Longitudinal Proteomic Profiling Defines Robust Molecular Subtypes Underlying the Heterogeneity of Parkinson’s Disease
The primary goal of this study was to define proteomic subtypes to understand the heterogeneity of Parkinson’s pathophysiology with the aim of understanding whether there exists an underlying biological signature of mechanism in distinct disease phenotypes. By running unsupervised clustering approaches we have detected common modules of expression. Uniquely we have used longitudinal data to compare these groupings during disease progression. Despite the complexities of disease progression we describe robust proteomic modules with insights about mechanism and subtypes of pathology.
Authors: Rashmi Maurya, Buddhiprabha Erabadda, Sacha E Gandhi, Hanjun Zhao, Natacha Loison, Raquel Real, Huw Morris, Alejo Nevado-Holgado, Donald G Grosset, and Laura M Winchester
Affiliations: University of Oxford, University of Glasgow, University College London, The Fourth Hospital of Hebei Medical University China
Proteomic data described in this study is available on application to GNPC.
Preprint doi: https://doi.org/10.1101/2025.11.27.691036