Perineuronal oligodendrocytes in health and disease: the journey so far

2019 ◽  
Vol 31 (1) ◽  
pp. 89-99 ◽  
Author(s):  
Hans-Gert Bernstein ◽  
Gerburg Keilhoff ◽  
Henrik Dobrowolny ◽  
Paul C. Guest ◽  
Johann Steiner
Keyword(s):  
Multiple Sclerosis ◽  
Alzheimer’S Disease ◽  
Bipolar Disorder ◽  
Cerebral Ischemia ◽  
Major Depression ◽  
Gray Matter ◽  
Neuronal Firing ◽  
Close Proximity ◽  
Health And Disease ◽  
Experimental Demyelination

Abstract Perineuronal oligodendrocytes (pn-Ols) are located in the cerebral gray matter in close proximity to neuronal perikarya and less frequently near dendrites and neurites. Although their morphology is indistinguishable from that of other oligodendrocytes, it is not known if pn-Ols have a similar or different cell signature from that of typical myelinating oligodendroglial cells. In this review, we discussed the potential roles of these cells in myelination under normal and pathophysiologic conditions as functional and nutritional supporters of neurons, as restrainers of neuronal firing, and as possible players in glutamate-glutamine homeostasis. We also highlighted the occurrences in which perineuronal oligodendroglia are altered, such as in experimental demyelination, multiple sclerosis, cerebral ischemia, epilepsy, Alzheimer’s disease, schizophrenia, major depression, and bipolar disorder.

The Role of Melatonin in Multiple Sclerosis, Huntington's Disease and Cerebral Ischemia

2014 ◽  
Vol 13 (6) ◽  
pp. 1096-1119 ◽  
Author(s):  
Begona Escribano ◽  
Ana Colin-Gonzalez ◽  
Abel Santamaria ◽  
Isaac Tunez
Keyword(s):  
Multiple Sclerosis ◽  
Cerebral Ischemia ◽  
Huntington's Disease ◽  
Huntington’S Disease

scholarly journals Topographic patterns of white matter hyperintensities are associated with multimodal neuroimaging biomarkers of Alzheimer’s disease

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Malo Gaubert ◽  
Catharina Lange ◽  
Antoine Garnier-Crussard ◽  
Theresa Köbe ◽  
Salma Bougacha ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
White Matter ◽  
Glucose Metabolism ◽  
Corpus Callosum ◽  
Gray Matter ◽  
Fdg Pet ◽  
White Matter Hyperintensities ◽  
Gray Matter Volume ◽  
Matter Volume

Abstract Background White matter hyperintensities (WMH) are frequently found in Alzheimer’s disease (AD). Commonly considered as a marker of cerebrovascular disease, regional WMH may be related to pathological hallmarks of AD, including beta-amyloid (Aβ) plaques and neurodegeneration. The aim of this study was to examine the regional distribution of WMH associated with Aβ burden, glucose hypometabolism, and gray matter volume reduction. Methods In a total of 155 participants (IMAP+ cohort) across the cognitive continuum from normal cognition to AD dementia, FLAIR MRI, AV45-PET, FDG-PET, and T1 MRI were acquired. WMH were automatically segmented from FLAIR images. Mean levels of neocortical Aβ deposition (AV45-PET), temporo-parietal glucose metabolism (FDG-PET), and medial-temporal gray matter volume (GMV) were extracted from processed images using established AD meta-signature templates. Associations between AD brain biomarkers and WMH, as assessed in region-of-interest and voxel-wise, were examined, adjusting for age, sex, education, and systolic blood pressure. Results There were no significant associations between global Aβ burden and region-specific WMH. Voxel-wise WMH in the splenium of the corpus callosum correlated with greater Aβ deposition at a more liberal threshold. Region- and voxel-based WMH in the posterior corpus callosum, along with parietal, occipital, and frontal areas, were associated with lower temporo-parietal glucose metabolism. Similarly, lower medial-temporal GMV correlated with WMH in the posterior corpus callosum in addition to parietal, occipital, and fontal areas. Conclusions This study demonstrates that local white matter damage is correlated with multimodal brain biomarkers of AD. Our results highlight modality-specific topographic patterns of WMH, which converged in the posterior white matter. Overall, these cross-sectional findings corroborate associations of regional WMH with AD-typical Aß deposition and neurodegeneration.

Acute and chronic synaptic pathology in multiple sclerosis gray matter

2021 ◽  
pp. 135245852110221
Author(s):  
Marco Vercellino ◽  
Stella Marasciulo ◽  
Silvia Grifoni ◽  
Elena Vallino-Costassa ◽  
Chiara Bosa ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Brain Tissue ◽  
Gray Matter ◽  
Axonal Loss ◽  
Strong Indication ◽  
Synaptic Loss ◽  
Synaptic Density ◽  
Synaptic Pathology ◽  
Gabaergic Synapses ◽  
And Control

Objectives: To investigate the extent of synaptic loss, and the contribution of gray matter (GM) inflammation and demyelination to synaptic loss, in multiple sclerosis (MS) brain tissue. Methods: This study was performed on two different post-mortem series of MS and control brains, including deep GM and cortical GM. MS brain samples had been specifically selected for the presence of active demyelinating GM lesions. Over 1,000,000 individual synapses were identified and counted using confocal microscopy, and further characterized as glutamatergic/GABAergic. Synaptic counts were also correlated with neuronal/axonal loss. Results: Important synaptic loss was observed in active demyelinating GM lesions (−58.9%), while in chronic inactive GM lesions, synaptic density was only mildly reduced compared to adjacent non-lesional gray matter (NLGM) (−12.6%). Synaptic loss equally affected glutamatergic and GABAergic synapses. Diffuse synaptic loss was observed in MS NLGM compared to control GM (−21.2% overall). Conclusion: This study provides evidence, in MS brain tissue, of acute synaptic damage/loss during active GM inflammatory demyelination and of synaptic reorganization in chronically demyelinated GM, affecting equally glutamatergic and GABAergic synapses. Furthermore, this study provides a strong indication of widespread synaptic loss in MS NLGM also independently from focal GM demyelination.

Reproducibility of Brain Volume Changes in Longitudinal Voxel-Based Morphometry Between Non-Accelerated and Accelerated Magnetic Resonance Imaging

2021 ◽  
pp. 1-10
Author(s):  
Hidemasa Takao ◽  
Shiori Amemiya ◽  
Osamu Abe ◽  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Magnetic Resonance ◽  
Gray Matter ◽  
Gray Matter Volume ◽  
Elderly Subjects ◽  
Voxel Based Morphometry ◽  
Volume Changes ◽  
Matter Volume ◽  
Healthy Elderly

Background: Scan acceleration techniques, such as parallel imaging, can reduce scan times, but reliability is essential to implement these techniques in neuroimaging. Objective: To evaluate the reproducibility of the longitudinal changes in brain morphology determined by longitudinal voxel-based morphometry (VBM) between non-accelerated and accelerated magnetic resonance images (MRI) in normal aging, mild cognitive impairment (MCI), and Alzheimer’s disease (AD). Methods: Using data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) 2 database, comprising subjects who underwent non-accelerated and accelerated structural T1-weighted MRI at screening and at a 2-year follow-up on 3.0 T Philips scanners, we examined the reproducibility of longitudinal gray matter volume changes determined by longitudinal VBM processing between non-accelerated and accelerated imaging in 50 healthy elderly subjects, 54 MCI patients, and eight AD patients. Results: The intraclass correlation coefficient (ICC) maps differed among the three groups. The mean ICC was 0.72 overall (healthy elderly, 0.63; MCI, 0.75; AD, 0.63), and the ICC was good to excellent (0.6–1.0) for 81.4%of voxels (healthy elderly, 64.8%; MCI, 85.0%; AD, 65.0%). The differences in image quality (head motion) were not significant (Kruskal–Wallis test, p = 0.18) and the within-subject standard deviations of longitudinal gray matter volume changes were similar among the groups. Conclusion: The results indicate that the reproducibility of longitudinal gray matter volume changes determined by VBM between non-accelerated and accelerated MRI is good to excellent for many regions but may vary between diseases and regions.

Sign in / Sign up

Export Citation Format

Share Document