7 research outputs found

    White matter cortico-striatal tracts predict apathy subtypes in Huntington's disease

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    Apathy is the neuropsychiatric syndrome that correlates most highly with Huntington's disease progression, and, like early patterns of neurodegeneration, is associated with lesions to cortico-striatal connections. However, due to its multidimensional nature and elusive etiology, treatment options are limited. To disentangle underlying white matter microstructural correlates across the apathy spectrum in Huntington's disease. Forty-six Huntington's disease individuals (premanifest (N = 22) and manifest (N = 24)) and 35 healthy controls were scanned at 3-tesla and underwent apathy evaluation using the short-Problem Behavior Assessment and short-Lille Apathy Rating Scale, with the latter being characterized into three apathy domains, namely emotional, cognitive, and auto-activation deficit. Diffusion tensor imaging was used to study whether individual differences in specific cortico-striatal tracts predicted global apathy and its subdomains. We elucidate that apathy profiles may develop along differential timelines, with the auto-activation deficit domain manifesting prior to motor onset. Furthermore, diffusion tensor imaging revealed that inter-individual variability in the disruption of discrete cortico-striatal tracts might explain the heterogeneous severity of apathy profiles. Specifically, higher levels of auto-activation deficit symptoms significantly correlated with increased mean diffusivity in the right uncinate fasciculus. Conversely, those with severe cognitive apathy demonstrated increased mean diffusivity in the right frontostriatal tract and left dorsolateral prefrontal cortex to caudate nucleus tract. The current study provides evidence that white matter correlates associated with emotional, cognitive, and auto-activation subtypes may elucidate the heterogeneous nature of apathy in Huntington's disease, as such opening a door for individualized pharmacological management of apathy as a multidimensional syndrome in other neurodegenerative disorders

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

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    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

    Role of flow cytometry immunophenotyping in the diagnosis of leptomeningeal carcinomatosis

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    PURPOSE: To explore the contribution of flow cytometry immunophenotyping (FCI) in detecting leptomeningeal disease in patients with solid tumors. EXPERIMENTAL DESIGN: Cerebrospinal fluid (CSF) samples from 78 patients who received a diagnosis of epithelial-cell solid tumors and had clinical data suggestive of leptomeningeal carcinomatosis (LC) were studied. A novel FCI protocol was used to identify cells expressing the epithelial cell antigen EpCAM and their DNA content. Accompanying inflammatory cells were also described. FCI results (positive or negative for malignancy) were compared with those from CSF cytology and with the diagnosis established by the clinicians: patients with LC (n = 49), without LC (n = 26), and undetermined (n = 3). RESULTS: FCI described a wide range of EpCAM-positive cells with a hyperdiploid DNA content in the CSF of patients with LC. Compared with cytology, FCI showed higher sensitivity (75.5 vs 65.3) and negative predictive value (67.6 vs 60.5), and similar specificity (96.1 vs 100) and positive predictive value (97.4 vs 100). Concordance between cytology and FCI was high (Kp = 0.83), although misdiagnosis of LC did not show differences between evaluating the CSF with 1 or 2 techniques (P = .06). Receiver-operator characteristic curve analyses showed that lymphocytes and monocytes had a different distribution between patients with and without LC. CONCLUSION: FCI seems to be a promising new tool for improving the diagnostic examination of patients with suspicion of LC. Detection of epithelial cells with a higher DNA content is highly specific of LC, but evaluation of the nonepithelial cell compartment of the CSF might also be useful for supporting this diagnosis

    Role of flow cytometry immunophenotyping in the diagnosis of leptomeningeal carcinomatosis

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    PURPOSE: To explore the contribution of flow cytometry immunophenotyping (FCI) in detecting leptomeningeal disease in patients with solid tumors. EXPERIMENTAL DESIGN: Cerebrospinal fluid (CSF) samples from 78 patients who received a diagnosis of epithelial-cell solid tumors and had clinical data suggestive of leptomeningeal carcinomatosis (LC) were studied. A novel FCI protocol was used to identify cells expressing the epithelial cell antigen EpCAM and their DNA content. Accompanying inflammatory cells were also described. FCI results (positive or negative for malignancy) were compared with those from CSF cytology and with the diagnosis established by the clinicians: patients with LC (n = 49), without LC (n = 26), and undetermined (n = 3). RESULTS: FCI described a wide range of EpCAM-positive cells with a hyperdiploid DNA content in the CSF of patients with LC. Compared with cytology, FCI showed higher sensitivity (75.5 vs 65.3) and negative predictive value (67.6 vs 60.5), and similar specificity (96.1 vs 100) and positive predictive value (97.4 vs 100). Concordance between cytology and FCI was high (Kp = 0.83), although misdiagnosis of LC did not show differences between evaluating the CSF with 1 or 2 techniques (P = .06). Receiver-operator characteristic curve analyses showed that lymphocytes and monocytes had a different distribution between patients with and without LC. CONCLUSION: FCI seems to be a promising new tool for improving the diagnostic examination of patients with suspicion of LC. Detection of epithelial cells with a higher DNA content is highly specific of LC, but evaluation of the nonepithelial cell compartment of the CSF might also be useful for supporting this diagnosis

    White matter cortico-striatal tracts predict apathy subtypes in Huntington's disease

    No full text
    Apathy is the neuropsychiatric syndrome that correlates most highly with Huntington's disease progression, and, like early patterns of neurodegeneration, is associated with lesions to cortico-striatal connections. However, due to its multidimensional nature and elusive etiology, treatment options are limited. To disentangle underlying white matter microstructural correlates across the apathy spectrum in Huntington's disease. Forty-six Huntington's disease individuals (premanifest (N = 22) and manifest (N = 24)) and 35 healthy controls were scanned at 3-tesla and underwent apathy evaluation using the short-Problem Behavior Assessment and short-Lille Apathy Rating Scale, with the latter being characterized into three apathy domains, namely emotional, cognitive, and auto-activation deficit. Diffusion tensor imaging was used to study whether individual differences in specific cortico-striatal tracts predicted global apathy and its subdomains. We elucidate that apathy profiles may develop along differential timelines, with the auto-activation deficit domain manifesting prior to motor onset. Furthermore, diffusion tensor imaging revealed that inter-individual variability in the disruption of discrete cortico-striatal tracts might explain the heterogeneous severity of apathy profiles. Specifically, higher levels of auto-activation deficit symptoms significantly correlated with increased mean diffusivity in the right uncinate fasciculus. Conversely, those with severe cognitive apathy demonstrated increased mean diffusivity in the right frontostriatal tract and left dorsolateral prefrontal cortex to caudate nucleus tract. The current study provides evidence that white matter correlates associated with emotional, cognitive, and auto-activation subtypes may elucidate the heterogeneous nature of apathy in Huntington's disease, as such opening a door for individualized pharmacological management of apathy as a multidimensional syndrome in other neurodegenerative disorders
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