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<p>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.</p>

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

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月25日

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

摘要

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.