Evidence map›Paper›PMID 40567892›Full record

ArticleNeuroimage. Reports2025

Unsupervised subtyping of motor dysfunction of Parkinson's disease and its structural brain imaging correlates.

Yu-Fan Lin, Jong-Ling Fuh, Albert C Yang

Abstract read
In one paragraph

Article in Neuroimage. Reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Yu-Fan LinSchool of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.
Jong-Ling FuhSchool of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.
Albert C YangSchool of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Parkinson's disease (PD) is a clinical neurodegenerative disorder. The Unified Parkinson's Disease Rating Scale (UPDRS) has been used as a standard measure of the PD symptom profile, and magnetic resonance (MR) imaging is widely used for identifying the critical brain regions involved in PD progression. Objectives: The present study aimed to (1) identify PD subtypes based on the motor dysfunction profile in the MDS-UPDRS and (2) find the differences in gray matter volumes of brain regions, and (3) compare non-motor features between the subtypes to explore their distinct clinical profiles. Methods: In total, 299 patients with PD and 173 healthy participants from the Parkinson's Progression Markers Initiative were included. A software package, Generalized Association Plots, was used to cluster the motor dysfunction profile in the MDS-UPDRS. Regression models and the Artificial Intelligence Platform as a Service were used to quantify the differences in gray matter volume of brain regions between subtypes. Results: We identified three PD subtypes-resting tremor, intermediate, and akinetic-rigid-using motor symptom clustering. MRI analysis revealed significant differences in brain regions, including the posterior cingulate gyrus, lenticular nucleus, olfactory cortex, and cerebellum. Non-motor features, such as cognitive decline and autonomic dysfunctions, varied across subtypes, highlighting distinct systemic profiles. Akinetic-rigid patients exhibited the most severe impairments, while tremor-dominant patients showed milder non-motor symptoms. Discussion: Three PD subtypes of motor dysfunction were identified. Structural brain imaging revealed subtype-specific differences not only in cingulum and putamen regions, but also in the olfactory cortex, parahippocampal gyrus, and cerebellum, correlating with motor symptoms. Non-motor features varied by subtype, with increasing severity from tremor-dominant to akinetic-rigid.

Indexed as

Machine learningMotor dysfunction subtypesParkinson's diseaseStructural brain imaging

Identifiers

PMID40567892
PMCPMC12172897

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.