Universal clinical Parkinson's disease axes identify a major influence of neuroinflammation.

ABSTRACT:

Background

There is large individual variation in both clinical presentation and progression between Parkinson's disease patients. Generation of deeply and longitudinally phenotyped patient cohorts has enormous potential to identify disease subtypes for prognosis and therapeutic targeting.

Methods

Replicating across three large Parkinson's cohorts (Oxford Discovery cohort (n = 842)/Tracking UK Parkinson's study (n = 1807) and Parkinson's Progression Markers Initiative (n = 472)) with clinical observational measures collected longitudinally over 5-10 years, we developed a Bayesian multiple phenotypes mixed model incorporating genetic relationships between individuals able to explain many diverse clinical measurements as a smaller number of continuous underlying factors ("phen

SUBMITTER: Sandor C 

PROVIDER: S-EPMC9670420 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature