Progression subtypes in Parkinson's disease identified by a data-driven multi cohort analysis.

ABSTRACT: The progression of Parkinson's disease (PD) is heterogeneous across patients, affecting counseling and inflating the number of patients needed to test potential neuroprotective treatments. Moreover, disease subtypes might require different therapies. This work uses a data-driven approach to investigate how observed heterogeneity in PD can be explained by the existence of distinct PD progression subtypes. To derive stable PD progression subtypes in an unbiased manner, we analyzed multimodal longitudinal data from three large PD cohorts and performed extensive cross-cohort validation. A latent time joint mixed-effects model (LTJMM) was used to align patients on a common disease timescale. Progression subtypes were identified by variational deep embedding with recurrence (VaDER). In each coho

SUBMITTER: Hahnel T 

PROVIDER: S-EPMC11066039 | biostudies-literature | 2024 May

REPOSITORIES: biostudies-literature