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Movement disorders : official journal of the Movement Disorder Society

September 3, 2026 · via Europe PMC

Distinct Spatiotemporal Patterns of Dopaminergic and Metabolic Imaging in De Novo Parkinson's Disease.

Lee JH, Na HK, Ahn SJ, +5 more, Lyoo CH.

Journal ArticleAbstract only — full text under license

AI summary — for doctors, generated from the abstract only

Combined dopaminergic and metabolic PET identified two subtypes of de novo Parkinson disease, one with more severe nonmotor features.

What was studied

A study of 147 drug-naive PD patients and 38 controls with FDG and FP-CIT PET analyzed using the SuStaIn algorithm.

Key findings

  • Subtype 1: fronto-striatal hypometabolism early
  • Subtype 2: mixed hypermetabolic-posterior hypometabolic pattern
  • Motor deficits similar; subtype 2 had worse cognition, olfaction, anxiety and RBD scores
  • Stage correlated with cognitive decline only in subtype 2

Clinical relevance

May aid research on PD heterogeneity and prognosis; cross-sectional subtyping needs longitudinal validation.

Who should care

Neurology

Limitations

Cross-sectional data from a single cohort.

De novo PD may comprise distinct metabolic subtypes.

This is an AI-generated summary of the published abstract, not a clinical recommendation. It may not reflect the full text or subsequent updates — verify against the original source before acting on it.

Abstract

Background

Understanding the heterogeneity of Parkinson's disease (PD) is essential to guide patient care, prognosis, and treatment.

Objective

We used 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET), 18F-N-(3-fluoropropyl)-2β-carbomethoxy-3β-(4-iodophenyl) nortropane (18F-FP-CIT) PET, and Subtype and Stage Inference (SuStaIn) algorithm to define subtypes in drug-naive patients with PD.

Methods

A total of 147 de novo PD patients and 38 healthy individuals who underwent 18F-FDG PET, 18F-FP-CIT, and brain magnetic resonance imaging were enrolled. The SuStaIn algorithm was employed to identify FP-CIT- and FDG-based subtypes. Motor and nonmotor features were compared between them. Correlations were analyzed to assess the associations between the progression stage and motor or cognitive scores within each subtype.

Results

Two distinct subtypes were identified: subtype 1 (fronto-striatal hypometabolic) and subtype 2 (mixed hypermetabolic-posterior hypometabolic). In subtype 1, striatal dopamine transporter (DAT) loss was accompanied by decreases in frontal and caudate metabolism at earlier stages, whereas hypometabolism in the posterior cortical and limbic regions appeared at later stages. In subtype 2, striatal DAT deficit and hypermetabolism of the putamen, medial temporal, and anterior cingulate cortices and lateral occipital hypometabolism appeared in the early stages. This metabolic reduction subsequently involved parieto-temporal, frontal, and limbic regions. Motor deficits were comparable between the subtypes. Those with subtype 2 exhibited poorer cognitive and olfactory performance, higher anxiety scores, higher Rapid Eye Movement Behavior Disorder Screening Questionnaire scores, and lower putaminal DAT availability and asymmetry than in subtype 1. The stage correlated with cognitive decline only in subtype 2, with a marginally significant stage-by-group interaction.

Conclusions

De novo PD can be classified into two distinct metabolic subtypes: fronto-striatal hypometabolic and mixed hypermetabolic-posterior hypometabolic, with nonmotor manifestations being more severe in the latter. © 2026 International Parkinson and Movement Disorder Society.

DOI

10.1002/mds.70498

PMID

42693703

Research metadata (titles, abstracts, authors, publication dates) is sourced from Europe PMC, which aggregates content from PubMed/MEDLINE, PubMed Central, and other providers under the U.S. National Library of Medicine (NLM/NCBI). NLM does not claim copyright on abstracts; the original journal publishers or authors may hold rights to the full articles. AI-generated summaries are derived only from the abstract, never the full text, and are always labeled as AI-generated.

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