Objective/Rationale:
There is an increasingly interest in finding biomarkers that can objectively evaluate the disease progression and the effects of neuroprotective treatment on the course of Parkinson’s disease (PD). The goal of the present study is to use a novel resting state functional MRI (fMRI) method to develop a simple, non-invasive biomarker for evaluation of disease progression and early diagnosis of PD.
Project Description:
In a previous study, we found that there are PD-related, specific changes of neural activity in the resting state. These changes are secondary to dopamine deficiency, and related to the severity of the disease. The current study will further apply resting state fMRI method on (1) 60 PD patients at different stage (from early to late stage), at both off and on levodopa conditions, (2) 40 patients with atypical parkinsonian syndromes (including MSA-P and PSP patients), (3) 20 aSymptoms & Side Effects carriers of mutation of genes associated with familiar PD (e.g. parkin, LRRK2), and (4) normal control subjects. We will use network analysis to explore PD-associated specific neural activity pattern, and determine whether the pattern can be detected in early PD, and whether it is related to disease severity.
Relevance to Diagnosis/Treatment of Parkinson’s Disease:
If we can establish the PD-associated specific neural activity pattern, we can potentially provide a useful non-invasive biomarker, which can be helpful in (1) increasing the accuracy in differentiatial diagnosis of PD and atypical parkinsonian syndromes; (2) early diagnosis and evaluation of disease progression of PD, and (3) objectively evaluating the effects of neuroprotective treatment on the course of the disease.
Anticipated Outcome:
It is predicted that (1) there is a PD-related specific neural activity pattern, (2) this pattern can be relatively normalized after administration of levodopa, which will prove that this abnormal pattern is due to dopamine deficiency; (3) this pattern can be detected in early PD, and correlates with the disease severity and duration, (4) using this pattern can differentiate PD from patients with atypical parkinsonian syndromes, and (5) this pattern may be found in aSymptoms & Side Effects carriers of PD gene mutation.