Hao Meng-Lei, Zuo Xiao-Qin, Qiu Yong, Li Jian
Department of Endocrinology, Zigong First People's Hospital, Zigong Academy of Medical Sciences, Zigong, Sichuan Province, People's Republic of China.
Department of Geriatric Medicine, Affiliated Hospital of Qinghai University, Xining, Qinghai Province, People's Republic of China.
Int J Gen Med. 2021 Nov 16;14:8341-8353. doi: 10.2147/IJGM.S336310. eCollection 2021.
Postmenopausal osteoporosis (PMO) patients may suffer from chronic pain and increased fractures due to brittle bones that seriously affect their normal work and life. Exploring the pathogenesis of PMO can help clinicians construct individualized therapeutic targets.
Differentially expressed genes (DEGs) were identified by analyzing the microarray assays of monocytes from 20 PMO and 20 control samples. Weighted correlation network analysis (WGCNA) and gene set enrichment analysis (GAEA) were performed. Genes associated with PMO were identified in the Comparative Toxicogenomics Database (CTD). miRNAs associated with osteoporosis were found in miRNet, and target genes were predicted. Hub genes and functional pathways associated with PMO were also identified. miRNA-mRNA networks were constructed. The association between hub genes and PMO was analyzed in the CTD.
A total of 1055 genes were up-regulated, and 694 genes were down-regulated in PMO samples (P<0.01). Five modules were identified by WGCNA. The blue module was significantly associated with PMO and selected for further analysis (P < 0.05). A total of 229 genes were significantly associated with PMO gene significance and module membership. Pathway variations were predominantly enriched in mRNA metabolic process, RNA splicing, Notch signaling pathway, apoptosis, cytokine-cytokine receptor interaction and so on. We identified 10 hub genes associated with PMO with different inference scores.
We identified genes, miRNAs, and pathways associated with PMO. These molecules may participate in the pathogenesis of PMO and serve as therapeutic targets.
绝经后骨质疏松症（PMO）患者可能因骨骼脆弱而遭受慢性疼痛并增加骨折风险，这严重影响他们的正常工作和生活。探索PMO的发病机制有助于临床医生构建个性化的治疗靶点。
通过分析20例PMO患者和20例对照样本的单核细胞微阵列检测结果，鉴定差异表达基因（DEG）。进行加权基因共表达网络分析（WGCNA）和基因集富集分析（GAEA）。在比较毒理基因组学数据库（CTD）中鉴定与PMO相关的基因。在miRNet中找到与骨质疏松症相关的miRNA，并预测其靶基因。还鉴定了与PMO相关的枢纽基因和功能通路。构建miRNA-mRNA网络。在CTD中分析枢纽基因与PMO之间的关联。
PMO样本中共有1055个基因上调，694个基因下调（P<0.01）。通过WGCNA鉴定出五个模块。蓝色模块与PMO显著相关，并被选作进一步分析（P<0.05）。共有229个基因与PMO基因显著性和模块成员资格显著相关。通路变异主要富集在mRNA代谢过程、RNA剪接、Notch信号通路、凋亡、细胞因子-细胞因子受体相互作用等方面。我们鉴定出10个与PMO相关的枢纽基因，其推理得分不同。
我们鉴定出了与PMO相关的基因、miRNA和通路。这些分子可能参与PMO的发病机制，并可作为治疗靶点。
