Longitudinal Imaging Biomarkers Correlate with Progressive Motor Deficit in the Mouse Model of Charlevoix-Saguenay Ataxia

纵向影像生物标志物与夏洛瓦-萨格奈共济失调小鼠模型的进行性运动功能障碍相关

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作者:Valentina Gigliucci ,Su-Chun Huang ,Giorgio Boschetti ,Alessandra Scaravilli ,Valerio Castoldi ,Paola Podini ,Angelo Quattrini ,Sirio Cocozza ,Letizia Leocani ,Francesca Maltecca

Abstract

Objective: In autosomal recessive spastic ataxia of Charlevoix-Saguenay (ARSACS) disease, severity and age of onset vary greatly, hindering to objectively measure and predict clinical progression. Thickening of the retinal nerve fiber layer is distinctive of ARSACS patients, as assessed by optical coherence tomography, whereas conventional brain magnetic resonance imaging findings include both supratentorial and infratentorial changes. Because longitudinal imaging studies in ARSACS patients are not available to define these changes as biomarkers of disease progression, we aimed to address this issue in the ARSACS mouse model. Methods: We performed longitudinal retinal OCT and brain MRI in the Sacs-/- ARSACS mouse model, alongside motor and coordination assessment in the beam walking test. We also investigated visual function and the molecular mechanisms underlying RNFL increased thickness by histology and immunofluorescence. Results: We demonstrated that RNFL thickening by OCT gradually increases in the early stages of pathology in the Sacs-/- mouse model, reflecting the progression of motor impairment, and later reaches a plateau when thinning of the posterior corpus callosum becomes detectable by MRI. Mechanistically, we unveiled that RNFL thickening is associated with aberrant accumulation of non-phosphorylated neurofilament H and glial fibrillary acidic protein. We also uncovered mild signs of myelin pathology coherent with increased latency of visual evoked potentials, and altered retinal activation by photopic electroretinography. Interpretation: We show that both RNFL thickening and MRI changes may represent biomarkers of disease progression in the Sacs-/- mouse model. Our data gathers knowledge instrumental to clinical studies, holding potential as readout for treatment efficacy. ANN NEUROL 2025;97:425-434.

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