Human embryonic dopamine-neuron transplants survive in patients with severe Parkinson's disease and result in some clinical benefit in younger but not in older patients.

No abstract

Network analysis of functional brain imaging data is an innovative approach to study circuit abnormalities in neurodegenerative diseases. In Parkinson's disease, spatial covariance analysis of resting state metabolic images has identified specific regional patterns associated with motor and cognitive symptoms. With functional imaging, these metabolic networks have recently been used to measure system-related progression and evaluate novel treatment strategies. Network analysis is also being used to characterize specific functional biomarkers for Huntington's disease and Alzheimer's disease. These networks have been particularly helpful in uncovering compensatory mechanisms in genetically at-risk individuals. Ongoing developments in network applications are likely to enhance the role of functional imaging in the investigation of neurodegenerative disorders.

Parkinson's disease (PD) is associated with an abnormal pattern of regional brain function. The expression of this PD-related covariance pattern (PDRP) has been used to assess disease progression and the response to treatment. In this study, we validated the PDRP network as a measure of parkinsonism by prospectively computing its expression (PDRP scores) in 15 O-water (H 2 15 O) and 18 F-fluorodeoxyglucose (FDG) positron emission tomography (PET) scans from PD patients and healthy volunteers. The reliability of this measure was also assessed within subjects using a test-retest design in mildly affected and advanced PD patients scanned at baseline and during treatment with levodopa or deep brain stimulation (DBS). We found that PDRP expression was significantly elevated in PD patients (P < 0.001) relative to controls in a prospective analysis of brain scans obtained with either H 2 15 O or FDG PET. A significant correlation (R 2 = 0.61; P < 0.001) was evident between PDRP scores computed from H 2 15 O and FDG images in PD subjects scanned with both tracers. Test-retest reproducibility was very high (intraclass correlation coefficient (ICC) > 0.92) for PDRP scores measured both within PET session and between sessions separated by up to 2 months. This high reproducibility was observed in both early stage and advanced PD patients scanned at baseline and during treatment. The within-subject variability of this measure was less than 10% for both unmedicated and treated conditions. These findings suggest that the PDRP network is a reproducible and stable descriptor of regional functional abnormalities in parkinsonism. The quantification of PDRP expression in PD patients can serve as a potential biomarker in PET intervention studies for this disorder.

The motor manifestations of Parkinson's disease (PD) have been linked to an abnormal spatial covariance pattern involving basal ganglia thalamocortical pathways. By contrast, little is known about the functional networks that underlie cognitive dysfunction in this disorder. To identify such patterns, we studied 15 non-demented PD patients using FDG PET and a voxel-based network modeling approach. We detected a significant covariance pattern that correlated (p< 0.01) with performance on tests of memory and executive functioning. This PD-related cognitive pattern (PDCP) was characterized by metabolic reductions in frontal and parietal association areas and relative increases in the cerebellar vermis and dentate nuclei. To validate this pattern, we analyzed data from 32 subsequent PD patients of similar age, disease duration and severity. Prospective measurements of PDCP activity predicted memory performance (p<0.005), visuospatial function (p<0.01), and perceptual motor speed (p<0.005) in this validation sample. PDCP scores additionally exhibited an excellent degree of test-retest reliability (intraclass correlation coefficient, ICC=0.89) in patients undergoing repeat FDG PET at an 8-week interval. Unlike the PD-related motor pattern, PDCP expression was not significantly altered by antiparkinsonian treatment with either intravenous levodopa or deep brain stimulation (DBS). These findings substantiate the PDCP as a reproducible imaging marker of cognitive function in PD. Because PDCP expression is not altered by routine antiparkinsonian treatment, this measure of network activity may prove useful in clinical trials targeting the progression of non-motor manifestations of this disorder.

Parkinson's disease (PD) is associated with abnormal activity in spatially distributed neural systems mediating the motor and cognitive manifestations of this disorder. Metabolic PET studies have demonstrated that this illness is characterized by a set of reproducible functional brain networks that correlate with these clinical features. The time at which these abnormalities appear is unknown, as is their relationship to concurrent clinical and dopaminergic indices of disease progression. In this longitudinal study, 15 early stage PD patients (age 58.0 +/- 10.2 years; Hoehn and Yahr Stage 1.2 +/- 0.3) were enrolled within 2 years of diagnosis. The subjects underwent multitracer PET imaging at baseline, 24 and 48 months. At each timepoint they were scanned with [18F]-fluorodeoxyglucose (FDG) to assess longitudinal changes in regional glucose utilization and in the expression of the PD-related motor (PDRP) and cognitive metabolic covariance patterns (PDCP). At each timepoint the subjects also underwent PET imaging with [18F]-fluoropropyl betaCIT (FP-CIT) to quantify longitudinal changes in caudate and putamen dopamine transporter (DAT) binding. Regional metabolic changes across the three timepoints were localized using statistical parametric mapping (SPM). Longitudinal changes in regional metabolism and network activity, caudate/putamen DAT binding, and Unified Parkinson's Disease Rating Scale (UPDRS) motor ratings were assessed using repeated measures analysis of variance (RMANOVA). Relationships between these measures of disease progression were assessed by computing within-subject correlation coefficients. We found that disease progression was associated with increasing metabolism in the subthalamic nucleus (STN) and internal globus pallidus (GPi) (P < 0.001), as well as in the dorsal pons and primary motor cortex (P < 0.0001). Advancing disease was also associated with declining metabolism in the prefrontal and inferior parietal regions (P < 0.001). PDRP expression was elevated at baseline relative to healthy control subjects (P < 0.04), and increased progressively over time (P < 0.0001). PDCP activity also increased with time (P < 0.0001). However, these changes in network activity were slower than for the PDRP (P < 0.04), reaching abnormal levels only at the final timepoint. Changes in PDRP activity, but not PDCP activity, correlated with concurrent declines in striatal DAT binding (P < 0.01) and increases in motor ratings (P < 0.005). Significant within-subject correlations (P < 0.01) were also evident between the latter two progression indices. The early stages of PD are associated with progressive increases and decreases in regional metabolism at key nodes of the motor and cognitive networks that characterize the illness. Potential disease-modifying therapies may alter the time course of one or both of these abnormal networks.

It has been proposed that deep brain stimulation (DBS) of the subthalamic nucleus (STN DBS) and dopaminergic therapy ameliorate the symptoms of Parkinson's disease through similar functional mechanisms. We examined this notion using PET to compare the metabolic effects of these treatment approaches. Nine Parkinson's disease patients (age 61.7 ± 11.1 years) were scanned ON and OFF STN stimulation and nine others (age 60.0 ± 9.3 years) were scanned ON and OFF an individual titrated intravenous levodopa infusion. The two treatment groups were matched for baseline disease severity as well as clinical response to therapy. Similarities and differences in the effects of treatment on regional metabolism were assessed using statistical parametric mapping (SPM). In addition, we used network analysis to assess the effect of therapy on the expression of an abnormal Parkinson's disease-related spatial covariance pattern (PDRP). We found that both STN DBS and levodopa therapy were associated with significant (P < 0.001) metabolic reductions in the putamen/globus pallidus, sensorimotor cortex and cerebellar vermis, as well as increases in the precuneus (BA 7). The metabolic effects of the two interventions differed in the STN and medial prefrontal cortex, with relative increases with stimulation in the former structure and decreases in the latter. Network quantification disclosed reductions in PDRP activity with both interventions, which correlated with clinical improvement (P < 0.05). The degree of network modulation by therapy did not differ significantly for the two treatment approaches (P > 0.6). These findings support the results of previous imaging studies indicating that effective symptomatic therapies for Parkinson's disease involve a common mechanism. The modulation of pathological brain networks is a critical feature of the treatment response in parkinsonism. KeywordsParkinson s disease; subthalamic nucleus; deep brain stimulation; brain metabolism; PET

Dystonia is a brain disorder characterized by sustained involuntary muscle contractions. It is typically inherited as an autosomal dominant trait with incomplete penetrance. While lacking clear degenerative neuropathology, primary dystonia is thought to involve microstructural and functional changes in neuronal circuitry. In the current study, we used magnetic resonance diffusion tensor imaging and probabilistic tractography to identify the specific circuit abnormalities that underlie clinical penetrance in carriers of genetic mutations for this disorder. This approach revealed reduced integrity of cerebellothalamocortical fiber tracts, likely developmental in origin, in both manifesting and clinically nonmanifesting dystonia mutation carriers. In these subjects, reductions in cerebellothalamic connectivity correlated with increased motor activation responses, consistent with loss of inhibition at the cortical level. Nonmanifesting mutation carriers were distinguished by an additional area of fiber tract disruption situated distally along the thalamocortical segment of the pathway, in tandem with the proximal cerebellar outflow abnormality. In individual gene carriers, clinical penetrance was determined by the difference in connectivity measured at these two sites. Overall, these findings point to a novel mechanism to explain differences in clinical expression in carriers of genes for brain disease.