Functional Connectivity Networks in Asymptomatic and Symptomatic DYT1 Carriers.

Background: DYT1 mutation is characterized by focal to generalized dystonia and incomplete penetrance. To explore the complex perturbations in the different neural networks and the mutual interactions among them, we studied symptomatic and asymptomatic DTY1 mutation carriers by resting-state functional MRI.

Methods: A total of 7 symptomatic DYT1, 10 asymptomatic DYT1, and 26 healthy controls were considered.

Looking for Measures of Disease Severity in the Frontotemporal Dementia Continuum.

Frontotemporal dementia (FTD) is characterized by executive dysfunctions, behavioral disturbances, language deficits and extrapyramidal symptoms. Frontotemporal lobar degeneration-modified Clinical Dementia Rating Scale (FTLD modified-CDR) has been proposed to measure disease severity in behavioral variant FTD (bvFTD). No tools of global disease severity are available in the other FTLD phenotypes [primary progressive aphasias (PPAs), progressive supranuclear palsy (PSP), and corticobasal syndrome (CBS)].

Dyslexia susceptibility genes influence brain atrophy in frontotemporal dementia.

Objective: In this study, we evaluated whether variations within genes specifically associated with dyslexia, namely KIAA0319, DCDC2, and CNTNAP2, were associated with greater damage of language-related regions in patients with frontotemporal dementia (FTD) and primary progressive aphasia (PPA) in particular.

Methods: A total of 118 patients with FTD, 84 with the behavioral variant of FTD (bvFTD) and 34 with PPA, underwent neuropsychological examination, genetic analyses, and brain MRI. KIAA0319 rs17243157 G/A, DCDC2 rs793842 A/G, and CNTNAP2 rs17236239 A/G genetic variations were assessed.

Looking for Neuroimaging Markers in Frontotemporal Lobar Degeneration Clinical Trials: A Multi-Voxel Pattern Analysis Study in Granulin Disease.

In light of future pharmacological interventions, neuroimaging markers able to assess the response to treatment would be crucial. In Granulin (GRN) disease, preclinical data will prompt pharmacological trials in the future. Two main points need to be assessed: (1) to identify target regions in different disease stages and (2) to determine the most accurate functional and structural neuroimaging index to be used.