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Updated: Apr 16, 2026

Isolating, Sequencing and Analyzing Extracellular MicroRNAs from Human Mesenchymal Stem Cells
Published on: March 8, 2019
Comprehensive transcriptome analysis of mesenchymal stem cells in elderly patients with osteoporosis
Zihui Zhou1, Mingjie Gao1, Qingbin Liu1
1Department of Orthopaedic, Shanghai First People's Hospital, No. 85 Wujin road, Shanghai, 200080, China.
Objective:
To explore the role of aging in the pathogenesis of osteoporosis, several differentially expressed genes (DEGs) and altered biological pathways were identified in mesenchymal stem cells (MSCs) in elderly patients with osteoporosis.
Methods:
Raw data were downloaded from Gene Expression Omnibus database. A total of 14 human MSC samples were available, including five samples from elderly patients suffering from osteoporosis, five controls from young non-osteoporotic donors and five controls from old non-osteoporotic donors. The DEGs were identified using LIMMA package among the three groups. Gene ontology and KEGG pathway analysis were carried out using DAVID. A protein-protein interaction (PPI) network of DEGs was constructed with STRING and then visualized with Cytoscape.
Results:
A total of 3179 DEGs were screened, including 1071 up- and 2108 down-regulated genes. Compared with young and old controls, 271 and 781 genes were up-regulated in osteoporosis, respectively, and 17 genes were shared. Function and pathway enrichment showed that the up-regulated genes in osteoporosis were involved in extracellular matrix (ECM)-receptor interaction, focal adhesion and mammalian target of rapamycin signaling pathway. Moreover, a range of genes linked to cell adhesion, ECM-receptor interaction and cell cycle were revealed in the PPI network, such as transforming growth factor beta 1, insulin-like growth factor 2 and integrin beta 2.
Conclusion:
A number of DEGs and altered pathways were screened in osteoporosis. Our study provided insights into the role of aging in the pathogenesis of osteoporosis and some DEGs might be potential biomarkers for osteoporosis.

