Safety of Deutetrabenazine for the Treatment of Tardive Dyskinesia and Chorea Associated with Huntington Disease.

INTRODUCTION: Deutetrabenazine is a vesicular monoamine transporter 2 inhibitor used to treat tardive dyskinesia (TD) and chorea associated with Huntington disease (HD). To enhance detection of safety signals across individual trials, integrated safety analyses of deutetrabenazine in TD and HD chorea were conducted. METHODS: For TD, safety data were integrated from two 12-week pivotal studies (ARM-TD and AIM-TD) and through week 15 of the open-label extension (OLE) study (RIM-TD). Data were analyzed by deutetrabenazine treatment group and placebo. For HD, safety data were integrated from the 12-week pivotal study (First-HD) and through week 15 of the OLE study (ARC-HD) for patients previously receiving placebo. Integrated deutetrabenazine data were compared with placebo from the pivotal study. RESULTS: For TD, deutetrabenazine (n = 384) was generally well tolerated compared with placebo (n = 130). Adverse event (AE) incidence was numerically higher in the response-driven deutetrabenazine vs the fixed-dose deutetrabenazine and placebo groups, respectively (any AE, 59.5% vs 44.4-50.0% and 53.8%; treatment-related AE, 38.1% vs 18.1-25.0% and 30.8%). Serious AEs were reported for 2.8-8.3% of patients in the deutetrabenazine groups and 6.9% in the placebo group. Common AEs (≥ 4%) included headache, somnolence, nausea, anxiety, fatigue, dry mouth, and diarrhea. AE incidence was higher during the titration vs maintenance periods. For HD, AE incidence was numerically higher with deutetrabenazine (n = 84) vs placebo (n = 45; any AE, 64.3% vs 60.0%; treatment-related AE, 38.1% vs 26.7%); serious AEs were reported for similar proportions for the deutetrabenazine and placebo groups, 2.4% and 2.2%, respectively. Common AEs (≥ 4%) included irritability, fall, depression, dry mouth, and fatigue. CONCLUSIONS: Data from an integrated analysis of studies in TD and an integrated analysis of studies of chorea in HD showed that deutetrabenazine has a favorable safety profile and is well tolerated across indications. TRIAL REGISTRATION: ClinicalTrials.gov identifiers, NCT02291861, NCT02195700, NCT01795859, NCT02198794, NCT01897896.

Unintended movements are often the first sign of Huntington disease. This type of unintended movement is called chorea in Huntington disease. Tardive dyskinesia causes unintended body movements. Deutetrabenazine is a medicine used to treat both types of movements. This report summarizes deutetrabenazine safety across five clinical studies. Safety was assessed via adverse events (side effects). Adverse events were compared between deutetrabenazine and inactive treatment (placebo). Serious adverse events were also compared. Serious adverse events cause substantial impairment or disruption. In tardive dyskinesia and chorea in Huntington disease studies, most patients kept taking deutetrabenazine. Adverse events were not a common reason to stop treatment. For tardive dyskinesia, adverse event rates were similar between deutetrabenazine (≤ 60%) and placebo (54%). Serious adverse event rates were also similar for deutetrabenazine (≤ 8%) and placebo (7%). Adverse events tended to be reported earlier in treatment. Common adverse events were headache, sleepiness, nausea, anxiety, fatigue, dry mouth, and diarrhea. For chorea in Huntington disease, adverse event rates were similar for deutetrabenazine (64%) and placebo (60%). Serious adverse event rates were also similar for deutetrabenazine (2%) and placebo (2%). Irritability, fall, depression, dry mouth, and fatigue were common adverse events. Adverse events were similar between deutetrabenazine and placebo in both conditions. Deutetrabenazine was well tolerated for patients with either tardive dyskinesia or chorea in Huntington disease.

Long-term safety, tolerability and efficacy of apomorphine sublingual film in patients with Parkinson's disease complicated by OFF episodes: a phase 3, open-label study.

BACKGROUND: Apomorphine sublingual film (SL-APO) is an on-demand treatment for OFF episodes in patients with Parkinson's disease (PD). OBJECTIVE: To assess the long-term (≥ 3 years) safety/tolerability and efficacy of SL-APO. METHODS: Study CTH-301 ( http://www. CLINICALTRIALS: gov NCT02542696; registered 2015-09-03) was a phase 3, multicentre, open-label study of SL-APO in PD patients with motor fluctuations, comprised of a dose-titration and long-term safety phase. All participants received SL-APO. The primary endpoint was safety/tolerability (treatment-emergent adverse events [TEAEs]) during the long-term safety phase. Efficacy assessments included the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) part III (motor examination), assessed at weeks 24, 36 and 48 during the first year of the long-term safety phase. RESULTS: 496 patients were included and 120 (24.2%) completed the long-term safety phase. Mean duration of SL-APO exposure was 294.3 days. TEAEs related to study drug were experienced by 65.3% of patients (most common: nausea [6.0%], stomatitis [1.8%], lip swelling [1.8%], dizziness [1.6%], oral mucosal erythema [1.6%], mouth ulceration [1.6%]). TEAEs leading to study drug withdrawal were experienced by 34.0% of patients (most common: nausea [5.4%], lip swelling [4.5%], mouth ulceration [2.6%], stomatitis [2.3%]). A clinically meaningful reduction in MDS-UPDRS part III score was observed as soon as 15 min following administration of SL-APO, with peak effects observed approximately 30 min post-dose and sustained up to 90 min post-dose; results were consistent over 48 weeks. CONCLUSIONS: SL-APO was generally well tolerated and efficacious over the long term as an on-demand treatment for OFF episodes in patients with PD.

Preclinical Evaluation of Novel Positron Emission Tomography (PET) Probes for Imaging Leucine-Rich Repeat Kinase 2 (LRRK2).

Parkinson's disease (PD) is one of the most highly debilitating neurodegenerative disorders, which affects millions of people worldwide, and leucine-rich repeat kinase 2 (LRRK2) mutations have been involved in the pathogenesis of PD. Developing a potent LRRK2 positron emission tomography (PET) tracer would allow for in vivo visualization of LRRK2 distribution and expression in PD patients. In this work, we present the facile synthesis of two potent and selective LRRK2 radioligands [11C]3 ([11C]PF-06447475) and [18F]4 ([18F]PF-06455943). Both radioligands exhibited favorable brain uptake and specific bindings in rodent autoradiography and PET imaging studies. More importantly, [18F]4 demonstrated significantly higher brain uptake in the transgenic LRRK2-G2019S mutant and lipopolysaccharide (LPS)-injected mouse models. This work may serve as a roadmap for the future design of potent LRRK2 PET tracers.

Impact of deep brain stimulation on gait in Parkinson disease: A kinematic study.

BACKGROUND: The effect of Deep Brain Stimulation (DBS) on gait in Parkinson's Disease (PD) is poorly understood. Kinematic studies utilizing quantitative gait outcomes such as speed, cadence, and stride length have shown mixed results and were done mostly before and after acute DBS discontinuation. OBJECTIVE: To examine longitudinal changes in kinematic gait outcomes before and after DBS surgery. METHOD: We retrospectively assessed changes in quantitative gait outcomes via motion capture in 22 PD patients before and after subthalamic (STN) or globus pallidus internus (GPi) DBS, in on medication state. Associations between gait outcomes and clinical variables were also assessed. RESULT: Gait speed reduced from 110.7 ± 21.3 cm/s before surgery to 93.6 ± 24.9 after surgery (7.7 ± 2.9 months post-surgery, duration between assessments was 15.0 ± 3.8 months). Cadence, step length, stride length, and single support time reduced, while total support time, and initial double support time increased. Despite this, there was overall improvement in the Movement Disorder Society-Unified Parkinson Disease Rating Scale-Part III score "on medication/on stimulation" score (from 19.8 ± 10.7-13.9 ± 8.6). Change of gait speed was not related to changes in levodopa dosage, disease duration, unilateral vs bilateral stimulation, or target nucleus. CONCLUSION: Quantitative gait outcomes in on medication state worsened after chronic DBS therapy despite improvement in other clinical outcomes. Whether these changes reflect the effects of DBS as opposed to ongoing disease progression is unknown.

Classifying Tremor Dominant and Postural Instability and Gait Difficulty Subtypes of Parkinson's Disease from Full-Body Kinematics.

Characterizing motor subtypes of Parkinson's disease (PD) is an important aspect of clinical care that is useful for prognosis and medical management. Although all PD cases involve the loss of dopaminergic neurons in the brain, individual cases may present with different combinations of motor signs, which may indicate differences in underlying pathology and potential response to treatment. However, the conventional method for distinguishing PD motor subtypes involves resource-intensive physical examination by a movement disorders specialist. Moreover, the standardized rating scales for PD rely on subjective observation, which requires specialized training and unavoidable inter-rater variability. In this work, we propose a system that uses machine learning models to automatically and objectively identify some PD motor subtypes, specifically Tremor-Dominant (TD) and Postural Instability and Gait Difficulty (PIGD), from 3D kinematic data recorded during walking tasks for patients with PD (MDS-UPDRS-III Score, 34.7 ± 10.5, average disease duration 7.5 ± 4.5 years). This study demonstrates a machine learning model utilizing kinematic data that identifies PD motor subtypes with a 79.6% F1 score (N = 55 patients with parkinsonism). This significantly outperformed a comparison model using classification based on gait features (19.8% F1 score). Variants of our model trained to individual patients achieved a 95.4% F1 score. This analysis revealed that both temporal, spectral, and statistical features from lower body movements are helpful in distinguishing motor subtypes. Automatically assessing PD motor subtypes simply from walking may reduce the time and resources required from specialists, thereby improving patient care for PD treatments. Furthermore, this system can provide objective assessments to track the changes in PD motor subtypes over time to implement and modify appropriate treatment plans for individual patients as needed.

Assessing the Severity of Cervical Dystonia: Ask the Doctor or Ask the Patient?

Background: Assessing disease severity can be performed using either clinician-rated scales (CRS) or patient-rated outcome (PRO) tools. These two measures frequently demonstrate poor correlations. Objectives: To determine if the correlation between a CRS and PRO for motor features of cervical dystonia (CD) improves by accounting for non-motor features. Methods: Subjects with CD (N = 209) were evaluated using a CRS (Toronto Western Spasmodic Torticollis Rating Scale, TWSTRS) and a PRO (Cervical Dystonia Impact Profile, CDIP-58). Results: Linear regression revealed a weak correlation between the two measures, even when considering only the motor subscales of each. The strength of this relationship improved with a regression model that included non-motor symptoms of pain, depression, and disability. Conclusions: These results argue that the results of motor assessments in a PRO for CD cannot be fully appreciated without simultaneous assessment of non-motor co-morbidities. This conclusion might apply to other disorders, especially those with frequent non-motor co-morbidities.

Gait Declines Differentially in, and Improves Prediction of, People with Parkinson's Disease Converting to a Freezing of Gait Phenotype.

BACKGROUND: Freezing of gait (FOG) is a debilitating, variably expressed motor symptom in people with Parkinson's disease (PwPD) with limited treatments. OBJECTIVE: To determine if the rate of progression in spatiotemporal gait parameters in people converting from a noFOG to a FOG phenotype (FOGConv) was faster than non-convertors, and determine if gait parameters can help predict this conversion. METHODS: PwPD were objectively monitored longitudinally, approximately every 6 months. Non-motor assessments were performed at the initial visit. Steady-state gait in the levodopa ON-state was collected using a gait mat (Protokinetics) at each visit. The rate of progression in 8 spatiotemporal gait parameters was calculated. FOG convertors (FOGConv) were classified if they did not have FOG at initial visit and developed FOG at a subsequent visit. RESULTS: Thirty freezers (FOG) and 30 non-freezers were monitored an average of 3.5 years, with 10 non-freezers developing FOG (FOGConv). FOGConv and FOG had faster decline in mean stride-length, swing-phase-percent, and increase in mean total-double-support percent, coefficient of variability (CV) foot-strike-length and CV swing-phase-percent than the remaining non-freezers (noFOG). On univariate modeling, progression rates of mean stride-length, stride-velocity, swing-phase-percent, total-double-support-percent and of CV swing-phase-percent had high discriminative power (AUC > 0.83) for classification of the FOGConv and noFOG groups. CONCLUSION: FOGConv had a faster temporal decline in objectively quantified gait than noFOG, and progression rates of spatiotemporal gait parameters were more predictive of FOG phenotype conversion than initial (static) parameters Objectively monitoring gait in disease prediction models may help define FOG prone groups for testing putative treatments.

Neuromelanin-sensitive MRI correlates of cognitive and motor function in Parkinson's disease with freezing of gait.

Substantia nigra pars compacta (SNc) and locus coeruleus (LC) are neuromelanin-rich nuclei implicated in diverse cognitive and motor processes in normal brain function and disease. However, their roles in aging and neurodegenerative disease mechanisms have remained unclear due to a lack of tools to study them in vivo. Preclinical and post-mortem human investigations indicate that the relationship between tissue neuromelanin content and neurodegeneration is complex. Neuromelanin exhibits both neuroprotective and cytotoxic characteristics, and tissue neuromelanin content varies across the lifespan, exhibiting an inverted U-shaped relationship with age. Neuromelanin-sensitive MRI (NM-MRI) is an emerging modality that allows measurement of neuromelanin-associated contrast in SNc and LC in humans. NM-MRI robustly detects disease effects in these structures in neurodegenerative and psychiatric conditions, including Parkinson's disease (PD). Previous NM-MRI studies of PD have largely focused on detecting disease group effects, but few studies have reported NM-MRI correlations with phenotype. Because neuromelanin dynamics are complex, we hypothesize that they are best interpreted in the context of both disease stage and aging, with neuromelanin loss correlating with symptoms most clearly in advanced stages where neuromelanin loss and neurodegeneration are coupled. We tested this hypothesis using NM-MRI to measure SNc and LC volumes in healthy older adult control individuals and in PD patients with and without freezing of gait (FOG), a severe and disabling PD symptom. We assessed for group differences and correlations between NM-MRI measures and aging, cognition and motor deficits. SNc volume was significantly decreased in PD with FOG compared to controls. SNc volume correlated significantly with motor symptoms and cognitive measures in PD with FOG, but not in PD without FOG. SNc volume correlated significantly with aging in PD. When PD patients were stratified by disease duration, SNc volume correlated with aging, cognition, and motor deficits only in PD with disease duration >5 years. We conclude that in severe or advanced PD, identified by either FOG or disease duration >5 years, the observed correlations between SNc volume and aging, cognition, and motor function may reflect the coupling of neuromelanin loss with neurodegeneration and the associated emergence of a linear relationship between NM-MRI measures and phenotype.

Physiological measures and anatomical correlates of subthalamic deep brain stimulation effect on gait in Parkinson's disease.

We examined whether conflicting visual and non-visual information leads to gait abnormalities and how the subthalamic deep brain stimulation (STN DBS) influences gait dysfunction in Parkinson's disease (PD). We used a motion capture system to measure the kinematics of the lower limbs during treadmill walking in immersive virtual reality. The visual information provided in the virtual reality paradigm was modulated to create a mismatch between the optic-flow velocity of the visual scene and the walking speed on the treadmill. In each mismatched condition, we calculated the step duration, step length, step phase, step height, and asymmetries. The key finding of our study was that mismatch between treadmill walking speed and the optic-flow velocity did not consistently alter gait parameters in PD. We also found that STN DBS improved the PD gait pattern by changing the stride length and step height. The effects on phase and left/right asymmetry were not statistically significant. The DBS parameters and location also determined its effects on gait. Statistical effects on stride length and step height were noted when the DBS volume of activated tissue (VTA) was in the dorsal aspect of the subthalamus. The statistically significant effects of STN DBS was present when VTA significantly overlapped with MR tractogrphically measured motor and pre-motor hyperdirect pathways. In summary, our results provide novel insight into ways for controlling walking behavior in PD using STN DBS.

Scales for Antipsychotic-Associated Movement Disorders: Systematic Review, Critique, and Recommendations.

BACKGROUND: Antipsychotic-associated movement disorders remain common and disabling. Their screening and assessment are challenging due to clinical heterogeneity and different use of nomenclature between psychiatrists and neurologists. OBJECTIVE: An International Parkinson and Movement Disorder Society subcommittee aimed to rate psychometric quality of severity and screening instruments for antipsychotic-associated movement disorders. METHODS: Following the methodology adopted by previous International Parkinson and Movement Disorders Society subcommittee papers, instruments for antipsychotic-associated movement disorders were reviewed, applying a classification as "recommended," "recommended with caveats," "suggested," or "listed." RESULTS: Our review identified 23 instruments. The highest grade of recommendation reached is "recommended with caveats," assigned to seven severity rating instruments (Extrapyramidal Symptoms Rating Scale, Barnes Akathisia Rating Scale, Abnormal Involuntary Movements Scale, Drug-Induced Extra-Pyramidal Symptoms Scale, Maryland Psychiatric Research Centre involuntary movements scale, Simpson Angus Scale, and Matson Evaluation of Drug Side effects). Only three of these seven (Drug-Induced Extra-Pyramidal Symptoms Scale, Maryland Psychiatric Research Centre, Matson Evaluation of Drug Side effects) were also screening instruments. Their main caveats are insufficient demonstration of psychometric properties (internal consistency, skewing, responsiveness to change) and long duration of administration. Eight "suggested" instruments did not meet requirements for the "recommended" grade also because of insufficient psychometric validation. Other limitations shared by several instruments are lack of comprehensiveness in assessing the spectrum of antipsychotic-associated movement disorders and ambiguous nomenclature. CONCLUSIONS: The high number of instruments "recommended with caveats" does not support the need for developing new instruments for antipsychotic-associated movement disorders. However, addressing the caveats with new psychometric studies and revising existing instruments to improve the clarity of their nomenclature are recommended next steps. © 2023 International Parkinson and Movement Disorder Society.

Patients with Cognitive Impairment in Parkinson's Disease Benefit from Deep Brain Stimulation: A Case-Control Study.

Background: Deep brain stimulation (DBS) for Parkinson's disease (PD) is generally contraindicated in persons with dementia but it is frequently performed in people with mild cognitive impairment or normal cognition, and current clinical guidelines are primarily based on these cohorts. Objectives: To determine if moderately cognitive impaired individuals including those with mild dementia could meaningfully benefit from DBS in terms of motor and non-motor outcomes. Methods: In this retrospective case-control study, we identified a cohort of 40 patients with PD who exhibited moderate (two or more standard deviations below normative scores) cognitive impairment (CI) during presurgical workup and compared their 1-year clinical outcomes to a cohort of 40 matched patients with normal cognition (NC). The surgery targeted subthalamus, pallidus or motor thalamus, in a unilateral, bilateral or staged approach. Results: At preoperative baseline, the CI cohort had higher Unified Parkinson's Disease Rating Scale (UPDRS) subscores, but similar levodopa responsiveness compared to the NC cohort. The NC and CI cohorts demonstrated comparable degrees of postoperative improvement in the OFF-medication motor scores, motor fluctuations, and medication reduction. There was no difference in adverse event rates between the two cohorts. Outcomes in the CI cohort did not depend on the target, surgical staging, or impaired cognitive domain. Conclusions: Moderately cognitively impaired patients with PD can experience meaningful motor benefit and medication reduction with DBS.

Levodopa responsive freezing of gait is associated with reduced norepinephrine transporter binding in Parkinson's disease.

BACKGROUND: Freezing of gait (FOG) is a major cause of falling in Parkinson's disease (PD) and can be responsive or unresponsive to levodopa. Pathophysiology is poorly understood. OBJECTIVE: To examine the link between noradrenergic systems, the development of FOG in PD and its responsiveness to levodopa. METHODS: We examined norepinephrine transporter (NET) binding via brain positron emission tomography (PET) to evaluate changes in NET density associated with FOG using the high affinity selective NET antagonist radioligand [11C]MeNER (2S,3S)(2-[α-(2-methoxyphenoxy)benzyl]morpholine) in 52 parkinsonian patients. We used a rigorous levodopa challenge paradigm to characterize PD patients as non-freezing (NO-FOG, N = 16), levodopa responsive freezing (OFF-FOG, N = 10), and levodopa-unresponsive freezing (ONOFF-FOG, N = 21), and also included a non-PD FOG group, primary progressive freezing of gait (PP-FOG, N = 5). RESULTS: Linear mixed models identified significant reductions in whole brain NET binding in the OFF-FOG group compared to the NO-FOG group (-16.8%, P = 0.021) and regionally in the frontal lobe, left and right thalamus, temporal lobe, and locus coeruleus, with the strongest effect in right thalamus (P = 0.038). Additional regions examined in a post hoc secondary analysis including the left and right amygdalae confirmed the contrast between OFF-FOG and NO-FOG (P = 0.003). A linear regression analysis identified an association between reduced NET binding in the right thalamus and more severe New FOG Questionnaire (N-FOG-Q) score only in the OFF-FOG group (P = 0.022). CONCLUSION: This is the first study to examine brain noradrenergic innervation using NET-PET in PD patients with and without FOG. Based on the normal regional distribution of noradrenergic innervation and pathological studies in the thalamus of PD patients, the implications of our findings suggest that noradrenergic limbic pathways may play a key role in OFF-FOG in PD. This finding could have implications for clinical subtyping of FOG as well as development of therapies.

An Explainable Spatial-Temporal Graphical Convolutional Network to Score Freezing of Gait in Parkinsonian Patients.

Freezing of gait (FOG) is a poorly understood heterogeneous gait disorder seen in patients with parkinsonism which contributes to significant morbidity and social isolation. FOG is currently measured with scales that are typically performed by movement disorders specialists (i.e., MDS-UPDRS), or through patient completed questionnaires (N-FOG-Q) both of which are inadequate in addressing the heterogeneous nature of the disorder and are unsuitable for use in clinical trials The purpose of this study was to devise a method to measure FOG objectively, hence improving our ability to identify it and accurately evaluate new therapies. A major innovation of our study is that it is the first study of its kind that uses the largest sample size (>30 h, N = 57) in order to apply explainable, multi-task deep learning models for quantifying FOG over the course of the medication cycle and at varying levels of parkinsonism severity. We trained interpretable deep learning models with multi-task learning to simultaneously score FOG (cross-validated F1 score 97.6%), identify medication state (OFF vs. ON levodopa; cross-validated F1 score 96.8%), and measure total PD severity (MDS-UPDRS-III score prediction error ≤ 2.7 points) using kinematic data of a well-characterized sample of N = 57 patients during levodopa challenge tests. The proposed model was able to explain how kinematic movements are associated with each FOG severity level that were highly consistent with the features, in which movement disorders specialists are trained to identify as characteristics of freezing. Overall, we demonstrate that deep learning models' capability to capture complex movement patterns in kinematic data can automatically and objectively score FOG with high accuracy. These models have the potential to discover novel kinematic biomarkers for FOG that can be used for hypothesis generation and potentially as clinical trial outcome measures.

An explainable spatial-temporal graphical convolutional network to score freezing of gait in parkinsonian patients.

Freezing of gait (FOG) is a poorly understood heterogeneous gait disorder seen in patients with parkinsonism which contributes to significant morbidity and social isolation. FOG is currently measured with scales that are typically performed by movement disorders specialists (ie. MDS-UPDRS), or through patient completed questionnaires (N-FOG-Q) both of which are inadequate in addressing the heterogeneous nature of the disorder and are unsuitable for use in clinical trials The purpose of this study was to devise a method to measure FOG objectively, hence improving our ability to identify it and accurately evaluate new therapies. We trained interpretable deep learning models with multi-task learning to simultaneously score FOG (cross-validated F1 score 97.6%), identify medication state (OFF vs. ON levodopa; cross-validated F1 score 96.8%), and measure total PD severity (MDS-UPDRS-III score prediction error ≤ 2.7 points) using kinematic data of a well-characterized sample of N=57 patients during levodopa challenge tests. The proposed model was able to identify kinematic features associated with each FOG severity level that were highly consistent with the features that movement disorders specialists are trained to identify as characteristic of freezing. In this work, we demonstrate that deep learning models' capability to capture complex movement patterns in kinematic data can automatically and objectively score FOG with high accuracy. These models have the potential to discover novel kinematic biomarkers for FOG that can be used for hypothesis generation and potentially as clinical trial outcome measures.

Clinical Features and Evolution of Blepharospasm: A Multicenter International Cohort and Systematic Literature Review.

Objective: Blepharospasm is a type of dystonia where the diagnosis is often delayed because its varied clinical manifestations are not well recognized. The purpose of this study was to provide a comprehensive picture of its clinical features including presenting features, motor features, and non-motor features. Methods: This was a two-part study. The first part involved a systematic literature review that summarized clinical features for 10,324 cases taken from 41 prior reports. The second part involved a summary of clinical features for 884 cases enrolled in a large multicenter cohort collected by the Dystonia Coalition investigators, along with an analysis of the factors that contribute to the spread of dystonia beyond the periocular region. Results: For cases in the literature and the Dystonia Coalition, blepharospasm emerged in the 50s and was more frequent in women. Many presented with non-specific motor symptoms such as increased blinking (51.9%) or non-motor sensory features such as eye soreness or pain (38.7%), photophobia (35.5%), or dry eyes (10.7%). Non-motor psychiatric features were also common including anxiety disorders (34-40%) and depression (21-24%). Among cases presenting with blepharospasm in the Dystonia Coalition cohort, 61% experienced spread of dystonia to other regions, most commonly the oromandibular region and neck. Features associated with spread included severity of blepharospasm, family history of dystonia, depression, and anxiety. Conclusions: This study provides a comprehensive summary of motor and non-motor features of blepharospasm, along with novel insights into factors that may be responsible for its poor diagnostic recognition and natural history.

Stepping up to meet the challenge of freezing of gait in Parkinson's disease.

There has been a growing appreciation for freezing of gait as a disabling symptom that causes a significant burden in Parkinson's disease. Previous research has highlighted some of the key components that underlie the phenomenon, but these reductionist approaches have yet to lead to a paradigm shift resulting in the development of novel treatment strategies. Addressing this issue will require greater integration of multi-modal data with complex computational modeling, but there are a number of critical aspects that need to be considered before embarking on such an approach. This paper highlights where the field needs to address current gaps and shortcomings including the standardization of definitions and measurement, phenomenology and pathophysiology, as well as considering what available data exist and how future studies should be constructed to achieve the greatest potential to better understand and treat this devastating symptom.

Hold that pose: capturing cervical dystonia's head deviation severity from video.

OBJECTIVE: Deviated head posture is a defining characteristic of cervical dystonia (CD). Head posture severity is typically quantified with clinical rating scales such as the Toronto Western Spasmodic Torticollis Rating Scale (TWSTRS). Because clinical rating scales are inherently subjective, they are susceptible to variability that reduces their sensitivity as outcome measures. The variability could be circumvented with methods to measure CD head posture objectively. However, previously used objective methods require specialized equipment and have been limited to studies with a small number of cases. The objective of this study was to evaluate a novel software system-the Computational Motor Objective Rater (CMOR)-to quantify multi-axis directionality and severity of head posture in CD using only conventional video camera recordings. METHODS: CMOR is based on computer vision and machine learning technology that captures 3D head angle from video. We used CMOR to quantify the axial patterns and severity of predominant head posture in a retrospective, cross-sectional study of 185 patients with isolated CD recruited from 10 sites in the Dystonia Coalition. RESULTS: The predominant head posture involved more than one axis in 80.5% of patients and all three axes in 44.4%. CMOR's metrics for head posture severity correlated with severity ratings from movement disorders neurologists using both the TWSTRS-2 and an adapted version of the Global Dystonia Rating Scale (rho = 0.59-0.68, all p <0.001). CONCLUSIONS: CMOR's convergent validity with clinical rating scales and reliance upon only conventional video recordings supports its future potential for large scale multisite clinical trials.

Restless Legs Symptoms and Periodic Leg Movements in Sleep Among Patients with Parkinson's Disease.

BACKGROUND: The association between restless legs syndrome (RLS) and Parkinson's disease (PD) remains controversial, with epidemiologic and descriptive evidence suggesting some potential overlap while mechanistic/genetic studies suggesting relative independence of the conditions. OBJECTIVE: To examine a known, objectively measured endophenotype for RLS, periodic leg movements (PLMS) in sleep, in patients with PD and relate that objective finding to restless legs symptoms. METHODS: We performed polysomnography for one (n = 8) or two (n = 67) consecutive nights in 75 PD patients and examined the association of PLMS with restless legs symptoms. RESULTS: We found no association between restless legs symptoms and PLMS in PD. Prevalence of both was similar to data reported previously in other PD samples. CONCLUSION: We interpret these results as suggesting that restless legs symptoms in PD patients may represent a different phenomenon and pathophysiology than RLS in the non-PD population.