Nigrostriatal neuronal death in Parkinson’s disease — a passive or an active genetically-controlled process?
The cause for the rather selective degeneration of the nigrostriatal dopaminergic (DA) neurons in Parkinson’s disease (PD) is still enigmatic. The major current hypothesis suggests that nigral neuronal death in PD is due to excessive oxidant stress generated by auto- and enzymatic oxidation of DA, formation of neuromelanin and presence of high concentrations of iron. Such cell death is generally regarded as a passive, necrotic process, mainly resulting from membrane lipid peroxidation, leading to its dysfunction and rupture and then to neuronal disintegration.
We suggest a novel approach, that views neuronal degeneration in PD as an active process that occurs mainly the nuclear level. Our concept is based on the following observations: (1) Nigral histopathology in PD is characterized by a slow, protracted degeneration of individual neurons. We propose that it may be due to apoptosis [programmed cell-death (PCD), an active, genetically-controlled, intrinsic program of cell “suicide”] rather than to necrotic cell death. (2) DA exerts antitumor effect on melanoma and neuroblastoma cells. (3) Many anticancer drugs, trigger PCD by causing DNA damage. (4) DA has been shown to be genotoxic. (5) We recently first showed that DA, the endogenous neurotransmitter in the nigra, can trigger apoptosis in cultured, postmitotic sympathetic neurons. (6) We have also shown that PC-12 cells, transfected with the bcl-2 gene (a proto-oncogene that inhibits PCD) are relatively resistant to DA-apoptotic effect.
Degeneration of nigrostriatal neurons in PD may therefore be linked to dysregulation of the control mechanisms that normally restrain the PCD-triggering-potential of their own neurotransmitter.
KeywordsSympathetic Neuron Excessive Oxidant Stress Selective Degeneration Nigrostriatal Neuron Incidental Lewy Body Disease
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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