Safety and Feasibility of Serial Lumbar Punctures: Long-term Results from the Parkinson's Progression Markers Initiative.

Background: Cerebrospinal fluid (CSF) serves an essential role in biomarker research. New Parkinson's disease (PD) classifications incorporate CSF α-synuclein status into trial design. This study evaluated the safety and feasibility of serial CSF collection in participants enrolled in the Parkinson's Progression Markers Initiative (PPMI).

Improving Prediction of Falls and Cognitive Impairment in Parkinson Disease: Protocol for a Decentralized Observational Study.

Background: Falls and cognitive impairment are major sources of disability in Parkinson disease (PD). The ability to accurately identify individuals with PD at high risk for falls and cognitive impairment would provide an opportunity for intervention and potentially improve long-term outcomes. In a previous study, Assessing Telehealth Outcomes in Multiyear Extensions of Parkinson Disease Trials (AT-HOME PD), we remotely characterized participants with early PD who had participated in 1 of 2 PD clinical trials over 2 years of follow-up.

Stable two-year longitudinal clinical outcomes in LRRK2 G2019S non-manifest carriers in a remote nationwide study.

Background: Interest in Parkinson's disease (PD) prevention trials is growing, and genetically at-risk individuals may be ideal candidates. LRRK2 G2019S is the most common autosomal dominant genetic cause of PD and exhibits incomplete penetrance.

Objective: In a remote, prospective cohort study of LRRK2 G2019S carriers without PD, we examined change over time to better understand the natural history of LRRK2 PD.

Remote AI Screening for Parkinson's Disease: A Multimodal, Cross-Setting Validation Study.

PARK is a web-based artificial intelligence (AI) tool for remote screening of Parkinson's disease (PD) using video and audio recordings of speech, facial expression, and motor tasks performed via webcam. The study draws on data from 1,865 participants across diverse global demographics and recording environments, including supervised clinical settings and unsupervised home use. On three independent test sets (n=389; 188 with PD), PARK achieved strong predictive performance on classifying individuals with and without PD, with accuracy ranging from 80.

Long-Term Outcomes in a Parkinson's Disease Minor Phenomena Cohort.

Background: Minor phenomena, including illusions, feeling of presence, and passage hallucinations, are common in Parkinson's disease (PD) and may be a risk factor for the development of psychosis (hallucinations and delusions).

Objectives: The objective of this study was to determine the 3-year cumulative probability of developing psychosis among individuals with PD minor phenomena.

Methods: We conducted a 3-year, prospective, observational study of individuals with PD minor phenomena with biannual study visits.

Using wearable sensors and machine learning to assess upper limb function in Huntington's disease.

Background: Huntington's disease, a neurodegenerative disorder, impairs both upper and lower limb function, typically assessed in clinical settings. However, wearable sensors offer the opportunity to monitor real-world data that complements clinical assessments, providing a more comprehensive understanding of disease symptoms.

Methods: In this study, we monitor upper limb function in individuals with Huntington's disease (HD, n = 16), prodromal HD (pHD, n = 7), and controls (CTR, n = 16) using a wrist-worn wearable sensor over a 7-day period.

Return of individual research results to participants with and at risk for Parkinson's disease.

In a prospective, remote natural history study of 277 individuals with (60) and genetically at risk for (217) Parkinson's disease (PD), we examined interest in the return of individual research results (IRRs) and compared characteristics of those who opted for versus against the return of IRRs. Most ( = 180, 65%) requested sharing of IRRs with either a primary care provider, neurologist, or themselves. Among individuals without PD, those who requested sharing of IRRs with a clinician reported more motor symptoms than those who did not request any sharing (mean (SD) 2.

Digital assessment of speech in Huntington disease.

Background: Speech changes are an early symptom of Huntington disease (HD) and may occur prior to other motor and cognitive symptoms. Assessment of HD commonly uses clinician-rated outcome measures, which can be limited by observer variability and episodic administration. Speech symptoms are well suited for evaluation by digital measures which can enable sensitive, frequent, passive, and remote administration.

The Importance of Digital Health Literacy in an Evolving Parkinson's Disease Care System.

Digital health technologies are growing at a rapid pace and changing the healthcare landscape. Our current understanding of digital health literacy in Parkinson's disease (PD) is limited. In this review, we discuss the potential challenges of low digital health literacy in PD with particular attention to telehealth, deep brain stimulation, wearable sensors, and smartphone applications.

Using AI to measure Parkinson's disease severity at home.

We present an artificial intelligence (AI) system to remotely assess the motor performance of individuals with Parkinson's disease (PD). In our study, 250 global participants performed a standardized motor task involving finger-tapping in front of a webcam. To establish the severity of Parkinsonian symptoms based on the finger-tapping task, three expert neurologists independently rated the recorded videos on a scale of 0-4, following the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS).

Minor Phenomena in Parkinson's Disease-Prevalence, Associations, and Risk of Developing Psychosis.

Background: Minor phenomena, including passage phenomena, feeling of presence, and illusions, are common and may represent a prodromal form of psychosis in Parkinson's disease (PD). We examined the prevalence and clinical correlates of minor phenomena, and their potential role as a risk factor for PD psychosis.

Methods: A novel questionnaire, the Psychosis and Mild Perceptual Disturbances Questionnaire for PD (PMPDQ), was completed by Fox Insight cohort participants with and without PD.

Trichloroethylene: An Invisible Cause of Parkinson's Disease?

The etiologies of Parkinson's disease (PD) remain unclear. Some, such as certain genetic mutations and head trauma, are widely known or easily identified. However, these causes or risk factors do not account for the majority of cases.

Monitoring gait at home with radio waves in Parkinson's disease: A marker of severity, progression, and medication response.

Parkinson's disease (PD) is the fastest-growing neurological disease in the world. A key challenge in PD is tracking disease severity, progression, and medication response. Existing methods are semisubjective and require visiting the clinic.

A Remote Longitudinal Observational Study of Individuals at Genetic Risk for Parkinson Disease: Baseline Results.

Background And Objectives: To recruit and characterize a national cohort of individuals who have a genetic variant ( G2019S) that increases risk of Parkinson disease (PD), assess participant satisfaction with a decentralized, remote research model, and evaluate interest in future clinical trials.

Methods: In partnership with 23andMe, Inc., a personal genetics company, G2019S carriers with and without PD were recruited to participate in an ongoing 36-month decentralized, remote natural history study.

Change in the Parkinson Anxiety Scale correlates with change in other clinical measures of anxiety over time.

The Parkinson's disease (PD)-specific Parkinson Anxiety Scale (PAS) is an anxiety rating scale that has been validated in cross-sectional studies. In a study of buspirone for anxiety in PD, it appears that the PAS may be sensitive to change in anxiety demonstrating moderate-to-high correlation with participant-reported and clinician-administered scales.

Recruitment for Remote Decentralized Studies in Parkinson's Disease.

Background: Traditional in-person Parkinson's disease (PD) research studies are often slow to recruit and place unnecessary burden on participants. The ongoing COVID-19 pandemic has added new impetus to the development of new research models.

Objective: To compare recruitment processes and outcomes of three remote decentralized observational PD studies with video visits.