Faculty Bibliography

Neurocognitive decline, including deficits in motor learning, occurs in the presymptomatic phase of Huntington's disease (HD) and precedes the onset of motor symptoms. Findings from recent neuroimaging studies have linked these deficits to alterations in fronto-striatal and fronto-parietal brain networks. However, little is known about the temporal dynamics of these networks when subjects approach phenoconversion. Here, 10 subjects with presymptomatic HD were scanned with 15O-labeled water at baseline and again 1.5 years later while performing a motor sequence learning task and a kinematically matched control task. Spatial covariance analysis was utilized to characterize patterns of change in learning-related neural activation occurring over time in these individuals. Pattern expression was compared to corresponding values in 10 age-matched healthy control subjects. Spatial covariance analysis revealed significant longitudinal changes in the expression of a specific learning-related activation pattern characterized by increasing activity in the right orbitofrontal cortex, with concurrent reductions in the right medial prefrontal and posterior cingulate regions, the left insula, left precuneus, and left cerebellum. Changes in the expression of this pattern over time correlated with baseline measurements of disease burden and learning performance. The network changes were accompanied by modest improvement in learning performance that took place concurrently in the gene carriers. The presence of increased network activity in the setting of stable task performance is consistent with a discrete compensatory mechanism. The findings suggest that this effect is most pronounced in the late presymptomatic phase of HD, as subjects approach clinical onset.

Corticobasal degeneration is an uncommon parkinsonian variant condition that is diagnosed mainly on clinical examination. To facilitate the differential diagnosis of this disorder, we used metabolic brain imaging to characterize a specific network that can be used to discriminate corticobasal degeneration from other atypical parkinsonian syndromes. Ten non-demented patients (eight females/two males; age 73.9 +/- 5.7 years) underwent metabolic brain imaging with 18F-fluorodeoxyglucose positron emission tomography for atypical parkinsonism. These individuals were diagnosed clinically with probable corticobasal degeneration. This diagnosis was confirmed in the three subjects who additionally underwent post-mortem examination. Ten age-matched healthy subjects (five females/five males; age 71.7 +/- 6.7 years) served as controls for the imaging studies. Spatial covariance analysis was applied to scan data from the combined group to identify a significant corticobasal degeneration-related metabolic pattern that discriminated (P < 0.001) the patients from the healthy control group. This pattern was characterized by bilateral, asymmetric metabolic reductions involving frontal and parietal cortex, thalamus, and caudate nucleus. These pattern-related changes were greater in magnitude in the cerebral hemisphere opposite the more clinically affected body side. The presence of this corticobasal degeneration-related metabolic topography was confirmed in two independent testing sets of patient and control scans, with elevated pattern expression (P < 0.001) in both disease groups relative to corresponding normal values. We next determined whether prospectively computed expression values for this pattern accurately discriminated corticobasal degeneration from multiple system atrophy and progressive supranuclear palsy (the two most common atypical parkinsonian syndromes) on a single case basis. Based upon this measure, corticobasal degeneration was successfully distinguished from multiple system atrophy (P < 0.001) but not progressive supranuclear palsy, presumably because of the overlap ( approximately 24%) that existed between the corticobasal degeneration- and the progressive supranuclear palsy-related metabolic topographies. Nonetheless, excellent discrimination between these disease entities was achieved by computing hemispheric asymmetry scores for the corticobasal degeneration-related pattern on a prospective single scan basis. Indeed, a logistic algorithm based on the asymmetry scores combined with separately computed expression values for a previously validated progressive supranuclear palsy-related pattern provided excellent specificity (corticobasal degeneration: 92.7%; progressive supranuclear palsy: 94.1%) in classifying 58 testing subjects. In conclusion, corticobasal degeneration is associated with a reproducible disease-related metabolic covariance pattern that may help to distinguish this disorder from other atypical parkinsonian syndromes.

Patient responses to placebo and sham effects are a major obstacle to the development of therapies for brain disorders, including Parkinson's disease (PD). Here, we used functional brain imaging and network analysis to study the circuitry underlying placebo effects in PD subjects randomized to sham surgery as part of a double-blind gene therapy trial. Metabolic imaging was performed prior to randomization, then again at 6 and 12 months after sham surgery. In this cohort, the sham response was associated with the expression of a distinct cerebello-limbic circuit. The expression of this network increased consistently in patients blinded to treatment and correlated with independent clinical ratings. Once patients were unblinded, network expression declined toward baseline levels. Analogous network alterations were not seen with open-label levodopa treatment or during disease progression. Furthermore, sham outcomes in blinded patients correlated with baseline network expression, suggesting the potential use of this quantitative measure to identify "sham-susceptible" subjects before randomization. Indeed, Monte Carlo simulations revealed that a priori exclusion of such individuals substantially lowers the number of randomized participants needed to demonstrate treatment efficacy. Individualized subject selection based on a predetermined network criterion may therefore limit the need for sham interventions in future clinical trials.

IMPORTANCE Coenzyme Q10 (CoQ10), an antioxidant that supports mitochondrial function, has been shown in preclinical Parkinson disease (PD) models to reduce the loss of dopamine neurons, and was safe and well tolerated in early-phase human studies. A previous phase II study suggested possible clinical benefit. OBJECTIVE To examine whether CoQ10 could slow disease progression in early PD. DESIGN, SETTING, AND PARTICIPANTS A phase III randomized, placebo-controlled, double-blind clinical trial at 67 North American sites consisting of participants 30 years of age or older who received a diagnosis of PD within 5 years and who had the following inclusion criteria: the presence of a rest tremor, bradykinesia, and rigidity; a modified Hoehn and Yahr stage of 2.5 or less; and no anticipated need for dopaminergic therapy within 3 months. Exclusion criteria included the use of any PD medication within 60 days, the use of any symptomatic PD medication for more than 90 days, atypical or drug-induced parkinsonism, a Unified Parkinson's Disease Rating Scale (UPDRS) rest tremor score of 3 or greater for any limb, a Mini-Mental State Examination score of 25 or less, a history of stroke, the use of certain supplements, and substantial recent exposure to CoQ10. Of 696 participants screened, 78 were found to be ineligible, and 18 declined participation. INTERVENTIONS The remaining 600 participants were randomly assigned to receive placebo, 1200 mg/d of CoQ10, or 2400 mg/d of CoQ10; all participants received 1200 IU/d of vitamin E. MAIN OUTCOMES AND MEASURES Participants were observed for 16 months or until a disability requiring dopaminergic treatment. The prospectively defined primary outcome measure was the change in total UPDRS score (Parts I-III) from baseline to final visit. The study was powered to detect a 3-point difference between an active treatment and placebo. RESULTS The baseline characteristics of the participants were well balanced, the mean age was 62.5 years, 66% of participants were male, and the mean baseline total UPDRS score was 22.7. A total of 267 participants required treatment (94 received placebo, 87 received 1200 mg/d of CoQ10, and 86 received 2400 mg/d of CoQ10), and 65 participants (29 who received placebo, 19 who received 1200 mg/d of CoQ10, and 17 who received 2400 mg/d of CoQ10) withdrew prematurely. Treatments were well tolerated with no safety concerns. The study was terminated after a prespecified futility criterion was reached. At study termination, both active treatment groups showed slight adverse trends relative to placebo. Adjusted mean changes (worsening) in total UPDRS scores from baseline to final visit were 6.9 points (placebo), 7.5 points (1200 mg/d of CoQ10; P = .49 relative to placebo), and 8.0 points (2400 mg/d of CoQ10; P = .21 relative to placebo). CONCLUSIONS AND RELEVANCE Coenzyme Q10 was safe and well tolerated in this population, but showed no evidence of clinical benefit. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT00740714.

To generate imaging biomarkers from disease-specific brain networks, we have implemented a general toolbox to rapidly perform scaled subprofile modeling (SSM) based on principal component analysis (PCA) on brain images of patients and normals. This SSMPCA toolbox can define spatial covariance patterns whose expression in individual subjects can discriminate patients from controls or predict behavioral measures. The technique may depend on differences in spatial normalization algorithms and brain imaging systems. We have evaluated the reproducibility of characteristic metabolic patterns generated by SSMPCA in patients with Parkinson's disease (PD). We used [(18) F]fluorodeoxyglucose PET scans from patients with PD and normal controls. Motor-related (PDRP) and cognition-related (PDCP) metabolic patterns were derived from images spatially normalized using four versions of SPM software (spm99, spm2, spm5, and spm8). Differences between these patterns and subject scores were compared across multiple independent groups of patients and control subjects. These patterns and subject scores were highly reproducible with different normalization programs in terms of disease discrimination and cognitive correlation. Subject scores were also comparable in patients with PD imaged across multiple PET scanners. Our findings confirm a very high degree of consistency among brain networks and their clinical correlates in PD using images normalized in four different SPM platforms. SSMPCA toolbox can be used reliably for generating disease-specific imaging biomarkers despite the continued evolution of image preprocessing software in the neuroimaging community. Network expressions can be quantified in individual patients independent of different physical characteristics of PET cameras. Hum Brain Mapp 35:1801-1814, 2014. (c) 2013 Wiley Periodicals, Inc.

OBJECTIVE: To determine whether the Parkinson disease-related covariance pattern (PDRP) expression is abnormally increased in idiopathic REM sleep behavior disorder (RBD) and whether increased baseline activity is associated with greater individual risk of subsequent phenoconversion. METHODS: For this cohort study, we recruited 2 groups of RBD and control subjects. Cohort 1 comprised 10 subjects with RBD (63.5 +/- 9.4 years old) and 10 healthy volunteers (62.7 +/- 8.6 years old) who underwent resting-state metabolic brain imaging with (18)F-fluorodeoxyglucose PET. Cohort 2 comprised 17 subjects with RBD (68.9 +/- 4.8 years old) and 17 healthy volunteers (66.6 +/- 6.0 years old) who underwent resting brain perfusion imaging with ethylcysteinate dimer SPECT. The latter group was followed clinically for 4.6 +/- 2.5 years by investigators blinded to the imaging results. PDRP expression was measured in both RBD groups and compared with corresponding control values. RESULTS: PDRP expression was elevated in both groups of subjects with RBD (cohort 1: p < 0.04; cohort 2: p < 0.005). Of the 17 subjects with long-term follow-up, 8 were diagnosed with Parkinson disease or dementia with Lewy bodies; the others did not phenoconvert. For individual subjects with RBD, final phenoconversion status was predicted using a logistical regression model based on PDRP expression and subject age at the time of imaging (r(2) = 0.64, p < 0.0001). CONCLUSIONS: Latent network abnormalities in subjects with idiopathic RBD are associated with a greater likelihood of subsequent phenoconversion to a progressive neurodegenerative syndrome.

BACKGROUND: The evaluation of effective disease-modifying therapies for neurodegenerative disorders relies on objective and accurate measures of progression in at-risk individuals. Here we used a computational approach to identify a functional brain network associated with the progression of preclinical Huntington's disease (HD). METHODS: Twelve premanifest HD mutation carriers were scanned with [18F]-fluorodeoxyglucose PET to measure cerebral metabolic activity at baseline and again at 1.5, 4, and 7 years. At each time point, the subjects were also scanned with [11C]-raclopride PET and structural MRI to measure concurrent declines in caudate/putamen D2 neuroreceptor binding and tissue volume. The rate of metabolic network progression in this cohort was compared with the corresponding estimate obtained in a separate group of 21 premanifest HD carriers who were scanned twice over a 2-year period. RESULTS: In the original premanifest cohort, network analysis disclosed a significant spatial covariance pattern characterized by progressive changes in striato-thalamic and cortical metabolic activity. In these subjects, network activity increased linearly over 7 years and was not influenced by intercurrent phenoconversion. The rate of network progression was nearly identical when measured in the validation sample. Network activity progressed at approximately twice the rate of single region measurements from the same subjects. CONCLUSION: Metabolic network measurements provide a sensitive means of quantitatively evaluating disease progression in premanifest individuals. This approach may be incorporated into clinical trials to assess disease-modifying agents. TRIAL REGISTRATION: Registration is not required for observational studies. FUNDING: NIH (National Institute of Neurological Disorders and Stroke, National Institute of Biomedical Imaging and Bioengineering) and CHDI Foundation Inc.

The use of functional imaging in neurodegenerative diseases has increased in recent years, with applications in research into the underlying pathophysiology, aiding in diagnosis, or evaluating new treatments. In Parkinson's disease (PD), these imaging methods have expanded our understanding of the disease beyond dopaminergic deficits. Moreover, functional imaging methods have described alterations in functional networks relating not only to the motor symptoms, but also to many nonmotor features of PD, such as cognitive dysfunction. From a clinical viewpoint, functional imaging methods can assist in monitoring disease progression, such as in the context of clinical trials, and holds the potential to aid in early diagnosis of PD and differentiation from other parkinsonian disorders.

BACKGROUND: Abetalipoproteinemia is a rare disorder of fat absorption, characterized by vitamin deficiency, acanthocytosis, and neurologic symptoms including ataxia and tremor. CASE REPORT: A 41-year-old male with abetalipoproteinemia is presented. He underwent staged bilateral thalamic deep brain stimulation (DBS) for the treatment of his tremors. After DBS, the patient achieved significant improvements in his tremors, ataxia, and quality of life. DISCUSSION: Thalamic DBS proved to be both safe and efficacious in the management of ataxia and tremors in a patient with abetalipoproteinemia. This is the first report of DBS in abetalipoproteinemia in the literature.

Movement kinematic variables related to force production can be modulated to respond appropriately to different contexts. We previously showed that in a choice-reaction time and a predictable timed-response task, normal subjects perform reaching movements to the same targets with two different kinematic patterns, a marker of flexibility. Here, we used the two tasks to determine whether basal ganglia are involved in the selection and modulation of movement kinematics and therefore in flexible force production. We tested seventeen patients in the early stages of Parkinson's disease, eleven pre-symptomatic Huntington's disease carriers and sixteen age-matched normal controls with the above-mentioned motor tasks. In both patient groups, the difference in kinematics (movement duration, peak velocity and acceleration) between the two tasks was significantly reduced compared to controls, indicating a limited range of choices or flexibility. However, this reduction was skewed in opposite directions in the two disorders, with force production being generally higher in Huntington's carriers and lower in Parkinson's patients compared to controls. We conclude that basal ganglia are involved in adapting movement to different contexts and selecting the appropriate movement force. The opposite trends in Parkinson's and Huntington's disease suggest that such regulation might depend on the balance between the outputs of direct and indirect pathways