Evidence map›Paper›PMID 42185343›Full record

ArticleNPJ Parkinson's disease2026

Multiparametric MRI and imaging transcriptomics reveal molecular and cellular correlates of neurodegeneration in experimental Parkinsonism.

Eugene Kim, Diana Cash, Daniel Martins, Camilla Simmons, Antonio Heras-Garvin, Elena Klippel, Florian Krismer, Laura Mantoan Ritter, Nadia Stefanova

Abstract read
In one paragraph

Article in NPJ Parkinson's disease, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Eugene KimThe Brain Centre, Department of Neuroimaging; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
Diana CashThe Brain Centre, Department of Neuroimaging; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
Daniel MartinsThe Brain Centre, Department of Neuroimaging; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
Camilla SimmonsThe Brain Centre, Department of Neuroimaging; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
Antonio Heras-GarvinDivision of Neurobiology, Department of Neurology, Medical University Innsbruck, Innsbruck, Austria.
Elena KlippelDivision of Neurobiology, Department of Neurology, Medical University Innsbruck, Innsbruck, Austria.
Florian KrismerDivision of Neurobiology, Department of Neurology, Medical University Innsbruck, Innsbruck, Austria.
Laura Mantoan Ritter *Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
Nadia Stefanova *Division of Neurobiology, Department of Neurology, Medical University Innsbruck, Innsbruck, Austria. nadia.stefanova@i-med.ac.at.ORCID http://orcid.org/0000-0001-8188-639X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multiple system atrophy (MSA) is an atypical Parkinsonian disorder marked by oligodendroglial α-synucleinopathy and selective neurodegeneration. Although MRI can capture regional atrophy and microstructural alterations in the MSA brain, the molecular substrates underlying these phenotypes remain poorly defined. Imaging transcriptomics provides a computational framework to relate spatial imaging patterns to brain-wide gene expression. While this approach has been applied to human MSA, interpretation is constrained by limited experimental control and a lack of disease-matched molecular validation. Here, we apply imaging transcriptomics in a controlled preclinical setting by integrating high-resolution ex vivo multimodal MRI with transcriptomic mapping in the PLP-αSyn mouse model of MSA. Structural and diffusion MRI revealed distinct patterns of regional atrophy and microstructural abnormalities. Atlas-based analyses associated imaging phenotypes with gene programs related to oligodendrocyte biology, energy metabolism, and neuroinflammation, with modality-specific signatures. These associations were supported by independent RNA-sequencing and showed convergence with human MSA findings. Our work benchmarks MRI-transcriptomic relationships in MSA and provides a translational framework for interpreting imaging biomarkers in synucleinopathies.

Identifiers

PMID42185343
PMCPMC13482189

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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.