Tau Aggregation Research Articles

Associations of mid‐life cardiovascular function with late‐life Alzheimer’s disease pathology burden in the Heart SCORE study

AbstractBackgroundCardiovascular (CV) disease is associated with dementia and Alzheimer’s disease (AD), but its relationship with AD pathology remains elusive. We examined whether mid‐life arterial stiffness, endothelial function, and blood pressure are associated with late‐life beta‐amyloid (Aß) and tau burden.MethodParticipants in the Heart Strategies Concentrating on Risk (SCORE) study completed cardiovascular phenotyping between 2003‐2005 (midlife; 45‐59 years) and up to three brain PET sessions between 2018‐2022 (late‐life; >65 years). Mid‐life assessments included augmentation index (AI75; N = 134) as a measure of arterial stiffness, Framingham reactive hyperemia index (fRHI; N = 130) as a measure of endothelial function, and systolic‐blood pressure (SBP; N = 141); late‐life measures were global [11C]Pittsburgh Compound‐B (PiB) standardized uptake value ratio (SUVR) and regional (medial temporal, entorhinal, inferior temporal, amygdala) [18F]flortaucipir (FTP) SUVR as indices of Aß and tau deposition, respectively. In individual linear regression models, we tested associations of mid‐life AI75, RHI, and SBP with late‐life PiB and FTP SUVRs. We used mixed effects models to examine these relationships longitudinally. All models were adjusted for time between CV and PET measurements, baseline age, sex, racialization, apolipoprotein‐E4, BMI, and history of hypertension, high cholesterol, smoking, and diabetes.ResultIn multivariable models, higher mid‐life SBP was associated with lower late‐life FTP SUVR in the medial temporal lobe (β = ‐0.20, p = 0.04) and inferior temporal gyrus (β = ‐0.23, p = 0.01; Table 1); higher mid‐life SBP was also negatively associated with FTP SUVR trajectories in these regions (medial temporal lobe: β = ‐0.0004, p = 0.02; inferior temporal gyrus: β = ‐0.001, p = 0.01; Table 2). We did not detect significant relationships of mid‐life AI75 or RHI with late‐life FTP SUVRs (p≥0.05) or between any mid‐life cardiovascular measures and late‐life PiB SUVR (p≥0.08).ConclusionIn this dementia‐free, community‐based cohort, higher mid‐life SBP was associated with lower late‐life regional tau deposition and accumulation. Though counterintuitive, our findings are consistent with results of cross‐sectional studies, which suggest that CV risk factors may be followed by an initial brain arteriole response that is protective against tau accumulation through early years of late‐adulthood1,2. Future studies should interrogate the potential mechanisms and age‐modifying effects that may underlie the relationship between mid‐life CV risk factors and late‐life tau deposition.

Brain vasculature influences local tau accumulation in the human inferior temporal gyrus

AbstractBackgroundAlzheimer’s disease (AD) is a neurodegenerative disease that involves the accumulation of pathological tau protein. While the mechanisms behind tau accumulation are not well understood, they are pivotal to understanding the pathogenesis of AD. Because protein clearance in the brain is mediated in part by vasculature, we hypothesize that vasculature may direct the accumulation and distribution of tau pathology. In this study, we analyzed the spatial relationship between tau distribution and vasculature to elucidate vasculature’s role in tau clearance.MethodPost‐mortem human tissue samples (∼1 cm3) from the inferior temporal gyrus of 6 AD and 6 control donors were sliced at thicknesses of 500 µm to 1 mm. Tissue slices were prepared with tissue clearing. Cleared samples were stained with antibodies for tau (AT8), vasculature (GLUT1), nuclei (DAPI), and neurons (HUD). Images were collected using confocal fluorescence microscopy. A virtual reality tracing method was developed to segment individual blood vessels across large tissue volumes and 12‐21 individual vessels were isolated in each sample. Novel MATLAB scripts were developed to calculate the intensity of tau as a function of distance from the blood vessels’ surfaces.ResultIn AD samples, tau intensity varied along the length of the blood vessel and with distance from the blood vessel surface. Regions with high tau accumulation on the blood vessel surface exhibited elevated tau accumulation in the surrounding tissue. In regions with low tau accumulation on the blood vessel surface, tau intensity was observed to decrease near the vessel. The influence of blood vessels on tau intensity dissipated as distance from the vessel surface increased, where tau intensity approached the bulk value (average tau intensity across the entire image). Compared to AD samples, control tissue showed little AT8+ tau labeling and the relationship between tau and distance from blood vessels was not apparent.ConclusionThese results indicate that pathological tau accumulation is spatially related to blood vessels in AD. In addition, these data imply that blood vessels contribute to tau clearance and that vascular tau clearance is disrupted in regions with high tau accumulation.

RNAi knockdown of microtubule‐associated protein Tau prevents axonal damage and clears pre‐existing Tau aggregates in P301S transgenic tauopathy model mice

AbstractBackgroundThe hyperphosphorylation and subsequent aggregation of the microtubule‐associated protein Tau (encoded by the MAPT gene) is one of the major histopathological hallmarks of numerous tauopathies, including Alzheimer’s disease and progressive supranuclear palsy. The intracellular accumulation of aggregated Tau is associated with neuronal loss and disease progression in tauopathies. There is a high‐unmet need to identify strategies to target the intracellular accumulation of Tau aggregates with the aim of slowing tauopathy progression.MethodTo model this, we used mice carrying multiple copies of a transgene with a prion promoter driving human MAPT with human tauopathy‐inducing mutation P301S. P301S‐Tau transgenic mice progressively accumulate neuroglial Tau aggregates associated with axonal damage, gliosis, body weight loss, and ambulatory dysfunction.ResultP301S mice treated with a single intracerebroventricular injection of Tau siRNA at eight months of age, had a sustainable decrease in MAPT mRNA and soluble Tau protein for three months following siRNA treatment (reduced ∼83% and ∼59%, respectively). siRNA treatment also prevented the progressive decrease in body weight and abrogated axonal damage, evidenced by decreased neurofilament light (NFL) chain in plasma and cerebrospinal fluid of eleven‐month‐old mice. Importantly, immunohistochemical analysis of misfolded Tau in vivo and HEK293‐4RD‐CFP/YFP Tau aggregate biosensor assay testing in vitro revealed a ∼97% decrease of Tau aggregates in the eleven‐month‐old mice, suggesting there exists a yet‐to‐be identified mechanism of Tau fibril clearance.ConclusionTogether, these results suggest an RNAi therapeutics approach targeting of MAPT mRNA may be sufficient to improve multiple parameters of tauopathy disease progression and a provide a compelling rationale for further development of Tau‐lowering strategies.

Characteristics of AD‐brain tau aggregate internalisation by human astrocytes and the responses induced

AbstractBackgroundHighly phosphorylated tau aggregates are deposited in tauopathy brain as disease progresses, driven by a prion‐like spread of tau seeds. Evidence suggests that astrocytes may influence tau spread. However, the efficiency of uptake of disease‐associated tau species is not well defined, nor are the effects of tau uptake on astrocyte reactivity and function. We investigate human astrocyte ability to internalise and clear tau aggregates derived from multiple Alzheimer’s disease (AD) cases, and their impact on astrocyte function and reactivity. We further explore alterations in endogenous tau expression, APP processing and cytoskeletal proteins following tau uptake.MethodControl human iPSC‐derived astrocytes were cultured for 70 days. Aggregated (sarkosyl‐insoluble) tau was isolated from postmortem AD brain. Post‐translational modifications (PTM) of isolated AD‐brain tau aggregates were analysed by mass spectrometry. Tau (0.1 ng/µL) and extracts from control human brain were spiked into astrocyte cultures. Internalisation of aggregated tau and the localised response of S100B and GFAP were quantified by ICC. Changes to tau, APP, functional and reactivity related genes were measured by qPCR and/or proteins by SDS‐PAGE.ResultAggregated tau from AD brain is readily internalised by human astrocytes, and sequesters GFAP and S100B. Differences in the rate of uptake, clearance and seeding of tau correlates with cytoskeletal protein accumulation and specific changes in astrocyte mRNA and protein levels. Work is in progress to relate these changes to characteristics of tau aggregates.ConclusionOur data shows that the capacity of AD brain aggregates to be internalised, cleared and induce seeding of endogenous tau varies by case. Investigations are underway to pinpoint the tau characteristics that underlie these differences. We also show that seeding ability is associated with changes in cytoskeletal elements and reactivity markers at mRNA and protein level. This work agrees with growing evidence that tau variability in AD is linked with specific cell type vulnerabilities that contribute to tau spread and disease progression.

The AD/ADRD Interdisciplinary Research Network on Biologically Active Tau Aggregate Polymorphs from Alzheimer’s Disease and Related Dementias

AbstractBackgroundTauopathies, including Alzheimer’s disease (AD), are characterized by intracellular lesions composed of aggregated and post‐translationally modified tau proteins. Methods for preparation and biochemical characterization of stable filaments from various tauopathies are well established. In contrast, methods for preparation of soluble oligomeric tau aggregates have not been standardized to the same degree. Additionally, the structures of oligomers which associate most closely with disease propagation and toxicity, are not fully established. The AD/ADRD Resource Network aims to isolate structurally vetted tau filaments and oligomers from human tauopathy cases and distribute them to the research community. In addition, it seeks to bank and distribute detection reagents and associated protocols. The overall mission of the network is to support impactful tauopathy research.MethodTauopathies, including Alzheimer’s disease (AD), are characterized by intracellular lesions composed of aggregated and post‐translationally modified tau proteins. Methods for preparation and biochemical characterization of stable filaments from various tauopathies are well established. In contrast, methods for preparation of soluble oligomeric tau aggregates have not been standardized to the same degree. Additionally, the structures of oligomers which associate most closely with disease propagation and toxicity, are not fully established. The AD/ADRD Resource Network aims to isolate structurally vetted tau filaments and oligomers from human tauopathy cases and distribute them to the research community. In addition, it seeks to bank and distribute detection reagents and associated protocols. The overall mission of the network is to support impactful tauopathy research.ResultProtocols for simultaneous isolation of oligomeric and filamentous tau aggregates have been developed along with analytical and quantitative methods to estimate sample heterogenicity and stability. Resource Network members are establishing cross‐laboratory analytical benchmarks for experiments to ensure rigor and reproducibility of results.ConclusionThe AD/ADRD Research Network banks rigorously validated preparations of structurally vetted tau aggregates along with directed protocols and reagents. Dissemination of these reagents is expected to maximize rigor and reproducibility of basic research involving tau protein aggregates.

Comparison of longitudinal rates of atrophy and tau accumulation between posterior cortical atrophy and logopenic progressive aphasia

AbstractBackgroundPosterior cortical atrophy (PCA) and logopenic progressive aphasia (LPA) are atypical variants of Alzheimer’s disease which typically show different cross‐sectional patterns of atrophy and tau deposition. Patterns of atrophy remain distinct longitudinally. A direct comparison of rates of atrophy and tau accumulation between these syndromes has not yet been reported.MethodWe evaluated 20 PCA and 20 LPA patients; all were amyloid‐positive on [11C]PiB‐PET. Structural MRI and tau‐PET were performed at baseline and one‐year follow‐up. Annualized rates of change in grey matter volume (log Jacobians from tensor‐based morphometry) and flortaucipir‐PET SUVRs were calculated at the lobar level. A global tau SUVR was calculated using parietal, temporal, and occipital regions. Lobar rates were compared between PCA and LPA with linear models, accounting for education, sex, age, baseline global tau SUVR (for tau‐PET), with significance set at p = 0.05. SPM voxel‐level comparisons were performed, with the same covariates, with significance set at p = 0.001.ResultGroups did not differ in age, Apoe status, baseline global tau SUVR or whole brain volume, or their annualized rates of change. LPA had shorter disease duration. In the lobar models, PCA had faster rates of atrophy in the occipital lobe and there were no significant differences on rates of tau accumulation, but a trend for LPA having faster rates of tau accumulation in all lobes. Baseline global tau SUVR was negatively associated with rate of tau accumulation in parietal and temporal lobes. Age was negatively associated with rates of tau accumulation in frontal, temporal and occipital lobes and with rates of atrophy in frontal and parietal lobes. Voxel‐level analysis confirmed these results, with PCA showing faster rates of occipital atrophy, and LPA showing subtle evidence for diffuse faster rates of tau accumulation (Figure 1).ConclusionLongitudinal patterns of neuroimaging abnormalities differ between PCA and LPA, although with divergent results for tau accumulation and atrophy that may reflect differences in disease stage. Rates of change are strongly influenced by age and severity of baseline tau, with faster rates of tau accumulation in patients with younger age and lower baseline tau deposition.

Aβ accumulation associated with executive function decline and tau accumulation associated with memory decline in cognitively normal older people

AbstractBackgroundThe early accumulation of Aß and tau in cognitively‐normal people is predictive of future cognitive decline. It has been difficult, however, to disentangle their effects. Aß and tau target distinct regions in early stages. Frontal‐parietal regions are among the first to show Aß accumulation and are important for executive control. Temporal regions, especially the medial temporal lobe, are early sites where tau accumulates and are critical for memory. Their differential vulnerability to Aß and tau allows us to examine whether there are specific pathology‐cognitive associations, where faster decline in memory, beyond its expected level based on executive function, may be related to tau accumulation, and that faster executive function decline may be related to Aß accumulation.Method78 cognitively‐normal older adults from the Berkeley Aging Cohort Study underwent longitudinal 11C‐Pittsburgh compound‐B (PiB) PET, 18F‐flortaucipir (FTP) PET, and cognitive assessments of executive function and memory (Fig‐1A). We used linear mixed‐effects models to estimate longitudinal change in Aß (Fig‐1B), temporal tau (Fig‐1C), executive function (Fig‐1D), and memory (Fig‐1E). We focused on within‐individual variability in cognitive decline in different domains and computed two cognitive decline residual scores (executive function controlling for memory, Fig‐2A; memory controlling for executive function, Fig‐2B) to represent domain‐specific performance decline.ResultAß accumulation across wide‐spread regions, especially frontal/parietal cortex, was associated with faster executive function decline, but not memory, even after controlling for meta‐temporal tau change (Fig‐3A). On the other hand, temporal tau accumulation, especially in the medial temporal regions, was related to faster memory decline, but not executive function, even after controlling for global Aß change (Fig‐3B). Using raw cognitive slopes, instead of residual scores, yielded stronger associations with both pathologies but reduced the ability to detect specific pathology‐cognition relationships.ConclusionWe found evidence supporting specific associations between accumulating pathology and domain‐specific cognitive decline. The “Aß‐executive function, tau‐memory” association may reflect specific vulnerabilities in the executive control network and the memory network to different pathology, leading to cognitive decline in different domains. The variability of cognitive decline within the same individual across different domains provides unique information and may be used as behavioral markers for specific pathology.

Aβ accumulation associated with executive function decline and tau accumulation associated with memory decline in cognitively normal older people

AbstractBackgroundThe early accumulation of Aβ and tau in cognitively‐normal people is predictive of future cognitive decline. It has been difficult, however, to disentangle their effects. Aβ and tau target distinct regions in early stages. Frontal‐parietal regions are among the first to show Aβ accumulation and are important for executive control. Temporal regions, especially the medial temporal lobe, are early sites where tau accumulates and are critical for memory. Their differential vulnerability to Aβ and tau allows us to examine whether there are specific pathology‐cognitive associations, where faster decline in memory, beyond its expected level based on executive function, may be related to tau accumulation, and that faster executive function decline may be related to Aβ accumulation.Method78 cognitively‐normal older adults from the Berkeley Aging Cohort Study underwent longitudinal 11C‐Pittsburgh compound‐B (PiB) PET, 18F‐flortaucipir (FTP) PET, and cognitive assessments of executive function and memory (Fig‐1A). We used linear mixed‐effects models to estimate longitudinal change in Aβ (Fig‐1B), temporal tau (Fig‐1C), executive function (Fig‐1D), and memory (Fig‐1E). We focused on within‐individual variability in cognitive decline in different domains and computed two cognitive decline residual scores (executive function controlling for memory, Fig‐2A; memory controlling for executive function, Fig‐2B) to represent domain‐specific performance decline.ResultAβ accumulation across wide‐spread regions, especially frontal/parietal cortex, was associated with faster executive function decline, but not memory, even after controlling for meta‐temporal tau change (Fig‐3A). On the other hand, temporal tau accumulation, especially in the medial temporal regions, was related to faster memory decline, but not executive function, even after controlling for global Aβ change (Fig‐3B). Using raw cognitive slopes, instead of residual scores, yielded stronger associations with both pathologies but reduced the ability to detect specific pathology‐cognition relationships.ConclusionWe found evidence supporting specific associations between accumulating pathology and domain‐specific cognitive decline. The “Aβ‐executive function, tau‐memory” association may reflect specific vulnerabilities in the executive control network and the memory network to different pathology, leading to cognitive decline in different domains. The variability of cognitive decline within the same individual across different domains provides unique information and may be used as behavioral markers for specific pathology.

Comparison of longitudinal rates of atrophy and tau accumulation between posterior cortical atrophy and logopenic progressive aphasia

AbstractBackgroundPosterior cortical atrophy (PCA) and logopenic progressive aphasia (LPA) are atypical variants of Alzheimer’s disease which typically show different cross‐sectional patterns of atrophy and tau deposition. Patterns of atrophy remain distinct longitudinally. A direct comparison of rates of atrophy and tau accumulation between these syndromes has not yet been reported.MethodWe evaluated 20 PCA and 20 LPA patients; all were amyloid‐positive on [11C]PiB‐PET. Structural MRI and tau‐PET were performed at baseline and one‐year follow‐up. Annualized rates of change in grey matter volume (log Jacobians from tensor‐based morphometry) and flortaucipir‐PET SUVRs were calculated at the lobar level. A global tau SUVR was calculated using parietal, temporal, and occipital regions. Lobar rates were compared between PCA and LPA with linear models, accounting for education, sex, age, baseline global tau SUVR (for tau‐PET), with significance set at p = 0.05. SPM voxel‐level comparisons were performed, with the same covariates, with significance set at p = 0.001.ResultGroups did not differ in age, Apoe status, baseline global tau SUVR or whole brain volume, or their annualized rates of change. LPA had shorter disease duration. In the lobar models, PCA had faster rates of atrophy in the occipital lobe and there were no significant differences on rates of tau accumulation, but a trend for LPA having faster rates of tau accumulation in all lobes. Baseline global tau SUVR was negatively associated with rate of tau accumulation in parietal and temporal lobes. Age was negatively associated with rates of tau accumulation in frontal, temporal and occipital lobes and with rates of atrophy in frontal and parietal lobes. Voxel‐level analysis confirmed these results, with PCA showing faster rates of occipital atrophy, and LPA showing subtle evidence for diffuse faster rates of tau accumulation (Figure 1).ConclusionLongitudinal patterns of neuroimaging abnormalities differ between PCA and LPA, although with divergent results for tau accumulation and atrophy that may reflect differences in disease stage. Rates of change are strongly influenced by age and severity of baseline tau, with faster rates of tau accumulation in patients with younger age and lower baseline tau deposition.

Biofluid phospho‐tau with subthreshold tau‐PET predicts higher rates of tau accumulation: implications for secondary prevention trials

AbstractBackgroundAn important end‐point for disease‐modifying treatments is to target the accumulation of tau. This highlights the need to determine which individuals are most likely to accumulate tau in the future. Different biomarkers of tau become abnormal at different stages of Alzheimer’s disease and capturing the evolution of tau pathology in its entirety will rely on multi‐modal assessments. Here, we examine longitudinal changes in tau accumulation associated with elevated CSF p‐tau and tau‐PET biomarkers.MethodA total of 231 amyloid‐positive (A+) individuals from the BioFINDER‐2 study were categorised into groups based on cut‐offs for abnormal CSF p‐tau217 (P) and [18F]RO948 tau‐PET (T), yielding groups of tau‐concordant‐negative (A+P‐T‐;n = 30), tau‐discordant (A+P+T‐;n = 48) and tau‐concordant‐positive (A+P+T+;n = 18) individuals. In addition, 135 amyloid‐β‐negative, unimpaired individuals served as controls. Differences in regional tau‐PET between groups were assessed using general‐linear models, adjusted for age, sex, clinical‐diagnosis and (for cognitive measures) education. We additionally assessed the effects on cortical thickness and cognition. Mean follow‐up time was ∼2 years.ResultIn the A+P+T‐ group, even though below the threshold for positivity, tau‐PET was higher at baseline than in the control and A+P‐T‐ groups, while cortical thickness and cognition were not different between these groups. For the A+P+T+ group, tau‐PET was higher, and cortical thickness, and cognition were lower at baseline than for controls, A+P‐T‐ and A+P+T‐. Longitudinal increase in tau‐PET was faster in the A+P+T‐ group than in controls and A+P‐T‐, primarily in the medial‐temporal lobe. The A+P+T+ group showed a faster rate of tau‐PET compared to controls and A+P‐T‐ (across the entire brain), and compared to A+P+T‐ (primarily neocortex). There were no differences in cortical thinning or cognitive decline between controls, A+P+T‐ and A+P‐T‐. The A+P+T+ group showed faster cortical thinning and cognitive decline compared to controls, A+P‐T‐ and A+P+T‐.ConclusionThe A+P+T‐ group only shows tau accumulation and no cortical thinning or cognitive decline, and therefore represents an interesting population for early intervention in the AD pathological process, preventing downstream effects. The A+P+T+ group shows fast and widespread tau accumulation and will, therefore, show the greatest beneficial effect of tau‐targeted treatment but already shows cortical thinning and cognitive decline at baseline.

Uncovering Novel Modifiers of Tau Aggregation and Pathology using a Proximity Proteomics Approach (BioID)

AbstractBackgroundAlzheimer’s disease (AD) is characterized by the accumulation of neurofibrillary tangles (NFTs), comprised primarily of microtubule‐associated protein tau. NFTs are defining hallmarks of AD and its accumulation into pathological oligomers and fibrils has been associated with cognitive decline in AD and other tauopathies. Despite its pivotal role in the disease process, we still have a poor understanding of how their formation, toxicity, and spread across brain regions is regulated via tau‐associated proteins that regulate the oligomerization, pathological accumulation, and seeding of tau in affected cell types and vulnerable brain regions.MethodWe have established two proximity‐dependent biotin‐identification (BioID) models as novel approaches to identify the composition and proximal molecular environment of tau aggregates. Using an in vitro and ex vivo model approach coupled with mass spectrometry, we have identified proteins that were primarily associated with mutant tau aggregates vs. soluble wildtype tau and stratified them based on significance, molecular pathway and druggability. Immunoblotting and immunofluorescence were performed to assess the interaction of endogenous and overexpressed top candidates with tau, along with visualization with NFTs in the context of human AD pathology to assess their impact on tau‐aggregate formation and toxicity.ResultTo determine the physiological and aggregate specific interacting partners of tau, we are comparing wild type tau (TauWT) with mutant tau (Tau3xMUT) carrying three tauopathy‐associated mutations (A152T/P301L/S320F). The proteomic analysis from our combined proteomic datasets revealed that significantly changed proteins included candidates involved in RNA processing, as well as protein ubiquitination and proteasome degradation. We have begun validating proteins that are enriched in mutant tau in human tissue of AD, as well as primary tauopathies, that may be druggable targets for tauopathies.ConclusionThis study provides novel insights into cellular pathways and molecular mechanisms of neurodegeneration, by identifying in the context of living neurons and brain tissue different functional classes of tau‐associated proteins with relevance for AD pathophysiology. These are expected to include proteins that may mediate the toxic effect of NFTs, facilitate the formation or degradation of pathological tau aggregates, and catalyze posttranslational modifications of tau oligomers and associated proteins.

A brain‐seeded fibril amplification models the aggregation process of tau in Alzheimer’s disease for drug discovery

AbstractBackgroundThe microtubule‐associated protein tau is implicated in the development of a class of diverse neurodegenerative disorders, referred to as tauopathies, with symptoms of dementia and parkinsonism. Tauopathies comprise more than 20 clinicopathological entities, including Alzheimer’s disease, which accounts for 70% of dementia cases worldwide. In combination with clinical diagnosis and neuropathology, the reconstruction of different tau filaments by cryogenic electron microscopy (cryo‐EM) further points to the presence of distinct tau folds. The knowledge of these disease‐specific aggregate conformers provides a platform for the establishment of novel diagnostic methods and more tailored therapeutic approaches.MethodIn order to investigate this problem, this project aims to selectively amplify tau in vitro from human brain homogenates affected by Alzheimer’s disease (AD) and Pick’s diseases (PiD). Kinetic analysis for drug discovery for the specific process of tau aggregation that takes place in Alzheimer’s disease was performed.ResultStrain discrimination was achieved, with a significant acceleration relative to the off‐target control, suggesting formation of two different fibril structures. Cryo‐EM was performed to confirm whether the in vitro AD‐like tau aggregates resembled those extracted from brains.We identify specific tau aggregation inhibitors, through in silico docking to binding sites on the surface of the cryo‐EM structure of tau fibrils adopting an AD fold.ConclusionThe application of this line of research is illustrated by a study of the aggregation kinetics of AD‐like tau fibrils, and of its potential in drug discovery. In perspective, the approach that we present offer novel opportunities for the systematic in vitro study of the tau aggregation process as it may happen in the human brain.References(WHO), W. H. O. et al. (2019). Dementia fact sheet.Alzheimer’s disease facts and figures. Alzheimer’s and Dementia 18, 700‐789 (2022).Chia, S. et al. Structure‐Based Discovery of Small‐Molecule Inhibitors of the Autocatalytic Proliferation of alpha‐Synuclein Aggregates. Mol Pharm (2022).

RNA‐Binding Proteins Musashi and Tau Aggresome in Alzheimer’s disease

AbstractBackgroundTauopathies, such as Alzheimer’s disease (AD), are characterized by the accumulation of toxic tau oligomers in the brain and accumulation of proteinaceous inclusions stored in cellular structures called aggresomes. Recent studies suggest that AD also exhibits pathology related to RNA binding proteins (RBPs), including Musashi proteins. Our lab has previously discovered that Musashi 1 (MSI1) and Musashi 2 (MSI2) aggregate in human AD brains and we have also visualized co‐localization with tau oligomers, suggesting toxic direct crosstalk between tau and MSI proteins. With this discovery and the growing evidence indicating MSI proteins as contributors to AD pathology, through their loss of functions it is crucial to elucidate how the interactions between misfolded tau and MSI influence tau aggregation and perhaps formation of cellular aggresomes.MethodIn this study, we characterize which tau oligomeric species, including phosphorylated and ubiquitinated ones, interact with MSI within the human AD brain (Braak Stage V‐VI). We investigate the deposition and cellular location of MSI and tau aggregates in AD and age‐matched control human cortical brain tissues by biochemical, immunohistochemistry and co‐immunofluorescence assays. Using high‐resolution microscopy and imaging analysis we measured the differences in size and morphology of MSI/tau co‐aggregates.ResultInvestigation of these co‐aggregates showed specific accumulation in neurons as well as in glial cells (astrocytes and microglia). We performed biochemical assays using commercial and in‐house antibodies to qualitatively investigate MSI1, MSI2, and tau across in AD brains. Co‐IF was performed to investigate the spatial and quantitative distribution of MSI1, MSI2, and tau aggregates. MSI/tau aggregate morphological characterization was conducted to profile their size and shape in AD cortices.ConclusionFor the first time, we show that the presence and quantity of tau oligomeric species and MSI co‐aggregates vary across the AD brains, showing inter‐subjects’ variability in size and deposition density. We also identify that tau conformers with MSI1 and MSI2 form different co‐aggregates in size and morphology quantifying their colocalization in high‐resolution 3D imaging. Further investigations are warranted to determine the temporal and regional distribution of these tau species in association with MSI proteins as well as the mechanisms underlying their aggregation.

Uncovering new tau aggregation and spreading mechanism through AD tau‐seed interactome analysis

AbstractBackgroundPathological tau aggregates are key features of Alzheimer’s disease and other tauopathies. The current research aims to understand how tau aggregates spread in AD patient brains, but the mechanisms remain unclear. Our recent‐published study found that the protein Bassoon plays a key role in tau spreading and pathology in a mouse model for tauopathy using mass spectrometry to identify proteins interacting with tau seeds. Considering our finding enhancing the relevance of tau‐seed interactor on disease pathology, we aim to characterize the interactome of the tau‐seed isolated from AD brains using a similar approach.MethodIn this study, we used Size Exclusion Chromatography (SEC) to separate TBS‐soluble AD and healthy brain extracts into fractions and measured tau seeding activity using a flow cytometry‐based biosensor cell line (n = 3). Then, the fractions with higher seeding activity were subjected to immunoprecipitation to isolate the tau seed and performed a TMT‐tags‐based unbiased quantitative mass spectrometry to uncover the specific tau species involved in tau propagation and identify new tau‐seed interactors.ResultThe strongest seeding activity in AD brains was found in fraction 9, which contains high molecular weight (HMW) proteins (>2,000 kDa), including only 5% of total tau, as assayed by ELISA for tau. Levels of tau were similar in fraction 9 in age‐matched controls but lacked seeding activity. Our bioinformatic analysis revealed that a total of 504 proteins interact with HWM tau without seeding activity isolated from controls and 1192 proteins interact with HWM tau‐seed isolated from AD cases. In addition, a total of 385 interacting proteins were found in both HWM tau from control and tau‐seed from AD cases. Interestingly, DAVID analysis as well as networks and interactions analysis (STRING analysis), revealed enrichment in proteins related to both synaptic and mitochondrial pathways.ConclusionOur findings significantly contribute to our understanding of the mechanisms involved in tau propagation and offer new insights into the potential for targeting tau‐seed interactions as a therapeutic strategy for tauopathies. Previously, we have identified BSN as a key interactor of tau seeds, and our data suggest that inhibiting these interactions could represent a promising new approach to treating these debilitating conditions.

Selective vulnerability of subcortical nuclei in atypical Alzheimer’s Disease

AbstractBackgroundRecent evidence suggests that sleep‐wake dysregulation in Alzheimer’s disease (AD) is an early event and parallels the tau accumulation in the arousal system spefically noted in the locus coeruleus (LC) as well as other subcortical nuclei as the Pedunculopontine Tegmental Nucleus (PPTg), Laterodorsal Tegmental Nucleus (LDTg), and the Dorsal Raphe (DR). We have previously demonstrated that the pattern of sleep‐wake dysfunction is different among AD clinical variants. This existence of specific sleep‐wake profiles suggest differential degeneration patterns of the arousal system within differing AD presentations. This study continues this investigation at the cellular/molecular level to uncover the selective vulnerability of subcortical structures to AD specific tau accumulation. That remains elusive to‐date.MethodHuman postmortem brainstem samples were sourced from the Neurodegenerative Disease Brain Bank (NDBB) at UCSF. 24 subjects were selected based on primary diagnosis, including 6 amnestic AD, 17 non‐amnestic AD (5 EOAD, 3 PCA, 5 lvPPA, 4 CBS) and 1 control. Paraffin blocks containing the areas of interest were cut into 8‐lm‐thick sections that underwent double‐labeled immunohistochemistry (IHC) and brightfield imaging. The images were then overlayed to created mutlidimentaional maps and neurons were classified in 4 subgroups: (1) positive for the neurotransmitter of interest (NEU‐positive), (2) bearing hyperphosphorylated tau neuronal cytoplasmic inclusions (tau‐positive), (3) positive for the neurotransmitter of interest and bearing tau‐positive (NEU‐positive/tau‐positive colocalized neurons), and (4) negative for NEU and tau.ResultIn the LC, lvPPA had the highest had the highest percentage of tau postive neurons (40%), followed by amnestic AD (31.1%), PCA (29.3%), EOAD (27.1%), and finally CBS (24.3%). EOAD had the highest percentage of colocalized neurons (34.7%) as well as LOAD (31%) compared to PCA (0.02%), lvPPA (0.18%), CBS (0.09%).ConclusionMultidimensional quantitative analysis suggests differences in vulnerabliblity of sleep‐wake subcortical nuclei to AD, EOAD, PCA, lvPPA, and CBS. For instance the neuronal loss in EOAD was so extreme in the LC that few neurons remained to develop aggregates whereas in PCA, CBS, and lvPPA the high percentage of tau accumulation presents a neuropathological framework underlying atypical clinical manifestations and possible insight into therapeutic targets.

Plasma p‐tau and brain‐derived total tau biomarkers predict longitudinal changes in Aβ, tau, and cognition across the AD continuum

AbstractBackgroundRecent studies have suggested that plasma p‐tau biomarkers are associated with cross‐sectional brain amyloid(Aβ) rather than tau tangle pathology. However, it is still unclear if plasma tau biomarkers are closely related to changes in AD pathophysiology over time. In this work, we aimed to determine if cross‐sectional measures of plasma tau biomarkers are associated with longitudinal changes in Aβ‐PET, tau‐PET, and cognition across the AD spectrum.MethodWe evaluated 157 individuals(96 cognitively unimpaired(CU) and 61 cognitively impaired (CI)) with available baseline measures of plasma Aβ42/40, p‐tau(at threonine 181, 217+, and 231), N‐terminal tau fragments(NTA, a new brain derived tau marker), and glial fibrillary acidic protein(GFAP) and with longitudinal [18F]AZD4694 Aβ‐PET, [18F]MK6340 tau‐PET and Clinical Dementia Rating sum of boxes(CDR‐SB) score from the TRIAD cohort. We also included 321(118 CU and 203 CI) individuals from the ADNI cohort with baseline plasma p‐tau181 and [18F]florbetapir Aβ‐PET and longitudinal CDR‐SB. Using linear regressions adjusted for age and sex we tested the associations between plasma biomarkers and longitudinal changes in Aβ‐PET, tau‐PET, and CDR‐SB.ResultIn CU, changes in tau‐PET were significantly associated only with plasma p‐tau217+(β = 0.331, p<0.01,Figure1A). Changes in Aβ‐PET were significantly associated with p‐tau181(β = 0.594, p<0.01,Figure2A), p‐tau217+(β = 0.311, p = 0.02) and NTA(β = 0.435, p<0.01), while no plasma biomarker was associated with changes in cognition in CU(Figure3A). In CI, changes in tau‐PET were significantly associated with plasma p‐tau181(β = ‐0.338, p = 0.03,Figure1B) and NTA(β = ‐0.379, p = 0.03), while no plasma biomarker was significantly associated with changes in Aβ‐PET. Changes in cognition were significantly associated with plasma p‐tau181(β = 0.340, p = 0.01, Figure3B), p‐tau217+(β = 0.54, p<0.01), and NTA(β = 0.530, p<0.01). Similarly, in the ADNI cohort, plasma p‐tau181 was associated with longitudinal changes in cognition in CI (β = 0.247, p<0.01,Figure3D).ConclusionWe demonstrate that cross‐sectional measures of plasma p‐tau and NTA biomarkers were associated with longitudinal Aβ deposition and tau accumulation in CU, while in CI they were only associated with tau accumulation. Interestingly, plasma tau biomarkers were also associated with changes in cognition in CI individuals. The fact that abnormal levels of plasma tau biomarkers are associated with longitudinal changes in AD pathophysiology has implications for the use of these markers in clinical trials and practice.

Interferon regulatory factor 5 modulates microglia response to tau by interfering with phagocytosis

AbstractBackgroundThe role of the immune system in responding to neurodegenerative pathology is well established. Microglia are at the center of such response, conveying on one end a positive protective effect, but on the other end, as with senescence, contributing to the hyperinflammation that is a core feature of neurodegeneration. We have identified the transcription factor interferon regulatory factor 5 (IRF5) as a mediator of microglia activation in response to pathological tau, described its specific activation by human‐derived PHF tau and its over‐representation in AD brains. We are now proposing that IRF5 can control the phagocytic activity of microglia, hence modulating their tau‐directed activity.MethodWe utilized age‐ and sex‐matched Irf5+/+ (WT) and Irf5− / − littermate mice for the analysis of ex vivo phagocytic activity of primary microglia, at steady‐state and triggered by tau. We examined microglia morphology and numbers under these conditions and with ageing. Last, we injected PHF tau intracranially to WT and Irf5− / − mice, monitoring tau accumulation and IRF5 response.Result1) Irf5− / − microglia have higher baseline phagocytic activity compared to WT microglia, which may be modulated by tau. 2) Microglia numbers are reduced in ageing Irf5− / − 3) PHF tau‐injected Irf5− / − mice show significant soluble tau accumulation, but a different pattern of oligomeric and insoluble tau accumulation with age. 4) In WT mice, the PHF tau‐injected hemisphere showed significantly higher levels of IRF5 compared to the contralateral, confirming a specific response of IRF5 to tau.ConclusionTau is a specific activator of microglia and of the IRF5 pathway, which can modulate microglia response to pathology. Ageing is an active variable in the process, affecting the pattern of microglia response to tau, differentially in WT and Irf5− / − mice. Modulating the IRF5 pathway may be a viable therapeutic approach in tauopathies.

Reduced slow‐wave sleep is associated with greater tau accumulation and reduced cortical thickness in the temporal lobe

AbstractBackgroundSlow wave sleep (SWS) plays an important role in overnight memory consolidation and promotes overnight clearance of amyloid‐β and tau proteins. Reduced SWS has been associated with higher amyloid burden in CSF in preclinical stages of Alzheimer’s disease (AD). However, little is known about the relationship between SWS, tau burden and neurodegeneration in cognitively unimpaired (CU) adults. Thus, we investigated the relationships between slow‐wave sleep, regional tau PET (18F‐flortaucipir; FTP‐PET) and temporal lobe cortical thickness in cognitively unimpaired adults at risk of AD.MethodsThis study included 39 CU adults from the Harvard Aging Brain Study (mean age 74.6 years, 61.5% females) who underwent at‐home polysomnography (PSG; Compumedics Somte), tau PET (FTP‐PET, amyloid PET (PIB‐PET) and MRI (Table 1). We used separate multivariate linear regressions to assess associations between the percentage of slow‐wave sleep (SWS) and tau PET signal in the following ROIs: entorhinal cortex, inferior temporal cortex, and a temporal composite comprised of entorhinal, inferior temporal, middle temporal and fusiform cortices. Primary analyses were adjusted for age and sex. Secondary analyses also adjusted for global amyloid (PiB‐PET) burden. Lastly, we investigated the relationship between SWS and cortical thickness in the same ROIs, assessed using FreeSurfer v6.0.ResultsLower percentage of SWS was associated with greater tau burden in entorhinal (p = 0.036), inferior temporal (p = 0.011), and temporal composite ROIs (p = 0.005). Associations between reduced SWS and greater FTP‐PET signal in the inferior temporal cortex and temporal composite ROI remained after controlling for PiB‐PET (p = 0.028; p = 0.017, respectively; Table 2). Additionally, lower SWS was associated with reduced cortical thickness in the entorhinal (p = 0.031), inferior temporal (p = 0.023) and temporal composite ROIs (p = 0.002) (Table 3).ConclusionsLower SWS in CU adults was associated with higher tau burden in regions of the temporal lobe that are commonly sites of early tau accumulation. These effects were independent of amyloid burden, suggesting disrupted sleep may lead to increased tau accumulation via an amyloid‐independent pathway. Importantly, lower SWS was also associated with reduced cortical thickness in temporal regions, suggesting that disrupted sleep may be tied to early AD‐related neuronal loss in the temporal lobe.

In vivo tau is associated with retrospective change in memory and processing speed, but not reasoning, in cognitively unimpaired older adults.

AbstractBackgroundThe relationship between tau accumulation and cognitive decline in cognitively unimpaired older adults is still unclear. The tau PET tracer 18F‐MK‐6240 has shown favorable imaging carachteristics to identify early tau accumulation in older adults.MethodWe evaluated the relationship between in vivo tau levels (18F‐MK‐6240) and retrospective cognitive change over 5 years in episodic memory, processing speed, and reasoning. For tau quantification, we created a set of regions of Interest (ROIs), selected a priori based on previous literature: 1) Total‐ROIs comprising all 16 areas selected; 2) Medial Temporal Lobe‐ROI, 3) Lateral Temporal Lobe‐ROI and Cingulate/Parietal lobel‐ROI.Result41 cognitively unimpaired older adults was included in the study, 82% classified as amyloid‐b negative. Higher tau burden in most meta‐ROIs was associated with steeper decline in memory and speed. There were no associations between tau and reasoning change.ConclusionOur finding reforces the notion that early tau accumulation in areas related tio Alzheimer’s disease is associated with cognitive decline in cognitively unimpaired individuals, even in a sample characterized with low amyloid‐b pathology. The novel contributin of this work is the relevante of tau accumulation beyond memory, particularly in processing speed decline.

Neurophysiological changes associated with plasma p‐tau represent functional effects of amyloid accumulation and are modulated by APOE.

AbstractBackgroundAlzheimer disease (AD) is defined by the presence of cerebral amyloid‐β plaques and tau neurofibrillary tangles (NFT). Neurophysiological manifestations which depict the functional changes of neurons and circuits, demonstrate that amyloid‐β and tau have distinct effects—high cerebral amyloid‐β burden is associated with increased neural oscillatory activity while high tau burden with decreased activity. With the recent proliferation of fluid biomarkers, plasma p‐tau181 is known to reflect accumulation of amyloid‐β as well as tau, detected from molecular imaging and neuropathological analyses. It remains unknown whether the neurophysiological consequences of soluble p‐tau reflects the effects of amyloid‐β or those of NFT.MethodWe used multimodal imaging combining magnetoencephalography (MEG) to cross‐sectionally study the spectral signatures and positron emission tomography with Aβ binding tracers to define the global amyloid burden in early‐stage neuropathological spectrum including Aβ+ cognitively‐unimpaired (CU, n = 9), Aβ+ mild‐cognitive‐impairment (MCI, n = 20), and Aβ‐negative CU controls (n = 45). Plasma p‐tau181 and neurofilament light (NFL) were measured with Simoa. Using statistical mixed models we examined the associations of neural oscillatory signatures with plasma p‐tau181 and NFL.ResultThe characteristic oscillatory signature of increased delta‐theta and reduced alpha spectrum were detectable even in the earliest stages of global amyloid accumulation (Aβ+CU vs. Aβ‐CU; Fig.1). Increased p‐tau181 was associated with increased spectral signatures across the frequency spectrum in Aβ+ individuals (Fig.2). These positive correlations were more robust within delta‐theta (2‐7Hz) than alpha (8‐12 Hz) spectrum. Plasma NFL in Aβ+ individuals, in contrast, was associated with reduced spectral signatures. We also found APOE‐ɛ4 carriers have greater degree of neurodegeneration which modulated the associations between p‐tau181 and neural oscillations (Fig.3).ConclusionPrevious neurophysiological studies have demonstrated that Aβ accumulation is associated with increased oscillatory activity while tau accumulation is associated with reduced oscillatory activity. Positive correlations of p‐tau181 across the spectrum is therefore consistent with the effects of Aβ accumulation and not with tau accumulation. Plasm NFL may represent early effects of neurodegeneration. Collectively our findings indicate that p‐tau181 reflects earliest functional effects of Aβ rather than tau and have implications for the interpretation of plasma p‐tau along the AT(N) stages.