Genetic modifiers of Huntington disease differentially influence motor and cognitive domains.

Genome-wide association studies (GWASs) of Huntington disease (HD) have identified six DNA maintenance gene loci (among others) as modifiers and implicated a two step-mechanism of pathogenesis: somatic instability of the causative HTT CAG repeat with subsequent triggering of neuronal damage. The largest studies have been limited to HD individuals with a rater-estimated age at motor onset. To capitalize on the wealth of phenotypic data in several large HD natural history studies, we have performed algorithmic prediction by using common motor and cognitive measures to predict age at other disease landmarks as additional phenotypes for GWASs. Combined with imputation with the Trans-Omics for Precision Medicine reference panel, predictions using integrated measures provided objective landmark phenotypes with greater power to detect most modifier loci. Importantly, substantial differences in the relative modifier signal across loci, highlighted by comparing common modifiers at MSH3 and FAN1, revealed that individual modifier effects can act preferentially in the motor or cognitive domains. Individual components of the DNA maintenance modifier mechanisms may therefore act differentially on the neuronal circuits underlying the corresponding clinical measures. In addition, we identified additional modifier effects at the PMS1 and PMS2 loci and implicated a potential second locus on chromosome 7. These findings indicate that broadened discovery and characterization of HD genetic modifiers based on additional quantitative or qualitative phenotypes offers not only the promise of in-human validated therapeutic targets but also a route to dissecting the mechanisms and cell types involved in both the somatic instability and toxicity components of HD pathogenesis.

Dry-Cleaning Chemicals and a Cluster of Parkinson's Disease and Cancer: A Retrospective Investigation.

BACKGROUND: Environmental exposure to trichloroethylene (TCE), a carcinogenic dry-cleaning chemical, may be linked to Parkinson's disease (PD). OBJECTIVE: The objective of this study was to determine whether PD and cancer were elevated among attorneys who worked near a contaminated site. METHODS: We surveyed and evaluated attorneys with possible exposure and assessed a comparison group. RESULTS: Seventy-nine of 82 attorneys (96.3%; mean [SD] age: 69.5 [11.4] years; 89.9% men) completed at least one phase of the study. For comparison, 75 lawyers (64.9 [10.2] years; 65.3% men) underwent clinical evaluations. Four (5.1%) of them who worked near the polluted site reported PD, more than expected based on age and sex (1.7%; P = 0.01) but not significantly higher than the comparison group (n = 1 [1.3%]; P = 0.37). Fifteen (19.0%), compared to four in the comparison group (5.3%; P = 0.049), had a TCE-related cancer. CONCLUSIONS: In a retrospective study, diagnoses of PD and TCE-related cancers appeared to be elevated among attorneys who worked next to a contaminated dry-cleaning site. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Predicting Ambulatory Capacity in Parkinson's Disease to Analyze Progression, Biomarkers, and Trial Design.

BACKGROUND: In Parkinson's disease (PD), gait and balance is impaired, relatively resistant to available treatment and associated with falls and disability. Predictive models of ambulatory progression could enhance understanding of gait/balance disturbances and aid in trial design. OBJECTIVES: To predict trajectories of ambulatory abilities from baseline clinical data in early PD, relate trajectories to clinical milestones, compare biomarkers, and evaluate trajectories for enrichment of clinical trials. METHODS: Data from two multicenter, longitudinal, observational studies were used for model training (Tracking Parkinson's, n = 1598) and external testing (Parkinson's Progression Markers Initiative, n = 407). Models were trained and validated to predict individuals as having a "Progressive" or "Stable" trajectory based on changes of ambulatory capacity scores from the Movement Disorders Society Unified Parkinson's Disease Rating Scale parts II and III. Survival analyses compared time-to-clinical milestones and trial outcomes between predicted trajectories. RESULTS: On external evaluation, a support vector machine model predicted Progressive trajectories using baseline clinical data with an accuracy, weighted-F1 (proportionally weighted harmonic mean of precision and sensitivity), and sensitivity/specificity of 0.735, 0.799, and 0.688/0.739, respectively. Over 4 years, the predicted Progressive trajectory was more likely to experience impaired balance, loss of independence, impaired function and cognition. Baseline dopamine transporter imaging and select biomarkers of neurodegeneration were significantly different between predicted trajectory groups. For an 18-month, randomized (1:1) clinical trial, sample size savings up to 30% were possible when enrollment was enriched for the Progressive trajectory versus no enrichment. CONCLUSIONS: It is possible to predict ambulatory abilities from clinical data that are associated with meaningful outcomes in people with early PD. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Metadata Framework to Support Deployment of Digital Health Technologies in Clinical Trials in Parkinson's Disease.

Sensor data from digital health technologies (DHTs) used in clinical trials provides a valuable source of information, because of the possibility to combine datasets from different studies, to combine it with other data types, and to reuse it multiple times for various purposes. To date, there exist no standards for capturing or storing DHT biosensor data applicable across modalities and disease areas, and which can also capture the clinical trial and environment-specific aspects, so-called metadata. In this perspectives paper, we propose a metadata framework that divides the DHT metadata into metadata that is independent of the therapeutic area or clinical trial design (concept of interest and context of use), and metadata that is dependent on these factors. We demonstrate how this framework can be applied to data collected with different types of DHTs deployed in the WATCH-PD clinical study of Parkinson's disease. This framework provides a means to pre-specify and therefore standardize aspects of the use of DHTs, promoting comparability of DHTs across future studies.

Improving Access to Care: Telemedicine Across Medical Domains.

Over the past 20 years, the use of telemedicine has increased exponentially. Its fundamental aim is to improve access to care. In this review, we assess the extent to which telemedicine has fulfilled this promise across medical domains. Additionally, we assess whether telemedicine has improved related health outcomes. Finally, we determine who has benefited from this novel form of health care delivery. A review of the literature indicates that (a) telemedicine has improved access to care for a wide range of clinical conditions ranging from stroke to pregnancy; (b) telemedicine in select circumstances has demonstrated improved health outcomes; and (c) telemedicine has addressed geographical, but less so social, barriers to care. For telemedicine to fulfill its promise, additional evidence needs to be gathered on health outcomes and cost savings, the digital divide needs to be bridged, and policy changes that support telemedicine reimbursement need to be enacted.

The triple aim of clinical research.

The proposed triple aim of health care-enhanced patient experience, improved population health, and reduced per capita costs-can be applied to clinical research. A triple aim for clinical research would (1) improve the individual research participant's experience; (2) promote the health of populations; and (3) reduce per capita costs of clinical research. Such an approach is possible by designing trials around the needs of participants rather than sites, embracing digital measures of health, and advancing decentralized studies. Recent studies, including those evaluating therapies for COVID-19, have demonstrated the value of such an approach. Accelerating the adoption of these methods can help fulfill this new triple aim of clinical research.

Detecting Parkinson Disease Using a Web-Based Speech Task: Observational Study.

BACKGROUND: Access to neurological care for Parkinson disease (PD) is a rare privilege for millions of people worldwide, especially in resource-limited countries. In 2013, there were just 1200 neurologists in India for a population of 1.3 billion people; in Africa, the average population per neurologist exceeds 3.3 million people. In contrast, 60,000 people receive a diagnosis of PD every year in the United States alone, and similar patterns of rising PD cases-fueled mostly by environmental pollution and an aging population-can be seen worldwide. The current projection of more than 12 million patients with PD worldwide by 2040 is only part of the picture given that more than 20% of patients with PD remain undiagnosed. Timely diagnosis and frequent assessment are key to ensure timely and appropriate medical intervention, thus improving the quality of life of patients with PD. OBJECTIVE: In this paper, we propose a web-based framework that can help anyone anywhere around the world record a short speech task and analyze the recorded data to screen for PD. METHODS: We collected data from 726 unique participants (PD: 262/726, 36.1% were women; non-PD: 464/726, 63.9% were women; average age 61 years) from all over the United States and beyond. A small portion of the data (approximately 54/726, 7.4%) was collected in a laboratory setting to compare the performance of the models trained with noisy home environment data against high-quality laboratory-environment data. The participants were instructed to utter a popular pangram containing all the letters in the English alphabet, "the quick brown fox jumps over the lazy dog." We extracted both standard acoustic features (mel-frequency cepstral coefficients and jitter and shimmer variants) and deep learning-based embedding features from the speech data. Using these features, we trained several machine learning algorithms. We also applied model interpretation techniques such as Shapley additive explanations to ascertain the importance of each feature in determining the model's output. RESULTS: We achieved an area under the curve of 0.753 for determining the presence of self-reported PD by modeling the standard acoustic features through the XGBoost-a gradient-boosted decision tree model. Further analysis revealed that the widely used mel-frequency cepstral coefficient features and a subset of previously validated dysphonia features designed for detecting PD from a verbal phonation task (pronouncing "ahh") influence the model's decision the most. CONCLUSIONS: Our model performed equally well on data collected in a controlled laboratory environment and in the wild across different gender and age groups. Using this tool, we can collect data from almost anyone anywhere with an audio-enabled device and help the participants screen for PD remotely, contributing to equity and access in neurological care.

A New Day: The Role of Telemedicine in Reshaping Care for Persons With Movement Disorders.

The COVID-19 pandemic has demonstrated the fragility of clinic-based care for Parkinson's disease and other movement disorders. In response to the virus, many clinics across the world abruptly closed their doors to persons with Parkinson's disease. Fortunately, a niche care model, telemedicine-first described in this journal a generation ago-emerged as the dominant means of providing care. As we adjust to a new normal, we should focus future care not on clinics but on patients. Their needs, guided by clinicians, should determine how care is delivered, whether in the clinic, at home, remotely, or by some combination. Within this patient-centered approach, telemedicine is an attractive care option but not a complete replacement for in-person consultations, which are valuable for specific problems and for those who have access. Now that many clinicians and patients have gained exposure to telemedicine, we can better appreciate its advantages (eg, convenience) and disadvantages (eg, restricted examination). We can also create a new future that utilizes the Internet, video conferencing, smartphones, and sensors. This future will bring many clinicians to one patient, connect individual experts to countless patients, use widely available devices to facilitate diagnosis, and apply novel technologies to measure the disease in new ways. These approaches, which extend to education and research, enable a future where we can care for anyone anywhere and will help us stem the tide of Parkinson's disease. © 2020 International Parkinson and Movement Disorder Society.

A roadmap for implementation of patient-centered digital outcome measures in Parkinson's disease obtained using mobile health technologies.

Obtaining reliable longitudinal information about everyday functioning from individuals with Parkinson's disease (PD) in natural environments is critical for clinical care and research. Despite advances in mobile health technologies, the implementation of digital outcome measures is hindered by a lack of consensus on the type and scope of measures, the most appropriate approach for data capture (eg, in clinic or at home), and the extraction of timely information that meets the needs of patients, clinicians, caregivers, and health care regulators. The Movement Disorder Society Task Force on Technology proposes the following objectives to facilitate the adoption of mobile health technologies: (1) identification of patient-centered and clinically relevant digital outcomes; (2) selection criteria for device combinations that offer an acceptable benefit-to-burden ratio to patients and that deliver reliable, clinically relevant insights; (3) development of an accessible, scalable, and secure platform for data integration and data analytics; and (4) agreement on a pathway for approval by regulators, adoption into e-health systems and implementation by health care organizations. We have developed a tentative roadmap that addresses these needs by providing the following deliverables: (1) results and interpretation of an online survey to define patient-relevant endpoints, (2) agreement on the selection criteria for use of device combinations, (3) an example of an open-source platform for integrating mobile health technology output, and (4) recommendations for assessing readiness for deployment of promising devices and algorithms suitable for regulatory approval. This concrete implementation guidance, harmonizing the collaborative endeavor among stakeholders, can improve assessments of individuals with PD, tailor symptomatic therapy, and enhance health care outcomes. © 2019 International Parkinson and Movement Disorder Society.

Patient and Physician Perceptions of Virtual Visits for Parkinson's Disease: A Qualitative Study.

Background and Introduction: Delivering care through telemedicine directly into the patient's home is increasingly feasible, valuable, and beneficial. However, qualitative data on how patients' and physicians' perceive these virtual house calls are lacking. We conducted a qualitative analysis of perceptions of these visits for Parkinson's disease to (1) determine how patients and physicians perceive virtual visits and (2) identify components contributing to positive and negative perceptions. MATERIALS AND METHODS: Qualitative survey data were collected from patients and physicians during a 12-month randomized controlled trial of virtual house calls for Parkinson's disease. Data from 149 cases were analyzed using case-based qualitative content analysis and quantitative sentiment analysis techniques. RESULTS: Positive and negative perceptions of virtual visits were driven by three themes: (1) personal benefits of the virtual visit, (2) perceived quality of care, and (3) perceived quality of interpersonal engagement. In general, participants who identified greater personal benefit, high quality of care, and good interpersonal engagement perceived visits positively. Technical problems with the software were commonly mentioned. The sentiment analysis for patients was strongly favorable (+2.5) and moderately favorable for physicians (+0.8). Physician scores were lowest (-0.3) for the ability to perform a detailed motor examination remotely. DISCUSSION: Patients and providers generally view telemedicine favorably, but individual experiences are dependent on technical issues. CONCLUSIONS: Satisfaction with and effectiveness of remote care will likely increase as common technical problems are resolved.

Telemedicine Use for Movement Disorders: A Global Survey.

BACKGROUND: Telemedicine is increasingly used to care for patients with movement disorders, but data regarding its global use are limited. INTRODUCTION: To obtain baseline international data about telemedicine use among movement disorder clinicians. METHODS: An online survey was sent to all 6,056 Movement Disorder Society members in 2015. Scope, reimbursement, and perceived quality of telemedicine were assessed. RESULTS: There were 549 respondents (9.1% overall response rate) from 83 countries. Most (85.8%) were physicians, and most (70.9%) worked in an academic or university practice. Half of respondents (n = 287, from 57 countries) used telemedicine for clinical care; activities included e-mail (63.2%), video visits (follow-up [39.7%] and new [35.2%]), and video-based education (35.2%). One hundred five respondents personally conducted video visits, most frequently to outpatient clinics (53.5%), patient homes (30.8%), and hospital inpatients (30.3%). The most common challenges were a limited neurological examination (58.9%) and technological difficulties (53.3%), and the most common benefits were reduced travel time (92.9%) and patient costs (60.1%). The most frequent reimbursements were none (39.0%), public insurance (24.5%), and patient payment (9.3%). Half of respondents planned to use telemedicine in the future, and three-quarters were interested in telemedicine education. CONCLUSIONS: More than 250 respondents around the world engage in telemedicine for movement disorders; most perceived benefit for patients, despite challenges and reimbursement for clinicians. Formal instruction on telemedicine is highly desired. Although the survey response was low and possibly biased to over represent those with telemedicine experience, the study provides baseline data for future comparison and to improve telemedicine delivery.

Telemedicine for Parkinson's Disease: Limited Engagement Between Local Clinicians and Remote Specialists.

INTRODUCTION: The integration of remote specialists into local care teams has not been widely evaluated. METHODS: Therefore, we surveyed clinicians whose patients with Parkinson's disease had participated in a national randomized controlled trial of video visits to determine (1) whether clinicians received recommendations from remote specialists; (2) whether those recommendations were implemented; (3) what barriers to specialty care local clinicians perceived; and (4) whether they would recommend video visits. RESULTS: Of 183 clinicians surveyed, 89 (49%) responded. Less than half received the recommendations of remote specialists, but they implemented most of the recommendations they received and found them to be beneficial. CONCLUSION: The greatest perceived barrier among respondents was distance from patient to specialist, and 40% of local clinicians would recommend video visits. As telemedicine grows, improved communication between remote specialists and local clinicians is likely needed.

Forgiven but not Relieved: US Physician Workforce Consequences of Changes to Public Service Loan Forgiveness.

Public Service Loan Forgiveness (PSLF) was established in 2007 for public sector and nonprofit enterprise employees to pursue educational loan forgiveness. Under PSLF, graduates are offered complete loan forgiveness after 120 qualifying monthly payments while employed at public or nonprofit institutions, including payments made during residency for physicians. In response to concerns that PSLF will heavily subsidize lawyers, doctors, and other professionals, the President's 2017 budget proposes limiting maximum forgiveness. Using data from the Association of American Medical Colleges Graduation Questionnaire (n = 55,905; response rate of 80 %), we found that intended participation in PSLF among medical school graduates grew 20 % per year since 2010. Future primary care physicians intend to use PSLF more than programs that were historically designed to promote primary care, such as the National Health Service Corp (NHSC). The federal government's projected cost of PSLF will reach over $316 million for 2014 graduates (net present value), approximately seven times the annual contributions from the NHSC. The proposed cap will reduce the total anticipated forgiveness by nearly two-thirds and substantially reduce subsidies for physicians. More targeted measures of loan forgiveness could be considered, such as making forgiveness contingent on pursuing specialties that society needs or practicing in shortage areas.

Hospital care for mental health and substance abuse conditions in Parkinson's disease.

OBJECTIVE: The objective of this study was to examine mental health conditions among hospitalized individuals with Parkinson's disease in the United States. METHODS: This was a serial cross-sectional study of hospitalizations of individuals aged ≥60 identified in the Nationwide Inpatient Sample dataset from 2000 to 2010. We identified all hospitalizations with a diagnosis of PD, alcohol abuse, anxiety, bipolar disorder, depression, impulse control disorders, mania, psychosis, substance abuse, and attempted suicide/suicidal ideation. National estimates of each mental health condition were compared between hospitalized individuals with and without PD. Hierarchical logistic regression models determined which inpatient mental health diagnoses were associated with PD, adjusting for demographic, payer, geographic, and hospital characteristics. RESULTS: We identified 3,918,703 mental health and substance abuse hospitalizations. Of these, 2.8% (n = 104, 437) involved a person also diagnosed with PD. The majority of mental health and substance abuse patients were white (86.9% of PD vs 83.3% of non-PD). Women were more common than men in both groups (male:female prevalence ratio, PD: 0.78, 0.78-0.79, non-PD: 0.58, 0.57-0.58). Depression (adjusted odds ratio 1.32, 1.31-1.34), psychosis (adjusted odds ratio 1.25, 1.15-1.33), bipolar disorder (adjusted odds ratio 2.74, 2.69-2.79), impulse control disorders (adjusted odds ratio 1.51, 1.31-1.75), and mania (adjusted odds ratio 1.43, 1.18-1.74) were more likely among PD patients, alcohol abuse was less likely (adjusted odds ratio 0.26, 0.25-0.27). We found no PD-associated difference in suicide-related care. CONCLUSIONS: PD patients have unique patterns of acute care for mental health and substance abuse. Research is needed to guide PD treatment in individuals with pre-existing psychiatric illnesses, determine cross provider reliability of psychiatric diagnoses in PD patients, and inform efforts to improve psychiatric outcomes. © 2016 International Parkinson and Movement Disorder Society.

A review of disease progression models of Parkinson's disease and applications in clinical trials.

Quantitative disease progression models for neurodegenerative disorders are gaining recognition as important tools for drug development and evaluation. In Parkinson's disease (PD), several models have described longitudinal changes in the Unified Parkinson's Disease Rating Scale (UPDRS), one of the most utilized outcome measures for PD trials assessing disease progression. We conducted a literature review to examine the methods and applications of quantitative disease progression modeling for PD using a combination of key words including "Parkinson disease," "progression," and "model." For this review, we focused on models of PD progression quantifying changes in the total UPDRS scores against time. Four different models reporting equations and parameters have been published using linear and nonlinear functions. The reasons for constructing disease progression models of PD thus far have been to quantify disease trajectories of PD patients in active and inactive treatment arms of clinical trials, to quantify and discern symptomatic and disease-modifying treatment effects, and to demonstrate how model-based methods may be used to design clinical trials. The historical lack of efficiency of PD clinical trials begs for model-based simulations in planning for studies that result in more informative conclusions, particularly around disease modification. © 2016 International Parkinson and Movement Disorder Society.

Moving Parkinson care to the home.

In many ways, the care of individuals with Parkinson disease does not meet their needs. Despite the documented benefits of receiving care from clinicians with Parkinson disease expertise, many patients (if not most) do not. Moreover, current care models frequently require older individuals with impaired mobility, cognition, and driving ability to be driven by overburdened caregivers to large, complex urban medical centers. Moving care to the patient's home would make Parkinson disease care more patient-centered. Demographic factors, including aging populations, and social factors, such as the splintering of the extended family, will increase the need for home-based care. Technological advances, especially the ability to assess and deliver care remotely, will enable the transition of care back to the home. However, despite its promise, this next generation of home-based care will have to overcome barriers, including outdated insurance models and a technological divide. Once these barriers are addressed, home-based care will increase access to high quality care for the growing number of individuals with Parkinson disease. © 2016 International Parkinson and Movement Disorder Society.

Technology in Parkinson's disease: Challenges and opportunities.

The miniaturization, sophistication, proliferation, and accessibility of technologies are enabling the capture of more and previously inaccessible phenomena in Parkinson's disease (PD). However, more information has not translated into a greater understanding of disease complexity to satisfy diagnostic and therapeutic needs. Challenges include noncompatible technology platforms, the need for wide-scale and long-term deployment of sensor technology (among vulnerable elderly patients in particular), and the gap between the "big data" acquired with sensitive measurement technologies and their limited clinical application. Major opportunities could be realized if new technologies are developed as part of open-source and/or open-hardware platforms that enable multichannel data capture sensitive to the broad range of motor and nonmotor problems that characterize PD and are adaptable into self-adjusting, individualized treatment delivery systems. The International Parkinson and Movement Disorders Society Task Force on Technology is entrusted to convene engineers, clinicians, researchers, and patients to promote the development of integrated measurement and closed-loop therapeutic systems with high patient adherence that also serve to (1) encourage the adoption of clinico-pathophysiologic phenotyping and early detection of critical disease milestones, (2) enhance the tailoring of symptomatic therapy, (3) improve subgroup targeting of patients for future testing of disease-modifying treatments, and (4) identify objective biomarkers to improve the longitudinal tracking of impairments in clinical care and research. This article summarizes the work carried out by the task force toward identifying challenges and opportunities in the development of technologies with potential for improving the clinical management and the quality of life of individuals with PD. © 2016 International Parkinson and Movement Disorder Society.