The future of stem cell therapies for Parkinson disease.

Cell-replacement therapies have long been an attractive prospect for treating Parkinson disease. However, the outcomes of fetal tissue-derived cell transplants in individuals with Parkinson disease have been variable, in part owing to the limitations of fetal tissue as a cell source, relating to its availability and the lack of possibility for standardization and to variation in methods. Advances in developmental and stem cell biology have allowed the development of cell-replacement therapies that comprise dopamine neurons derived from human pluripotent stem cells, which have several advantages over fetal cell-derived therapies. In this Review, we critically assess the potential trajectory of this line of translational and clinical research and address its possibilities and current limitations and the broader range of Parkinson disease features that dopamine cell replacement based on generating neurons from human pluripotent stem cells could effectively treat in the future.

Personalized iPSC-Derived Dopamine Progenitor Cells for Parkinson's Disease.

We report the implantation of patient-derived midbrain dopaminergic progenitor cells, differentiated in vitro from autologous induced pluripotent stem cells (iPSCs), in a patient with idiopathic Parkinson's disease. The patient-specific progenitor cells were produced under Good Manufacturing Practice conditions and characterized as having the phenotypic properties of substantia nigra pars compacta neurons; testing in a humanized mouse model (involving peripheral-blood mononuclear cells) indicated an absence of immunogenicity to these cells. The cells were implanted into the putamen (left hemisphere followed by right hemisphere, 6 months apart) of a patient with Parkinson's disease, without the need for immunosuppression. Positron-emission tomography with the use of fluorine-18-L-dihydroxyphenylalanine suggested graft survival. Clinical measures of symptoms of Parkinson's disease after surgery stabilized or improved at 18 to 24 months after implantation. (Funded by the National Institutes of Health and others.).

Baseline Differences in Long-term Survivors and Nonsurvivors of the Colorado/Columbia Fetal Implant Trial.

OBJECTIVE: This study is based on long-term follow-up of participants in a randomized double-blind sham surgery-controlled trial (1995-1999) designed to determine the effectiveness of implantation of human embryonic mesencephalic tissue containing dopamine neuron precursors into the brains of patients with advanced Parkinson's disease (PD). We investigated differences between long-term survivors and nonsurvivors at baseline in order to contribute to information regarding optimal patient selection for upcoming stem cell trials. METHOD: Forty participants were randomly assigned to receive either neural implantation or sham surgery. Thirty-four patients who ultimately received the implant were followed periodically with the most recent assessment occurring in 2015-2016. Demographic information, neurological measures, positron emission tomography (PET) imaging, neuropsychological assessments, and a personality assessment were included in the current analyses. T-tests were used to compare survivors and nonsurvivors. Logistic regression analyses examined predictors of survivorship. RESULTS: Five of six survivors were female. They were younger than nonsurvivors (p = .03) and more neuropsychologically "intact" across a broad range of cognitive areas (significance levels ranged from <.001 to .045). There were no differences between survivors and nonsurvivors off medications at baseline on neurological or PET assessments. Survivors reported more "Openness to Experience" (p = .004) than nonsurvivors. Using empirically derived predictor variables, results of logistic regression analyses indicated that Animal Naming (cognitive task) and Openness to Experience (personality variable) were the strongest predictors of survivorship. CONCLUSIONS: Variables to consider when selecting participants for future cell-based therapies include being "intact" neuropsychologically, level of Openness to Experience, younger age, and inclusion of women.

A machine learning and network framework to discover new indications for small molecules.

Drug repurposing, identifying novel indications for drugs, bypasses common drug development pitfalls to ultimately deliver therapies to patients faster. However, most repurposing discoveries have been led by anecdotal observations (e.g. Viagra) or experimental-based repurposing screens, which are costly, time-consuming, and imprecise. Recently, more systematic computational approaches have been proposed, however these rely on utilizing the information from the diseases a drug is already approved to treat. This inherently limits the algorithms, making them unusable for investigational molecules. Here, we present a computational approach to drug repurposing, CATNIP, that requires only biological and chemical information of a molecule. CATNIP is trained with 2,576 diverse small molecules and uses 16 different drug similarity features, such as structural, target, or pathway based similarity. This model obtains significant predictive power (AUC = 0.841). Using our model, we created a repurposing network to identify broad scale repurposing opportunities between drug types. By exploiting this network, we identified literature-supported repurposing candidates, such as the use of systemic hormonal preparations for the treatment of respiratory illnesses. Furthermore, we demonstrated that we can use our approach to identify novel uses for defined drug classes. We found that adrenergic uptake inhibitors, specifically amitriptyline and trimipramine, could be potential therapies for Parkinson's disease. Additionally, using CATNIP, we predicted the kinase inhibitor, vandetanib, as a possible treatment for Type 2 Diabetes. Overall, this systematic approach to drug repurposing lays the groundwork to streamline future drug development efforts.

Effect of Urate-Elevating Inosine on Early Parkinson Disease Progression: The SURE-PD3 Randomized Clinical Trial.

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 (<5.8 mg/dL) were randomized between August 2016 and December 2017 at 58 US sites, and were followed up through June 2019. Interventions: Inosine, dosed by blinded titration to increase serum urate concentrations to 7.1-8.0 mg/dL (n = 149) or matching placebo (n = 149) for up to 2 years. Main Outcomes and Measures: The primary outcome was rate of change in the Movement Disorder Society Unified Parkinson Disease Rating Scale (MDS-UPDRS; parts I-III) total score (range, 0-236; higher scores indicate greater disability; minimum clinically important difference of 6.3 points) prior to dopaminergic drug therapy initiation. Secondary outcomes included serum urate to measure target engagement, adverse events to measure safety, and 29 efficacy measures of disability, quality of life, cognition, mood, autonomic function, and striatal dopamine transporter binding as a biomarker of neuronal integrity. Results: Based on a prespecified interim futility analysis, the study closed early, with 273 (92%) of the randomized participants (49% women; mean age, 63 years) completing the study. Clinical progression rates were not significantly different between participants randomized to inosine (MDS-UPDRS score, 11.1 [95% CI, 9.7-12.6] points per year) and placebo (MDS-UPDRS score, 9.9 [95% CI, 8.4-11.3] points per year; difference, 1.26 [95% CI, -0.59 to 3.11] points per year; P = .18). Sustained elevation of serum urate by 2.03 mg/dL (from a baseline level of 4.6 mg/dL; 44% increase) occurred in the inosine group vs a 0.01-mg/dL change in serum urate in the placebo group (difference, 2.02 mg/dL [95% CI, 1.85-2.19 mg/dL]; P<.001). There were no significant differences for secondary efficacy outcomes including dopamine transporter binding loss. Participants randomized to inosine, compared with placebo, experienced fewer serious adverse events (7.4 vs 13.1 per 100 patient-years) but more kidney stones (7.0 vs 1.4 stones per 100 patient-years). Conclusions and Relevance: Among patients recently diagnosed as having PD, treatment with inosine, compared with placebo, did not result in a significant difference in the rate of clinical disease progression. The findings do not support the use of inosine as a treatment for early PD. Trial Registration: ClinicalTrials.gov Identifier: NCT02642393.

Cerebrospinal fluid, plasma, and saliva in the BioFIND study: Relationships among biomarkers and Parkinson's disease Features.

OBJECTIVE: Examine relationships among neurodegenerative biomarkers and PD motor and nonmotor symptoms. BACKGROUND: CSF alpha-synuclein is decreased in PD versus healthy controls, but whether plasma and saliva alpha-synuclein differentiate these groups is controversial. Correlations of alpha-synuclein among biofluids (CSF, plasma, saliva) or biomarkers (eg, beta-amyloid, tau [total, phosphorylated]) are not fully understood. The relationships of these biomarkers with PD clinical features remain unclear. METHODS: BioFIND, a cross-sectional, observational study, examines clinical and biomarker characteristics in moderate-advanced PD and matched healthy controls. We compared alpha-synuclein concentrations across diagnosis, biofluids, and CSF biomarkers. Correlations of CSF biomarkers and MDS-UPDRS, motor phenotype, MoCA, and rapid eye movement sleep behavior disorder questionnaire scores in PD were examined. RESULTS: CSF alpha-synuclein was lower in PD versus controls (P = .01), controlling for age, gender, and education. Plasma and saliva alpha-synuclein did not differ between PD and controls, and alpha-synuclein did not significantly correlate among biofluids. CSF beta-amyloid1-42 was lower in PD versus controls (P < .01), and correlated weakly with MoCA recall scores (r = 0.23, P = .02). CSF alpha-synuclein was lower in the postural instability/gait difficulty phenotype than other motor phenotypes (P < .01). No CSF biomarkers predicted or correlated with total motor or rapid eye movement sleep behavior disorder scores. CSF alpha-synuclein correlated with beta-amyloid1-42 , total-tau, and phosphorylated-tau (r = 0.41, 0.81, 0.43, respectively; Ps < .001). CONCLUSION: Lower CSF alpha-synuclein is associated with diagnosis and motor phenotype in moderate-advanced PD. Plasma and saliva alpha-synuclein neither correlate with CSF alpha-synuclein, nor distinguish PD from controls. CSF beta-amyloid1-42 remains a potential biomarker for cognitive impairment in PD. © 2017 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

The BioFIND study: Characteristics of a clinically typical Parkinson's disease biomarker cohort.

BACKGROUND: Identifying PD-specific biomarkers in biofluids will greatly aid in diagnosis, monitoring progression, and therapeutic interventions. PD biomarkers have been limited by poor discriminatory power, partly driven by heterogeneity of the disease, variability of collection protocols, and focus on de novo, unmedicated patients. Thus, a platform for biomarker discovery and validation in well-characterized, clinically typical, moderate to advanced PD cohorts is critically needed. METHODS: BioFIND (Fox Investigation for New Discovery of Biomarkers in Parkinson's Disease) is a cross-sectional, multicenter biomarker study that established a repository of clinical data, blood, DNA, RNA, CSF, saliva, and urine samples from 118 moderate to advanced PD and 88 healthy control subjects. Inclusion criteria were designed to maximize diagnostic specificity by selecting participants with clinically typical PD symptoms, and clinical data and biospecimen collection utilized standardized procedures to minimize variability across sites. RESULTS: We present the study methodology and data on the cohort's clinical characteristics. Motor scores and biospecimen samples including plasma are available for practically defined off and on states and thus enable testing the effects of PD medications on biomarkers. Other biospecimens are available from off state PD assessments and from controls. CONCLUSION: Our cohort provides a valuable resource for biomarker discovery and validation in PD. Clinical data and biospecimens, available through The Michael J. Fox Foundation for Parkinson's Research and the National Institute of Neurological Disorders and Stroke, can serve as a platform for discovering biomarkers in clinically typical PD and comparisons across PD's broad and heterogeneous spectrum. © 2016 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Dance for PD: a preliminary investigation of effects on motor function and quality of life among persons with Parkinson's disease (PD).

In 2001, Dance for Parkinson's disease (DfPD(®)) classes for persons with Parkinson's disease and care partners were developed by Brooklyn Parkinson Group and Mark Morris Dance Group. A previous assessment suggested that individuals experience positive benefits from DfPD(®). The current preliminary uncontrolled study investigated the effects of a dance intervention on several motor and quality of life aspects of PD following 16 sessions (8 weeks; 20 h) taught by professional dancers/teachers. A mixed methods design was used to determine the effects of the class. Assessment instruments administered at baseline and post-intervention included the Hoehn and Yahr, UPDRS (part III), Berg Balance Scale, Beck Depression Inventory, and PDQ-39 and individual interviews after the last class. Hoehn and Yahr scores ranged from 1 to 4. UPDRS III total scores and sub scores of gait and tremor improved following the intervention (P < 0.05). During interviews participants reported physical, emotional, and social benefits. Despite the diversity of baseline measures post-class interview results were consistently positive across the sample. Twelve of 14 subjects (mean age 66.2) with idiopathic PD completed the sessions. After 4 years, four participants regularly attended DfPD(®) classes. The low attrition rate and continued attendance suggest notable adherence to the DfPD(®) class. The importance of the results is both clinical and conceptual, highlighting the value of using both quantitative and qualitative data to evaluate the benefits of dance with PD.

Learning Phenotypic Associations for Parkinson's Disease with Longitudinal Clinical Records.

Parkinson's disease (PD) is associated with multiple clinical motor and non-motor manifestations. Understanding of PD etiologies has been informed by a growing number of genetic mutations and various fluid-based and brain imaging biomarkers. However, the mechanisms underlying its varied phenotypic features remain elusive. The present work introduces a data-driven approach for generating phenotypic association graphs for PD cohorts. Data collected by the Parkinson's Progression Markers Initiative (PPMI), the Parkinson's Disease Biomarkers Program (PDBP), and the Fox Investigation for New Discovery of Biomarkers (BioFIND) were analyzed by this approach to identify heterogeneous and longitudinal phenotypic associations that may provide insight into the pathology of this complex disease. Findings based on the phenotypic association graphs could improve understanding of longitudinal PD pathologies and how these relate to patient symptomology.

Identification of Parkinson's disease PACE subtypes and repurposing treatments through integrative analyses of multimodal data.

Parkinson's disease (PD) is a serious neurodegenerative disorder marked by significant clinical and progression heterogeneity. This study aimed at addressing heterogeneity of PD through integrative analysis of various data modalities. We analyzed clinical progression data (≥5 years) of individuals with de novo PD using machine learning and deep learning, to characterize individuals' phenotypic progression trajectories for PD subtyping. We discovered three pace subtypes of PD exhibiting distinct progression patterns: the Inching Pace subtype (PD-I) with mild baseline severity and mild progression speed; the Moderate Pace subtype (PD-M) with mild baseline severity but advancing at a moderate progression rate; and the Rapid Pace subtype (PD-R) with the most rapid symptom progression rate. We found cerebrospinal fluid P-tau/α-synuclein ratio and atrophy in certain brain regions as potential markers of these subtypes. Analyses of genetic and transcriptomic profiles with network-based approaches identified molecular modules associated with each subtype. For instance, the PD-R-specific module suggested STAT3, FYN, BECN1, APOA1, NEDD4, and GATA2 as potential driver genes of PD-R. It also suggested neuroinflammation, oxidative stress, metabolism, PI3K/AKT, and angiogenesis pathways as potential drivers for rapid PD progression (i.e., PD-R). Moreover, we identified repurposable drug candidates by targeting these subtype-specific molecular modules using network-based approach and cell line drug-gene signature data. We further estimated their treatment effects using two large-scale real-world patient databases; the real-world evidence we gained highlighted the potential of metformin in ameliorating PD progression. In conclusion, this work helps better understand clinical and pathophysiological complexity of PD progression and accelerate precision medicine.

Neuroimaging markers of motor and nonmotor features of Parkinson's disease: an 18f fluorodeoxyglucose positron emission computed tomography study.

AIM: We sought to identify markers of motor and nonmotor function in Parkinson's disease (PD) using advanced neuroimaging techniques in subjects with PD. METHODS: We enrolled 26 nondemented PD subjects and 12 control subjects. All subjects underwent [(18)F]fluorodeoxyglucose positron emission computed tomography (FDG-PET) and magnetic resonance imaging, and a complete neuropsychological battery. RESULTS: FDG-PET of subjects with PD revealed significant metabolic elevations in the bilateral posterior lentiform nucleus, posterior cingulate, and parahippocampus, and metabolic reductions in the bilateral temporoparietal association cortex and occipital lobe versus controls. PD subjects had significant reductions in executive/attention function, memory/verbal learning, and speed of thinking, and significantly increased depression, anxiety and apathy scores compared with controls. Motor dysfunction correlated with increased metabolism in the posterior lentiform nucleus, pons, and cerebellum, and decreased metabolism in the temporoparietal lobe. Cognitive dysfunction correlated with increased posterior cingulate metabolism and decreased temporoparietal lobe metabolism. Depressive symptoms correlated with increased amygdala metabolism; anxiety scores correlated with decreased caudate metabolism, and apathy scores correlated with increased metabolism in the anterior cingulate and orbitofrontal lobe and decreased metabolism in the temporoparietal association cortex. CONCLUSIONS: Our findings showed that motor, cognitive, and emotional dysfunction in PD are associated with distinct patterns of cerebral metabolic changes.

Tablet-based patient educational interventions in care and management of complex movement disorders.

BACKGROUND: Patient education is an essential part of management of complex, disabling neurological disorders. Mobile web-based educational materials provide a novel and potentially valuable means to communicate clinical information that can aid in both medical management and rehabilitation. AIMS: We, therefore, evaluated an educational tablet-based intervention in three patient cohorts regarding the following topics: Parkinson's disease (PD) medications, dystonia and botulinum toxin treatment. METHODS: A total of 50 subjects with PD, 32 with dystonia and 61 receiving botulinum toxin treatment for movement disorders or sialorrhoea were enrolled. Participants in each cohort completed a specific educational module at the time of their regularly scheduled clinic visit, comprising slides, in addition to pre- and post-module quizzes and a satisfaction survey. Additionally, participants in the dystonia and botulinum toxin modules were given a follow-up test at their 3- or 6-month clinical treatment visit. RESULTS: There were 143 participants with 50 completing the PD module, 32 completing the dystonia module and 61 completing the botulinum toxin module. All three groups demonstrated significant improvement in knowledge of module content between their pre- and post-module test scores (PD: p=.0001, dystonia: p<.0001 and botulinum toxin: p=.008), and those who took the dystonia module maintained significant improvement at either a 3- or 6-month follow up compared to pre-module (p <.0001). CONCLUSIONS: Tablet-based teaching modules are an effective means of communicating key concepts to patients. This study supports their use for improving patient understanding that can support lifelong approaches to managing disabling, neurological conditions.Implication for RehabilitationTablet-based modules are relatively easy to use for enhancing education during clinic visits and can possibly help reduce and maintain disability with chronic conditions like Parkinson's disease and dystonia.Improvements in post-test scores suggested that patient participants were able to retain information from the tablets about their complex and challenging conditions and treatments.Adding patients who are fluent in another language would have made this study more generalizable and future studies exploring educational interventions are warranted to help better tailor interventions to patients with chronic neurologic illnesses to help understand the complex aspects of their medical and rehabilitation therapy.The effect of cognitive changes in neurological conditions and understanding of educational information needs to be further tested.This positive result is especially meaningful during the COVID-19 pandemic when in-person access to both medical and rehabilitative care has been curtailed.

Neurologic and psychiatric features of impending neurodegeneration in iRBD.

Introduction: Idiopathic rapid eye movement (REM) sleep behavior disorder (iRBD) is linked to Parkinson's disease and other alpha-synucleinopathies, but various subsets of iRBD may not carry equal risk (i.e., those with depression are at higher risk than those without). Here, we prospectively focus on neurologic and psychiatric aspects of subjects with iRBD, in an attempt to determine what factors are prominent in those who undergo phenoconversion as opposed to those who do not. Methods: We analyzed data from the "REM Sleep Behavior Disorder Associations with Parkinson's Disease Study (RAPiDS)" cohort both at baseline and then at follow-up evaluations (1 to 3 years later) utilizing several neurologic batteries, including the Movement Disorder Society's Unified Parkinson's Disease Rating Scale (MDS-UPDRS), the Montreal Cognitive Assessment (MoCA), the Questionnaire for Impulsive-Compulsive Disorders in Parkinson's Disease (QUIP), the 10-M Walk Test (10MWT), and the Epworth Sleepiness Scale. Determination of phenoconversion was ascertained from physical examination and medical chart review from the initial evaluation onward. Results: Of those who completed both evaluations, there were 33 subjects with iRBD, with an average age of 63.1 ± 12.8 years, with 9 women and 24 men. Of these, 8 (24%) iRBD subjects developed neurodegenerative illness, and demonstrated multiple areas of neurologic and psychiatric signs and symptoms, such as speech and movement problems as well as anxiety and depression. Conclusions: Our data adds to the literature regarding risk of phenoconversion in those with iRBD. Further study will be needed, but it is clear that not all subjects with iRBD present the same risk for neurodegeneration.

Can google glass™ technology improve freezing of gait in parkinsonism? A pilot study.

PURPOSE: Freezing of gait (FOG) is a disabling phenomenon defined by the periodic absence or reduction of forward progression of the feet despite the intention to walk. We sought to understand whether Google Glass (GG), a lightweight wearable device that provides simultaneous visual-auditory cues, might improve FOG in parkinsonism. METHODS: Patients with parkinsonism and FOG utilized GG custom-made auditory-visual cue applications: "Walk With Me" and "Unfreeze Me" in a single session intervention. We recorded ambulation time with and without GG under multiple conditions including 25 feet straight walk, dual task of performing serial 7's while straight walking, 180 degree turn after walking 25 feet, and walking through a doorway. FOG and patient experience questionnaires were administered. RESULTS: Using the GG "Walk With Me" program, improvements were noted in the following: average 25 feet straight walk by 0.32 s (SD 2.12); average dual task of serial 7's and 25 feet straight walk by 1.79 s (SD 2.91); and average walk through doorway by 0.59 s (SD 0.81). Average 180 degree turn after 25 feet walk worsened by 1.89 s (SD 10.66). Using the "Unfreeze Me" program, only the average dual task of serial 7's and 25 feet straight walk improved (better by 0.82 s (SD 3.08 sec). All other tasks had worse performance in terms of speed of completion. CONCLUSION: This feasibility study provides preliminary data suggesting that some walking tasks may improve with GG, which uses various musical dance programs to provide visual and auditory cueing for patients with FOG.IMPLICATIONS FOR REHABILITATIONFreezing of gait in parkinsonian syndromes is a disabling motor block described by patients as having their feet stuck to the floor leading to difficulty in initiation of gait and increased risk for falls.Wearable assistive devices such as Google Glass™ use visual and auditory cueing that may improve gait pattern in patients with freezing of gait.Augmented reality programs using wearable assistive devices are a home-based therapy, with the potential for reinforcing physical therapy techniques; this is especially meaningful during the COVID-19 pandemic when access to both medical and rehabilitative care has been curtailed.

Biomarkers in Parkinson's disease: an update.

PURPOSE OF REVIEW: This review article is focused upon the most recent biomarker studies of Parkinson's disease. It provides an update on promising areas of biomarker research in a rapidly expanding field, and discusses future directions that might lead to successful development of Parkinson's disease biomarkers. RECENT FINDINGS: Studies of molecular-genetic and biochemical biomarkers of Parkinson's disease have not only targeted hypothesis-driven measures of specific substrates involved in processes such as protein misprocessing, but also have made use of sophisticated analyses such as transcriptomic, proteomic, and metabolomic approaches. Whereas none of these are yet established as Parkinson's disease biomarkers, brain imaging using the 123I-ioflupane ligand with single-photon emission computed tomography was recently approved in the United States to aid in Parkinson's disease diagnosis, and research on other imaging modalities is ongoing. Neurophysiological tests are also being adapted for biomarker research, and we review recent promising data. SUMMARY: The search for effective biomarkers for diagnosis and surveillance of Parkinson's disease continues. A battery of biomarkers comprising different modalities might be required to address clinical needs in this complex disorder. Critically, collaborative efforts including centralized tissue repository and clinical research infrastructure that are being organized will advance this field further.

The role of dopaminergic imaging in patients with symptoms of dopaminergic system neurodegeneration.

Diagnosis of neurological and psychiatric conditions associated with disturbances of dopaminergic functioning can be challenging, especially in the early stages, and may be assisted with biomarkers such as dopamine system imaging. Distinguishing between Alzheimer's disease and dementia with Lewy bodies is a major diagnostic challenge. Clinical diagnosis of Parkinson's disease is straightforward with classic presentation, but accurate distinction among Parkinsonian variants may be difficult; non-Parkinson's disease conditions are commonly misdiagnosed as Parkinson's disease, and ~20% of patients with Parkinson's disease are not clinically diagnosed despite coming to medical attention. Early and accurate diagnosis is desirable to improve management. Imaging of the dopamine transporter using single-photon emission computed tomography may be of particular utility in this regard. Abnormal imaging indicates underlying nigrostriatal neurodegeneration, supportive of a diagnosis of Parkinson's disease, atypical parkinsonism or dementia with Lewy bodies, and identifies patient groups in whom dopaminergic therapy may be beneficial. Normal imaging supports diagnosis of a condition not involving nigrostriatal neurodegeneration such as Alzheimer's disease, essential tremor or drug-induced parkinsonism and hence a different therapeutic approach. In patients in whom there was diagnostic uncertainty between degenerative parkinsonism and non-degenerative tremor disorders, baseline imaging with the dopamine transporter ligand [(123)I]ioflupane (DaTscan™) has shown 78% sensitivity and 97% specificity with reference to clinical diagnosis at 3 years, versus 93% and 46%, respectively, for baseline clinical diagnosis. In a Phase III trial of [(123)I]ioflupane in patients with initial clinical diagnosis of probable or possible dementia with Lewy bodies or non-Lewy body dementia, mean specificity for excluding non-Lewy body dementia (predominantly Alzheimer's disease) was 90.4%. Using clinical diagnosis as a reference against which to assess sensitivity and specificity of dopamine transporter imaging is a limitation, but definitive diagnosis via pathological confirmation is generally not feasible. In a series of patients with post-mortem brain examination, imaging using [(123)I]ioflupane has demonstrated higher sensitivity (88%) and specificity (100%) for differentiating dementia with Lewy bodies from non-Lewy body dementia than clinical diagnosis (75% and 42%, respectively). Dopaminergic system imaging may be particularly valuable in patients with clinically inconclusive parkinsonism or a clinical diagnosis of possible dementia with Lewy bodies; it is not helpful in differentiating between Parkinson's disease and atypical parkinsonism, although postsynaptic dopaminergic imaging may be of utility. Other potential uses of dopamine transporter imaging include identification of patients with premotor Parkinson's disease, monitoring disease progression in testing novel therapeutics, and as an inclusion criterion for entry into clinical trials.

Clinical Review of Smartphone Applications in Parkinson's Disease.

BACKGROUND: Parkinson's disease (PD) is the second leading neurodegenerative disease worldwide. Important advances in monitoring and treatment have been made in recent years. This article reviews literature on utility of smartphone applications in monitoring PD symptoms that may ultimately facilitate improved patient care, and on movement modulation as a potential therapeutic. REVIEW SUMMARY: Novel mobile phone applications can provide one-time and/or continuous data to monitor PD motor symptoms in person or remotely, that may support precise therapeutic adjustments and management decisions. Apps have also been developed for medication management and treatment. CONCLUSIONS: Smartphone applications provide a wide array of platforms allowing for meaningful short-term and long-term data collection and are also being tested for intervention. However, the variability of the applications and the need to translate complicated sensor data may hinder immediate clinical applicability. Future studies should involve stake-holders early in the design process to promote usability and streamline the interface between patients, clinicians, and PD apps.

Development of a standard of care for patients with valosin-containing protein associated multisystem proteinopathy.

Valosin-containing protein (VCP) associated multisystem proteinopathy (MSP) is a rare inherited disorder that may result in multisystem involvement of varying phenotypes including inclusion body myopathy, Paget's disease of bone (PDB), frontotemporal dementia (FTD), parkinsonism, and amyotrophic lateral sclerosis (ALS), among others. An international multidisciplinary consortium of 40+ experts in neuromuscular disease, dementia, movement disorders, psychology, cardiology, pulmonology, physical therapy, occupational therapy, speech and language pathology, nutrition, genetics, integrative medicine, and endocrinology were convened by the patient advocacy organization, Cure VCP Disease, in December 2020 to develop a standard of care for this heterogeneous and under-diagnosed disease. To achieve this goal, working groups collaborated to generate expert consensus recommendations in 10 key areas: genetic diagnosis, myopathy, FTD, PDB, ALS, Charcot Marie Tooth disease (CMT), parkinsonism, cardiomyopathy, pulmonology, supportive therapies, nutrition and supplements, and mental health. In April 2021, facilitated discussion of each working group's conclusions with consensus building techniques enabled final agreement on the proposed standard of care for VCP patients. Timely referral to a specialty neuromuscular center is recommended to aid in efficient diagnosis of VCP MSP via single-gene testing in the case of a known familial VCP variant, or multi-gene panel sequencing in undifferentiated cases. Additionally, regular and ongoing multidisciplinary team follow up is essential for proactive screening and management of secondary complications. The goal of our consortium is to raise awareness of VCP MSP, expedite the time to accurate diagnosis, define gaps and inequities in patient care, initiate appropriate pharmacotherapies and supportive therapies for optimal management, and elevate the recommended best practices guidelines for multidisciplinary care internationally.

Comprehensive subtyping of Parkinson's disease patients with similarity fusion: a case study with BioFIND data.

Parkinson's disease (PD) is a complex neurodegenerative disorder with diverse clinical manifestations. To better understand this disease, research has been done to categorize, or subtype, patients, using an array of criteria derived from clinical assessments and biospecimen analyses. In this study, using data from the BioFIND cohort, we aimed at identifying subtypes of moderate-to-advanced PD via comprehensively considering motor and non-motor manifestations. A total of 103 patients were included for analysis. Through the use of a patient-wise similarity matrix fusion technique and hierarchical agglomerative clustering analysis, three unique subtypes emerged from the clustering results. Subtype I, comprised of 60 patients (~58.3%), was characterized by mild symptoms, both motor and non-motor. Subtype II, comprised of 20 (~19.4%) patients, was characterized by an intermediate severity, with a high tremor score and mild non-motor symptoms. Subtype III, comprised of 23 (~22.3%) patients, was characterized by more severe motor and non-motor symptoms. These subtypes show statistically significant differences when looking at motor (on and off medication) clinical features and non-motor clinical features, while there was no clear difference in demographics, biomarker levels, and genetic risk scores.