RANKL-RANK-OPG Pathway in Charcot Diabetic Foot: Pathophysiology and Clinical-Therapeutic Implications.
Tommaso GrecoAntonio MascioChiara ComisiChiara PolichettiAlessandro RussoMassimiliano MoscaNicola MondanelliElisa TroianoGiulio MaccauroCarlo PerisanoPublished in: International journal of molecular sciences (2023)
Charcot Foot (CF), part of a broader condition known as Charcot Neuro-Osteoarthropathy (CNO), is characterized by neuropathic arthropathy with a progressive alteration of the foot. CNO is one of the most devastating complications in patients with diabetes mellitus and peripheral neuropathy but can also be caused by neurological or infectious diseases. The pathogenesis is multifactorial; many studies have demonstrated the central role of inflammation and the Receptor Activator of NF-κB ligand (RANKL)-Receptor Activator of NF-κB (RANK)-Osteoprotegerin (OPG) pathway in the acute phase of the disease, resulting in the serum overexpression of RANKL. This overexpression and activation of this signal lead to increased osteoclast activity and osteolysis, which is a prelude to bone destruction. The aim of this narrative review is to analyze this signaling pathway in bone remodeling, and in CF in particular, to highlight its clinical aspects and possible therapeutic implications of targeting drugs at different levels of the pathway. Drugs that act at different levels in this pathway are anti-RANKL monoclonal antibodies (Denosumab), bisphosphonates (BP), and calcitonin. The literature review showed encouraging data on treatment with Denosumab, although in a few studies and in small sample sizes. In contrast, BPs have been re-evaluated in recent years in relation to the high possibility of side effects, while calcitonin has shown little efficacy on CNO.
Keyphrases
- nuclear factor
- bone loss
- signaling pathway
- bone mineral density
- toll like receptor
- infectious diseases
- oxidative stress
- cystic fibrosis
- pi k akt
- cell proliferation
- epithelial mesenchymal transition
- multiple sclerosis
- transcription factor
- computed tomography
- postmenopausal women
- type diabetes
- risk factors
- insulin resistance
- immune response
- cancer therapy
- soft tissue
- machine learning
- inflammatory response
- body composition
- combination therapy
- artificial intelligence