Validating a minipig model of reversible cerebral demyelination using human diagnostic modalities and electron microscopy

使用人类诊断方式和电子显微镜验证可逆性脑脱髓鞘小型猪模型

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作者:Mihai Ancău, Goutam Kumar Tanti, Vicki Marie Butenschoen, Jens Gempt, Igor Yakushev, Stephan Nekolla, Mark Mühlau, Christian Scheunemann, Sebastian Heininger, Benjamin Löwe, Erik Löwe, Silke Baer, Johannes Fischer, Judith Reiser, Sai S Ayachit, Friederike Liesche-Starnecker, Jürgen Schlegel, Kaspar

Background

Inflammatory demyelinating diseases of the central nervous system, such as multiple sclerosis, are significant sources of morbidity in young adults despite therapeutic advances. Current murine models of remyelination have limited applicability due to the low white matter content of their brains, which restricts the spatial resolution of diagnostic imaging. Large animal models might be more suitable but pose significant technological, ethical and logistical challenges.

Methods

We induced targeted cerebral demyelinating lesions by serially repeated injections of lysophosphatidylcholine in the minipig brain. Lesions were amenable to follow-up using the same clinical imaging modalities (3T magnetic resonance imaging, 11C-PIB positron emission tomography) and standard histopathology protocols as for human diagnostics (myelin, glia and neuronal cell markers), as well as electron microscopy (EM), to compare against biopsy data from two patients. Findings: We demonstrate controlled, clinically unapparent, reversible and multimodally trackable brain white matter demyelination in a large animal model. De-/remyelination dynamics were slower than reported for rodent models and paralleled by a degree of secondary axonal pathology. Regression modelling of ultrastructural parameters (g-ratio, axon thickness) predicted EM features of cerebral de- and remyelination in human data. Interpretation: We validated our minipig model of demyelinating brain diseases by employing human diagnostic tools and comparing it with biopsy data from patients with cerebral demyelination. Funding: This work was supported by the DFG under Germany's Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (EXC 2145 SyNergy, ID 390857198) and TRR 274/1 2020, 408885537 (projects B03 and Z01).

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