Metabolic Regulation of Glial Phenotypes: Implications in Neuron–Glia Interactions and Neurological Disorders

Ruqayya Afridi, Jong Heon Kim, Md Habibur Rahman, Kyoungho Suk

Research output: Contribution to journalReview articlepeer-review

56 Scopus citations


Glial cells are multifunctional, non-neuronal components of the central nervous system with diverse phenotypes that have gained much attention for their close involvement in neuroinflammation and neurodegenerative diseases. Glial phenotypes are primarily characterized by their structural and functional changes in response to various stimuli, which can be either neuroprotective or neurotoxic. The reliance of neurons on glial cells is essential to fulfill the energy demands of the brain for its proper functioning. Moreover, the glial cells perform distinct functions to regulate their own metabolic activities, as well as work in close conjunction with neurons through various secreted signaling or guidance molecules, thereby constituting a complex network of neuron-glial interactions in health and disease. The emerging evidence suggests that, in disease conditions, the metabolic alterations in the glial cells can induce structural and functional changes together with neuronal dysfunction indicating the importance of neuron–glia interactions in the pathophysiology of neurological disorders. This review covers the recent developments that implicate the regulation of glial phenotypic changes and its consequences on neuron–glia interactions in neurological disorders. Finally, we discuss the possibilities and challenges of targeting glial metabolism as a strategy to treat neurological disorders.

Original languageEnglish
Article number20
JournalFrontiers in Cellular Neuroscience
StatePublished - 11 Feb 2020


  • glia
  • metabolism
  • neurological disorders
  • neuron
  • neuron–glia interaction


Dive into the research topics of 'Metabolic Regulation of Glial Phenotypes: Implications in Neuron–Glia Interactions and Neurological Disorders'. Together they form a unique fingerprint.

Cite this