Neuropathology and Applied Neurobiology最新文献

Aims: Lecanemab, an Alzheimer's disease US Food and Drug Administration-approved monoclonal antibody, was previously reported to have a high affinity against intermediately sized amyloid-β aggregates. Subsequently, it was observed by immunogold labelling that lecanemab can also bind to human type I amyloid-β fibrils. To determine whether lecanemab binds to amyloid-β fibril structures other than type I, we analysed its binding capacity to various structurally defined and pathologically relevant amyloid-β fibrils.

Methods: We performed immunogold labelling with lecanemab on extracted amyloid-β fibril preparations from six different Alzheimer´s disease mouse models whose structures were previously solved by cryo-EM and quantified the relative binding affinities of lecanemab to the different fibril polymorphs.

Results: Our results show that lecanemab exhibits high binding affinity to amyloid-β fibril structures that have a flexible N-terminus in common, as is the case for type I, type II and murine type III amyloid-β fibril polymorphs, which resemble or are identical to human structures observed in sporadic and familial cases of Alzheimer's disease, including a case with the Arctic (E22G) mutation. In contrast, only weak lecanemab binding was observed for murine amyloid-β fibrils with a fixed and ordered N-terminus.

Conclusions: These findings may also explain the low incidence of ARIA-E with lecanemab in clinical trials. This is because human meningeal amyloid-β fibrils derived from cerebral amyloid angiopathy affected brain tissue also contain a fixed and ordered N-terminus, most likely preventing lecanemab binding.

Summary: Lecanemab binds to Aβ fibrils from several Alzheimer's disease tg-mice whose structures resemble the type I, type II and Arctic folds found in Alzheimer's patients, all of which share a flexible, unstructured N-terminus. Lecanemab is therefore expected to be active against all common familial and sporadic Alzheimer's cases containing these folds. Lecanemab binding ability is unaffected by and tolerates the Arctic E22G mutation, at least in type I or Arctic folds. Only weak, if any, lecanemab binding was observed to Aβ fibrils derived from tg-SwDI mice, whose structures DI1, DI2 and DI3 all share structured and fixed N-termini. Since the fixed N-termini of tg-SwDI DI1 fibrils and human meningeal Aβ40 fibrils derived from CAA-affected brain are identical, most likely preventing lecanemab binding, treatment with lecanemab may be less effective or ineffective against CAA, but may explain the reported beneficial low ARIA-E frequency with this antibody.

Aims: To identify potential image biomarkers of neuromuscular disease by analysing morphological and network-derived features in skeletal muscle biopsies from a murine model of amyotrophic lateral sclerosis (ALS), the SOD1^G93A mouse and wild-type (WT) controls at distinct stages of disease progression.

Methods: Using the NDICIA computational framework, we quantitatively evaluated histological differences between skeletal muscle biopsies from SOD1^G93A and WT mice. The process involved the selection of a subset of features revealing these differences. A subset of discriminative features was selected to characterise these differences, and their temporal dynamics were assessed across disease stages.

Results: Our findings demonstrate that muscle pathology in the mutant model evolves from early alterations in muscle fibre arrangement, detectable at the presymptomatic stage through graph theory features, to the subsequent development of the typical morphological pattern of neurogenic atrophy at more advanced disease stages.

Conclusions: Our assay identifies a neurogenic signature in mutant muscle biopsies, even when the disease is phenotypically imperceptible.

Aims: The aim of this study is to identify the prevalence of frontotemporal dementia (FTD)/corticobasal syndrome (CBS) in a large cohort of pathologically confirmed cases of multiple system atrophy (MSA) and to determine the α-synuclein seeding characteristics and electron cryo-microscopy (cryo-EM) filament structure in frontotemporal lobar degeneration with MSA-type α-synuclein pathology (FTLD-synuclein).

Methods: The archives of the Queen Square Brain Bank (1989-2023) were searched for histologically confirmed MSA cases, and those with a clinical diagnosis of FTD/CBS were reviewed for pathological features of FTLD-synuclein. Phosphotungstic acid (PTA)-precipitated brain homogenates from FTLD-synuclein, dementia with Lewy bodies (DLB) and G51D SNCA synucleinopathy cases were used to seed aggregation in α-syn140*A53T-YFP HEK293T cells. The structure of α-synuclein filaments from an FTLD-synuclein case was determined by cryo-EM.

Results: We identified 283 cases of MSA. Four cases had a clinical diagnosis of CBS, one of which met pathological criteria for FTLD-synuclein. Genetic studies in this case were negative for SNCA variants, and PTA-precipitated brain homogenates seeded abundant cytoplasmic α-synuclein inclusions that were morphologically indistinguishable from those of typical MSA but distinct from those of G51D SNCA and DLB. MSA Type II α-synuclein filaments were identified by cryo-EM.

Conclusions: FTD/CBS is rarely associated with MSA pathology. The cell seeding characteristics and cryo-EM findings support the classification of FTLD-synuclein as a subtype of MSA, differentiating it from genetic synucleinopathies, such as those with SNCA variants G51D and A53E, which have neuropathological features overlapping with MSA and Lewy body diseases. These cases expand the clinicopathological spectrum of MSA and FTLD and have implications for our understanding of selective neuronal vulnerability in MSA and the interpretation of α-synuclein biomarker studies.

Aims: In Alzheimer's disease (AD), the pathological accumulation of tau in synapses contributes to synapse dysfunction and loss. However, the small and complex structure of synapses limits the investigation when using conventional techniques. In this work, we describe the combination of array tomography (AT) with two-colour direct stochastic optical reconstruction microscopy (dSTORM) to enhance lateral resolution for resolving synaptic terminals in human postmortem brain.

Methods: We applied this combination to study synapses in brain samples (from biopsy and postmortem) from healthy subjects and pathological synaptic tau (aggregates and oligomers) in samples from AD patients.

Results: AT combined with dSTORM allowed the characterisation of the orientation and shape of the synaptic terminals and the synaptic cleft. In addition, this combination confirmed the presence of oligomeric tau in synaptic terminals in AD.

Conclusions: Overall, we found that the combination of AT and two-colour dSTORM provides optimal resolution to detect pathological synaptic tau and its spatial relationship with presynaptic and postsynaptic terminals.

Aims: Lafora disease (LD; OMIM#254780) is a rare form of progressive myoclonus epilepsy characterised by the accumulation of insoluble deposits of glycogen in the brain and peripheral tissues. In mouse models of LD, we have identified neuroinflammation as a secondary hallmark of the disease, characterised by increased levels of reactive astrocytes and activated microglia. Our previous work demonstrated that the TNF and IL-6 inflammatory signalling pathways are the primary drivers of this neuroinflammatory phenotype. In this work, we aimed to investigate whether TNF and IL-6 pathway activation contributes to alterations in the glutamatergic and GABAergic signalling pathways.

Methods: We performed immunofluorescence and western blot analyses on the hippocampus of a mouse model of LD to evaluate potential changes in proteins associated with glutamatergic and GABAergic signalling pathways.

Results: Our findings reveal dysregulation in the expression of subunits of excitatory glutamatergic receptors (phospho-GluN2B and GluK2), as well as an increase in the levels of the GABA transporter GAT1. In addition, we detected activated forms of the Src and Lyn protein kinases in the hippocampus. More importantly, these alterations predominantly occur in nonneuronal cells, such as reactive astrocytes and microglia, underscoring the critical involvement of glial cells in the pathophysiology of LD.

Conclusions: The observed upregulation of glutamatergic receptor subunits likely amplifies excitatory glutamatergic signalling, whereas the increased expression of GAT1 may reduce the inhibitory GABAergic tone. These changes contribute to the characteristic hyperexcitability of LD.

Aims: Posterior cortical atrophy (PCA) is a predominantly young-onset neurodegenerative syndrome, typically caused by Alzheimer's disease (PCA-AD). PCA-AD presents with visual and spatial dysfunction attributed to occipito-parietal or 'posterior' brain regions rather than memory difficulties characteristic of typical amnestic-led Alzheimer's disease (a-AD) attributed to medial temporal regions. Imaging and neuropathological studies suggest that PCA-AD is associated with a more posterior distribution of tau neurofibrillary tangles (NFTs), whereas β-amyloid pathology (Aβ) is diffusely deposited throughout the cortex. This study characterised the neuropathological substrates of PCA-AD in comparison with a-AD, to further understanding of the biological basis of phenotypical heterogeneity in AD.

Methods: Immunohistochemistry for Aβ; tau; the microglial markers CD68, CR3-43 and Iba1; α-synuclein; and TDP-43 was carried out on 26 PCA-AD and 27 age and gender-matched a-AD cases at the Queen Square Brain Bank. Aβ, tau and the three microglial markers were quantified in the superior frontal, superior temporal, superior parietal and occipital (primary visual cortex) cortices, with α-synuclein and TDP-43 assessed using formal staging criteria. In addition, microglial circularity, a morphological indicator of microglial activation state, was calculated.

Results: There was a higher load of Aβ and tau in the parietal region of PCA-AD compared to a-AD. In the PCA-AD compared to the a-AD group, there were significant increases in tau load in parietal and frontal relative to temporal regions. There was no difference in cerebral amyloid angiopathy (CAA) severity between PCA-AD and a-AD. There was a significantly lower temporal CD68 load in a-AD compared with PCA-AD. In a-AD, CD68 load was lowest and tau load highest in the temporal relative to all other regions.

Conclusions: This study demonstrates differences in the distribution of Aβ and tau and variations in regional neuroinflammatory response in PCA-AD and a-AD. These findings extend our understanding of the biological substrates underpinning PCA-AD and highlight the potential for exploring phenotypic variants to understand selective vulnerability in neurodegenerative diseases.

Aims: Alcohol use disorder (AUD) involves excessive and chronic ethanol consumption, leading to various health issues, including cerebellar atrophy. The cerebellum is particularly susceptible to ethanol-induced damage through neuroinflammation, oxidative stress and excitotoxicity. This damage has been documented predominantly in the anterior lobe, primarily due to its role in motor function, which is often impaired in patients with AUD. However, less is known about the impact of AUD on the posterior cerebellar lobes. In contrast, alterations in the posterior lobe have been associated with cerebellar cognitive affective syndrome (CCAS). Moreover, the cerebellum is an asymmetric structure with spatial functions being left-lateralised. We hypothesised that the posterior cerebellar lobe in AUD cases would show increased inflammation compared with healthy controls.

Methods: This cross-sectional study examined the structural integrity and neuroinflammatory state of the left posterior cerebellar lobe cortex in post-mortem samples from nine males with chronic AUD and 9 control cases.

Results: Chronic AUD cases showed significant cerebellar damage. Immunohistochemistry revealed higher levels of reactive astrogliosis (GFAP), increased T_reg cell markers (CD45 and FOXP3), increased mitochondria marker (MitoTracker^TM), elevated COX2 (indicating inflammation and T_reg cell activity), increased cFos protein (cell activity marker), and higher caspase 3 (Casp3) levels, suggesting excessive cell death. These findings indicate that chronic AUD leads to atrophy in the left posterior cerebellar lobe cortex due to neuroinflammation driven by reactive astrogliosis, T_reg cell infiltration, and COX2 activity.

Conclusions: The study highlights the inflammatory consequences of chronic AUD, potentially linked to cerebellar atrophy and subsequent motor and cognitive impairments. Targeting neuroinflammation could help mitigate the neurodegenerative effects of chronic AUD.

Aims: Muscle morphology provides important information in differentiating disease aetiology, but its measurement remains challenging because of the lack of an efficient and objective method. This study aimed to quantitatively refine the morphological features of muscle fibres in neuromuscular diseases using machine learning.

Methods: In this retrospective study, we analysed muscle biopsy specimens on haematoxylin and eosin-staining. Machine learning-based software was developed to segment muscle fibre contours and perform automated muscle morphometry and subsequent graph theory-based spatial analysis of atrophied fibre grouping. A decision tree-based framework, LightGBM, was trained to predict underlying aetiologies based on morphometric and spatial variables.

Results: The study included 100 muscle samples, including 20 normal muscles, 49 myopathies and 19 neuropathies. The fine-tuned segmentation model, YOLOv8, achieved a mask average precision of 0.819. The muscle morphometry revealed the significance of fibre circularity. The mean circularity was higher in the myopathy group, and the SD of circularity was elevated in the neuropathy group. Although most cases were consistent with textbook findings, atypical presentations, such as dermatomyositis with angular atrophy and amyotrophic lateral sclerosis with round atrophy, were objectively documented. Spatial analysis quantified grouped atrophy, showing the potential to feature specific atrophy patterns. The LightGBM model successfully predicted the final clinical diagnosis of the myopathies and neuropathies with an accuracy of 0.852, which exceeded that of 0.808 by human annotation.

Conclusion: Automated muscle morphometry and spatial analysis provide quantification of muscle morphology and patterns of atrophy, which will facilitate objective and efficient investigation of neuromuscular diseases.