RPS4Y1, GSK3B, and FGF13. Furthermore, 76 TFs were found to regulate these hub genes, and 15 existing drugs targeting four of these hub genes were identified. This integrative bioinformatics study reveals 15 candidate therapeutic agents that target key regulatory genes shared between osteoporosis and COVID-19, offering promising treatment strategies for osteoporotic patients, especially those impacted by or at risk of SARS-CoV-2 infection.
骨质疏松症是一种进行性骨病,其特征是骨密度降低和骨微结构恶化,主要影响老年人群。持续的新冠疫情给骨质疏松症的管理带来了额外挑战,这可能是由于全身炎症以及病毒对骨代谢的直接影响。本研究旨在识别骨质疏松症和新冠疫情之间共有的常见差异表达基因(DEG)和关键分子途径,目标是通过生物信息学分析揭示潜在的治疗靶点。分析公开可用的基因表达数据集GSE164805(骨质疏松症)和GSE230665(新冠疫情)以识别重叠的DEG。使用基因本体论(GO)进行功能富集分析、途径分析、蛋白质-蛋白质相互作用(PPI)网络构建以及转录因子(TF)-枢纽基因调控网络分析,以探索这些DEG的生物学意义和调控机制。在骨质疏松症和新冠疫情之间共识别出325个常见DEG。GO富集分析显示其显著参与信号转导和质膜成分。途径分析突出了“细胞因子-细胞因子受体相互作用”途径作为核心参与者。PPI网络分析识别出一个由193个基因组成的模块,具有397个相互作用,从中确定了10个关键枢纽基因:ACTB、CDH1、RPS8、IFNG、RPL17、UBC、RPL36、RPS4Y1、GSK3B和FGF13。此外,发现76个TF调节这些枢纽基因,并识别出15种针对其中4个枢纽基因的现有药物。这项综合生物信息学研究揭示了15种候选治疗药物,它们靶向骨质疏松症和新冠疫情之间共有的关键调控基因,为骨质疏松症患者,尤其是那些受SARS-CoV-2感染影响或有感染风险的患者提供了有前景的治疗策略。