Ellagic acid protects ovariectomy-induced bone loss in mice by inhibiting osteoclast differentiation and bone resorption.
Xixi LinGuixin YuanZhaoning LiMengyu ZhouXianghua HuFangming SongSiyuan ShaoFangsheng FuJinmin ZhaoJiake XuQian LiuHaotian FengPublished in: Journal of cellular physiology (2020)
Osteoporosis is a devastating disease that features reduced bone quantity and microstructure, which causes fragility fracture and increases mortality, especially in the aged population. Due to the long-term side-effects of current drugs for osteoporosis, it is of importance to find other safe and effective medications. Ellagic acid (EA) is a phenolic compound found in nut galls, plant extracts, and fruits, and exhibits antioxidant and antineoplastic effects. Here, we showed that EA attenuated the formation and function of osteoclast dose-dependently. The underlying mechanism was further discovered by western blot, immunofluorescence assay, and luciferase assay, which elucidated that EA suppressed osteoclastogenesis and bone resorption mainly through attenuating receptor activator of nuclear factor-κB (NF-κB) ligand-induced NF-κB activation and extracellular signal-regulated kinase signaling pathways, accompanied by decreased protein expression of nuclear factor of activated T-cells calcineurin-dependent 1 and c-Fos. Moreover, EA inhibits osteoclast marker genes expression including Dc-stamp, Ctsk, Atp6v0d2, and Acp5. Intriguingly, we also found that EA treatment could significantly protect ovariectomy-induced bone loss in vivo. Conclusively, this study suggested that EA might have the therapeutic potentiality for preventing or treating osteoporosis.
Keyphrases
- bone loss
- nuclear factor
- toll like receptor
- signaling pathway
- bone mineral density
- high glucose
- postmenopausal women
- diabetic rats
- oxidative stress
- drug induced
- inflammatory response
- epithelial mesenchymal transition
- immune response
- anti inflammatory
- combination therapy
- insulin resistance
- adipose tissue
- hip fracture
- endoplasmic reticulum stress
- bioinformatics analysis