Parkinson's disease (PD), the most common movement disorder afflicting millions of Americans, is diagnosed when patients present with cardinal parkinsonian signs, e.g. bradykinesia, rigidity, and tremor, and show favorable response to levodopa or dopamine (DA) agonists. However, there are quite a few other movement disorders that mimic PD clinically including response to levodopa and DA agonists, making accurate diagnosis of PD difficult sometimes even in the best hands. In addition, the natural course of PD varies substantially, with most patients developing first the mild cognitive impairment (MCI) and then dementia as the disease progresses. While current functional neuroimaging methods to monitor PD progression with fluorodopa positron-emission tomography (F-Dopa-PET) or beta-CIT single photon emission computer tomography (Beta-CIT-SPECT) show relatively high sensitivity and specificity, they are not widely accessible, particularly in developing countries, and do not elucidate biological mechanisms of PD progression. Furthermore, there are no comparable biomarkers for monitoring MCI or even dementia in PD, which has important clinical consequences in these patients with regard to increased mortality, caregiver burden, and risk of admission to nursing home. We hypothesize that there are unique protein markers for PD, PD progression, and PD dementia in brain tissue, and some of which will be reflected in the human cerebrospinal fluid (CSF). Hence, we are proposing to use a high throughput proteomic approach to identify proteins unique to PD, PD progression, and development of cognitive deficits in PD first in pathologically involved brain tissues and then select a panel of unique proteins in CSF that could serve as the basis of a highly sensitive and specific enzyme-linked immunosorbent assay (ELISA) to diagnose PD, to monitor PD progression, and to detect PD patients at risk to develop cognitive deficits.
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