Molecular Processing of Tau Protein in Progressive Supranuclear Palsy: Neuronal and Glial Degeneration

Connecting cellular mechanisms and extracellular vesicle cargo in traumatic brain injury

Traumatic brain injury is followed by a cascade of dynamic and complex events occurring at the cellular level. These events include: diffuse axonal injury, neuronal cell death, blood-brain barrier break down, glial activation and neuroinflammation, edema, ischemia, vascular injury, energy failure, and peripheral immune cell infiltration. The timing of these events post injury has been linked to injury severity and functional outcome. Extracellular vesicles are membrane bound secretory vesicles that contain markers and cargo pertaining to their cell of origin and can cross the blood-brain barrier. These qualities make extracellular vesicles intriguing candidates for a liquid biopsy into the pathophysiologic changes occurring at the cellular level post traumatic brain injury. Herein, we review the most commonly reported cargo changes in extracellular vesicles from clinical traumatic brain injury samples. We then use knowledge from animal and in vitro models to help infer what these changes may indicate regrading cellular responses post traumatic brain injury. Future research should prioritize labeling extracellular vesicles with markers for distinct cell types across a range of timepoints post traumatic brain injury.

The Role of Liquid-Liquid Phase Separation in the Accumulation of Pathological Proteins: New Perspectives on the Mechanism of Neurodegenerative Diseases

It is widely accepted that living organisms form highly dynamic membrane-less organelles (MLOS) with various functions through phase separation, and the indispensable role that phase separation plays in the mechanisms of normal physiological functions and pathogenesis is gradually becoming clearer. Pathological aggregates, regarded as hallmarks of neurodegenerative diseases, have been revealed to be closely related to aberrant phase separation. Specific proteins are assembled into condensates and transform into insoluble inclusions through aberrant phase separation, contributing to the development of diseases. In this review, we present an overview of the progress of phase separation research, involving its biological mechanisms and the status of research in neurodegenerative diseases, focusing on five main disease-specific proteins, tau, TDP-43, FUS, α-Syn and HTT, and how exactly these proteins reside within dynamic liquid-like compartments and thus turn into solid deposits. Further studies will yield new perspectives for understanding the aggregation mechanisms and potential therapeutic strategies, and future research directions are anticipated.

Insights into amyloid precursor protein target through PPI network analysis

Alzheimer's disease (AD) is the leading cause of dementia worldwide with therapeutic lacunae till date. The beta-amyloid (Aβ) accumulation triggers AD pathogenesis, though clinical trials lowering Aβ have not altered disease outcomes suggesting other interacting factors to be identified for drug design of AD. Therefore, it is of interest to identify potential hub proteins interlinked with disease-driving pathways using a network-based approach for AD therapeutic designing. Literature mining was done to identify proteins implicated in AD etiology. Protein-protein interactions (PPIs) were retrieved from the STRING database and merged into a single network using Cytoscape 3.10.1. The hub proteins involved in AD etiology were predicted based on the topological algorithms of CytoHubba. Six major proteins, with STRING database identifiers - APP, BACE1, PSEN1, MAPT, APOE4 and TREM2, were identified to be involved in AD pathogenesis. The merged network of PPIs of these proteins contained 51 nodes and 211 edges, as predicted by Analyzer module of Cytoscape. The Amyloid precursor protein (APP) emerged as the highest-scoring hub protein across multiple centrality measures and topological algorithms. Thus, current data provides evidence to support the ongoing investigation of APP's multifaceted functions and therapeutic potential for AD.

Alzheimer's Disease Puzzle: Delving into Pathogenesis Hypotheses

Alzheimer's disease (AD) is a prevalent neurodegenerative disease characterized by both amnestic and non-amnestic clinical manifestations. It accounts for approximately 60-70% of all dementia cases worldwide. With the increasing number of AD patients, elucidating underlying mechanisms and developing corresponding interventional strategies are necessary. Hypotheses about AD such as amyloid cascade, Tau hyper-phosphorylation, neuroinflammation, oxidative stress, mitochondrial dysfunction, cholinergic, and vascular hypotheses are not mutually exclusive, and all of them play a certain role in the development of AD. The amyloid cascade hypothesis is currently the most widely studied; however, other hypotheses are also gaining support. This article summarizes the recent evidence regarding major pathological hypotheses of AD and their potential interplay, as well as the strengths and weaknesses of each hypothesis and their implications for the development of effective treatments. This could stimulate further studies and promote the development of more effective therapeutic strategies for AD.

Tolfenamic Acid Derivatives: A New Class of Transcriptional Modulators with Potential Therapeutic Applications for Alzheimer's Disease and Related Disorders

The field of Alzheimer's disease (AD) has witnessed recent breakthroughs in the development of disease-modifying biologics and diagnostic markers. While immunotherapeutic interventions have provided much-awaited solutions, nucleic acid-based tools represent other avenues of intervention; however, these approaches are costly and invasive, and they have serious side effects. Previously, we have shown in AD animal models that tolfenamic acid (TA) can lower the expression of AD-related genes and their products and subsequently reduce pathological burden and improve cognition. Using TA as a scaffold and the zinc finger domain of SP1 as a pharmacophore, we developed safer and more potent brain-penetrating analogs that interfere with sequence-specific DNA binding at transcription start sites and predominantly modulate the expression of SP1 target genes. More importantly, the proteome of treated cells displayed ~75% of the downregulated products as SP1 targets. Specific levels of SP1-driven genes and AD biomarkers such as amyloid precursor protein (APP) and Tau proteins were also decreased as part of this targeted systemic response. These small molecules, therefore, offer a viable alternative to achieving desired therapeutic outcomes by interfering with both amyloid and Tau pathways with limited off-target systemic changes.

microRNA and circRNA in Parkinson's Disease and atypical parkinsonian syndromes

Multiple System Atrophy (MSA) and Progressive Supranuclear Palsy (PSP) are atypical parkinsonian syndromes (APS) with various clinical phenotypes and considerable clinical overlap with idiopathic Parkinson's disease (iPD). This disease heterogeneity makes ante-mortem diagnosis extremely challenging with up to 24% of patients misdiagnosed. Because diagnosis is predominantly clinical, there is great interest in identifying biomarkers for early diagnosis and differentiation of the different types of parkinsonism. Compared to protein biomarkers, microRNAs (miRNAs) and circularRNAs (circRNAs) are stable tissue-specific molecules that can be accurately measured by reverse transcription-quantitative polymerase chain reaction (RT-qPCR). This chapter critically reviews miRNAs and circRNAs as diagnostic biomarkers and therapeutics to differentiate atypical parkinsonian disorders and their role in disease pathogenesis.

Concomitant Neuronal Tau Deposition and FKBP52 Decrease Is an Early Feature of Different Human and Experimental Tauopathies

BACKGROUND

Pathological tau proteins constitute neurofibrillary tangles that accumulate in tauopathies including Alzheimer's disease (AD), progressive supranuclear palsy (PSP), and familial frontotemporal lobar degeneration (FTLD-Tau). We previously showed that the FKBP52 immunophilin interacts functionally with tau and strongly decreases in AD brain neurons in correlation with tau deposition. We also reported that FKBP52 co-localizes with autophagy-lysosomal markers and an early pathological tau isoform in AD neurons, suggesting its involvement in autophagic tau clearance.

OBJECTIVE

Our objective was to evaluate if differences in neuronal FKBP52 expression levels and subcellular localization might be detected in AD, PSP, familial FTLD-Tau, and in the hTau-P301 S mouse model compared to controls.

METHODS

Cell by cell immunohistofluorescence analyses and quantification of FKBP52 were performed on postmortem brain samples of some human tauopathies and on hTau-P301 S mice spinal cords.

RESULTS

We describe a similar FKBP52 decrease and its localization with early pathological tau forms in the neuronal autophagy-lysosomal pathway in various tauopathies and hTau-P301 S mice. We find that FKBP52 decreases early during the pathologic process as it occurs in rare neurons with tau deposits in the marginally affected frontal cortex region of AD Braak IV brains and in the spinal cord of symptomless 1-month-old hTau-P301 S mice.

CONCLUSION

As FKBP52 plays a significant role in cellular signaling and conceivably in tau clearance, our data support the idea that the prevention of FKBP52 decrease or the restoration of its normal expression at early pathologic stages might represent a new potential therapeutic approach in tauopathies including AD, familial FTLD-Tau, and PSP.

Interpretable Classification of Tauopathies with a Convolutional Neural Network Pipeline Using Transfer Learning and Validation against Post-Mortem Clinical Cases of Alzheimer's Disease and Progressive Supranuclear Palsy

Neurodegenerative diseases, tauopathies, constitute a serious global health problem. The etiology of these diseases is unclear and an increase in their incidence has been projected in the next 30 years. Therefore, the study of the molecular mechanisms that might stop these neurodegenerative processes is very relevant. Classification of neurodegenerative diseases using Machine and Deep Learning algorithms has been widely studied for medical imaging such as Magnetic Resonance Imaging. However, post-mortem immunofluorescence imaging studies of the brains of patients have not yet been used for this purpose. These studies may represent a valuable tool for monitoring aberrant chemical changes or pathological post-translational modifications of the Tau polypeptide. We propose a Convolutional Neural Network pipeline for the classification of Tau pathology of Alzheimer's disease and Progressive Supranuclear Palsy by analyzing post-mortem immunofluorescence images with different Tau biomarkers performed with models generated with the architecture ResNet-IFT using Transfer Learning. These models' outputs were interpreted with interpretability algorithms such as Guided Grad-CAM and Occlusion Analysis. To determine the best classifier, four different architectures were tested. We demonstrated that our design was able to classify diseases with an accuracy of 98.41% on average whilst providing an interpretation concerning the proper classification involving different structural patterns in the immunoreactivity of the Tau protein in NFTs present in the brains of patients with Progressive Supranuclear Palsy and Alzheimer's disease.

Tau interactome and RNA binding proteins in neurodegenerative diseases

Pathological tau aggregation is a primary neuropathological feature of many neurodegenerative diseases. Intriguingly, despite the common presence of tau aggregates in these diseases the affected brain regions, clinical symptoms, and morphology, conformation, and isoform ratio present in tau aggregates varies widely. The tau-mediated disease mechanisms that drive neurodegenerative disease are still unknown. Tau interactome studies are critically important for understanding tauopathy. They reveal the interacting partners that define disease pathways, and the tau interactions present in neuropathological aggregates provide potential insight into the cellular environment and protein interactions present during pathological tau aggregation. Here we provide a combined analysis of 12 tau interactome studies of human brain tissue, human cell culture models and rodent models of disease. Together, these studies identified 2084 proteins that interact with tau in human tissue and 1152 proteins that interact with tau in rodent models of disease. Our combined analysis of the tau interactome revealed consistent enrichment of interactions between tau and proteins involved in RNA binding, ribosome, and proteasome function. Comparison of human and rodent tau interactome studies revealed substantial differences between the two species. We also performed a second analysis to identify the tau interacting proteins that are enriched in neurons containing granulovacuolar degeneration or neurofibrillary tangle pathology. These results revealed a timed dysregulation of tau interactions as pathology develops. RNA binding proteins, particularly HNRNPs, emerged as early disease-associated tau interactors and therefore may have an important role in driving tau pathology.

Liquid-Liquid Phase Separation Promotes Protein Aggregation and Its Implications in Ferroptosis in Parkinson’s Disease Dementia

The pathological features of PDD are represented by dopaminergic neuronal death and intracellular α-synuclein (α-syn) aggregation. The interaction of iron accumulation with α-syn and tau was further explored as an essential pathological mechanism of PDD. However, the links and mechanisms between these factors remain unclear. Studies have shown that the occurrence and development of neurodegenerative diseases such as PDD are closely related to the separation of abnormal phases. Substances such as proteins can form droplets through liquid-liquid phase separation (LLPS) under normal physiological conditions and even undergo further liquid-solid phase transitions to form solid aggregates under disease or regulatory disorders, leading to pathological phenomena. By analyzing the existing literature, we propose that LLPS is the crucial mechanism causing abnormal accumulation of α-syn, tau, and other proteins in PDD, and its interaction with iron metabolism disorder is the key factor driving ferroptosis in PDD. Therefore, we believe that LLPS can serve as one of the means to explain the pathological mechanism of PDD. Determining the significance of LLPS in neurodegenerative diseases such as PDD will stimulate interest in research into treatments based on interference with abnormal LLPS.

A Novel Automatic Quantification Protocol for Biomarkers of Tauopathies in the Hippocampus and Entorhinal Cortex of Post-Mortem Samples Using an Extended Semi-Siamese U-Net

Simple Summary

Tauopathies is a term coined to describe an umbrella of disorders characterized by abnormal Tau polypeptide deposits in neurons, glial cells, and extracellular space. In this work, we propose a novel quantification protocol for the study of tauopathies based on the U-Net neural network architecture. We also compare the proposed method against other state of the art variations of the U-Net to test its efficacy.

Abstract

Efforts have been made to diagnose and predict the course of different neurodegenerative diseases through various imaging techniques. Particularly tauopathies, where the tau polypeptide is a key participant in molecular pathogenesis, have significantly increased their morbidity and mortality in the human population over the years. However, the standard approach to exploring the phenomenon of neurodegeneration in tauopathies has not been directed at understanding the molecular mechanism that causes the aberrant polymeric and fibrillar behavior of the tau protein, which forms neurofibrillary tangles that replace neuronal populations in the hippocampal and cortical regions. The main objective of this work is to implement a novel quantification protocol for different biomarkers based on pathological post-translational modifications undergone by tau in the brains of patients with tauopathies. The quantification protocol consists of an adaptation of the U-Net neural network architecture. We used the resulting segmentation masks for the quantification of combined fluorescent signals of the different molecular changes tau underwent in neurofibrillary tangles. The quantification considers the neurofibrillary tangles as an individual study structure separated from the rest of the quadrant present in the images. This allows us to detect unconventional interaction signals between the different biomarkers. Our algorithm provides information that will be fundamental to understanding the pathogenesis of dementias with another computational analysis approach in subsequent studies.