WGCNA Identification of Genes and Pathways Involved in the Pathogenesis of Postmenopausal Osteoporosis
Meng-Lei Hao,1,* Xiao-Qin Zuo,2,* Yong Qiu,3,* Jian Li1 1Department of Endocrinology, Zigong First People’s Hospital, Zigong Academy of Medical Sciences, Zigong, Sichuan Province, People’s Republic of China; 2Department of Geriatric Medicine, Affiliated Hospital of Qinghai Un...
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| Main Authors: | , , , |
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| Format: | article |
| Language: | EN |
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Dove Medical Press
2021
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| Online Access: | https://doaj.org/article/e764e360a884439c9980d51931a2306f |
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| Summary: | Meng-Lei Hao,1,* Xiao-Qin Zuo,2,* Yong Qiu,3,* Jian Li1 1Department of Endocrinology, Zigong First People’s Hospital, Zigong Academy of Medical Sciences, Zigong, Sichuan Province, People’s Republic of China; 2Department of Geriatric Medicine, Affiliated Hospital of Qinghai University, Xining, Qinghai Province, People’s Republic of China; 3Department of Anesthesiology, Zigong First People’s Hospital, Zigong Academy of Medical Sciences, Zigong, Sichuan Province, People’s Republic of China*These authors contributed equally to this workCorrespondence: Jian LiDepartment of Endocrinology, Zigong First People’s Hospital, Zigong Academy of Medical Sciences, Zigong, Sichuan Province, People’s Republic of ChinaEmail lijianzgyy@163.comPurpose: 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.Methods: 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.Results: 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.Conclusion: We identified genes, miRNAs, and pathways associated with PMO. These molecules may participate in the pathogenesis of PMO and serve as therapeutic targets.Keywords: PMO, DEGs, CTD, bioinformatics |
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