Specific patterns of brain alterations underlie distinct clinical profiles in Huntington's disease

Huntington's disease (HD) is a genetic neurodegenerative disease which involves a triad of motor, cognitive and psychiatric disturbances. However, there is great variability in the prominence of each type of symptom across individuals. The neurobiological basis of such variability remains poorly understood but would be crucial for better tailored treatments. Multivariate multimodal neuroimaging approaches have been successful in disentangling these profiles in other disorders. Thus we applied for the first time such approach to HD. We studied the relationship between HD symptom domains and multimodal measures sensitive to grey and white matter structural alterations. Forty-three HD gene carriers (23 manifest and 20 premanifest individuals) were scanned and underwent behavioural assessments evaluating motor, cognitive and psychiatric domains. We conducted a multimodal analysis integrating different structural neuroimaging modalities measuring grey matter volume, cortical thickness and white matter diffusion indices - fractional anisotropy and radial diffusivity. All neuroimaging measures were entered into a linked independent component analysis in order to obtain multimodal components reflecting common inter-subject variation across imaging modalities. The relationship between multimodal neuroimaging independent components and behavioural measures was analysed using multiple linear regression. We found that cognitive and motor symptoms shared a common neurobiological basis, whereas the psychiatric domain presented a differentiated neural signature. Behavioural measures of different symptom domains correlated with different neuroimaging components, both the brain regions involved and the neuroimaging modalities most prominently associated with each type of symptom showing differences. More severe cognitive and motor signs together were associated with a multimodal component consisting in a pattern of reduced grey matter, cortical thickness and white matter integrity in cognitive and motor related networks. In contrast, depressive symptoms were associated with a component mainly characterised by reduced cortical thickness pattern in limbic and paralimbic regions. In conclusion, using a multivariate multimodal approach we were able to disentangle the neurobiological substrates of two distinct symptom profiles in HD: one characterised by cognitive and motor features dissociated from a psychiatric profile. These results open a new view on a disease classically considered as a uniform entity and initiates a new avenue for further research considering these qualitative individual differences

Disentangling apathy subtypes in Huntington's disease: A white matter biomarker of disease profile and progression

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Gray matter vulnerabilities predict longitudinal development of apathy in Huntington's disease

Background: Apathy, a common neuropsychiatric disturbance in Huntington's disease (HD), is subserved by a complex neurobiological network. However, no study has yet employed a whole-brain approach to examine underlying regional vulnerabilities that may precipitate apathy changes over time. Objectives: To identify whole-brain gray matter volume (GMV) vulnerabilities that may predict longitudinal apathy development in HD. Methods: Forty-five HD individuals (31 female) were scanned and evaluated for apathy and other neuropsychiatric features using the short-Problem Behavior Assessment for a maximum total of six longitudinal visits (including baseline). In order to identify regions where changes in GMV may describe changes in apathy, we performed longitudinal voxel-based morphometry (VBM) on those 33 participants with a magnetic resonance imaging (MRI) scan on their second visit at 18 ± 6 months follow-up (78 MRI datasets). We next employed a generalized linear mixed-effects model (N = 45) to elucidate whether initial and specific GMV may predict apathy development over time. Results: Utilizing longitudinal VBM, we revealed a relationship between increases in apathy and specific GMV atrophy in the right middle cingulate cortex (MCC). Furthermore, vulnerability in the right MCC volume at baseline successfully predicted the severity and progression of apathy over time. Conclusions: This study highlights that individual differences in apathy in HD may be explained by variability in atrophy and initial vulnerabilities in the right MCC, a region implicated in action-initiation. These findings thus serve to facilitate the prediction of an apathetic profile, permitting targeted, time-sensitive interventions in neurodegenerative disease with potential implications in otherwise healthy populations