Ataluren prevented bone loss induced by ovariectomy and aging in mice through the BMP-SMAD signaling pathway

Area of Science:

• Biomedical research
• Drug discovery
• Osteoporosis research

Background:

• Osteoporosis is linked to estrogen deficiency and aging.
• Novel therapeutic agents for osteoporosis are actively sought.
• Transcriptional profiles offer a basis for drug screening.

Purpose of the Study:

• To identify novel therapeutic agents for osteoporosis using a deep learning-based system.
• To evaluate the efficacy of ataluren in preclinical osteoporosis models.
• To elucidate the mechanism of action of ataluren in bone formation.

Main Methods:

• Screening potential drugs using a deep learning-based efficacy prediction system (DLEPS) on transcriptional profiles.
• Assessing ataluren's effect on bone loss in ovariectomized and aged mice.
• Evaluating ataluren's impact on human bone marrow-derived mesenchymal stem cell (hBMMSC) osteogenic differentiation in vitro.
• Investigating the role of the BMP-SMAD pathway in ataluren's mechanism.

Main Results:

• DLEPS identified ataluren as a potential osteoporosis therapeutic.
• Ataluren significantly reversed bone loss in both ovariectomized and aged mice.
• Ataluren enhanced hBMMSC osteogenic differentiation without cytotoxicity, upregulating key osteogenic genes.
• Ataluren activated SMAD phosphorylation, indicating BMP-SMAD pathway involvement.

Conclusions:

• Ataluren shows therapeutic potential for osteoporosis.
• The drug functions by promoting hBMMSC osteogenic differentiation through the BMP-SMAD pathway.
• DLEPS is an effective tool for novel osteoporosis drug discovery.