Evidence mapPaperPMID 41361244Full record

ArticleNPJ Parkinson's disease2025

Brain age gap as predictor of disease progression in Parkinson's disease.

Tom Hähnel, Shammi More, Felix Hoffstaedter, Kaustubh R Patil, Holger Fröhlich, Björn H Falkenburger

Abstract read
In one paragraph

Article in NPJ Parkinson's disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

1 citing paper in PubMed.

  1. Association of imaging-defined brain age with disease severity and adverse outcomes in CADASIL.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Article
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

6 authors.

Tom HähnelDepartment of Neurology, Medical Faculty and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany. tom.haehnel@ukdd.de.
Shammi MoreDepartment of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, Germany.
Felix HoffstaedterInstitute of Neuroscience and Medicine (INM-7), Research Centre Jülich, Jülich, Germany.
Kaustubh R PatilInstitute of Neuroscience and Medicine (INM-7), Research Centre Jülich, Jülich, Germany.
Holger Fröhlich *Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, Germany.
Björn H Falkenburger *Department of Neurology, Medical Faculty and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany.

Funding

European Union 101168379
6 · The paper itself

Abstract

Parkinson's disease (PD) exhibits high heterogeneity in disease progression, complicating management and increasing required sample sizes for clinical trials. This study evaluates Brain Age Gap (BAG)-the difference between brain age and chronological age-for predicting disease progression in PD. Structural MRI-derived gray matter volumes were analyzed for 451 early-stage PD patients and 172 healthy controls from the PPMI cohort. PD patients had a baseline BAG of 1.1 years, with fast-progressing patients exhibiting a BAG of 3.0 years, whereas slow-progressing patients resembled the BAG of healthy controls. Higher BAG was associated with more severe baseline symptoms, faster cognitive decline in several domains, increased hazard of developing mild cognitive impairment, and faster progression of dopaminergic neuron loss in longitudinal DaTSCANs. BAG-based patient stratification could reduce sample sizes of randomized clinical trials by 23-58%. These findings suggest BAG as a prognostic biomarker of disease progression, which may accelerate the development of disease-modifying treatments.

Identifiers

PMID41361244
PMCPMC12689644

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.