relationship of white and gray matter abnormalities to clinical and genetic features in myotonic dystrophy type 1
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2016
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Abstract
Background: Myotonic dystrophy type 1 (DM1) represents a multisystemic disorder in which diffuse brain white and gray matter alterations related to clinical and genetic features have been described. We aimed to evaluate in the brain of adult patients with DM1 (i) white and gray matter differences, including cortical-subcortical gray matter volume and cortical thickness and (ii) their correlation with clinical disability, global neuropsychological performance and triplet expansion.
Methods: We included 24 adult genetically-confirmed DM1 patients (14 males; age: 38.5 ± 11.8 years) and 25 age- and sex-matched healthy controls (14 males; age: 38.5 ± 11.3 years) who underwent an identical brain MR protocol including high-resolution 3D T1-weighted, axial T2 FLAIR and DTI sequences. All patients underwent an extensive clinical and neuropsychological evaluation. Voxel-wise analyses of white matter, performed by using Tract Based Spatial Statistics, and of gray matter, with Voxel-based Morphometry and Cortical Thickness, were carried out in order to test for differences between patients with DM1 and healthy controls (p < 0.05, corrected). The correlation between MRI measures and clinical-genetic features was also assessed.
Results: Patients with DM1 showed widespread abnormalities of all DTI parameters in the white matter, which were associated with reduced gray matter volume in all brain lobes and thinning in parieto-temporo-occipital cortices, albeit with less extensive cortical alterations when congenital cases were removed from the analyses. White matter alterations correlated with clinical disability, global cognitive performance and triplet expansions.
Conclusion: In patients with DM1, the combined smaller overall gray matter volume and white matter alterations seem to be the main morpho-structural substrates of CNS involvement in this condition. The correlation of white matter differences with both clinical and genetic findings lends support to this notion.
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| Reference Key |
zanigni2016neuroimage:relationship
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| Authors | ;Stefano Zanigni;Stefania Evangelisti;Maria Pia Giannoccaro;Federico Oppi;Roberto Poda;Antonio Giorgio;Claudia Testa;David Neil Manners;Patrizia Avoni;Laura Ludovica Gramegna;Nicola De Stefano;Raffaele Lodi;Caterina Tonon;Rocco Liguori |
| Journal | chemical engineering journal |
| Year | 2016 |
| DOI |
10.1016/j.nicl.2016.04.012
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