Age-Dependent Levels of Protein Kinase Cs in Brain: Reduction of Endogenous Mechanisms of Neuroprotection.
Donatella PastoreFrancesca PacificiKunjan R DaveRaffaele PalmirottaAlfonso BelliaGuido PasquantonioFiorella GuadagniGiulia DonadelNicola Di DanielePasquale AbeteDavide LauroTatjana RundekMiguel A Perez-PinzonDavid Della-MortePublished in: International journal of molecular sciences (2019)
Neurodegenerative diseases are among the leading causes of mortality and disability worldwide. However, current therapeutic approaches have failed to reach significant results in their prevention and cure. Protein Kinase Cs (PKCs) are kinases involved in the pathophysiology of neurodegenerative diseases, such as Alzheimer's Disease (AD) and cerebral ischemia. Specifically ε, δ, and γPKC are associated with the endogenous mechanism of protection referred to as ischemic preconditioning (IPC). Existing modulators of PKCs, in particular of εPKC, such as ψεReceptor for Activated C-Kinase (ψεRACK) and Resveratrol, have been proposed as a potential therapeutic strategy for cerebrovascular and cognitive diseases. PKCs change in expression during aging, which likely suggests their association with IPC-induced reduction against ischemia and increase of neuronal loss occurring in senescent brain. This review describes the link between PKCs and cerebrovascular and cognitive disorders, and proposes PKCs modulators as innovative candidates for their treatment. We report original data showing εPKC reduction in levels and activity in the hippocampus of old compared to young rats and a reduction in the levels of δPKC and γPKC in old hippocampus, without a change in their activity. These data, integrated with other findings discussed in this review, demonstrate that PKCs modulators may have potential to restore age-related reduction of endogenous mechanisms of protection against neurodegeneration.
Keyphrases
- cerebral ischemia
- protein kinase
- subarachnoid hemorrhage
- brain injury
- blood brain barrier
- small molecule
- big data
- poor prognosis
- type diabetes
- multiple sclerosis
- cardiovascular disease
- ischemia reperfusion injury
- binding protein
- coronary artery disease
- artificial intelligence
- cardiovascular events
- risk factors
- cognitive decline
- oxidative stress
- middle aged
- mild cognitive impairment
- deep learning
- tyrosine kinase