Accelerating Parkinson's Disease drug development with federated learning approaches.

Parkinson's Disease is a progressive neurodegenerative disorder afflicting almost 12 million people. Increased understanding of its complex and heterogenous disease pathology, etiology and symptom manifestations has resulted in the need to design, capture and interrogate substantial clinical datasets. Herein we advocate how advances in the deployment of artificial intelligence models for Federated Data Analysis and Federated Learning can help spearhead coordinated and sustainable approaches to address this grand challenge.

Analysis of NINDS Health Disparities and Health Equity Research Portfolio, 2016-2020: Results and a Process for Transparency, Accuracy, and Reliability.

Background And Objectives: As detailed throughout this special issue, the National Institute of Neurological Disorders and Stroke (NINDS) recently undertook a strategic planning effort to guide the Institute's efforts and priorities in health disparities and health equity (HD/HE) research. One input into this effort was to conduct a 5-year longitudinal, in-depth analysis of NINDS-supported HD/HE research newly funded between the years 2016 and 2020. The goals of this analysis were to describe NINDS's portfolio according to consistent, contemporary definitions and HD/HE disciplinary theory.

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.

Parkinson's disease biomarkers: perspective from the NINDS Parkinson's Disease Biomarkers Program.

Biomarkers for Parkinson's disease (PD) diagnosis, prognostication and clinical trial cohort selection are an urgent need. While many promising markers have been discovered through the National Institute of Neurological Disorders and Stroke Parkinson's Disease Biomarker Program (PDBP) and other mechanisms, no single PD marker or set of markers are ready for clinical use. Here we discuss the current state of biomarker discovery for platforms relevant to PDBP.