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Selective vulnerability to atrophy in sporadic Creutzfeldt‐Jakob disease

OBJECTIVE: Identification of brain regions susceptible to quantifiable atrophy in sporadic Creutzfeldt‐Jakob disease (sCJD) should allow for improved understanding of disease pathophysiology and development of structural biomarkers that might be useful in future treatment trials. Although brain atro...

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Detalles Bibliográficos
Autores principales: Younes, Kyan, Rojas, Julio C., Wolf, Amy, Sheng‐Yang, Goh M., Paoletti, Matteo, Toller, Gianina, Caverzasi, Eduardo, Luisa Mandelli, Maria, Illán‐Gala, Ignacio, Kramer, Joel H., Cobigo, Yann, Miller, Bruce L., Rosen, Howard J., Geschwind, Michael D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8164858/
https://www.ncbi.nlm.nih.gov/pubmed/33949799
http://dx.doi.org/10.1002/acn3.51290
Descripción
Sumario:OBJECTIVE: Identification of brain regions susceptible to quantifiable atrophy in sporadic Creutzfeldt‐Jakob disease (sCJD) should allow for improved understanding of disease pathophysiology and development of structural biomarkers that might be useful in future treatment trials. Although brain atrophy is not usually present by visual assessment of MRIs in sCJD, we assessed whether using voxel‐based morphometry (VBM) can detect group‐wise brain atrophy in sCJD. METHODS: 3T brain MRI data were analyzed with VBM in 22 sCJD participants and 26 age‐matched controls. Analyses included relationships of regional brain volumes with major clinical variables and dichotomization of the cohort according to expected disease duration based on prion molecular classification (i.e., short‐duration/Fast‐progressors (MM1, MV1, and VV2) vs. long‐duration/Slow‐progressors (MV2, VV1, and MM2)). Structural equation modeling (SEM) was used to assess network‐level interactions of atrophy between specific brain regions. RESULTS: sCJD showed selective atrophy in cortical and subcortical regions overlapping with all but one region of the default mode network (DMN) and the insulae, thalami, and right occipital lobe. SEM showed that the effective connectivity model fit in sCJD but not controls. The presence of visual hallucinations correlated with right fusiform, bilateral thalami, and medial orbitofrontal atrophy. Interestingly, brain atrophy was present in both Fast‐ and Slow‐progressors. Worse cognition was associated with bilateral mesial frontal, insular, temporal pole, thalamus, and cerebellum atrophy. INTERPRETATION: Brain atrophy in sCJD preferentially affects specific cortical and subcortical regions, with an effective connectivity model showing strength and directionality between regions. Brain atrophy is present in Fast‐ and Slow‐progressors, correlates with clinical findings, and is a potential biomarker in sCJD.