Repurposing Acebutolol for Osteoporosis Treatment: Insights From Multi-Omics and Multi-Modal Data Analysis

Area of Science:

• Computational Biology
• Pharmacology
• Genetics

Background:

• Osteoporosis is a prevalent aging-related metabolic bone disease marked by low bone mineral density (BMD) and increased fracture risk.
• Current osteoporosis treatments have limitations due to side effects and comorbidities with long-term use.

Purpose of the Study:

• To identify novel repurposable drugs for osteoporosis treatment using network-based approaches.
• To investigate the potential of Acebutolol, a beta-blocker, as a therapeutic agent for osteoporosis.

Main Methods:

• Utilized driver signaling network identification (DSNI) and drug functional networks (DFN) with multi-omics data to construct osteoporosis driver signaling networks (ODSN).
• Screened over 10,000 compounds, integrating ODSN, DFN, and drug-induced transcriptional responses.
• Employed Mendelian randomization, zebrafish models (dexamethasone-induced bone loss), and population-based data analysis (propensity score matching) for validation.

Main Results:

• Identified Ruxolitinib, Alfacalcidol, Doxercalciferol, and Acebutolol as potential anti-osteoporosis drugs.
• Acebutolol and Alfacalcidol demonstrated significant protective effects in zebrafish osteoporosis models.
• Population data analysis revealed higher BMD in individuals using beta-blocker drugs compared to other cardiovascular medications.

Conclusions:

• Acebutolol emerges as a novel candidate for osteoporosis treatment, supported by multi-omics analysis, experimental validation, and real-world data.
• Further mechanistic studies and clinical trials are warranted to confirm Acebutolol's efficacy in managing osteoporosis.