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Updated: May 27, 2026
Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Published on: June 26, 2013
Multiparametric MRI and imaging transcriptomics reveal molecular and cellular correlates of neurodegeneration in
Eugene Kim1, Diana Cash1, Daniel Martins1,2,3
1The Brain Centre, Department of Neuroimaging; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
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.
Insights
This study links brain imaging patterns to gene expression in a mouse model of Multiple System Atrophy (MSA). Findings reveal molecular underpinnings of MSA's neurodegeneration and validate imaging biomarkers for synucleinopathies.
Area of Science:
- Neuroscience
- Biomedical Imaging
- Genomics
Background:
- Multiple system atrophy (MSA) is a neurodegenerative disorder characterized by alpha-synuclein accumulation and neuronal loss.
- Magnetic Resonance Imaging (MRI) detects brain atrophy and microstructural changes in MSA, but underlying molecular mechanisms are unclear.
- Imaging transcriptomics links spatial imaging data with gene expression, but prior human studies lacked experimental control and molecular validation.
Purpose of the Study:
- To apply imaging transcriptomics in a controlled preclinical model of MSA.
- To integrate high-resolution ex vivo multimodal MRI with transcriptomic mapping in the PLP-αSyn mouse model.
- To establish a translational framework for interpreting imaging biomarkers in synucleinopathies.
Main Methods:
- Utilized multimodal MRI (structural and diffusion) on the PLP-αSyn mouse model of MSA.
- Performed transcriptomic mapping and RNA-sequencing.
- Applied atlas-based analyses to associate imaging phenotypes with gene expression patterns.
Main Results:
- Structural and diffusion MRI identified distinct patterns of regional atrophy and microstructural abnormalities.
- Imaging phenotypes correlated with gene programs involved in oligodendrocyte biology, energy metabolism, and neuroinflammation.
- Associations were validated by independent RNA-sequencing and showed convergence with human MSA findings.
Conclusions:
- This study establishes MRI-transcriptomic relationships in a preclinical MSA model.
- The findings provide a translational framework for understanding imaging biomarkers in synucleinopathies.
- The research clarifies molecular substrates underlying MRI phenotypes in MSA.
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