Objective/Rationale:
The presence of perineuronal nets (PNNs), structural elements associated with specific circuits within brain areas affected by Parkinson’s disease, may limit the efficacy of growth factor (neurotrophin)-based treatments. Our objective is to determine whether the enzymatic removal of these structures, which in the past has been shown to increase brain plasticity, will improve the access of exogenously applied growth factors to these neural networks, thus improving the efficacy of neurotrophic therapy.
Project Description:
The key innovation of our approach is to simultaneously treat pre-clinical models of Parkinson’s disease with neurotrophin and Chondroitinase ABC, an enzyme that specifically targets glycoproteins that are a primary constituent of PNNs. PNNs are associated with key regulatory neurons within the caudate and putamen, and the input nuclei of the basal ganglia, and a key recipient of dopaminergic afferents (nerves that conduct impulses from the peripheral body to the brain or spinal cord) from the substantia nigra. By removing PNNs, we anticipate improved access of neurotrophins to these specific dopaminergic terminals. We will determine the efficacy of our proposed method by comparing anatomical and behavioral outcomes in MPTP-treated models that have received our combination treatment with those that have only been treated with neurotrophins.
Relevance to Diagnosis/Treatment of Parkinson’s Disease:
Parkinson’s disease is a progressive, neurodegenerative disorder. Accordingly, any treatment that can either slow the progression of, or otherwise delay the onset of symptoms associated with the disease can be beneficial. If successful, our approach has the potential to improve the efficacy and duration of neurotrophin-based therapies, a promising, yet thus far limited treatment for Parkinson’s disease.
Anticipated Outcome:
This project will reveal whether removing PNNs will improve the access of neurotrophins to appropriate targets, effectively increasing neuroprotective and neuroregenerative effects on specific neural circuits affected by Parkinson’s disease. Our results will further determine whether this novel approach will improve functional recovery, as well as increase the duration of therapeutic efficacy for neurotrophic treatments in a pre-clinical model of Parkinson’s disease.