The relationship between hippocampal amyloid beta burden and spatial distribution of neurofibrillary degeneration.

INTRODUCTION: Neurofibrillary degeneration in Alzheimer's disease (AD) typically involves the entorhinal cortex and CA1 subregion of the hippocampus early in the disease process, whereas in primary age-related tauopathy (PART), there is an early selective vulnerability of the CA2 subregion. METHODS: Image analysis-based quantitative pixel assessments were used to objectively evaluate amyloid beta (Aß) burden in the medial temporal lobe in relation to the distribution of hyperphosphorylated-tau (p-tau) in 142 cases of PART and AD. RESULTS: Entorhinal, CA1, CA3, and CA4 p-tau deposition levels are significantly correlated with Aß burden, while CA2 p-tau is not. Furthermore, the CA2/CA1 p-tau ratio is inversely correlated with Aß burden and distribution. In addition, cognitive impairment is correlated with overall p-tau burden. DISCUSSION: These data indicate that the presence and extent of medial temporal lobe Aß may determine the distribution and spread of neurofibrillary degeneration. The resulting p-tau distribution patterns may discriminate between PART and AD. HIGHLIGHTS: Subregional hyperphosphorylated-tau (p-tau) distribution is influenced by hippocampal amyloid beta burden. Higher CA2/CA1 p-tau ratio is predictive of primary age-related tauopathy-like neuropathology. Cognitive function is correlated with the overall hippocampal p-tau burden.

Genome-wide association study and functional validation implicates JADE1 in tauopathy.

Primary age-related tauopathy (PART) is a neurodegenerative pathology with features distinct from but also overlapping with Alzheimer disease (AD). While both exhibit Alzheimer-type temporal lobe neurofibrillary degeneration alongside amnestic cognitive impairment, PART develops independently of amyloid-ß (Aß) plaques. The pathogenesis of PART is not known, but evidence suggests an association with genes that promote tau pathology and others that protect from Aß toxicity. Here, we performed a genetic association study in an autopsy cohort of individuals with PART (n = 647) using Braak neurofibrillary tangle stage as a quantitative trait. We found some significant associations with candidate loci associated with AD (SLC24A4, MS4A6A, HS3ST1) and progressive supranuclear palsy (MAPT and EIF2AK3). Genome-wide association analysis revealed a novel significant association with a single nucleotide polymorphism on chromosome 4 (rs56405341) in a locus containing three genes, including JADE1 which was significantly upregulated in tangle-bearing neurons by single-soma RNA-seq. Immunohistochemical studies using antisera targeting JADE1 protein revealed localization within tau aggregates in autopsy brains with four microtubule-binding domain repeats (4R) isoforms and mixed 3R/4R, but not with 3R exclusively. Co-immunoprecipitation in post-mortem human PART brain tissue revealed a specific binding of JADE1 protein to four repeat tau lacking N-terminal inserts (0N4R). Finally, knockdown of the Drosophila JADE1 homolog rhinoceros (rno) enhanced tau-induced toxicity and apoptosis in vivo in a humanized 0N4R mutant tau knock-in model, as quantified by rough eye phenotype and terminal deoxynucleotidyl transferase dUTP nick end-labeling (TUNEL) in the fly brain. Together, these findings indicate that PART has a genetic architecture that partially overlaps with AD and other tauopathies and suggests a novel role for JADE1 as a modifier of neurofibrillary degeneration.

Artificial intelligence in neuropathology: deep learning-based assessment of tauopathy.

Accumulation of abnormal tau in neurofibrillary tangles (NFT) occurs in Alzheimer disease (AD) and a spectrum of tauopathies. These tauopathies have diverse and overlapping morphological phenotypes that obscure classification and quantitative assessments. Recently, powerful machine learning-based approaches have emerged, allowing the recognition and quantification of pathological changes from digital images. Here, we applied deep learning to the neuropathological assessment of NFT in postmortem human brain tissue to develop a classifier capable of recognizing and quantifying tau burden. The histopathological material was derived from 22 autopsy brains from patients with tauopathies. We used a custom web-based informatics platform integrated with an in-house information management system to manage whole slide images (WSI) and human expert annotations as ground truth. We utilized fully annotated regions to train a deep learning fully convolutional neural network (FCN) implemented in PyTorch against the human expert annotations. We found that the deep learning framework is capable of identifying and quantifying NFT with a range of staining intensities and diverse morphologies. With our FCN model, we achieved high precision and recall in naive WSI semantic segmentation, correctly identifying tangle objects using a SegNet model trained for 200 epochs. Our FCN is efficient and well suited for the practical application of WSIs with average processing times of 45 min per WSI per GPU, enabling reliable and reproducible large-scale detection of tangles. We measured performance on test data of 50 pre-annotated regions on eight naive WSI across various tauopathies, resulting in the recall, precision, and an F1 score of 0.92, 0.72, and 0.81, respectively. Machine learning is a useful tool for complex pathological assessment of AD and other tauopathies. Using deep learning classifiers, we have the potential to integrate cell- and region-specific annotations with clinical, genetic, and molecular data, providing unbiased data for clinicopathological correlations that will enhance our knowledge of the neurodegeneration.

Differential Vulnerability of Hippocampal Subfields in Primary Age-Related Tauopathy and Chronic Traumatic Encephalopathy.

Chronic traumatic encephalopathy (CTE) is a tauopathy associated with repetitive mild head impacts characterized by perivascular hyperphosphorylated tau (p-tau) in neurofibrillary tangles (NFTs) and neurites in the depths of the neocortical sulci. In moderate to advanced CTE, NFTs accumulate in the hippocampus, potentially overlapping neuroanatomically with primary age-related tauopathy (PART), an age-related tauopathy characterized by Alzheimer disease-like tau pathology in the hippocampus devoid of amyloid plaques. We measured p-tau burden using positive-pixel counts on immunohistochemically stained and neuroanatomically segmented hippocampal tissue. Subjects with CTE had a higher total p-tau burden than PART subjects in all sectors (p = 0.005). Within groups, PART had significantly higher total p-tau burden in CA1/subiculum compared to CA3 (p = 0.02) and CA4 (p = 0.01) and total p-tau burden in CA2 trended higher than CA4 (p = 0.06). In CTE, total p-tau burden in CA1/subiculum was significantly higher than in the dentate gyrus; and CA2 also trended higher than dentate gyrus (p = 0.01, p = 0.06). When controlling for p-tau burden across the entire hippocampus, CA3 and CA4 had significantly higher p-tau burden in CTE than PART (p < 0.0001). These data demonstrate differences in hippocampal p-tau burden and regional distribution in CTE compared to PART that might be helpful in differential diagnosis and reveal insights into disease pathogenesis.

Artificial intelligence-derived neurofibrillary tangle burden is associated with antemortem cognitive impairment.

Tauopathies are a category of neurodegenerative diseases characterized by the presence of abnormal tau protein-containing neurofibrillary tangles (NFTs). NFTs are universally observed in aging, occurring with or without the concomitant accumulation of amyloid-beta peptide (Aß) in plaques that typifies Alzheimer disease (AD), the most common tauopathy. Primary age-related tauopathy (PART) is an Aß-independent process that affects the medial temporal lobe in both cognitively normal and impaired subjects. Determinants of symptomology in subjects with PART are poorly understood and require clinicopathologic correlation; however, classical approaches to staging tau pathology have limited quantitative reproducibility. As such, there is a critical need for unbiased methods to quantitatively analyze tau pathology on the histological level. Artificial intelligence (AI)-based convolutional neural networks (CNNs) generate highly accurate and precise computer vision assessments of digitized pathology slides, yielding novel histology metrics at scale. Here, we performed a retrospective autopsy study of a large cohort (n = 706) of human post-mortem brain tissues from normal and cognitively impaired elderly individuals with mild or no Aß plaques (average age of death of 83.1 yr, range 55-110). We utilized a CNN trained to segment NFTs on hippocampus sections immunohistochemically stained with antisera recognizing abnormal hyperphosphorylated tau (p-tau), which yielded metrics of regional NFT counts, NFT positive pixel density, as well as a novel graph-theory based metric measuring the spatial distribution of NFTs. We found that several AI-derived NFT metrics significantly predicted the presence of cognitive impairment in both the hippocampus proper and entorhinal cortex (p < 0.0001). When controlling for age, AI-derived NFT counts still significantly predicted the presence of cognitive impairment (p = 0.04 in the entorhinal cortex; p = 0.04 overall). In contrast, Braak stage did not predict cognitive impairment in either age-adjusted or unadjusted models. These findings support the hypothesis that NFT burden correlates with cognitive impairment in PART. Furthermore, our analysis strongly suggests that AI-derived metrics of tau pathology provide a powerful tool that can deepen our understanding of the role of neurofibrillary degeneration in cognitive impairment.

Interpretable deep learning of myelin histopathology in age-related cognitive impairment.

Age-related cognitive impairment is multifactorial, with numerous underlying and frequently co-morbid pathological correlates. Amyloid beta (Aß) plays a major role in Alzheimer's type age-related cognitive impairment, in addition to other etiopathologies such as Aß-independent hyperphosphorylated tau, cerebrovascular disease, and myelin damage, which also warrant further investigation. Classical methods, even in the setting of the gold standard of postmortem brain assessment, involve semi-quantitative ordinal staging systems that often correlate poorly with clinical outcomes, due to imperfect cognitive measurements and preconceived notions regarding the neuropathologic features that should be chosen for study. Improved approaches are needed to identify histopathological changes correlated with cognition in an unbiased way. We used a weakly supervised multiple instance learning algorithm on whole slide images of human brain autopsy tissue sections from a group of elderly donors to predict the presence or absence of cognitive impairment (n = 367 with cognitive impairment, n = 349 without). Attention analysis allowed us to pinpoint the underlying subregional architecture and cellular features that the models used for the prediction in both brain regions studied, the medial temporal lobe and frontal cortex. Despite noisy labels of cognition, our trained models were able to predict the presence of cognitive impairment with a modest accuracy that was significantly greater than chance. Attention-based interpretation studies of the features most associated with cognitive impairment in the top performing models suggest that they identified myelin pallor in the white matter. Our results demonstrate a scalable platform with interpretable deep learning to identify unexpected aspects of pathology in cognitive impairment that can be translated to the study of other neurobiological disorders.

Antemortem detection of Parkinson's disease pathology in peripheral biopsies using artificial intelligence.

The diagnosis of Parkinson's disease (PD) is challenging at all stages due to variable symptomatology, comorbidities, and mimicking conditions. Postmortem assessment remains the gold standard for a definitive diagnosis. While it is well recognized that PD manifests pathologically in the central nervous system with aggregation of α-synuclein as Lewy bodies and neurites, similar Lewy-type synucleinopathy (LTS) is additionally found in the peripheral nervous system that may be useful as an antemortem biomarker. We have previously found that detection of LTS in submandibular gland (SMG) biopsies is sensitive and specific for advanced PD; however, the sensitivity is suboptimal especially for early-stage disease. Further, visual microscopic assessment of biopsies by a neuropathologist to identify LTS is impractical for large-scale adoption. Here, we trained and validated a convolutional neural network (CNN) for detection of LTS on 283 digital whole slide images (WSI) from 95 unique SMG biopsies. A total of 8,450 LTS and 35,066 background objects were annotated following an inter-rater reliability study with Fleiss Kappa = 0.72. We used transfer learning to train a CNN model to classify image patches (151 × 151 pixels at 20× magnification) with and without the presence of LTS objects. The trained CNN model showed the following performance on image patches: sensitivity: 0.99, specificity: 0.99, precision: 0.81, accuracy: 0.99, and F-1 score: 0.89. We further tested the trained network on 1230 naïve WSI from the same cohort of research subjects comprising 42 PD patients and 14 controls. Logistic regression models trained on features engineered from the CNN predictions on the WSI resulted in sensitivity: 0.71, specificity: 0.65, precision: 0.86, accuracy: 0.69, and F-1 score: 0.76 in predicting clinical PD status, and 0.64 accuracy in predicting PD stage, outperforming expert neuropathologist LTS density scoring in terms of sensitivity but not specificity. These findings demonstrate the practical utility of a CNN detector in screening for LTS, which can translate into a computational tool to facilitate the antemortem tissue-based diagnosis of PD in clinical settings.

Asymmetry of Hippocampal Tau Pathology in Primary Age-Related Tauopathy and Alzheimer Disease.

Primary age-related tauopathy (PART) is a neurodegenerative entity defined as neurofibrillary degeneration generally restricted to the medial temporal region (Braak stage I-IV) with complete or near absence of diffuse and neuritic plaques. Symptoms range in severity but are generally milder and later in onset than in Alzheimer disease (AD). Recently, an early predilection for neurofibrillary degeneration in the hippocampal CA2 subregion has been demonstrated in PART, whereas AD neuropathologic change (ADNC) typically displays relative sparing of CA2 until later stages. In this study, we utilized a semiquantitative scoring system to evaluate asymmetry of neurofibrillary degeneration between left and right hippocampi in 67 PART cases and 17 ADNC cases. 49% of PART cases demonstrated asymmetric findings in at least one hippocampal subregion, and 79% of the asymmetric cases displayed some degree of CA2 asymmetry. Additionally, 19% of cases revealed a difference in Braak score between the right and left hippocampi. There was a significant difference in CA2 neurofibrillary degeneration (p = 0.0006) and CA2/CA1 ratio (p < 0.0001) when comparing the contralateral sides, but neither right nor left was more consistently affected. These data show the importance of analyzing bilateral hippocampi in the diagnostic evaluation of PART and potentially of other neurodegenerative diseases.

Predictors of cognitive impairment in primary age-related tauopathy: an autopsy study.

Primary age-related tauopathy (PART) is a form of Alzheimer-type neurofibrillary degeneration occurring in the absence of amyloid-beta (Aß) plaques. While PART shares some features with Alzheimer disease (AD), such as progressive accumulation of neurofibrillary tangle pathology in the medial temporal lobe and other brain regions, it does not progress extensively to neocortical regions. Given this restricted pathoanatomical pattern and variable symptomatology, there is a need to reexamine and improve upon how PART is neuropathologically assessed and staged. We performed a retrospective autopsy study in a collection (n = 174) of post-mortem PART brains and used logistic regression to determine the extent to which a set of clinical and neuropathological features predict cognitive impairment. We compared Braak staging, which focuses on hierarchical neuroanatomical progression of AD tau and Aß pathology, with quantitative assessments of neurofibrillary burden using computer-derived positive pixel counts on digitized whole slide images of sections stained immunohistochemically with antibodies targeting abnormal hyperphosphorylated tau (p-tau) in the entorhinal region and hippocampus. We also assessed other factors affecting cognition, including aging-related tau astrogliopathy (ARTAG) and atrophy. We found no association between Braak stage and cognitive impairment when controlling for age (p = 0.76). In contrast, p-tau burden was significantly correlated with cognitive impairment even when adjusting for age (p = 0.03). The strongest correlate of cognitive impairment was cerebrovascular disease, a well-known risk factor (p < 0.0001), but other features including ARTAG (p = 0.03) and hippocampal atrophy (p = 0.04) were also associated. In contrast, sex, APOE, psychiatric illness, education, argyrophilic grains, and incidental Lewy bodies were not. These findings support the hypothesis that comorbid pathologies contribute to cognitive impairment in subjects with PART. Quantitative approaches beyond Braak staging are critical for advancing our understanding of the extent to which age-related tauopathy changes impact cognitive function.

Early Selective Vulnerability of the CA2 Hippocampal Subfield in Primary Age-Related Tauopathy.

Primary age-related tauopathy (PART) is a neurodegenerative entity defined as Alzheimer-type neurofibrillary degeneration primarily affecting the medial temporal lobe with minimal to absent amyloid-ß (Aß) plaque deposition. The extent to which PART can be differentiated pathoanatomically from Alzheimer disease (AD) is unclear. Here, we examined the regional distribution of tau pathology in a large cohort of postmortem brains (n = 914). We found an early vulnerability of the CA2 subregion of the hippocampus to neurofibrillary degeneration in PART, and semiquantitative assessment of neurofibrillary degeneration in CA2 was significantly greater than in CA1 in PART. In contrast, subjects harboring intermediate-to-high AD neuropathologic change (ADNC) displayed relative sparing of CA2 until later stages of their disease course. In addition, the CA2/CA1 ratio of neurofibrillary degeneration in PART was significantly higher than in subjects with intermediate-to-high ADNC burden. Furthermore, the distribution of tau pathology in PART diverges from the Braak NFT staging system and Braak stage does not correlate with cognitive function in PART as it does in individuals with intermediate-to-high ADNC. These findings highlight the need for a better understanding of the contribution of PART to cognitive impairment and how neurofibrillary degeneration interacts with Aß pathology in AD and PART.

Tau Phosphorylation and Aggregation in the Developing Human Brain.

Tau hyperphosphorylation, mostly at serine (Ser) or threonine (Thr) residues, plays a key role in the pathogenesis of Alzheimer disease (AD) and other tauopathies. Rodent studies show similar hyperphosphorylation in the developing brain, which may be involved in regulating axonal growth and plasticity, but detailed human studies are lacking. Here, we examine tau phosphorylation by immunohistochemistry and immunoblotting in human fetal and adult autopsy brain tissue. Of the 20 cases with sufficient tissue preservation, 18 (90%) showed positive staining for S214 (pSer214), with the majority also positive for CP13 (pSer202), and PHF-1 (pSer396/pSer404). AT8 (pSer202/pThr205) and RZ3 (pThr231) were largely negative while PG5 (pSer409) was negative in all cases. Immunoblotting showed tau monomers with a similar staining pattern. We also observed phospho-tau aggregates in the fetal molecular layer, staining positively for S214, CP13, and PHF1 and negative for thioflavin S. These corresponded to high-molecular weight (∼150 kD) bands seen on Western blots probed with S214, PHF1, and PG5. We therefore conclude that fetal phosphorylation overlaps with AD in some residues, while others (e.g. T231, S409) appear to be unique to AD, and that tau is capable of forming nontoxic aggregates in the developing brain. These findings suggest that the fetal brain is resilient to formation of toxic aggregates, the mechanism for which may yield insights into the pathogenesis of tau aggregation and toxicity in the aging brain.

Quantitative Assessment of Pathological Tau Burden in Essential Tremor: A Postmortem Study.

Essential tremor (ET) patients develop more cognitive impairment and dementia than controls, although there are surprisingly few data on the neuropathological basis for cognitive changes in ET. In this postmortem study, we assessed tau and other pathologies in 26 ET cases and 73 controls (non-ET) (1:3 matching). The mean age = 88.6 years; 55% were cognitively normal, 24% had mild cognitive impairment (MCI), and 20% had dementia. We found similar burdens of pathology using Braak, ß-amyloid and Lewy body assessments in ET and controls. In contrast, among cognitively normal subjects, ET cases had a higher number of NFT-positive neurons in the neocortex than controls (p < 0.001); the number of NFT-positive neurons in the medial temporal lobe was similar in these 2 groups (p = 0.22). Among subjects with MCI, ET cases also had higher numbers of NFT-positive neurons in the neocortex than controls (p < 0.001) but again, not in the medial temporal lobe (p = 0.55). Among subjects with dementia, the number of NFT-positive neurons was similar in ET cases and controls. Cognitive function correlated with quantitative neurofibrillary tangle counts in ET cases and controls. In the context of ET, pre-dementia tau burden is higher than in the absence of ET, suggesting a predisposition to tau pathology.