Dickson, Dennis W

Primary progressive aphasia (PPA) is a progressive language disorder often due to an underlying neurodegenerative disease. The most common pathologies associated with PPA include frontotemporal lobar degeneration (FTLD)‐tau, FTLD‐associated with transactivation response DNA‐binding protein of 43 kDa (TDP‐43) (FTLD‐TDP), and Alzheimer's disease (AD). Accumulating evidence has suggested that Lewy body disease (LBD) can also be associated with PPA. We herein report a 78‐year‐old Caucasian woman who initially presented with levodopa‐responsive parkinsonism at age 67 and later developed cognitive impairment, visual hallucinations, rapid eye movement sleep behavior disorder, and progressive aphasia, characterized by reduced spontaneous speech, word‐finding difficulty, and difficulties in writing and reading. 18Fluorodeoxyglucoase (FDG)‐positron emission tomography (PET) performed at the age of 73 years identified hypometabolism in the frontal (right > left), temporal (left > right), and parietal (left > right) lobes. Neuropathological assessment revealed diffuse LBD (DLBD), AD, and TDP‐43 stage 6 with prehippocampal sclerosis. Senile plaques were numerous, but only a few neurofibrillary tangles were present in the neocortex. The Braak neurofibrillary tangle stage was IV, and the Thal amyloid phase was 3. Lewy‐related pathology was severe in the neocortex, as well as limbic cortices, basal forebrain, amygdala, and brainstem. Compared to 166 DLBD cases with a clinical diagnosis of dementia with Lewy bodies (DLB), the Lewy body count of the patient in this report was highest in the inferior parietal cortex, followed by midfrontal and superior temporal cortices. The findings suggest that severe cortical LBD pathology has contributed to her progressive aphasia. Autopsy cases of LBD presenting as PPA have been reported, but patients with PD and autopsy‐proven DLBD who later developed progressive aphasia have not been reported. Our findings indicate that PD can be associated with progressive aphasia later in the disease course. Although uncommon, LBD should be considered as a differential diagnosis of progressive aphasia.

Abstract Frontotemporal lobar degeneration with TDP-43 inclusions (FTLD-TDP) is a complex heterogeneous neurodegenerative disorder for which mechanisms are poorly understood. To explore transcriptional changes underlying FTLD-TDP, we performed RNA-sequencing on 66 genetically unexplained FTLD-TDP patients, 24 FTLD-TDP patients with GRN mutations and 24 control participants. Using principal component analysis, hierarchical clustering, differential expression and coexpression network analyses, we showed that GRN mutation carriers and FTLD-TDP-A patients without a known mutation shared a common transcriptional signature that is independent of GRN loss-of-function. After combining both groups, differential expression as compared to the control group and coexpression analyses revealed alteration of processes related to immune response, synaptic transmission, RNA metabolism, angiogenesis and vesicle-mediated transport. Deconvolution of the data highlighted strong cellular alterations that were similar in FTLD-TDP-A and GRN mutation carriers with NSF as a potentially important player in both groups. We propose several potentially druggable pathways such as the GABAergic, GDNF and sphingolipid pathways. Our findings underline new disease mechanisms and strongly suggest that affected pathways in GRN mutation carriers extend beyond GRN and contribute to genetically unexplained forms of FTLD-TDP-A.

R47H- TREM2 mutation enhances AKT signaling in human AD microglia and mediates proinflammatory and synaptic toxicity in a tauopathy mouse model.

Abstract Aims Accumulating evidence suggests that patients with frontotemporal lobar degeneration (FTLD) can have pathologic accumulation of multiple proteins, including tau and TDP‐43. This study aimed to determine the frequency and characteristics of concurrent tau pathology in FTLD with TDP‐43 pathology (FTLD‐TDP). Methods The study included 146 autopsy‐confirmed cases of FTLD‐TDP and 55 cases of FTLD‐TDP with motor neuron disease (FTLD‐MND). Sections from the basal forebrain were screened for tau pathology with phosphorylated‐tau immunohistochemistry. For cases with tau pathology on the screening section, additional brain sections were studied to establish a diagnosis. Genetic analysis of C9orf72 , GRN and MAPT was performed on select cases. Results We found 72 cases (36%) with primary age‐related tauopathy (PART), 85 (42%) with ageing‐related tau astrogliopathy (ARTAG), 45 (22%) with argyrophilic grain disease (AGD) and 2 cases (1%) with corticobasal degeneration (CBD). Patients with ARTAG or AGD were significantly older than those without these comorbidities. One of the patients with FTLD‐TDP and CBD had C9orf72 mutation and relatively mild tau pathology, consistent with incidental CBD. Conclusion The coexistence of TDP‐43 and tau pathologies was relatively common, particularly PART and ARTAG. Although rare, patients with FTLD can have multiple neurodegenerative proteinopathies. The absence of TDP‐43‐positive astrocytic plaques may suggest that CBD and FTLD‐TDP were independent disease processes in the two patients with both tau and TDP‐43 pathologies. It remains to be determined if mixed cases represent a unique disease process or two concurrent disease processes in an individual.

TSC1/hamartin haploinsufficiency increases risk for tauopathy by promoting tau acetylation and accumulation.

A rare APOE variant APOE3 -Jac reduces self-aggregation and promotes healthy brain aging.

Abstract Aims This study aimed to develop a deep learning‐based model for differentiating tauopathies, including Alzheimer's disease (AD), progressive supranuclear palsy (PSP), corticobasal degeneration (CBD) and Pick's disease (PiD), based on tau‐immunostained digital slide images. Methods We trained the YOLOv3 object detection algorithm to detect five tau lesion types: neuronal inclusions, neuritic plaques, tufted astrocytes, astrocytic plaques and coiled bodies. We used 2522 digital slide images of CP13‐immunostained slides of the motor cortex from 10 cases each of AD, PSP and CBD for training. Data augmentation was performed to increase the size of the training dataset. We next constructed random forest classifiers using the quantitative burdens of each tau lesion from motor cortex, caudate nucleus and superior frontal gyrus, ascertained from the object detection model. We split 120 cases (32 AD, 36 PSP, 31 CBD and 21 PiD) into training (90 cases) and test (30 cases) sets to train random forest classifiers. Results The resultant random forest classifier achieved an average test score of 0.97, indicating that 29 out of 30 cases were correctly diagnosed. A validation study using hold‐out datasets of CP13‐ and AT8‐stained slides from 50 cases (10 AD, 17 PSP, 13 CBD and 10 PiD) showed >92% (without data augmentation) and >95% (with data augmentation) diagnostic accuracy in both CP13‐ and AT8‐stained slides. Conclusion Our diagnostic model trained with CP13 also works for AT8; therefore, our diagnostic tool can be potentially used by other investigators and may assist medical decision‐making in neuropathological diagnoses of tauopathies.

Nuclear accumulation of CHMP7 leads to multiple cellular pathologies that can be mitigated via CHMP7 ASOs in familial and sporadic ALS iPSNs.