Mechanisms associated with diabetic peripheral neuralgia and potential interventions

Authors

  • Yudie Du
  • He Xiao
  • Xinting Huang
  • Yiming Shao
  • Ke Song

DOI:

https://doi.org/10.71423/aimed.20251106

Keywords:

Diabetes, Diabetic peripheral neuropathy, Neuropathy pathogenesis, Pathway-selective therapeutics., machine learning, AI-assisted diagnosis, biomarker discovery

Abstract

Diabetes mellitus (DM), the most prevalent metabolic disorder globally, has been extensively investigated due to its significant clinical implications. Among its most common complications is diabetic peripheral neuropathy (DPN), which predominantly manifests as bilateral limb pain, numbness, and paresthesia. In advanced cases, DPN may progress to foot ulceration and potentially necessitate limb amputation. The precise etiology and pathogenesis of diabetic neuropathy remain incompletely understood; however, sustained hyperglycemia, dysregulated lipid metabolism, and impaired insulin signaling are recognized as key triggers for the cascade of pathophysiological alterations in DPN. Under these metabolic disturbances, the peripheral nervous system’s structural and functional integrity—encompassing myelinated and unmyelinated axons, neuronal somata, neurovascular units, and glial cells—is progressively undermined. This review synthesizes recent mechanistic advances in DPN research, centering on the sigma-1 receptor’s modulatory orchestration, SGC dysfunction and GalCer metabolic dysregulation in DPN pathogenesis, inhibition of neuroinflammation and apoptosis by microRNA-146a, nerve damage due to Ca²⁺ overload, and dorsal root ganglia neuronal apoptosis resulting from SFA, and summarize possible interventions based on these mechanisms. A systems-level understanding of how these mechanisms collectively drive neuropathy pathogenesis is critical for advancing both early diagnostic tools and pathway-selective therapeutics.

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Published

2025-11-06

Issue

Section

Computer Science and Artificial Intelligence