Citations

Abstract Synucleinopathies are clinically and pathologically heterogeneous disorders characterized by pathologic aggregates of α-synuclein in neurons and glia, in the form of Lewy bodies, Lewy neurites, neuronal cytoplasmic inclusions, and glial cytoplasmic inclusions (GCIs). Synucleinopathies can be divided into two major disease entities: Lewy body disease (LBD) and multiple system atrophy (MSA). Common clinical presentations of LBD are Parkinson's disease (PD), PD with dementia (PDD), and dementia with Lewy bodies (DLB), while MSA has two major clinical subtypes, MSA with predominant cerebellar ataxia (MSA-C) and MSA with predominant parkinsonism (MSA-P). There are currently no disease-modifying therapies for the synucleinopathies, but elucidation of genetics and mechanisms of α-synuclein conversion to pathologic oligomers and insoluble fibrils offer hope for eventual therapies. It remains unclear how α-synuclein can be associated with distinct cellular pathologies (e.g., Lewy bodies and GCI) and what factors determine neuroanatomical and cell type vulnerability. Accumulating evidence from in vitro and in vivo experiments suggests that α-synuclein species derived from LBD and MSA are distinct "strains" having different seeding properties. Recent advancements in in vitro seeding assays, such as real-time quaking-induced conversion (RT-QuIC) and protein misfolding cyclic amplification (PMCA), not only demonstrate distinct seeding activity in the synucleinopathies, but also offer exciting opportunities for molecular diagnosis using readily accessible peripheral tissues. Cryogenic electron microscopy (cryo-EM) structural studies of α-synuclein derived from recombinant or brain-derived filaments provide new insight into mechanisms of seeding in synucleinopathies. In this review, we describe clinical, genetic and neuropathologic features of synucleinopathies, including a review of classification and staging schemes for LBD. We also review evidence supporting the existence of distinct α-synuclein strains in LBD and MSA.

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.

AbstractAimsThis study aimed to clarify the different topographical distribution of tau pathology between progressive supranuclear palsy (PSP) and corticobasal degeneration (CBD) and establish a machine learning‐based decision tree classifier.MethodsParaffin‐embedded sections of the temporal cortex, motor cortex, caudate nucleus, globus pallidus, subthalamic nucleus, substantia nigra, red nucleus, and midbrain tectum from 1020 PSP and 199 CBD cases were assessed by phospho‐tau immunohistochemistry. The severity of tau lesions (i.e., neurofibrillary tangle, coiled body, tufted astrocyte or astrocytic plaque, and tau threads) was semi‐quantitatively scored in each region. Hierarchical cluster analysis was performed using tau pathology scores. A decision tree classifier was made with tau pathology scores using 914 cases. Cross‐validation was done using 305 cases. An additional ten cases were used for a validation study.ResultsCluster analysis displayed two distinct clusters; the first cluster included only CBD, and the other cluster included all PSP and six CBD cases. We built a decision tree, which used only seven decision nodes. The scores of tau threads in the caudate nucleus were the most decisive factor for predicting CBD. In a cross‐validation, 302 out of 305 cases were correctly diagnosed. In the pilot validation study, three investigators made a correct diagnosis in all cases using the decision tree.ConclusionRegardless of the morphology of astrocytic tau lesions, semi‐quantitative tau pathology scores in select brain regions are sufficient to distinguish PSP and CBD. The decision tree simplifies neuropathologic differential diagnosis of PSP and CBD.

Abstract This study aimed to develop a deep learning-based image classification model that can differentiate tufted astrocytes (TA), astrocytic plaques (AP), and neuritic plaques (NP) based on images of tissue sections stained with phospho-tau immunohistochemistry. Phospho-tau-immunostained slides from the motor cortex were scanned at 20× magnification. An automated deep learning platform, Google AutoML, was used to create a model for distinguishing TA in progressive supranuclear palsy (PSP) from AP in corticobasal degeneration (CBD) and NP in Alzheimer disease (AD). A total of 1500 images of representative tau lesions were captured from 35 PSP, 27 CBD, and 33 AD patients. Of those, 1332 images were used for training, and 168 images for cross-validation. We tested the model using 100 additional test images taken from 20 patients of each disease. In cross-validation, precision and recall for each individual lesion type were 100% and 98.0% for TA, 98.5% and 98.5% for AP, and 98.0% and 100% for NP, respectively. In a test set, all images of TA and NP were correctly predicted. Only eleven images of AP were predicted to be TA or NP. Our data indicate the potential usefulness of deep learning-based image classification methods to assist in differential diagnosis of tauopathies.

AbstractBackground: Abnormal aggregates of α‐synuclein are pathologic hallmarks of multiple system atrophy (MSA) and Lewy body disease (LBD). LBD sometimes coexists with MSA, but the impact of co‐pathology, particularly diffuse LBD, on presentation of MSA has not been studied. We aimed to determine the frequency and clinicopathologic features of MSA with LBD (MSA+LBD). Methods: Using hematoxylin & eosin and α‐synuclein‐immunostained slides, we assessed the distribution and severity of LBD in 230 autopsy‐confirmed MSA patients collected from 1998 to 2018. Alzheimer‐type pathology was assessed to assign the likelihood of clinical presentations of dementia with Lewy body (DLB) using the consensus criteria for DLB. We reviewed medical records to characterize clinicopathologic features of MSA+LBD. Genetic risk factors for LBD, including APOE ε4 allele and mutations in GBA, SNCA, LRRK2, and VPS35, were analyzed. Results: LBD was observed in 11 MSA patients (5%); seven were brainstem type, three were transitional type, and one was diffuse type. The latter four had an intermediate or high likelihood of DLB. Three of the four had an antemortem diagnosis of Parkinson’s disease with dementia (PDD) or clinically probable DLB. Two patients had neuronal loss in the substantia nigra, but not in striatal or olivocerebellar systems with widespread glial cytoplasmic inclusions, consistent with minimal change MSA. In these cases, LBD was considered the primary pathology, and MSA was considered coincidental. APOE ε4 allele frequency was not different between MSA+LBD and MSA without LBD. Two of nine MSA+LBD patients had a risk variant of GBA (p.T408M and p.E365K). Conclusions: Although rare, MSA with transitional or diffuse LBD can develop clinical features of PDD or DLB. Minimal change MSA can be interpreted as a coincidental, but distinct, α‐synucleinopathy in a subset of patients with diffuse LBD.

Abstract Background Intronic variant rs564309 in tripartite motif containing 11 (TRIM11 ) is associated with clinical phenotypic differences in progressive supranuclear palsy (PSP), whereby the minor allele (A) is more common in atypical PSP than typical PSP (PSP‐Richardson's syndrome). However, rs564309 has not been investigated relative to neuropathological outcomes. Objective Evaluate the association of rs564309 with the neuropathologically assessed severity of tau pathology, as measured by semi‐quantitative scores for neurofibrillary tangles, tufted astrocytes, neuropil threads, and oligodendroglial coiled bodies. Methods 797 neuropathologically confirmed PSP cases were genotyped for TRIM11 rs564309 and assessed for tau pathology across 20 neuroanatomical regions. Tau pathology measures and age at death were examined for association with TRIM11 rs564309‐A using multivariable linear regression models. Results TRIM11 rs564309‐A was associated with increased neurofibrillary tangles pathology ( P = 0.050), but was not significantly associated with age at death, neuropil threads, coiled bodies, or tufted astrocytes tau pathology scores. Conclusions TRIM11 rs564309 may influence burden of neurofibrillary tangles tau pathology in PSP; further study is warranted. © 2020 International Parkinson and Movement Disorder Society

Is tau load associated with long-term outcomes of TBI? By using PET to assess tau deposits in patients with chronic TBI, Takahata et al. reveal elevated tau load compared to age-matched controls, and show that the abundance of tau in white matter is associated with late-onset neuropsychiatric symptoms.

AbstractBackgroundGenetic variation at the microtubule‐associated protein tau locus is associated with clinical parkinsonism. However, it is unclear as to whether microtubule‐associated protein tau H1 subhaplotypes are associated with the burden of neuropathological features of Lewy body disease.ObjectivesTo evaluate associations of microtubule‐associated protein tau haplotypes with severity of Lewy body pathology and markers of SN neuronal loss in Lewy body disease cases.MethodsFive hundred eighty‐five autopsy‐confirmed Lewy body disease cases were included. Six microtubule‐associated protein tau variants (rs1467967, rs242557, rs3785883, rs2471738, rs8070723, and rs7521) were genotyped to define common microtubule‐associated protein tau haplotypes. Lewy body counts were measured in five cortical regions. Ventrolateral and medial SN neuronal loss were assessed semiquantitatively. Nigrostriatal dopaminergic degeneration was quantified by image analysis of tyrosine hydroxylase immunoreactivity in the dorsolateral and ventromedial putamen.ResultsThe common microtubule‐associated protein tau H2 haplotype did not show a strong effect on pathological burden in Lewy body disease. The rare H1j haplotype (1.3%) was significantly associated with a lower dorsolateral putaminal tyrosine hydroxylase immunoreactivity (and therefore greater dopaminergic degeneration) compared to other microtubule‐associated protein tau haplotypes (P = 0.0016). Microtubule‐associated protein tau H1j was also nominally (P ≤ 0.05) associated with a lower ventromedial putaminal tyrosine hydroxylase immunoreactivity (P = 0.010), but this did not survive multiple testing correction. Other nominally significant associations between microtubule‐associated protein tau H1 subhaplotypes and neuropathological outcomes were observed.ConclusionsA rare microtubule‐associated protein tau H1 subhaplotype (H1j) may be associated with more severe putaminal dopaminergic degeneration in Lewy body disease cases. Microtubule‐associated protein tau H1j has been associated previously with an increased risk of PD, and therefore our exploratory findings provide insight into the mechanism by which H1j modulates PD risk. © 2019 International Parkinson and Movement Disorder Society