Structural signature of classical versus late-onset friedreich's ataxia by Multimodality brain MRI

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Date
2017
Authors
Rezende, Thiago Junqueira R.
Martinez, Alberto Rolim M.
Faber, Ingrid
Girotto, Karen
Pedroso, Jose Luiz [UNIFESP]
Barsottini, Orlando G. [UNIFESP]
Lopes-Cendes, Iscia
Cendes, Fernando
Faria, Andreia V.
Franca, Marcondes C.
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Abstract
IntroductionFriedreich's ataxia (FRDA) is the most common autosomal-recessive ataxia worldwide. It is characterized by early onset, sensory abnormalities, and slowly progressive ataxia. However, some individuals manifest the disease after the age of 25 years and are classified as late-onset FRDA (LOFA). Therefore, we propose a transversal multimodal MRI-based study to investigate which anatomical substrates are involved in classical (cFRDA) and LOFA. MethodsWe enrolled 36 patients (13 with LOFA) and 29 healthy controls. All subjects underwent magnetic resonance imaging in a 3T device
three-dimensional high-resolution T1-weighted images and diffusion tensor images were used to assess gray and white matter, respectively. We used T1 multiatlas approach to assess deep gray matter and cortical thickness measures to evaluate cerebral cortex and DTI multiatlas approach to assess white matter. All analyses were corrected for multiple comparisons. ResultsGroup comparison showed that both groups presented gray matter atrophy mostly in the motor cortex. Regarding white matter, we found abnormalities in the cerebellar peduncles, pyramidal tracts, midbrain, pons, and medulla oblongata for both groups, but the microstructural abnormalities in the cFRDA group were more widespread. In addition, we found that the corticospinal tract presented more severe microstructural damage in the LOFA group. Finally, the midbrain volume of the cFRDA, but not of the LOFA group, correlated with disease duration (R=-0.552, P=0.012) and severity (R=-0.783, P<0.001). ConclusionThe cFRDA and LOFA groups have similar, but not identical neuroimaging damage pattern. These structural differences might help to explain the phenotypic variability observed in FRDA. Hum Brain Mapp 38:4157-4168, 2017. (c) 2017 Wiley Periodicals, Inc.
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Human Brain Mapping. Hoboken, v. 38, n. 8, p. 4157-4168, 2017.
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