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Bone & Joint Research
Vol. 13, Issue 2 | Pages 52 - 65
1 Feb 2024
Yao C Sun J Luo W Chen H Chen T Chen C Zhang B Zhang Y

Aims. To investigate the effects of senescent osteocytes on bone homeostasis in the progress of age-related osteoporosis and explore the underlying mechanism. Methods. In a series of in vitro experiments, we used tert-Butyl hydroperoxide (TBHP) to induce senescence of MLO-Y4 cells successfully, and collected conditioned medium (CM) and senescent MLO-Y4 cell-derived exosomes, which were then applied to MC3T3-E1 cells, separately, to evaluate their effects on osteogenic differentiation. Furthermore, we identified differentially expressed microRNAs (miRNAs) between exosomes from senescent and normal MLO-Y4 cells by high-throughput RNA sequencing. Based on the key miRNAs that were discovered, the underlying mechanism by which senescent osteocytes regulate osteogenic differentiation was explored. Lastly, in the in vivo experiments, the effects of senescent MLO-Y4 cell-derived exosomes on age-related bone loss were evaluated in male SAMP6 mice, which excluded the effects of oestrogen, and the underlying mechanism was confirmed. Results. The CM and exosomes collected from senescent MLO-Y4 cells inhibited osteogenic differentiation of MC3T3-E1 cells. RNA sequencing detected significantly lower expression of miR-494-3p in senescent MLO-Y4 cell-derived exosomes compared with normal exosomes. The upregulation of exosomal miR-494-3p by miRNA mimics attenuated the effects of senescent MLO-Y4 cell-derived exosomes on osteogenic differentiation. Luciferase reporter assay demonstrated that miR-494-3p targeted phosphatase and tensin homolog (PTEN), which is a negative regulator of the phosphoinositide 3-kinase (PI3K)/AKT pathway. Overexpression of PTEN or inhibition of the PI3K/AKT pathway blocked the functions of exosomal miR-494-3p. In SAMP6 mice, senescent MLO-Y4 cell-derived exosomes accelerated bone loss, which was rescued by upregulation of exosomal miR-494-3p. Conclusion. Reduced expression of miR-494-3p in senescent osteocyte-derived exosomes inhibits osteogenic differentiation and accelerates age-related bone loss via PTEN/PI3K/AKT pathway. Cite this article: Bone Joint Res 2024;13(2):52–65


Bone & Joint Research
Vol. 9, Issue 8 | Pages 524 - 530
1 Aug 2020
Li S Mao Y Zhou F Yang H Shi Q Meng B

Osteoporosis (OP) is a chronic metabolic bone disease characterized by the decrease of bone tissue per unit volume under the combined action of genetic and environmental factors, which leads to the decrease of bone strength, makes the bone brittle, and raises the possibility of bone fracture. However, the exact mechanism that determines the progression of OP remains to be underlined. There are hundreds of trillions of symbiotic bacteria living in the human gut, which have a mutually beneficial symbiotic relationship with the human body that helps to maintain human health. With the development of modern high-throughput sequencing (HTS) platforms, there has been growing evidence that the gut microbiome may play an important role in the programming of bone metabolism. In the present review, we discuss the potential mechanisms of the gut microbiome in the development of OP, such as alterations of bone metabolism, bone mineral absorption, and immune regulation. The potential of gut microbiome-targeted strategies in the prevention and treatment of OP was also evaluated. Cite this article: Bone Joint Res 2020;9(8):524–530


Aims

This study examined the relationship between obesity (OB) and osteoporosis (OP), aiming to identify shared genetic markers and molecular mechanisms to facilitate the development of therapies that target both conditions simultaneously.

Methods

Using weighted gene co-expression network analysis (WGCNA), we analyzed datasets from the Gene Expression Omnibus (GEO) database to identify co-expressed gene modules in OB and OP. These modules underwent Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and protein-protein interaction analysis to discover Hub genes. Machine learning refined the gene selection, with further validation using additional datasets. Single-cell analysis emphasized specific cell subpopulations, and enzyme-linked immunosorbent assay (ELISA), protein blotting, and cellular staining were used to investigate key genes.