Exploring the Logic and Conducting a Comprehensive Evaluation of the Adiponectin Receptor Agonists AdipoRon and AdipoAI’s Impacts on Bone Metabolism and Repair-A Systematic Review

Abstract

Introduction: Adiponectin replacement therapy shows promising outcomes in various diseases, especially for bone-related disorders. Challenges in using the complete protein have led to alternative approaches, with AdipoRon and AdipoAI emerging as extensively researched drug candidates. Their influence on models of bone-related disorders has progressed considerably but there has been no review of their effectiveness in modulating bone metabolism and repair. Method: This systematic review seeks to address this knowledge gap. Based on preclinical evidence from PubMed, EMBASE, and COCHRANE, ten studies were included following PRISMA guidelines. The JBI Checklist Critical Appraisal Tool assessed the quality of this systematic review. The studies encompassed various animal models, addressing bone defects, osseointegration, diabetes-associated periodontitis, fracture repair, growth retardation, and diabetes-associated peri-implantitis. Result: AdipoRon and AdipoAI demonstrated effectiveness in modulating bone metabolism and repair through diverse pathways, including the activation of AdipoR1/APPL1, inhibition of F-actin ring formation, suppression of IκB-α phosphorylation, p65 nuclear translocation and Wnt5a-Ror2 signaling pathway, reduction of CCL2 secretion and expression, regulation of autophagy via LC3A/B expression, modulation of SDF-1 production, activation of the ERK-1/2 signaling pathway, modulation of bone integration-related markers and osteokines such as RANKL, BMP-2, OPG, OPN, and Runx2, inhibition of RANKL in osteoblasts, and inhibition of podosome formation via the activation of AMPK. Conclusion: While preclinical studies show promise, human trials are crucial to confirm the clinical safety and effectiveness of AdipoRon and AdipoAI. Caution is necessary due to potential off-target effects, especially in bone therapy with multi-target approaches. Structural biology and computational methods can help predict and understand these effects.