Delivering a Diagnosis of Parkinson's Disease and Parkinsonism with Wisdom and Sensitivity.

Parkinson's disease (PD) is a chronic, progressive, complex movement disorder. In addition to the motor manifestations, changes in mood and cognition frequently occur. It is understandable that receiving this diagnosis can be difficult for patients and their significant others. For the clinician, delivering a PD diagnosis can be challenging and requires a comprehensive patient assessment followed by a thoughtful treatment plan. How this diagnosis is conveyed can have a long-term impact on patient outcomes such as treatment adherence, participation in decision making, understanding of PD, and satisfaction with care. Because a PD diagnosis is often complicated by uncertainty about the diagnosis itself as well as future prognosis, a sensitive patient-centered approach to care, balanced with realistic expectations, is recommended. Full disclosure, honesty, and empathy on the part of the entire healthcare team are required. This includes relevant information tailored to the patient's unique needs at the time of diagnosis as well as referrals to appropriate rehabilitation and support services. Consistent, timely follow-up of all interventions is essential. It is essential that a diagnosis of PD is properly delivered to optimize understanding of PD, treatment adherence, participation in decision making, and satisfaction with care. In this article, we provide guidance on delivery of this diagnosis based on a growing body of evidence and our >35-year collective clinical experience and work developing and utilizing pertinent, creative educational tools and comprehensive, sensitive support programs for newly diagnosed patients and their significant others. Although most of the evidence we present pertains to PD, our experience suggests it could also apply to other forms of Parkinsonism and other chronic or progressive movement disorders.

Natural Walking Intensity in Persons With Parkinson Disease.

BACKGROUND AND PURPOSE: Few persons with Parkinson disease (PD) appear to engage in moderate-intensity walking associated with disease-modifying health benefits. How much time is spent walking at lower, yet still potentially beneficial, intensities is poorly understood. The purpose of this exploratory, observational study was to describe natural walking intensity in ambulatory persons with PD. METHODS: Accelerometer-derived real-world walking data were collected for more than 7 days at baseline from 82 participants enrolled in a PD clinical trial. Walking intensity was defined according to the number of steps in each active minute (1-19, 20-39, 40-59, 60-79, 80-99, or ≥100 steps). Daily minutes of walking and duration of the longest sustained walking bout were calculated at each intensity. Number of sustained 10 to 19, 20 to 29, and 30-minute bouts and greater at any intensity also were calculated. Values were analyzed in the context of physical activity guidelines. RESULTS: Most daily walking occurred at lower intensities (157.3 ± 58.1 min of 1-19 steps; 81.3 ± 32.6 min of 20-39 steps; 38.2 ± 21.3 min of 40-59 steps; 15.1 ± 11.5 min of 60-79 steps; 7.4 ± 7.0 min of 80-99 steps; 7.3 ± 9.6 min of ≥100 steps). The longest daily sustained walking bout occurred at the lowest intensity level (15.9 ± 5.2 min of 1-19 steps). Few bouts lasting 20 minutes and greater occurred at any intensity. DISCUSSION AND CONCLUSIONS: Despite relatively high daily step counts, participants tended to walk at remarkably low intensity, in bouts of generally short duration, with relatively few instances of sustained walking. The findings reinforced the need for health promotion interventions designed specifically to increase walking intensity.Video Abstract available for more insight from authors (see the Video, Supplemental Digital Content 1 available at: http://links.lww.com/JNPT/A426 ).

Development and validation of an interpretable deep learning framework for Alzheimer's disease classification.

Alzheimer's disease is the primary cause of dementia worldwide, with an increasing morbidity burden that may outstrip diagnosis and management capacity as the population ages. Current methods integrate patient history, neuropsychological testing and MRI to identify likely cases, yet effective practices remain variably applied and lacking in sensitivity and specificity. Here we report an interpretable deep learning strategy that delineates unique Alzheimer's disease signatures from multimodal inputs of MRI, age, gender, and Mini-Mental State Examination score. Our framework linked a fully convolutional network, which constructs high resolution maps of disease probability from local brain structure to a multilayer perceptron and generates precise, intuitive visualization of individual Alzheimer's disease risk en route to accurate diagnosis. The model was trained using clinically diagnosed Alzheimer's disease and cognitively normal subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset (n = 417) and validated on three independent cohorts: the Australian Imaging, Biomarker and Lifestyle Flagship Study of Ageing (AIBL) (n = 382), the Framingham Heart Study (n = 102), and the National Alzheimer's Coordinating Center (NACC) (n = 582). Performance of the model that used the multimodal inputs was consistent across datasets, with mean area under curve values of 0.996, 0.974, 0.876 and 0.954 for the ADNI study, AIBL, Framingham Heart Study and NACC datasets, respectively. Moreover, our approach exceeded the diagnostic performance of a multi-institutional team of practicing neurologists (n = 11), and high-risk cerebral regions predicted by the model closely tracked post-mortem histopathological findings. This framework provides a clinically adaptable strategy for using routinely available imaging techniques such as MRI to generate nuanced neuroimaging signatures for Alzheimer's disease diagnosis, as well as a generalizable approach for linking deep learning to pathophysiological processes in human disease.

Are Mobile Persons With Parkinson Disease Necessarily More Active?

BACKGROUND AND PURPOSE: Walking activity in persons with Parkinson disease (PD) is important for preventing functional decline. The contribution of walking activity to home and community mobility in PD is poorly understood. METHODS: Cross-sectional baseline data (N = 69) were analyzed from a randomized controlled PD trial. The Life-Space Assessment (LSA) quantified the extent, frequency, and independence across 5 expanding levels of home and community mobility, producing individual subscores and a total score. Two additional summed scores were used to represent mobility within (Levels 1-3) and beyond (Levels 4-5) neighborhood limits. An accelerometer measured walking activity for 7 days. Regression and correlation analyses evaluated relationships between daily steps and mobility scores. Mann-Whitney U tests secondarily compared differences in mobility scores between the active and sedentary groups. RESULTS: Walking activity contributed significantly to the summed Level 1-3 score (ß = 0.001, P = 0.004) but not to the summed Level 4-5 (ß = 0.001, P = 0.33) or total (ß = 0.002, P = 0.07) scores. Walking activity was significantly related to Level 1 (ρ = 0.336, P = 0.005), Level 2 (ρ = 0.307, P = 0.010), and Level 3 (ρ = 0.314, P = 0.009) subscores. Only the summed Level 1-3 score (P = 0.030) was significantly different between the active and sedentary groups. DISCUSSION AND CONCLUSIONS: Persons with PD who demonstrated greater mobility beyond the neighborhood were not necessarily more active; walking activity contributed more so to home and neighborhood mobility. Compared with LSA total score, the Level 1-3 summed score may be a more useful participation-level measure for assessing the impact of changes in walking activity.Video Abstract available for more insights from the authors (see the Video, Supplemental Digital Content 1 available at: http://links.lww.com/JNPT/A349).

Design of the WHIP-PD study: a phase II, twelve-month, dual-site, randomized controlled trial evaluating the effects of a cognitive-behavioral approach for promoting enhanced walking activity using mobile health technology in people with Parkinson-disease.

BACKGROUND: Parkinson disease (PD) is a debilitating and chronic neurodegenerative disease resulting in ambulation difficulties. Natural walking activity often declines early in disease progression despite the relative stability of motor impairments. In this study, we propose a paradigm shift with a "connected behavioral approach" that targets real-world walking using cognitive-behavioral training and mobile health (mHealth) technology. METHODS/DESIGN: The Walking and mHealth to Increase Participation in Parkinson Disease (WHIP-PD) study is a twelve-month, dual site, two-arm, randomized controlled trial recruiting 148 participants with early to mid-stage PD. Participants will be randomly assigned to connected behavioral or active control conditions. Both conditions will include a customized program of goal-oriented walking, walking-enhancing strengthening exercises, and eight in-person visits with a physical therapist. Participants in the connected behavioral condition also will (1) receive cognitive-behavioral training to promote self-efficacy for routine walking behavior and (2) use a mHealth software application to manage their program and communicate remotely with their physical therapist. Active control participants will receive no cognitive-behavioral training and manage their program on paper. Evaluations will occur at baseline, three-, six-, and twelve-months and include walking assessments, self-efficacy questionnaires, and seven days of activity monitoring. Primary outcomes will include the change between baseline and twelve months in overall amount of walking activity (mean number of steps per day) and amount of moderate intensity walking activity (mean number of minutes per day in which > 100 steps were accumulated). Secondary outcomes will include change in walking capacity as measured by the six-minute walk test and ten-meter walk test. We also will examine if self-efficacy mediates change in amount of walking activity and if change in amount of walking activity mediates change in walking capacity. DISCUSSION: We expect this study to show the connected behavioral approach will be more effective than the active control condition in increasing the amount and intensity of real-world walking activity and improving walking capacity. Determining effective physical activity interventions for persons with PD is important for preserving mobility and essential for maintaining quality of life. Clinical trials registration NCT03517371, May 7, 2018. TRIAL REGISTRATION: ClinicalTrials.gov: NCT03517371. Date of registration: May 7, 2018. Protocol version: Original.

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.

A randomized trial of inhaled levodopa (CVT-301) for motor fluctuations in Parkinson's disease.

BACKGROUND: Although levodopa is the most effective oral PD therapy, many patients experience motor fluctuations, including sudden loss of dose effect and delayed benefit. CVT-301 is a levodopa inhalation powder with the potential for rapid onset of action. The objective of this study was to evaluate CVT-301 self-administered by PD patients to relieve OFF episodes. METHODS: PD patients with ≥2 hours per day of OFF time despite oral levodopa ≥4 times per day were randomized to CVT-301 or placebo for 4 weeks, to be used up to 3 times per day for OFF episodes. After 2 weeks, the study-drug dose was escalated from 35 to 50 mg. The primary end point was mean change in UPDRS Part III score from a predose OFF state to the average of postdose scores obtained at 10, 20, 30, and 60 minutes, as assessed in-clinic at the end of week 4. Home diaries were recorded. RESULTS: Eighty-six patients used the study drug at an average frequency of 2.1 times per day for CVT-301 and for placebo. At 4 weeks, least-squares mean change in UPDRS Part III score favored CVT-301 by 7.0 points (P < 0.001). A treatment effect was evident at 10 minutes. At 4 weeks, least-squares mean OFF-time change from baseline favored CVT-301 by 0.9 hours per day (P = 0.045). The most frequently reported adverse events in the CVT-301 group were dizziness, cough, and nausea, each in 7% (3 of 43 patients). CONCLUSIONS: CVT-301 self-administered during OFF episodes provided rapid improvement of motor function, and daily OFF time was significantly reduced at the higher dose. CVT-301 was generally safe and well-tolerated. © 2016 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Stigma as a key determinant of health-related quality of life in Parkinson's disease.

PURPOSE: People with Parkinson's disease (PD) may experience stigma due to their visible features of movement and communication difficulties. This paper aimed to examine the role of experienced stigma in health-related quality of life (QOL), after controlling for personal and clinical characteristics. METHODS: This is a preliminary analysis of a subset of baseline data from the Social Self-Management of Parkinson's Disease Study (SocM-PD), an ongoing 3-year prospective cohort study. Seventy-three people with PD (M age = 65.72, 29 women) participated in this study. Hierarchical multiple regression analyses were used to determine the role of stigma in QOL, after controlling for gender, disease severity, depression, and motor difficulties of daily living. RESULTS: Significant correlations were found between QOL with gender (r = .26), disease severity (r = .38), depression (r = .65), motor difficulties of daily living (r = .71), and stigma (r = .83). After controlling for the significant covariates, stigma made a significant and unique contribution to the explanation of QOL by 13.7 % (p < 0.001). A final hierarchical multiple regression with stigma and the 4 covariates revealed an overall model that explained 77.8 % of the total variance of QOL (F [5, 63] = 48.79, p < 0.001). CONCLUSIONS: Experienced stigma appears to be a key determinant of QOL in people with PD. The results suggest the importance of further understanding stigma in PD to develop possible intervention strategies. Future work is also needed to verify the results with a larger and longitudinal dataset of the SocM-PD.

Highly Challenging Balance Program Reduces Fall Rate in Parkinson Disease.

BACKGROUND AND PURPOSE: There is a paucity of effective treatment options to reduce falls in Parkinson disease (PD). Although a variety of rehabilitative approaches have been shown to improve balance, evidence of a reduction in falls has been mixed. Prior balance trials suggest that programs with highly challenging exercises had superior outcomes. We investigated the effects of a theory-driven, progressive, highly challenging group exercise program on fall rate, balance, and fear of falling. METHODS: Twenty-three subjects with PD participated in this randomized cross-over trial. Subjects were randomly allocated to 3 months of active balance exercises or usual care followed by the reverse. During the active condition, subjects participated in a progressive, highly challenging group exercise program twice weekly for 90 minutes. Outcomes included a change in fall rate over the 3-month active period and differences in balance (Mini-Balance Evaluation Systems Test [Mini-BESTest]), and fear of falling (Falls Efficacy Scale-International [FES-I]) between active and usual care conditions. RESULTS: The effect of time on falls was significant (regression coefficient = -0.015 per day, P < 0.001). The estimated rate ratio comparing incidence rates at time points 1 month apart was 0.632 (95% confidence interval, 0.524-0.763). Thus, there was an estimated 37% decline in fall rate per month (95% confidence interval, 24%-48%). Improvements were also observed on the Mini-BESTest (P = 0.037) and FES-I (P = 0.059). DISCUSSION AND CONCLUSIONS: The results of this study show that a theory-based, highly challenging, and progressive exercise program was effective in reducing falls, improving balance, and reducing fear of falling in PD.Video abstract available for more insights from the authors (see Supplemental Digital Content 1, http://links.lww.com/JNPT/A120).

Effect of Deutetrabenazine on Chorea Among Patients With Huntington Disease: A Randomized Clinical Trial.

IMPORTANCE: Deutetrabenazine is a novel molecule containing deuterium, which attenuates CYP2D6 metabolism and increases active metabolite half-lives and may therefore lead to stable systemic exposure while preserving key pharmacological activity. OBJECTIVE: To evaluate efficacy and safety of deutetrabenazine treatment to control chorea associated with Huntington disease. DESIGN, SETTING, AND PARTICIPANTS: Ninety ambulatory adults diagnosed with manifest Huntington disease and a baseline total maximal chorea score of 8 or higher (range, 0-28; lower score indicates less chorea) were enrolled from August 2013 to August 2014 and randomized to receive deutetrabenazine (n = 45) or placebo (n = 45) in a double-blind fashion at 34 Huntington Study Group sites. INTERVENTIONS: Deutetrabenazine or placebo was titrated to optimal dose level over 8 weeks and maintained for 4 weeks, followed by a 1-week washout. MAIN OUTCOMES AND MEASURES: Primary end point was the total maximal chorea score change from baseline (the average of values from the screening and day-0 visits) to maintenance therapy (the average of values from the week 9 and 12 visits) obtained by in-person visits. This study was designed to detect a 2.7-unit treatment difference in scores. The secondary end points, assessed hierarchically, were the proportion of patients who achieved treatment success on the Patient Global Impression of Change (PGIC) and on the Clinical Global Impression of Change (CGIC), the change in 36-Item Short Form- physical functioning subscale score (SF-36), and the change in the Berg Balance Test. RESULTS: Ninety patients with Huntington disease (mean age, 53.7 years; 40 women [44.4%]) were enrolled. In the deutetrabenazine group, the mean total maximal chorea scores improved from 12.1 (95% CI, 11.2-12.9) to 7.7 (95% CI, 6.5-8.9), whereas in the placebo group, scores improved from 13.2 (95% CI, 12.2-14.3) to 11.3 (95% CI, 10.0-12.5); the mean between-group difference was -2.5 units (95% CI, -3.7 to -1.3) (P < .001). Treatment success, as measured by the PGIC, occurred in 23 patients (51%) in the deutetrabenazine group vs 9 (20%) in the placebo group (P = .002). As measured by the CGIC, treatment success occurred in 19 patients (42%) in the deutetrabenazine group vs 6 (13%) in the placebo group (P = .002). In the deutetrabenazine group, the mean SF-36 physical functioning subscale scores decreased from 47.5 (95% CI, 44.3-50.8) to 47.4 (44.3-50.5), whereas in the placebo group, scores decreased from 43.2 (95% CI, 40.2-46.3) to 39.9 (95% CI, 36.2-43.6), for a treatment benefit of 4.3 (95% CI, 0.4 to 8.3) (P = .03). There was no difference between groups (mean difference of 1.0 unit; 95% CI, -0.3 to 2.3; P = .14), for improvement in the Berg Balance Test, which improved by 2.2 units (95% CI, 1.3-3.1) in the deutetrabenazine group and by 1.3 units (95% CI, 0.4-2.2) in the placebo group. Adverse event rates were similar for deutetrabenazine and placebo, including depression, anxiety, and akathisia. CONCLUSIONS AND RELEVANCE: Among patients with chorea associated with Huntington disease, the use of deutetrabenazine compared with placebo resulted in improved motor signs at 12 weeks. Further research is needed to assess the clinical importance of the effect size and to determine longer-term efficacy and safety. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT01795859.

Common SNP-based haplotype analysis of the 4p16.3 Huntington disease gene region.

Age at the onset of motor symptoms in Huntington disease (HD) is determined largely by the length of a CAG repeat expansion in HTT but is also influenced by other genetic factors. We tested whether common genetic variation near the mutation site is associated with differences in the distribution of expanded CAG alleles or age at the onset of motor symptoms. To define disease-associated single-nucleotide polymorphisms (SNPs), we compared 4p16.3 SNPs in HD subjects with population controls in a case:control strategy, which revealed that the strongest signals occurred at a great distance from the HD mutation as a result of "synthetic association" with SNP alleles that are of low frequency in population controls. Detailed analysis delineated a prominent ancestral haplotype that accounted for ∼50% of HD chromosomes and extended to at least 938 kb on about half of these. Together, the seven most abundant haplotypes accounted for ∼83% of HD chromosomes. Neither the extended shared haplotype nor the individual local HTT haplotypes were associated with altered CAG-repeat length distribution or residual age at the onset of motor symptoms, arguing against modification of these disease features by common cis-regulatory elements. Similarly, the 11 most frequent control haplotypes showed no trans-modifier effect on age at the onset of motor symptoms. Our results argue against common local regulatory variation as a factor influencing HD pathogenesis, suggesting that genetic modifiers be sought elsewhere in the genome. They also indicate that genome-wide association analysis with a small number of cases can be effective for regional localization of genetic defects, even when a founder effect accounts for only a fraction of the disorder.

Emergence and evolution of social self-management of Parkinson's disease: study protocol for a 3-year prospective cohort study.

BACKGROUND: Parkinson's disease affects facial, vocal and trunk muscles. As symptoms progress, facial expression becomes masked, limiting the person's ability to communicate emotions and intentions to others. As people with the disease live and reside in their homes longer, the burden of caregiving is unmitigated by social and emotional rewards provided by an expressive individual. Little is known about how adults living with Parkinson's disease manage their social lives and how an inability to be emotionally expressive can affect social connections and health. Because social networks have been shown to be crucial to the overall well-being of people living with chronic diseases, research is needed on how expressive capacity affects life trajectories and health. METHODS/DESIGN: The overall objective is to understand the emergence and evolution of the trajectories of the self-management of the social lives of people living with Parkinson's disease. The central hypothesis is that expressive capacity predicts systematic change in the pattern of social self-management and quality of life outcomes. The specific aims of this 3-year longitudinal study of 120 people with the disease and a maximum of 120 care partners are: 1) characterize social self-management trajectories over a 3-year period; 2) estimate the degree to which expressive nonverbal capacity predicts the trajectory; and 3) determine the moderating effect of gender on the association between expressive capacity and change in social self-management. Each participant will be assessed 14 times to detect rapid and non-linear changes in social participation and management of social activities; social network; and social comfort, general health and well-being. DISCUSSION: This project will provide evidence to guide the development of interventions for supporting social integration of those living with Parkinson's disease, thus leading to improved overall health. It focuses on the novel construct of social self-management and known factors-expressive capacity and gender-that contribute to stigmatization. The repeated measures design detects triggers of rapid changes in social and health outcomes.

AI-based differential diagnosis of dementia etiologies on multimodal data.

Differential diagnosis of dementia remains a challenge in neurology due to symptom overlap across etiologies, yet it is crucial for formulating early, personalized management strategies. Here, we present an artificial intelligence (AI) model that harnesses a broad array of data, including demographics, individual and family medical history, medication use, neuropsychological assessments, functional evaluations and multimodal neuroimaging, to identify the etiologies contributing to dementia in individuals. The study, drawing on 51,269 participants across 9 independent, geographically diverse datasets, facilitated the identification of 10 distinct dementia etiologies. It aligns diagnoses with similar management strategies, ensuring robust predictions even with incomplete data. Our model achieved a microaveraged area under the receiver operating characteristic curve (AUROC) of 0.94 in classifying individuals with normal cognition, mild cognitive impairment and dementia. Also, the microaveraged AUROC was 0.96 in differentiating the dementia etiologies. Our model demonstrated proficiency in addressing mixed dementia cases, with a mean AUROC of 0.78 for two co-occurring pathologies. In a randomly selected subset of 100 cases, the AUROC of neurologist assessments augmented by our AI model exceeded neurologist-only evaluations by 26.25%. Furthermore, our model predictions aligned with biomarker evidence and its associations with different proteinopathies were substantiated through postmortem findings. Our framework has the potential to be integrated as a screening tool for dementia in clinical settings and drug trials. Further prospective studies are needed to confirm its ability to improve patient care.

AI-based differential diagnosis of dementia etiologies on multimodal data.

Differential diagnosis of dementia remains a challenge in neurology due to symptom overlap across etiologies, yet it is crucial for formulating early, personalized management strategies. Here, we present an AI model that harnesses a broad array of data, including demographics, individual and family medical history, medication use, neuropsychological assessments, functional evaluations, and multimodal neuroimaging, to identify the etiologies contributing to dementia in individuals. The study, drawing on 51,269 participants across 9 independent, geographically diverse datasets, facilitated the identification of 10 distinct dementia etiologies. It aligns diagnoses with similar management strategies, ensuring robust predictions even with incomplete data. Our model achieved a micro-averaged area under the receiver operating characteristic curve (AUROC) of 0.94 in classifying individuals with normal cognition, mild cognitive impairment and dementia. Also, the micro-averaged AUROC was 0.96 in differentiating the dementia etiologies. Our model demonstrated proficiency in addressing mixed dementia cases, with a mean AUROC of 0.78 for two co-occurring pathologies. In a randomly selected subset of 100 cases, the AUROC of neurologist assessments augmented by our AI model exceeded neurologist-only evaluations by 26.25%. Furthermore, our model predictions aligned with biomarker evidence and its associations with different proteinopathies were substantiated through postmortem findings. Our framework has the potential to be integrated as a screening tool for dementia in various clinical settings and drug trials, with promising implications for person-level management.

Candidate glutamatergic and dopaminergic pathway gene variants do not influence Huntington's disease motor onset.

Huntington's disease (HD) is a neurodegenerative disorder characterized by motor, cognitive, and behavioral disturbances. It is caused by the expansion of the HTT CAG repeat, which is the major determinant of age at onset (AO) of motor symptoms. Aberrant function of N-methyl-D-aspartate receptors and/or overexposure to dopamine has been suggested to cause significant neurotoxicity, contributing to HD pathogenesis. We used genetic association analysis in 1,628 HD patients to evaluate candidate polymorphisms in N-methyl-D-aspartate receptor subtype genes (GRIN2A rs4998386 and rs2650427, and GRIN2B rs1806201) and functional polymorphisms in genes in the dopamine pathway (DAT1 3' UTR 40-bp variable number tandem repeat (VNTR), DRD4 exon 3 48-bp VNTR, DRD2 rs1800497, and COMT rs4608) as potential modifiers of the disease process. None of the seven polymorphisms tested was found to be associated with significant modification of motor AO, either in a dominant or additive model, after adjusting for ancestry. The results of this candidate-genetic study therefore do not provide strong evidence to support a modulatory role for these variations within glutamatergic and dopaminergic genes in the AO of HD motor manifestations.

High-resolution tracking of motor disorders in Parkinson's disease during unconstrained activity.

Parkinson's disease (PD) can present with a variety of motor disorders that fluctuate throughout the day, making assessment a challenging task. Paper-based measurement tools can be burdensome to the patient and clinician and lack the temporal resolution needed to accurately and objectively track changes in motor symptom severity throughout the day. Wearable sensor-based systems that continuously monitor PD motor disorders may help to solve this problem, although critical shortcomings persist in identifying multiple disorders at high temporal resolution during unconstrained activity. The purpose of this study was to advance the current state of the art by (1) introducing hybrid sensor technology to concurrently acquire surface electromyographic (sEMG) and accelerometer data during unconstrained activity and (2) analyzing the data using dynamic neural network algorithms to capture the evolving temporal characteristics of the sensor data and improve motor disorder recognition of tremor and dyskinesia. Algorithms were trained (n=11 patients) and tested (n=8 patients; n=4 controls) to recognize tremor and dyskinesia at 1-second resolution based on sensor data features and expert annotation of video recording during 4-hour monitoring periods of unconstrained daily activity. The algorithms were able to make accurate distinctions between tremor, dyskinesia, and normal movement despite the presence of diverse voluntary activity. Motor disorder severity classifications averaged 94.9% sensitivity and 97.1% specificity based on 1 sensor per symptomatic limb. These initial findings indicate that new sensor technology and software algorithms can be effective in enhancing wearable sensor-based system performance for monitoring PD motor disorders during unconstrained activities.

Clinical Use of On-Demand Therapies for Patients with Parkinson's Disease and OFF Periods.

On-demand therapies for Parkinson's disease (PD) provide rapid, reliable relief for patients experiencing OFF periods; however, practical guidelines on the use of these therapies are not generally available. This paper reviews the use of on-demand treatments. Motor fluctuations occur in nearly all patients with PD after long-term use of levodopa. As the goal of PD treatment is to provide good ON time, on-demand treatments that have a more rapid reliable onset than the slower-acting oral medications provide rapid relief for OFF periods. All current on-demand treatments bypass the gastrointestinal tract, providing dopaminergic therapy directly into the blood stream by subcutaneous injection, through the buccal mucosa, or by inhalation into the pulmonary circulation. On-demand treatments are fast acting (10- to 20-min onset), with maximum, reliable, and significant responses reached within 30 min after administration. Oral medications pass through the gastrointestinal tract and thus have slower absorption owing to gastroparesis and competition with food. On-demand therapies, by providing fast-acting relief, can have a positive impact on a patient's quality of life when patients are experiencing OFF periods.

Population stratification may bias analysis of PGC-1α as a modifier of age at Huntington disease motor onset.

Huntington's disease (HD) is an inherited neurodegenerative disorder characterized by motor, cognitive and behavioral disturbances, caused by the expansion of a CAG trinucleotide repeat in the HD gene. The CAG allele size is the major determinant of age at onset (AO) of motor symptoms, although the remaining variance in AO is highly heritable. The rs7665116 SNP in PPARGC1A, encoding the mitochondrial regulator PGC-1α, has been reported to be a significant modifier of AO in three European HD cohorts, perhaps due to affected cases from Italy. We attempted to replicate these findings in a large collection of (1,727) HD patient DNA samples of European origin. In the entire cohort, rs7665116 showed a significant effect in the dominant model (p value = 0.008) and the additive model (p value = 0.009). However, when examined by origin, cases of Southern European origin had an increased rs7665116 minor allele frequency (MAF), consistent with this being an ancestry-tagging SNP. The Southern European cases, despite similar mean CAG allele size, had a significantly older mean AO (p < 0.001), suggesting population-dependent phenotype stratification. When the generalized estimating equations models were adjusted for ancestry, the effect of the rs7665116 genotype on AO decreased dramatically. Our results do not support rs7665116 as a modifier of AO of motor symptoms, as we found evidence for a dramatic effect of phenotypic (AO) and genotypic (MAF) stratification among European cohorts that was not considered in previously reported association studies. A significantly older AO in Southern Europe may reflect population differences in genetic or environmental factors that warrant further investigation.

TAA repeat variation in the GRIK2 gene does not influence age at onset in Huntington's disease.

Huntington's disease is a neurodegenerative disorder caused by an expanded CAG trinucleotide repeat whose length is the major determinant of age at onset but remaining variation appears to be due in part to the effect of genetic modifiers. GRIK2, which encodes GluR6, a mediator of excitatory neurotransmission in the brain, has been suggested in several studies to be a modifier gene based upon a 3' untranslated region TAA trinucleotide repeat polymorphism. Prior to investing in detailed studies of the functional impact of this polymorphism, we sought to confirm its effect on age at onset in a much larger dataset than in previous investigations. We genotyped the HD CAG repeat and the GRIK2 TAA repeat in DNA samples from 2,911 Huntington's disease subjects with known age at onset, and tested for a potential modifier effect of GRIK2 using a variety of statistical approaches. Unlike previous reports, we detected no evidence of an influence of the GRIK2 TAA repeat polymorphism on age at motor onset. Similarly, the GRIK2 polymorphism did not show significant modifier effect on psychiatric and cognitive age at onset in HD. Comprehensive analytical methods applied to a much larger sample than in previous studies do not support a role for GRIK2 as a genetic modifier of age at onset of clinical symptoms in Huntington's disease.