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Updated: Dec 11, 2025

Author Spotlight: Establishing a New Fluorescence-Based Protocol for In Vivo Mitochondrial Morphology Analysis in Parkinson's Disease
Published on: June 23, 2023
Association of specific biotypes in patients with Parkinson disease and disease progression
Linbo Wang1, Wei Cheng2, Edmund T Rolls1
1From the Institute of Science and Technology for Brain-inspired Intelligence (L.W., W.C., E.R., F.D, W.G., J. D., W.Z., S.W., J.F.), Fudan University; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (L.W., W.C., J. D., W.Z., S.W., J.F.) (Fudan University), Ministry of Education, Shanghai, China; Department of Computer Science (E.R., J.F.), University of Warwick, Coventry; Oxford Centre for Computational Neuroscience (E.R.), UK; Department of Neurology and National Clinical Research Center for Aging and Medicine (F.L., J.W.), Huashan Hospital, Fudan University, Shanghai, China; and Medical Research Council Brain Network Dynamics Unit (P.B.) and Nuffield Department of Clinical Neurosciences (P.B.), University of Oxford, UK.
Objective:
To identify biotypes in patients with newly diagnosed Parkinson disease (PD) and to test whether these biotypes could explain interindividual differences in longitudinal progression.
Methods:
In this longitudinal analysis, we use a data-driven approach clustering PD patients from the Parkinson's Progression Markers Initiative (n = 314, age 61.0 ± 9.5, years 34.1% female, 5 years of follow-up). Voxel-level neuroanatomic features were estimated with deformation-based morphometry (DBM) of T1-weighted MRI. Voxels with deformation values that were significantly correlated (p < 0.01) with clinical scores (Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale Parts I-III and total score, tremor score, and postural instability and gait difficulty score) at baseline were selected. Then, these neuroanatomic features were subjected to hierarchical cluster analysis. Changes in the longitudinal progression and neuroanatomic pattern were compared between different biotypes.
Results:
Two neuroanatomic biotypes were identified: biotype 1 (n = 114) with subcortical brain volumes smaller than heathy controls and biotype 2 (n = 200) with subcortical brain volumes larger than heathy controls. Biotype 1 had more severe motor impairment, autonomic dysfunction, and much worse REM sleep behavior disorder than biotype 2 at baseline. Although disease durations at the initial visit and follow-up were similar between biotypes, patients with PD with smaller subcortical brain volume had poorer prognosis, with more rapid decline in several clinical domains and in dopamine functional neuroimaging over an average of 5 years.
Conclusion:
Robust neuroanatomic biotypes exist in PD with distinct clinical and neuroanatomic patterns. These biotypes can be detected at diagnosis and predict the course of longitudinal progression, which should benefit trial design and evaluation.
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