Peripheral immune cell response to stimulation stratifies Parkinson's disease progression from prodromal to clinical stages.

The motor stage of idiopathic Parkinson's disease (iPD) can be preceded for years by a prodromal stage characterized by non-motor symptoms like REM sleep behavior disorder (RBD). Here, we show that multiple stages of iPD, including the pre-motor prodromal stage, can be stratified according to the inflammatory and immunometabolic responses to stimulation of peripheral blood mononuclear cells . We identified increased stimulation-dependent secretion of TNF, IL-1β, and IL-8 in monocytes from RBD patients and showed diminished proinflammatory cytokine secretion in monocytes and T cells in early and moderate stages of PD.

A General Neurologist's Practical Diagnostic Algorithm for Atypical Parkinsonian Disorders: A Consensus Statement.

Purpose Of Review: The most common four neurodegenerative atypical parkinsonian disorders (APDs) are progressive supranuclear palsy (PSP), multiple system atrophy (MSA), corticobasal syndrome (CBS), and dementia with Lewy bodies (DLB). Their formal diagnostic criteria often require subspecialty experience to implement as designed and all require excluding competing diagnoses without clearly specifying how to do that. Validated diagnostic criteria are not available at all for many of the other common APDs, including normal pressure hydrocephalus (NPH), vascular parkinsonism (VP), or drug-induced parkinsonism (DIP).

What the trained eye cannot see: Quantitative kinematics and machine learning detect movement deficits in early-stage Parkinson's disease from videos.

Background: Evaluation of disease severity in Parkinson's disease (PD) relies on motor symptoms quantification. However, during early-stage PD, these symptoms are subtle and difficult to quantify by experts, which might result in delayed diagnosis and suboptimal disease management.

Objective: To evaluate the use of videos and machine learning (ML) for automatic quantification of motor symptoms in early-stage PD.

Characterizing Disease Progression in Parkinson's Disease from Videos of the Finger Tapping Test.

Introduction: Parkinson's disease (PD) is characterized by motor symptoms whose progression is typically assessed using clinical scales, namely the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS). Despite its reliability, the scale is bounded by a 5-point scale that limits its ability to track subtle changes in disease progression and is prone to subjective interpretations. We aimed to develop an automated system to objectively quantify motor symptoms in PD using Machine Learning (ML) algorithms to analyze videos and capture nuanced features of disease progression.

Skin Biopsy Detection of Phosphorylated α-Synuclein in Patients With Synucleinopathies.

Importance: Finding a reliable diagnostic biomarker for the disorders collectively known as synucleinopathies (Parkinson disease [PD], dementia with Lewy bodies [DLB], multiple system atrophy [MSA], and pure autonomic failure [PAF]) is an urgent unmet need. Immunohistochemical detection of cutaneous phosphorylated α-synuclein may be a sensitive and specific clinical test for the diagnosis of synucleinopathies.

Objective: To evaluate the positivity rate of cutaneous α-synuclein deposition in patients with PD, DLB, MSA, and PAF.