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Parkinson's disease (PD) is a neurodegenerative disease with motor and non-motor manifestations that have been previously reported to affect patient quality of life (QoL). Our objective is to investigate the factors that contribute to QoL in a cohort of PD patients receiving care at a major academic institution.In this cross-sectional study of 124 participants (71.77% male, mean age 65.20, mean UPDRS-III score 11.25), we analyzed if certain clinical features such as UPDRS-III, QIDS-C, and total disease duration contributed to QoL as measured by two different metrics (PDQ-39 and EQ-5D) in PD patients at a university Movement Disorders Clinic.Motor symptoms of PD, with the exception of tremor, as well as depression and specific depressive symptoms were significantly and positively correlated with lower QoL metrics for patients with Parkinson's, with total depressive symptom severity (QIDS-CWhile severity of motor symptoms certainly impacted QoL in our cohort, our findings suggest that depressive symptoms contribute more to impaired QoL than severe motor symptoms do. This phenomenon suggests that concomitant depression in PD as well as one's psychological adjustment to disability may have a greater impact on QoL than severe motor symptoms.

INTRODUCTION: Predictive biomarkers of Parkinson’s Disease progression are needed to expedite neuroprotective treatment development and facilitate prognoses for patients. This work uses measures derived from resting-state functional magnetic resonance imaging, including regional homogeneity (ReHo) and fractional amplitude of low frequency fluctuations (fALFF), to predict an individual’s current and future severity over up to 4 years and to elucidate the most prognostic brain regions. METHODS: ReHo and fALFF are measured for 82 Parkinson’s Disease subjects and used to train machine learning predictors of baseline clinical and future severity at 1 year, 2 years, and 4 years follow-up as measured by the Movement Disorder Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS). Predictive performance is measured with nested cross-validation, validated on an external dataset, and again validated through leave-one-site-out cross-validation. Important predictive features are identified. RESULTS: The models explain up to 30.4% of the variance in current MDS-UPDRS scores, 55.8% of the variance in year 1 scores, and 47.1% of the variance in year 2 scores (p < 0.0001). For distinguishing high and low-severity individuals at each timepoint (MDS-UPDRS score above or below the median, respectively), the models achieve positive predictive values up to 79% and negative predictive values up to 80%. Higher ReHo and fALFF in several regions, including components of the default motor network, predicted lower severity across current and future timepoints. CONCLUSION: These results identify an accurate prognostic neuroimaging biomarker which may be used to better inform enrollment in trials of neuroprotective treatments and enable physicians to counsel their patients.

Using a multi-cohort, discovery-replication-validation design, we sought new plasma biomarkers that predict which individuals with Parkinson's disease (PD) will experience cognitive decline.In 108 discovery cohort PD individuals and 83 replication cohort PD individuals, we measured 940 plasma proteins on an aptamer-based platform. Using proteins associated with subsequent cognitive decline in both cohorts, we trained a logistic regression model to predict which patients with PD showed fast ( = 1 point drop/year on Montreal Cognitive Assessment [MoCA]) versus slow ( 1 point drop/year on MoCA) cognitive decline in the discovery cohort, testing it in the replication cohort. We developed alternate assays for the top 3 proteins and confirmed their ability to predict cognitive decline - defined by change in MoCA or development of incident mild cognitive impairment (MCI) or dementia - in a validation cohort of 118 individuals with PD. We investigated the top plasma biomarker for causal influence by Mendelian randomization (MR).A model with only 3 proteins (melanoma inhibitory activity protein [MIA], C-reactive protein [CRP], and albumin) separated fast versus slow cognitive decline subgroups with an area under the curve (AUC) of 0.80 in the validation cohort. The individuals with PD in the validation cohort in the top quartile of risk for cognitive decline based on this model were 4.4 times more likely to develop incident MCI or dementia than those in the lowest quartile. Genotypes at MIA single nucleotide polymorphism (SNP) rs2233154 associated with MIA levels and cognitive decline, providing evidence for MIA's causal influence.An easily obtained plasma-based predictor identifies individuals with PD at risk for cognitive decline. MIA may participate causally in development of cognitive decline. ANN NEUROL 2022;92:255-269.

Objective Motor fluctuations develop in most patients treated with carbidopa/levodopa for Parkinson disease. The continuous dopamine stimulation hypothesis suggests that longer-acting forms of levodopa might improve outcomes, but this has been inadequately tested in humans. We undertook to determine if there is any difference in symptom progression rate among patients taking immediate-release carbidopa/levodopa (IR), controlled-release carbidopa/levodopa (CR), or carbidopa/levodopa/entacapone (CLE) using standard outcome measures in a naturalistic study. Methods We evaluated Parkinson disease subjects prospectively followed for up to 48 months in the Parkinson's Disease Biomarker Project. Bayesian linear or generalized linear mixed-effects models were developed to determine if oral levodopa formulation influenced the rate of symptom progression as measured by 8 outcome measures. Results At baseline, the IR, CR, and CLE groups were similar except that the CR group had milder disease and was represented at only 1 site, and the CLE group had a longer disease duration. In the primary analysis, there was no difference in rate of symptom progression as measured by the Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale Part II, Part IV, or total score. In the secondary exploratory analysis, there was no difference in progression rate as measured by change in levodopa equivalent daily dose, Montreal Cognitive Assessment, Parkinson's Disease Questionnaire mobility subscore, Schwab and England Activities of Daily Living Scale, or a global composite outcome. Conclusions We found no difference in symptom progression rate in patients taking IR, CR, or CLE. This clinical observation supports pharmacokinetic studies demonstrating that none of these oral levodopa formulations achieve continuous dopamine stimulation.

Cognitive decline is common in Parkinson's disease (PD) and is a leading cause of reduced quality of life. Cognitive difficulty seen early in the course of PD takes the form of mild cognitive impairment (MCI-PD), and Parkinson's disease dementia (PDD) is nearly universal in the late stages of the disease. Although most people with MCI-PD will progress to PDD, the two entities have significant differences in terms of underlying pathophysiology as well as cognitive profiles and management strategies. The most important contributor to MCI-PD is frontostriatal dopamine depletion, whereas the major cause of PDD is Lewy body pathology spreading to the neocortex plus, in many cases, comorbid Alzheimer's pathology. Management strategies for both MCI-PD and PDD are limited. The best approach for MCI-PD is a combination of cognitive rehabilitation and appropriate titration of dopaminergic therapy, and the medications used in treatment of Alzheimer's disease appear to have a modest benefit for patients with PDD. [ Psychiatr Ann . 2020;50(3):100–106.]

In resting-state functional magnetic resonance imaging (rs-fMRI), artefactual signals arising from subject motion can dwarf and obfuscate the neuronal activity signal. Typical motion correction approaches involve the generation of nuisance regressors, which are timeseries of non-brain signals regressed out of the fMRI timeseries to yield putatively artifact-free data. Recent work suggests that concatenating all regressors into a single regression model is more effective than the sequential application of individual regressors, which may reintroduce previously removed artifacts. This work compares 18 motion correction pipelines consisting of head motion, independent components analysis, and non-neuronal physiological signal regressors in sequential or concatenated combinations. The pipelines are evaluated on a dataset of cognitively normal individuals with repeat imaging and on datasets of studies of Autism Spectrum Disorder, Major Depressive Disorder, and Parkinson’s Disease. Extensive metrics of motion artifact removal are measured, including resting state network recovery, Quality Control-Functional Connectivity (QC-FC) correlation, distance-dependent artifact, network modularity, and test-retest reliability of multiple rs-fMRI analyses. The results reveal limitations in previously proposed metrics, including the QC-FC correlation and modularity quality, and identify more robust motion correction metrics. The results also reveal limitations in the concatenated regression approach, which is outperformed by the sequential regression approach in the test-retest reliability metrics. Finally, pipelines are recommended that perform well based on quantitative and qualitative comparisons across multiple datasets and robust metrics. These new insights and recommendations help address the need for effective motion artifact correction to reduce noise and confounds in rs-fMRI.

IMPORTANCE: Urate elevation, despite associations with crystallopathic, cardiovascular, and metabolic disorders, has been pursued as a potential disease-modifying strategy for Parkinson disease (PD) based on convergent biological, epidemiological, and clinical data. OBJECTIVE: To determine whether sustained urate-elevating treatment with the urate precursor inosine slows early PD progression. DESIGN, PARTICIPANTS, AND SETTING: Randomized, double-blind, placebo-controlled, phase 3 trial of oral inosine treatment in early PD. A total of 587 individuals consented, and 298 with PD not yet requiring dopaminergic medication, striatal dopamine transporter deficiency, and serum urate below the population median concentration (

PurposeData augmentation improves the accuracy of deep learning models when training data is scarce by synthesizing additional samples. This work addresses the lack of validated augmentation methods specific for synthesizing anatomically realistic 4D (3D+time) images for neuroimaging, such as fMRI, by proposing a new augmentation method.Materials and MethodsThe proposed method, BLENDS, generates new nonlinear warp fields by combining intersubject coregistration maps, computed using symmetric normalization, through spatial blending. These new warp fields can be applied to existing 4D fMRI to create new augmented images. BLENDS is tested on two neuroimaging problems using de-identified datasets: 1) the prediction of antidepressant response from task-based fMRI in the EMBARC dataset (n = 163), and 2) the prediction of Parkinson’s Disease symptom trajectory from baseline resting-state fMRI regional homogeneity in the PPMI dataset (n = 43).ResultsBLENDS readily generates hundreds of new fMRI from existing images, with unique anatomical variations from the source images, that significantly improve prediction performance. For antidepressant response prediction, augmenting each original image once (2x the original training data) significantly increased prediction R2 from 0.055 to 0.098 (p < 1e-6), while at 10x augmentation R2 increased to 0.103. For the prediction of Parkinson’s Disease trajectory, 10x augmentation R2 increased from 0.294 to 0.548 (p < 1e-6).ConclusionAugmentation of fMRI through nonlinear transformations with BLENDS significantly improves the performance of deep learning models on clinically relevant predictive tasks. This method will help neuroimaging researchers overcome dataset size limitations and achieve more accurate predictive models.

Background: The literature is conflicting on whether rapid eye movement sleep behavior disorder (RBD) is associated with more rapid progression of Parkinson disease (PD).Objective: We aimed to determine (1) how stable probable RBD (pRBD) is over time and (2) whether it predicts faster PD progression.Methods: We evaluated participants in the Parkinson's Disease Biomarker Project (PDBP) who were prospectively assessed every 6–12 months with a series of motor, non-motor, disability, and health status scales. For aim 1, we calculated the incidence and disappearance rates of pRBD and compared stability of pRBD in PD with control subjects. For aim 2, we developed multiple regression models to determine if pRBD at baseline influenced the rate of change or average value at 48 months of 10 outcome variables.Results: We found that pRBD was a less stable diagnosis for PD than controls. In pRBD+ subjects, the Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS) part III score progressed 2.78 points per year faster (p < 0.01), MDS-UPDRS total score progressed 3.98 points per year faster (p < 0.01), a global composite outcome (GCO) worsened by 0.09 points per year faster (p = 0.02), and Parkinson's Disease Questionnaire (PDQ-39) mobility score progressed 2.57 percentage points per year faster (p < 0.01). The average scores at 48 months were 8.89 (p = 0.02) and 14.3 (p = 0.01) points higher for pRBD+ in MDS-UPDRS part III and total scores, respectively.Conclusions: Our study confirms that pRBD detected at the start of a study portends more rapid progression of PD. Knowing this could be useful for enriching clinical trials with fast progressors to accelerate discovery of a disease modifying agent.

Dystonia is defined as a movement disorder characterized by sustained or intermittent muscle contractions causing abnormal, often repetitive, movements, postures, or both. Dystonic movements are typically patterned and twisting and may be tremulous. Dystonia is often initiated or worsened by voluntary action and associated with overflow muscle activation. A recent revision now classifies dystonia into two axes: (1) clinical characteristics (age at onset, temporal pattern, body distribution, whether focal, segmental, or generalized; and associated features) and (2) etiology, whether idiopathic/genetic or secondary to other neurological/medical diseases. Pharmacological treatments for dystonia remain generally unsatisfactory and consist of various combinations of levodopa, anticholinergics, muscle-relaxing drugs as well as botulinum toxin injections in focal and segmental dystonia. Overall in outcomes are poor because of limited efficacy and the potential for significant side effects such as sedation and cognitive impairment. A humanitarian-device exemption from the Food and Drug Administration was issued for the treatment of medically refractory symptoms of generalized dystonia with the use of DBS. Bilateral GPi DBS surgery is effective for both generalized and focal dystonia including cervical dystonia and tardive dystonia. DBS may be the best available treatment for disabling symptoms of generalized, cervical, tardive, and other dystonia that have failed to respond to oral drugs and botulinum toxin injections (when applicable) as long as contractures have not developed, because in this situation, DBS will be ineffective. Rigorous patient selection and careful management of comorbidities are essential for favorable outcomes.

Tremor is an involuntary movement characterized by a rhythmic oscillation around a fixed point or trajectory. It can be classified based on its clinical features or underlying cause. Tremor was the first approved indication for deep brain stimulation (DBS) in the United States. Essential tremor (ET) is the most common movement disorder. These patients typically suffer from tremor of the hands and arms, and about 40% suffer from head tremor and 20% from voice tremor. Most candidates for functional neurosurgery have severe action or postural tremor that impairs function and quality of life to the extent that the risks, costs, and inconvenience of DBS treatment are justified. Unilateral procedures are commonly performed, although bilateral procedures should be considered when limb tremor is severe bilaterally or when head, voice, or trunk tremor causes significant disability. One reason for initially pursuing unilateral DBS for control of tremor in the dominant hand is that many patients will not require repeat surgery for the nondominant side despite residual tremor on that side. Many centers have developed a staged approach to DBS for ET that allows time to pass between the two stages; this can facilitate recovery and potentially diminish the negative consequences associated with a second procedure.

Patient selection is critical for optimizing clinical outcomes after deep brain stimulation (DBS) surgery. Patient expectations need to be addressed before DBS surgery to avoid disappointment. There are generally accepted criteria for DBS candidacy for treatment of Parkinson disease (PD), essential tremor (ET), and dystonia. For PD, selection criteria include a diagnosis of idiopathic PD and the presence of disabling or troubling motor symptoms such as motor fluctuations or dyskinesia (despite optimized pharmacologic treatment). Medication-resistant tremor is also an indication. The response of problematic motor symptoms to dopaminergic drugs is an important predictor of DBS response, favoring selection of patients for whom levodopa substantially improves tremor, bradykinesia, and rigidity. Rarely, gait is improved with DBS, and in some cases freezing can improve, although this is not a predictable post-DBS feature. Exclusion criteria include serious medical comorbidities, uncontrolled psychiatric illness (thought and mood disorders), and dementia. Preoperative magnetic resonance imaging with extensive white matter changes, vascular malformations, severe cerebral atrophy, or hydrocephalus can also be exclusions. The patient should clearly understand the risks and benefits of DBS, which should be assessed using a preoperative multidisciplinary evaluation (neurology, neurosurgery, neuropsychology, psychiatry, and rehabilitation). Use of a social worker and/or nutritionist can also be helpful in select cases.

Parkinson’s disease is the second most common neurodegenerative disorder and is characterized by the loss of ability to control voluntary movements. Predictive biomarkers of progression in Parkinson’s Disease are urgently needed to expedite the development of neuroprotective treatments and facilitate discussions about disease prognosis between clinicians and patients. Resting-state functional magnetic resonance imaging (rs-fMRI) shows promise in predicting progression, with derived measures, including regional homogeneity (ReHo) and fractional amplitude of low frequency fluctuations (fALFF), having been previously been associated withcurrentdisease severity. In this work, ReHo and fALFF features from 82 Parkinson’s Disease subjects are used to train machine learning predictors of baseline clinical severity and progression at 1 year, 2 years, and 4 years follow-up as measured by the Movement Disorder Society Unified Depression Rating Scale (MDS-UPDRS) score. This is the first time that rs-fMRI and machine learning have been combined to predictfuturedisease progression. The machine learning models explain up to 30.4% (R2= 0.304) of the variance in baseline MDS-UPDRS scores, 55.8% (R2= 0.558) of the variance in year 1 scores, and 47.1% (R2= 0.471) of the variance in year 2 scores with high statistical significance (p <0.0001). For distinguishing high- and low-progression individuals (MDS-UPDRS score above or below the median), the models achieve positive predictive values of up to 71% and negative predictive values of up to 84%. The models learn patterns of ReHo and fALFF measures that predict better and worse prognoses. Higher ReHo and fALFF in regions of the default motor network predicted lower current severity and lower future progression. The rs-fMRI features in the temporal lobe, limbic system, and motor cortex were also identified as predictors. These results present a potential neuroimaging biomarker that accurately predicts progression, which may be useful as a clinical decision-making tool and in future trials of neuroprotective treatments.

Magnetic resonance guided high intensity focused ultrasound is a novel, non-invasive, image-guided procedure that is able to ablate intracranial tissue with submillimetre precision. It is currently FDA approved for essential tremor and tremor dominant Parkinson’s disease. The aim of this update is to review the limitations of current landmark-based targeting techniques of the ventral intermediate nucleus and demonstrate the role of emerging imaging techniques that are relevant for both magnetic resonance guided high intensity focused ultrasound and deep brain stimulation. A significant limitation of standard MRI sequences is that the ventral intermediate nucleus, dentatorubrothalamic tract, and other deep brain nuclei cannot be clearly identified. This paper provides original, annotated images demarcating the ventral intermediate nucleus, dentatorubrothalamic tract, and other deep brain nuclei on advanced MRI sequences such as fast grey matter acquisition T1 inversion recovery, quantitative susceptibility mapping, susceptibility weighted imaging, and diffusion tensor imaging tractography. Additionally, the paper reviews clinical efficacy of targeting with these novel MRI techniques when compared to current established landmark-based targeting techniques. The paper has widespread applicability to both deep brain stimulation and magnetic resonance guided high intensity focused ultrasound.

Background Parkinson’s disease (PD) is a progressive neurodegenerative disease affecting about 5 million people worldwide with no disease-modifying therapies. We sought blood-based biomarkers in order to provide molecular characterization of individuals with PD for diagnostic confirmation and prediction of progression. Methods and findings In 141 plasma samples (96 PD, 45 neurologically normal control [NC] individuals; 45.4% female, mean age 70.0 years) from a longitudinally followed Discovery Cohort based at the University of Pennsylvania (UPenn), we measured levels of 1,129 proteins using an aptamer-based platform. We modeled protein plasma concentration (log10 of relative fluorescence units [RFUs]) as the effect of treatment group (PD versus NC), age at plasma collection, sex, and the levodopa equivalent daily dose (LEDD), deriving first-pass candidate protein biomarkers based on p-value for PD versus NC. These candidate proteins were then ranked by Stability Selection. We confirmed findings from our Discovery Cohort in a Replication Cohort of 317 individuals (215 PD, 102 NC; 47.9% female, mean age 66.7 years) from the multisite, longitudinally followed National Institute of Neurological Disorders and Stroke Parkinson’s Disease Biomarker Program (PDBP) Cohort. Analytical approach in the Replication Cohort mirrored the approach in the Discovery Cohort: each protein plasma concentration (log10 of RFU) was modeled as the effect of group (PD versus NC), age at plasma collection, sex, clinical site, and batch. Of the top 10 proteins from the Discovery Cohort ranked by Stability Selection, four associations were replicated in the Replication Cohort. These blood-based biomarkers were bone sialoprotein (BSP, Discovery false discovery rate [FDR]-corrected p = 2.82 × 10−2, Replication FDR-corrected p = 1.03 × 10−4), osteomodulin (OMD, Discovery FDR-corrected p = 2.14 × 10−2, Replication FDR-corrected p = 9.14 × 10−5), aminoacylase-1 (ACY1, Discovery FDR-corrected p = 1.86 × 10−3, Replication FDR-corrected p = 2.18 × 10−2), and growth hormone receptor (GHR, Discovery FDR-corrected p = 3.49 × 10−4, Replication FDR-corrected p = 2.97 × 10−3). Measures of these proteins were not significantly affected by differences in sample handling, and they did not change comparing plasma samples from 10 PD participants sampled both on versus off dopaminergic medication. Plasma measures of OMD, ACY1, and GHR differed in PD versus NC but did not differ between individuals with amyotrophic lateral sclerosis (ALS, n = 59) versus NC. In the Discovery Cohort, individuals with baseline levels of GHR and ACY1 in the lowest tertile were more likely to progress to mild cognitive impairment (MCI) or dementia in Cox proportional hazards analyses adjusting for age, sex, and disease duration (hazard ratio [HR] 2.27 [95% CI 1.04–5.0, p = 0.04] for GHR, and HR 3.0 [95% CI 1.24–7.0, p = 0.014] for ACY1). GHR’s association with cognitive decline was confirmed in the Replication Cohort (HR 3.6 [95% CI 1.20–11.1, p = 0.02]). The main limitations of this study were its reliance on the aptamer-based platform for protein measurement and limited follow-up time available for some cohorts. Conclusions In this study, we found that the blood-based biomarkers BSP, OMD, ACY1, and GHR robustly associated with PD across multiple clinical sites. Our findings suggest that biomarkers based on a peripheral blood sample may be developed for both disease characterization and prediction of future disease progression in PD., Alice Chen-Plotkin and colleagues investigate possible biomarkers for diagnosis and progression of Parkinson’s disease., Author summary Why was this study done? No blood tests currently exist that distinguish people with Parkinson’s disease (PD) from neurologically normal individuals or that predict the rate of disease progression in people who have already been diagnosed with PD. Blood tests that distinguish people with PD would be helpful for confirmation of diagnosis (diagnostic biomarkers), whereas blood tests that predict the rate of disease progression (prognostic biomarkers) would be helpful for clinical trials and clinical care. What did the researchers do and find? We screened more than 1,000 blood-based proteins from 527 people with PD, amyotrophic lateral sclerosis (ALS), or neither neurological disease in order to discover new diagnostic and prognostic biomarkers. We used one group of participants to identify potential biomarkers and then used a separate group of participants to confirm these biomarkers. We found that blood levels of four proteins—bone sialoprotein (BSP), osteomodulin (OMD), aminoacylase-1 (ACY1), and growth hormone receptor (GHR)—consistently differed in people with PD compared to people without PD. We found that lower GHR levels at baseline predicted a faster rate of cognitive decline in people with PD. What do these findings mean? Levels of some blood proteins consistently differ between people with versus without PD, and some of these proteins also predict which PD individuals may have faster progression of disease. It may be possible to develop blood-based tests to help confirm PD diagnosis and predict disease progression.

Caffeine is neuroprotective in animal models of PD and caffeine intake is inversely associated with the risk of Parkinson’s disease (PD). This association may be influenced by the genotype of GRIN2A, which encodes an NMDA-glutamate-receptor subunit. In two placebo-controlled studies, we detected no association of caffeine intake with the rate of clinical progression of PD, except among subjects taking creatine, for whom higher caffeine intake was associated with more rapid progression. We now have analyzed data from 420 subjects for whom DNA samples and caffeine intake data were available from a placebo-controlled study of creatine in PD. The GRIN2A genotype was not associated with the rate of clinical progression of PD in the placebo group. However, there was a 4-way interaction between GRIN2A genotype, caffeine, creatine and the time since baseline. Among subjects in the creatine group with high levels of caffeine intake, but not among those with low caffeine intake, the GRIN2A T allele was associated with more rapid progression (p = 0.03). These data indicate that the deleterious interaction between caffeine and creatine with respect to rate of progression of PD is influenced by GRIN2A genotype. This example of a genetic factor interacting with environmental factors illustrates the complexity of gene-environment interactions in the progression of PD.

Deep Brain Stimulation (DBS) has revolutionized the lives of patients of Parkinson disease, offering therapeutic options to those not benefiting entirely from medications alone. With its proven track record of outperforming the best medical management, the goal is to unlock the full potential of this therapy. Currently, the Globus Pallidus Interna (GPi) and Subthalamic Nucleus (STN) are both viable targets for DBS, and the choice of site should focus on the constellation of symptoms, both motor and nonmotor, which are key determinants to quality of life. Our article sheds light on the specific advantages and drawbacks of the two sites, highlighting the need for matching the inherent properties of a target with specific desired effects in patients. UT Southwestern Medical Center has a robust and constantly evolving DBS program and the narrative from our center provides invaluable insight into the practical realities of DBS. The ultimate decision in selecting a DBS target is complex, ideally made by a multidisciplinary team, tailored towards each patient’s profile and their expectations, by drawing upon scientific evidence coupled with experience. Ongoing research is expanding our knowledge base, which should be dynamically incorporated into an institute’s DBS paradigm to ensure that patients receive the optimal therapy.

Parkinson's disease (PD) is a common neurological disorder characterized by gait impairment. PD has no cure, and an impediment to developing a treatment is the lack of any accepted method to predict disease progression rate. The primary aim of this study was to develop a model using clinical measures and biomechanical measures of gait and postural stability to predict an individual's PD progression over two years. Data from 160 PD subjects were utilized. Machine learning models, including XGBoost and Feed Forward Neural Networks, were developed using extensive model optimization and cross-validation. The highest performing model was a neural network that used a group of clinical measures, achieved a PPV of 71% in identifying fast progressors, and explained a large portion (37%) of the variance in an individual's progression rate on held-out test data. This demonstrates the potential to predict individual PD progression rate and enrich trials by analyzing clinical and biomechanical measures with machine learning., Comment: 5 pages, 4 figures, IEEE ICASSP conference submission

Background Neuroprotection for Parkinson's disease (PD) remains elusive. Biomarkers hold the promise of removing roadblocks to therapy development. The National Institute of Neurological Disorders and Stroke has therefore established the Parkinson's Disease Biomarkers Program to promote discovery of PD biomarkers for use in phase II and III clinical trials. Methods Using a novel consortium design, the Parkinson's Disease Biomarker Program is focused on the development of clinical and laboratory-based biomarkers for PD diagnosis, progression, and prognosis. Standardized operating procedures and pooled reference samples were created to allow cross-project comparisons and assessment of batch effects. A web-based Data Management Resource facilitates rapid sharing of data and biosamples across the research community for additional biomarker projects. Results Eleven consortium projects are ongoing, seven of which recruit participants and obtain biosamples. As of October 2014, 1,082 participants have enrolled (620 PD, 101 with other causes of parkinsonism, 23 essential tremor, and 338 controls), 1,040 of whom have at least one biosample. Six thousand eight hundred ninety-eight total biosamples are available from baseline, 6-, 12-, and 18-month visits: 1,006 DNA, 1,661 RNA, 1,419 whole blood, 1,382 plasma, 1,200 serum, and 230 cerebrospinal fluid (CSF). Quality control analysis of plasma, serum, and CSF samples indicates that almost all samples are high quality (24 of 2,812 samples exceed acceptable hemoglobin levels). Conclusions By making samples and data widely available, using stringent operating procedures based on existing standards, hypothesis testing for biomarker discovery, and providing a resource that complements existing programs, the Parkinson's Disease Biomarker Program will accelerate the pace of PD biomarker research. © 2015 International Parkinson and Movement Disorder Society

Summary Background A systematic assessment of potential disease-modifying compounds for Parkinson's disease concluded that pioglitazone could hold promise for the treatment of patients with this disease. We assessed the effect of pioglitazone on the progression of Parkinson's disease in a multicentre, double-blind, placebo-controlled, futility clinical trial. Methods Participants with the diagnosis of early Parkinson's disease on a stable regimen of 1 mg/day rasagiline or 10 mg/day selegiline were randomly assigned (1:1:1) to 15 mg/day pioglitazone, 45 mg/day pioglitazone, or placebo. Investigators were masked to the treatment assignment. Only the statistical centre and the central pharmacy knew the treatment name associated with the randomisation number. The primary outcome was the change in the total Unified Parkinson's Disease Rating Scale (UPDRS) score between the baseline and 44 weeks, analysed by intention to treat. The primary null hypothesis for each dose group was that the mean change in UPDRS was 3 points less than the mean change in the placebo group. The alternative hypothesis (of futility) was that pioglitazone is not meaningfully different from placebo. We rejected the null if there was significant evidence of futility at the one-sided alpha level of 0·10. The study is registered at ClinicalTrials.gov , number NCT01280123 . Findings 210 patients from 35 sites in the USA were enrolled between May 10, 2011, and July 31, 2013. The primary analysis included 72 patients in the 15 mg group, 67 in the 45 mg group, and 71 in the placebo group. The mean total UPDRS change at 44 weeks was 4·42 (95% CI 2·55–6·28) for 15 mg pioglitazone, 5·13 (95% CI 3·17–7·08) for 45 mg pioglitazone, and 6·25 (95% CI 4·35–8·15) for placebo (higher change scores are worse). The mean difference between the 15 mg and placebo groups was −1·83 (80% CI −3·56 to −0·10) and the null hypothesis could not be rejected (p=0·19). The mean difference between the 45 mg and placebo groups was −1·12 (80% CI −2·93 to 0·69) and the null hypothesis was rejected in favour of futility (p=0·09). Planned sensitivity analyses of the primary outcome, using last value carried forward (LVCF) to handle missing data and using the completers' only sample, suggested that the 15 mg dose is also futile (p=0·09 for LVCF, p=0·09 for completers) but failed to reject the null hypothesis for the 45 mg dose (p=0·12 for LVCF, p=0·19 for completers). Six serious adverse events occurred in the 15 mg group, nine in the 45 mg group, and three in the placebo group; none were thought to be definitely or probably related to the study interventions. Interpretation These findings suggest that pioglitazone at the doses studied here is unlikely to modify progression in early Parkinson's disease. Further study of pioglitazone in a larger trial in patients with Parkinson's disease is not recommended. Funding National Institute of Neurological Disorders and Stroke.

Objective To examine the sensitivity and specificity of the Montreal Cognitive Assessment (MoCA), a brief cognitive screening measure previously validated for use in Parkinson's disease (PD), and Alzheimer's Disease-8 (AD8), an eight-item informant report used to screen for dementia, but not yet validated for use in PD, to identify cognitive impairment in a sample of 111 patients with PD. Methods Cognitive impairment was determined based on a battery of neuropsychological measures, excluding the MoCA and AD8. Classification rates of both the MoCA and AD8 in identifying cognitive impairment were examined using logistic regression and receiver operator characteristic (ROC) analysis. Optimal cutoff scores were determined to maximize sensitivity and specificity. Results The MoCA correctly classified 78.4% of participants (p

Biomarkers for Parkinson's disease (PD) diagnosis, prognostication and clinical trial cohort selection are an urgent need. While many promising markers have been discovered through the National Institute of Neurological Disorders and Stroke Parkinson's Disease Biomarker Program (PDBP) and other mechanisms, no single PD marker or set of markers are ready for clinical use. Here we discuss the current state of biomarker discovery for platforms relevant to PDBP. We discuss the role of the PDBP in PD biomarker identification and present guidelines to facilitate their development. These guidelines include: harmonizing procedures for biofluid acquisition and clinical assessments, replication of the most promising biomarkers, support and encouragement of publications that report negative findings, longitudinal follow-up of current cohorts including the PDBP, testing of wearable technologies to capture readouts between study visits and development of recently diagnosed (de novo) cohorts to foster identification of the earliest markers of disease onset.

Parkinson disease (PD) is the second most common neurodegenerative disease. Because dopaminergic neuronal loss begins years before motor symptoms appear, a biomarker for the early identification of the disease is critical for the study of putative neuroprotective therapies. Brain imaging of the nigrostriatal dopamine system has been used as a biomarker for early disease along with cerebrospinal fluid analysis of α-synuclein, but a less costly and relatively non-invasive biomarker would be optimal. We sought to identify an antibody biomarker in the blood of PD patients using a combinatorial peptoid library approach. We examined serum samples from 75 PD patients, 25 de novo PD patients, and 104 normal control subjects in the NINDS Parkinson’s Disease Biomarker Program. We identified a peptoid, PD2, which binds significantly higher levels of IgG3 antibody in PD versus control subjects (Pde novo PD. Also, IgG3 levels are significantly higher in PD versus control serum (Pr=0.457, P

Objective To develop a process to improve patient outcomes from deep brain stimulation (DBS) surgery for Parkinson disease (PD), essential tremor (ET), and dystonia. Methods We employed standard quality improvement methodology using the Plan-Do-Study-Act process to improve patient selection, surgical DBS lead implantation, postoperative programming, and ongoing assessment of patient outcomes. Results The result of this quality improvement process was the development of a neuromodulation network. The key aspect of this program is rigorous patient assessment of both motor and non-motor outcomes tracked longitudinally using a REDCap database. We describe how this information is used to identify problems and to initiate Plan-Do-Study-Act cycles to address them. Preliminary outcomes data is presented for the cohort of PD and ET patients who have received surgery since the creation of the neuromodulation network. Conclusions Careful outcomes tracking is essential to ensure quality in a complex therapeutic endeavor like DBS surgery for movement disorders. The REDCap database system is well suited to store outcomes data for the purpose of ongoing quality assurance monitoring.

Parkinson disease (PD) is the second most common neurodegenerative disease, after Alzheimer disease, and results in both motor and nonmotor dysfunction. Dementia is one of the most disabling nonmotor features. It has been found in an estimated 80% of patients followed longitudinally for 8–20 years,1, 2 and it predicts mortality.3 Depression is twice as common in patients with PD as in healthy controls,4 affecting 31% of patients5; it may predate the onset of motor impairment.6 Counseling about prognosis is an important aspect of care for newly diagnosed patients. Given the importance of dementia and depression to the ultimate disease burden, it is worthwhile to try to correlate presenting motor features with risk of cognitive impairment and depressed mood. Most previous research (31 of 36 studies reviewed by Verreyt et al)7 on the relationship between cognition and the distribution of motor symptoms in PD has evaluated location of the predominant symptoms at the time of the study. However, the type and distribution of symptoms at disease onset are of greater interest because any relationship established between onset site and risk of cognitive impairment can be used to counsel patients when they are first diagnosed. Previous studies suggested a higher risk of cognitive impairment with bilateral onset of symptoms,8 but no difference in risk between right-side and left-side onset.8, 9 Studies looking at the type of symptoms at onset found that in patients with tremor as their first symptom, dementia was less common and more delayed than in those with bradykinesia as their presenting feature.10 Further, cognitive function was found to be better preserved when first symptoms appear on the right side of the body than on the left.11 Katzen et al, for example, studied motor symptom type and laterality at disease onset by evaluating neuropsychological test results in 58 patients and controls.12 The patients whose presenting feature was an isolated tremor in the right hand had fully intact cognitive function, but patients with left-sided onset of any motor symptom or right-sided onset of bradykinesia and/or rigidity had impaired neuropsychological performance. Studies evaluating the link between laterality of PD symptoms and depressed mood have also shown conflicting results. Of 3 studies considering predominant involvement at the time of the study, 1 found that right-side-predominant symptoms were associated with a greater number of depressive symptoms,13 1 found a strong association between left-sided symptoms and more severe depression,14 and 1 showed no difference.15 In 2 studies that assessed the relationship between depression severity and laterality of symptoms at disease onset, both found that right-sided onset was associated with more severe depressive symptoms.16, 17 In this study, we sought to determine whether side and type of motor symptoms at onset were associated with later cognitive function and depressive symptoms in a high-functioning, nondemented cohort of patients with PD.

Background: This evidence-based guideline is an update of the 2005 American Academy of Neurology practice parameter on the treatment of essential tremor (ET). Methods: A literature review using MEDLINE, EMBASE, Science Citation Index, and CINAHL was performed to identify clinical trials in patients with ET published between 2004 and April 2010. Results and Recommendations: Conclusions and recommendations for the use of propranolol, primidone (Level A, established as effective); alprazolam, atenolol, gabapentin (monotherapy), sotalol, topiramate (Level B, probably effective); nadolol, nimodipine, clonazepam, botulinum toxin A, deep brain stimulation, thalamotomy (Level C, possibly effective); and gamma knife thalamotomy (Level U, insufficient evidence) are unchanged from the previous guideline. Changes to conclusions and recommendations from the previous guideline include the following: 1) levetiracetam and 3,4-diaminopyridine probably do not reduce limb tremor in ET and should not be considered (Level B); 2) flunarizine possibly has no effect in treating limb tremor in ET and may not be considered (Level C); and 3) there is insufficient evidence to support or refute the use of pregabalin, zonisamide, or clozapine as treatment for ET (Level U). Neurology ® 2011;77:1752–1755

Object The authors previously developed an optical stereotactic probe employing near-infrared (NIR) spectroscopy to provide intraoperative localization by distinguishing gray matter from white matter. In the current study they extend and further validate this technology. Methods Near-infrared probes were inserted 203 times during 138 procedures for movement disorders. Detailed validation with postoperative imaging was obtained for 121 of these procedures and with microelectrode recording (MER) for 30 procedures. Probes were constructed to interrogate tissue perpendicular to the probe path and to incorporate hollow channels for microelectrodes, deep brain stimulation (DBS) electrodes, and other payloads. Results The NIR data were highly correlated to imaging and MER recordings for thalamic targets. The NIR data were highly sensitive but less specific relative to imaging for subthalamic targets, confirming the ability to detect the subthalamic nucleus and to provide warnings of inaccurate localization. The difference between the NIR- and MER-detected midpoints of the subthalamic nucleus along the chosen tracks was 1.1 ± 1.2 mm (SD). Data obtained during insertion and withdrawal of the NIR probe suggested that DBS electrodes may push their targets ahead of their paths. There was one symptomatic morbidity. Detailed NIR data could be obtained from a 7-cm track in less than 10 minutes. Conclusions The NIR probe is a straightforward, quick, and robust tool for intraoperative localization during functional neurosurgery. Potential future applications include localization of targets for epilepsy and psychiatric disorders, and incorporation of NIR guidance into probes designed to convey various payloads.

Three hundred patients with Parkinson's disease taking dopamine agonists were surveyed for the presence of compulsions. Fifty-eight reported active compulsions which had developed after initiation of dopamine agonists. These included 25 with sexual compulsions and 28 with self-described compulsive gambling, of whom 17 met criteria for pathologic gambling. Males were over-represented. Patients with any compulsion and those with pathologic gambling were about 6 years younger than those without compulsions. These behavioral problems were not associated with an individual dopamine agonist, nor dose or duration, nor concomitant levodopa. Follow-up of the pathologic gamblers 1 year after intervention, which was cessation of the dopamine agonist in most cases, found ongoing but controlled gambling in five and complete cessation within 4 months in the remainder.

Objective: To determine if future studies of coenzyme Q10 and GPI-1485 in Parkinson disease (PD) may be warranted. Methods: We conducted a randomized, double-blind, calibrated futility clinical trial of coenzyme Q10 and GPI-1485 in early untreated PD using placebo data from the DATATOP study to establish the futility threshold. Results: The primary outcome measure (change in total Unified Parkinson's Disease Rating Scale scores over 1 year) did not meet the prespecified criteria for futility for either agent. Secondary analyses using calibration controls and other more recent placebo data question the appropriateness of the predetermined definition of futility, and suggest that a more restrictive threshold may be needed. Conclusions: Coenzyme Q10 and GPI-1485 may warrant further study in Parkinson disease, although the data are inconsistent. Additional factors (cost, availability of other agents, more recent data on placebo outcomes, other ongoing trials) should also be considered in the selection of agents for Phase III studies. NEUROLOGY 2007;68:20-28

Parkinsondisease (PD) is knowntoaffectmultipleneurotransmitter systems, resulting in both motor and nonmotor symptoms. Pain is an underrecognized but important nonmotor symptom of PD that may be verydisablingandisknownto impair quality of life.1 While significantprogresshasbeenmadeinamelioratingmotorsymptomsusing pharmacological, rehabilitative, and surgical treatments, thetreatmentofpain inthiscontexthasnotreceivedsufficientattention.Aliteraturereview2notedareportedprevalence ofpain inPDof40%to85%,yetonlyabouthalf ofpatientswith PDwhofeltpaintookanalgesics.ClassifyingPD-relatedpaininto its subtypes3 is important for rational treatment, and themost common subtypes of pain in PD are musculoskeletal and dystonic, with central neuropathic pain being the least common.2 Toaddresspainsuccessfully inPD,anunderstandingof itspathogenesis is important, yet this has remained elusive, in part because its causes areprotean. Just as certainmotor symptomsof PD aremore responsive to dopaminergic drugs and deep brain stimulation (DBS), somepainsubtypesmayrespondbetter than others to pharmacological and surgical intervention. Dysfunction of both dopaminergic and nondopaminergic basal ganglia pathwaysare likelytobe involvedinPD-relatedpain,whichmay explainwhysome typesofpain are responsive to levodopaand others are not.4 Deep brain stimulation of the subthalamic nucleus (STN) isnowanestablished treatmentofdisablingmotor symptoms in advanced PD, and it is therefore important to understand its effect on pain associated with PD. Previous reports5,6 on the effects of STNDBSonpain inPDshowthat the levelsofmusculoskeletal anddystonicpaindecreasedwhenassessed1yearafter surgery,but, toourknowledge, there isnoexisting information on the status of chronic pain. In this issue of JAMA Neurology, Jung and colleagues7 investigate the long-termeffect of STNDBSonpain in24patients withPDwhowereobservedfor8yearsafterundergoingtheprocedure for alleviating disabling motor symptoms. The beneficial effectsofSTNDBS in this cohort 3monthsafter surgeryand 24monthsafter surgeryhavebeenpreviouslypublished.8,9The subtypes of painwere classified according to Ford.3 The severity and body distribution of pain were compared between presurgical andpostsurgical states. Jungandcolleagues7notedsignificant improvement at 8 years in all pain types present preoperatively, regardlessofwhether thepreoperativepainwas responsive to levodopa or not.However, newpain, not present before surgery, developed in 75% of patients during prolonged follow-up. Musculoskeletal pain accounted for the majority of newpain cases. Although themean severity of painwas less at 8 years than at baseline,more patients experienced pain at the end of the observation period than preoperatively. Because previous studies on pain following STN DBS for PD are of short duration, the durability of the procedure’s effect on pain is not well established. The chief strength of the work by Jung and colleagues7 is the long follow-up period, which suggests that, althoughDBSmay relievepain for a time, this is not a durable effect owing to the onset of new, primarilymusculoskeletal pain.A recent report5wasconcordantwith the study by Jung and colleagues7 in showing the benefit of DBS on dystonic and musculoskeletal pain but was discordant in showingnoeffect ofDBSoncentral and radicular pain. Methodological differences, the subjective classification of pain, andamuchshorter observationperiod couldaccount for these discrepant findings. The study by Jung and colleagues7 has several limitations that the authors acknowledge, including a small cohort without a control group thatwas treatedmedically, the lack of correlation of pain scores with motor Unified Parkinson’s Disease Rating Scale scores (especially rigidity, which can potentially impact musculoskeletal pain), the lack of measures of disability or effect of pain on quality of life, and the lackofmoodandcognitiveassessments that can influencepain perception. In addition, an analysis of the effect of levodopa onpreoperative pain vs the effect of DBS onpainwas not performed. This would have been of interest in light of a previous report10 suggesting that the effects of DBS on pain can be predicted by measuring the effects of levodopa on pain. Despiteits limitations,thestudybyJungandcolleagues7providesanovelperspectiveon thedurabilityof thepain-relieving properties of STN DBS in PD. The authors direct our attention tothefactthatmusculoskeletalpainmayemergeyearsafterDBS, warranting individualized treatment. The next step is to pursueadeeperunderstandingof themechanismofpain inPD.Previous work11 with small numbers of participants has demonstrated altered pain processing in participants with PD who experienced pain comparedwith those who did not, such that STN DBS raises pain thresholds selectively in those who experiencepain.Althoughthere isagrowingconsensusthatSTNDBS decreases the level of pain in people with PD, the literature is mixed on the subtypes of pain that are responsive to DBS, and the study by Jung and colleagues7 shows that new pain arising years after the procedure is common. This underscores the importance of performing future trialswith larger cohorts, longer observational periods, and standard methods to enable effective interpretation of outcomes. For now,we have learned that STNDBS does not take the ouch out of PD in the long run. Related article page 504 Opinion

To examine the sensitivity and specificity of the Montreal Cognitive Assessment (MoCA), a brief cognitive screening measure previously validated for use in Parkinson's disease (PD), and Alzheimer's Disease-8 (AD8), an eight-item informant report used to screen for dementia, but not yet validated for use in PD, to identify cognitive impairment in a sample of 111 patients with PD.Cognitive impairment was determined based on a battery of neuropsychological measures, excluding the MoCA and AD8. Classification rates of both the MoCA and AD8 in identifying cognitive impairment were examined using logistic regression and receiver operator characteristic (ROC) analysis. Optimal cutoff scores were determined to maximize sensitivity and specificity.The MoCA correctly classified 78.4% of participants (p 0.001), and ROC analysis yielded an area under the curve (AUC) of 0.82. A MoCA cutoff score of25 yielded optimal sensitivity (0.77) and specificity (0.79) for identifying PD patients with cognitive impairment. Similar analyses for the AD8 were statistically nonsignificant, although the classification rate was 70.5%, with an AUC of 0.50.These results provide additional support for the MoCA, but not the AD8, in identifying cognitive impairment in patients with PD.

Neuroprotection for Parkinson's disease (PD) remains elusive. Biomarkers hold the promise of removing roadblocks to therapy development. The National Institute of Neurological Disorders and Stroke has therefore established the Parkinson's Disease Biomarkers Program to promote discovery of PD biomarkers for use in phase II and III clinical trials.Using a novel consortium design, the Parkinson's Disease Biomarker Program is focused on the development of clinical and laboratory-based biomarkers for PD diagnosis, progression, and prognosis. Standardized operating procedures and pooled reference samples were created to allow cross-project comparisons and assessment of batch effects. A web-based Data Management Resource facilitates rapid sharing of data and biosamples across the research community for additional biomarker projects.Eleven consortium projects are ongoing, seven of which recruit participants and obtain biosamples. As of October 2014, 1,082 participants have enrolled (620 PD, 101 with other causes of parkinsonism, 23 essential tremor, and 338 controls), 1,040 of whom have at least one biosample. Six thousand eight hundred ninety-eight total biosamples are available from baseline, 6-, 12-, and 18-month visits: 1,006 DNA, 1,661 RNA, 1,419 whole blood, 1,382 plasma, 1,200 serum, and 230 cerebrospinal fluid (CSF). Quality control analysis of plasma, serum, and CSF samples indicates that almost all samples are high quality (24 of 2,812 samples exceed acceptable hemoglobin levels).By making samples and data widely available, using stringent operating procedures based on existing standards, hypothesis testing for biomarker discovery, and providing a resource that complements existing programs, the Parkinson's Disease Biomarker Program will accelerate the pace of PD biomarker research. © 2015 International Parkinson and Movement Disorder Society.

Elevated homocysteine (Hcy), prevalent in Parkinson's disease (PD), is potentially a modifiable risk factor for neurologic deterioration. We measured cognitive, affective and motor changes over 2 years in a cohort of people with early PD. Subjects whose Hcy had been elevated (>14 μmol/L, n =31) at baseline were compared with the rest ( n =66). Overall progression in 2 years did not significantly differ ( p =0.20). Four subjects with elevated and one with normal Hcy had died ( p =0.03). We conclude that hyperhomocysteinemia does not predict significantly worse progression over 2 years in early PD. The data raised the possibility of higher mortality, but the number of deaths was small.

Background Sex differences in Parkinson disease clinical features have been reported, but few studies have examined sex influences on use of dopaminergic medication in early Parkinson disease. The objective of this study was to test if there are differences in the type of dopaminergic medication used and levodopa equivalent daily dose between men and women with early Parkinson disease enrolled in a large multicenter study of Creatine as a potential disease modifying therapy – the National Institute of Neurological Disorders and Stroke Exploratory Trials in Parkinson Disease Long-Term Study-1. Methods Baseline data of 1,741 participants from 45 participating sites were analyzed. Participants from the United States and Canada were enrolled within five years of Parkinson Disease diagnosis. Two outcome variables were studied: type of dopaminergic medication used and levodopa equivalent daily dose at baseline in the Long-Term Study-1. Chi-square statistic and linear regression models were used for statistical analysis. Results There were no statistically significant differences in the frequency of use of different types of dopaminergic medications at baseline between men and women with Parkinson Disease. A small but statistically significant difference was observed in the median unadjusted levodopa equivalent daily dose at baseline between women (300 mg) and men (325 mg), but this was not observed after controlling for disease duration (years since Parkinson disease diagnosis), disease severity (Unified Parkinson's Disease Rating Scale Motor and Activities of Daily Living Scores), and body weight. Conclusions In this large multicenter study, we did not observe sex differences in the type and dose of dopaminergic medications used in early Parkinson Disease. Further research is needed to evaluate the influence of male or female sex on use of dopaminergic medication in mid- and late-stage Parkinson Disease.