Faculty Profile: Phielipp, Nicolas
|Faculty Information||Lab Information (Packet Type, Course Title, & Department)||Location|
Brain Motor Control
|150 Med Surge 1|
Rationale: Parkinson disease is the second most prevalent neurodegenerative disease after Alzheimer disease, affecting an estimated one million people in the United States. Its prevalence is increasing in an aging population. Research over the last decade has shown that neuroprotective efforts to slow down or cure these diseases have been be “too little, too late” mainly because there are no serological or even clinical biomarkers to help diagnose this diseases at early stages. Specifically for Parkinson’s disease, there is a dire need to be able to predict progression in different phenotypes associated with different degrees of cognitive and/or motor impairments. Background and hypotheses: Previous research attempting to find clinical biomarkers has shown that Parkinson disease affects the ability to perform paced movements at frequencies above 2Hz (Stegemoller EL, et al.,2009a;Stegemoller EL, et al.,2009b). In this regard bradykinesia is the cardinal motor manifestation of parkinsonism. In addition a simple isometric motor task can help distinguish between Parkinson’s disease and Essential tremor (Poon C, et al.,2011) with high specificity and sensitivity. Regarding cognition Klassen BT et al found that slowness in the frequencies seen in background EEG can predict faster progression to cognitive impairment (Klassen BT, et al.,2011) and Nardone R et al found that short afferent inhibition (SAI) (a measure of cholinergic pathways), was reduced in patients who suffer from Rapid Eye Movement behavior disorder, which is considered a predictive clinical marker of faster progression to cognitive impairment (Nardone R, et al., 2013). In this setting clinical neurophysiology has already shown to be a useful tool to identify biomarkers. However the aforementioned studies included patients with moderate disease in which the clinical phenotype was already very distinct, enough to perform proper differential diagnoses. The novelty of our study is our focus on patients at early stages in which the clinical phenotype has not yet fulfilled definite clinical criteria for either Parkinson disease or its differential diagnoses such as Essential Tremor and idiopathic dystonia. Early diagnosis becomes essential for targeting specific therapies. So far in early cases, Dopamine Transporter (DaT) - Single Photon Emission Computed Tomography (SPECT) is clinically used to assess dopaminergic denervation to help to differentiate between parkinsonism and other disorders (Stoessl AJ, et al 2014). We hypothesize that a multivariate better biomarker can be achieved via : 1) a simple motor task (single task) using speed and rhythmicity as sensitizing factors will help differentiate Parkinsonism from other groups; 2) a dual-task (cognitive and motor concurrent task) approach will increase the sensitivity and specificity of the test since dual tasking (performing a concurrent simple motor and cognitive task such as walking and talking) is impaired in parkinsonian patients (Broeder et al 2014); 3) correlating errors during simple motor and dual tasking with SAI, background EEG frequencies, and DaT-SPECT will confirm if these biomarkers are still valid at an early disease stage and if so to identify which combination or single test is the more sensitive and specific. Goal: we aim to identify and confirm the efficacy of simple clinical and neurophysiologic biomarkers of Parkinson’s disease at an early disease stage and will also identify which combination of these has the best sensitivity and specificity to diagnose Parkinson’s disease and predict different cognitive outcomes. The final aim for which these biomarkers are sought is to be able to identify which patients are the best candidates for different therapeutic interventions. Implementation plan: Subjects: will be recruited through our large movement disorders clinical program. We expect to recruit a total of 15 subjects, including 5 healthy age-matched controls. Inclusion criteria will be patients in which a DaT-SCAN has been obtained for clinical purposes. Study Visits: subjects will be studied in two time points, at time 0, and six months later. During each time point we will collect demographic data, EEG, SAI, brief cognitive screening, videotape clinical assessment, and EMG recordings of motor tasks (two blocks of 2.5 hours each time point). Data Analysis: Outcome measures will include increasing errors comparing the single and dual tasking. Errors will be correlated with slowness in background EEG frequency, reduced SAI, and clinical measures. Preprocessing of basic data will be followed by determination of sensitivity and specificity and receiver operating characteristics curves will be determined for each test alone and in combination. References Broeder S, et al. The effects of dual tasking in handwriting in patients with Parkinson’s disease. Neuroscience 2014; 263:193-202. Klassen BT, et al. Quantitative EEG as a predictive biomarker for Parkinson disease dementia
Time Commitment per Week
3 - 4 hours per unit. 1 year Commitment.
Faculty Means of Evaluation
Attendance: 20pts. Lab Work: 40pts. Communication: 20pts. Lab citizenship: 20pts.