Tau interacts with SHP2 in neuronal systems and in Alzheimer's disease brains

Targeting Shp2 as a therapeutic strategy for neurodegenerative diseases

The incidence of neurodegenerative diseases (NDs) has increased recently. However, most of the current governance strategies are palliative and lack effective therapeutic drugs. Therefore, elucidating the pathological mechanism of NDs is the key to the development of targeted drugs. As a member of the tyrosine phosphatase family, the role of Shp2 has been studied in tumors, but the research in the nervous system is still in a sporadic state. It can be phosphorylated by tyrosine kinases and then positively regulate tyrosine kinase-dependent signaling pathways. It could also be used as an adaptor protein to mediate downstream signaling pathways. Most of the existing studies have shown that Shp2 may be a potential molecular "checkpoint" against NDs, but its role in promoting degenerative lesions is difficult to ignore as well, and its two-way effect of both activation and inhibition is very distinctive. Shp2 is closely related to NDs-related pathogenic factors such as oxidative stress, mitochondrial dysfunction, excitatory toxicity, immune inflammation, apoptosis, and autophagy. Its bidirectional effects interfere with these pathogenic factors, making it a core component of the feedback and crosstalk network between multiple signaling pathways. Therefore, this article reviews the molecular mechanism of Shp2 regulation in NDs and its regulatory role in various pathogenic factors, providing evidence for the treatment of NDs by targeting Shp2 and the development of molecular targeted drugs.

Interplay of force and local mechanisms in axonal plasticity and beyond

The interactions between mechanical forces and neuronal dynamics have long intrigued researchers. Several studies revealed that force plays a pivotal role in shaping axonal outgrowth. However, the molecular mechanisms underpinning force-driven axonal plasticity remain not completely elucidated. This review explores the relationship between force and axonal plasticity, with a focus on local mechanisms, including local translation and axonal transport, and the emerging concept of force-driven cross-talk, a dialogue in which local dynamics are tightly regulated. Recent experimental evidence suggests that microtubules may serve as key mediators of this cross-talk, orchestrating the coordination between local mechanisms and facilitating mass addition.

TYK2 regulates tau levels, phosphorylation and aggregation in a tauopathy mouse model

Alzheimer's disease is one of at least 26 diseases characterized by tau-positive accumulation in neurons, glia or both. However, it is still unclear what modifications cause soluble tau to transform into insoluble aggregates. We previously performed genetic screens that identified tyrosine kinase 2 (TYK2) as a candidate regulator of tau levels. Here we verified this finding and found that TYK2 phosphorylates tau at tyrosine 29 (Tyr29) leading to its stabilization and promoting its aggregation in human cells. We discovered that TYK2-mediated Tyr29 phosphorylation interferes with autophagic clearance of tau. We also show that TYK2-mediated phosphorylation of Tyr29 facilitates pathological tau accumulation in P301S tau-transgenic mice. Furthermore, knockdown of Tyk2 reduced total tau and pathogenic tau levels and rescued gliosis in a tauopathy mouse model. Collectively, these data suggest that partial inhibition of TYK2 could thus be a strategy to reduce tau levels and toxicity.

PINNet: a deep neural network with pathway prior knowledge for Alzheimer's disease

Introduction

Identification of Alzheimer's Disease (AD)-related transcriptomic signatures from blood is important for early diagnosis of the disease. Deep learning techniques are potent classifiers for AD diagnosis, but most have been unable to identify biomarkers because of their lack of interpretability.

Methods

To address these challenges, we propose a pathway information-based neural network (PINNet) to predict AD patients and analyze blood and brain transcriptomic signatures using an interpretable deep learning model. PINNet is a deep neural network (DNN) model with pathway prior knowledge from either the Gene Ontology or Kyoto Encyclopedia of Genes and Genomes databases. Then, a backpropagation-based model interpretation method was applied to reveal essential pathways and genes for predicting AD.

Results

The performance of PINNet was compared with a DNN model without a pathway. Performances of PINNet outperformed or were similar to those of DNN without a pathway using blood and brain gene expressions, respectively. Moreover, PINNet considers more AD-related genes as essential features than DNN without a pathway in the learning process. Pathway analysis of protein-protein interaction modules of highly contributed genes showed that AD-related genes in blood were enriched with cell migration, PI3K-Akt, MAPK signaling, and apoptosis in blood. The pathways enriched in the brain module included cell migration, PI3K-Akt, MAPK signaling, apoptosis, protein ubiquitination, and t-cell activation.

Discussion

By integrating prior knowledge about pathways, PINNet can reveal essential pathways related to AD. The source codes are available at https://github.com/DMCB-GIST/PINNet.

Exome-wide analysis reveals role of LRP1 and additional novel loci in cognition

Cognitive functioning is heritable, with metabolic risk factors known to accelerate age-associated cognitive decline. Identifying genetic underpinnings of cognition is thus crucial. Here, we undertake single-variant and gene-based association analyses upon 6 neurocognitive phenotypes across 6 cognition domains in whole-exome sequencing data from 157,160 individuals of the UK Biobank cohort to expound the genetic architecture of human cognition. We report 20 independent loci associated with 5 cognitive domains while controlling for APOE isoform-carrier status and metabolic risk factors; 18 of which were not previously reported, and implicated genes relating to oxidative stress, synaptic plasticity and connectivity, and neuroinflammation. A subset of significant hits for cognition indicates mediating effects via metabolic traits. Some of these variants also exhibit pleiotropic effects on metabolic traits. We further identify previously unknown interactions of APOE variants with LRP1 (rs34949484 and others, suggestively significant), AMIGO1 (rs146766120; pAla25Thr, significant), and ITPR3 (rs111522866, significant), controlling for lipid and glycemic risks. Our gene-based analysis also suggests that APOC1 and LRP1 have plausible roles along shared pathways of amyloid beta (Aβ) and lipid and/or glucose metabolism in affecting complex processing speed and visual attention. In addition, we report pairwise suggestive interactions of variants harbored in these genes with APOE affecting visual attention. Our report based on this large-scale exome-wide study highlights the effects of neuronal genes, such as LRP1, AMIGO1, and other genomic loci, thus providing further evidence of the genetic underpinnings for cognition during aging.

Cyclic microchip assay for measurement of hundreds of functional proteins in single neurons

Despite the fact that proteins carry out nearly all cellular functions and mark the differences of cells, the existing single-cell tools can only analyze dozens of proteins, a scale far from full characterization of cells and tissue yet. Herein, we present a single-cell cyclic multiplex in situ tagging (CycMIST) technology that affords the comprehensive functional proteome profiling of single cells. We demonstrate the technology by detecting 182 proteins that include surface markers, neuron function proteins, neurodegeneration markers, signaling pathway proteins, and transcription factors. Further studies on cells derived from the 5XFAD mice, an Alzheimer's Disease (AD) model, validate the utility of our technology and reveal the deep heterogeneity of brain cells. Through comparison with control mouse cells, we have identified differentially expressed proteins in AD pathology. Our technology could offer new insights into cell machinery and thus may advance many fields including drug discovery, molecular diagnostics, and clinical studies.

Targeting protein phosphatases for the treatment of inflammation-related diseases: From signaling to therapy

Inflammation is the common pathological basis of autoimmune diseases, metabolic diseases, malignant tumors, and other major chronic diseases. Inflammation plays an important role in tissue homeostasis. On one hand, inflammation can sense changes in the tissue environment, induce imbalance of tissue homeostasis, and cause tissue damage. On the other hand, inflammation can also initiate tissue damage repair and maintain normal tissue function by resolving injury and restoring homeostasis. These opposing functions emphasize the significance of accurate regulation of inflammatory homeostasis to ameliorate inflammation-related diseases. Potential mechanisms involve protein phosphorylation modifications by kinases and phosphatases, which have a crucial role in inflammatory homeostasis. The mechanisms by which many kinases resolve inflammation have been well reviewed, whereas a systematic summary of the functions of protein phosphatases in regulating inflammatory homeostasis is lacking. The molecular knowledge of protein phosphatases, and especially the unique biochemical traits of each family member, will be of critical importance for developing drugs that target phosphatases. Here, we provide a comprehensive summary of the structure, the "double-edged sword" function, and the extensive signaling pathways of all protein phosphatases in inflammation-related diseases, as well as their potential inhibitors or activators that can be used in therapeutic interventions in preclinical or clinical trials. We provide an integrated perspective on the current understanding of all the protein phosphatases associated with inflammation-related diseases, with the aim of facilitating the development of drugs that target protein phosphatases for the treatment of inflammation-related diseases.

Decoding Genetic Markers of Multiple Phenotypic Layers Through Biologically Constrained Genome-To-Phenome Bayesian Sparse Regression

The applicability of multivariate approaches for the joint analysis of genomics and phenomics information is currently limited by the lack of scalability, and by the difficulty of interpreting the related findings from a biological perspective. To tackle these limitations, we present Bayesian Genome-to-Phenome Sparse Regression (G2PSR), a novel multivariate regression method based on sparse SNP-gene constraints. The statistical framework of G2PSR is based on a Bayesian neural network, were constraints on SNPs-genes associations are integrated by incorporating a priori knowledge linking variants to their respective genes, to then reconstruct the phenotypic data in the output layer. Interpretability is promoted by inducing sparsity on the genes through variational dropout, allowing to estimate the uncertainty associated with each gene, and related SNPs, in the reconstruction task. Ultimately, G2PSR is conceived to prevent multiple testing correction and to assess the combined effect of SNPs, thus increasing the statistical power in detecting genome-to-phenome associations. The effectiveness of G2PSR was demonstrated on synthetic and real data, with respect to state-of-the-art methods based on group-wise sparsity constraints. The application on real data consisted in an imaging-genetics analysis on the Alzheimer's Disease Neuroimaging Initiative data, relating SNPs from more than 3,500 genes to clinical and multi-variate brain volumetric information. The experimental results show that our method can provide accurate selection of relevant genes in dataset with large SNPs-to-samples ratio, thus overcoming the main limitations of current genome-to-phenome association methods.

Memory enhancement effect of saponins from Eleutherococcus senticosus leaves and blood-brain barrier-permeated saponins profiling using a pseudotargeted monitoring strategy

Dried Eleutherococcus senticosus leaves (ESL), also known as Siberian ginseng tea, are beneficial for human neural disorders. Our previous studies showed that the aqueous extract of ESL enhanced memory in...

SARS-CoV-2 Exacerbates Beta-Amyloid Neurotoxicity, Inflammation and Oxidative Stress in Alzheimer's Disease Patients

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) triggered the pandemic Coronavirus Disease 19 (COVID-19), causing millions of deaths. The elderly and those already living with comorbidity are likely to die after SARS-CoV-2 infection. People suffering from Alzheimer’s disease (AD) have a higher risk of becoming infected, because they cannot easily follow health roles. Additionally, those suffering from dementia have a 40% higher risk of dying from COVID-19. Herein, we collected from Gene Expression Omnibus repository the brain samples of AD patients who died of COVID-19 (AD+COVID-19), AD without COVID-19 (AD), COVID-19 without AD (COVID-19) and control individuals. We inspected the transcriptomic and interactomic profiles by comparing the COVID-19 cohort against the control cohort and the AD cohort against the AD+COVID-19 cohort. SARS-CoV-2 in patients without AD mainly activated processes related to immune response and cell cycle. Conversely, 21 key nodes in the interactome are deregulated in AD. Interestingly, some of them are linked to beta-amyloid production and clearance. Thus, we inspected their role, along with their interactors, using the gene ontologies of the biological process that reveals their contribution in brain organization, immune response, oxidative stress and viral replication. We conclude that SARS-CoV-2 worsens the AD condition by increasing neurotoxicity, due to higher levels of beta-amyloid, inflammation and oxidative stress.

Tau Protein Interaction Partners and Their Roles in Alzheimer's Disease and Other Tauopathies

Tau protein plays a critical role in the assembly, stabilization, and modulation of microtubules, which are important for the normal function of neurons and the brain. In diseased conditions, several pathological modifications of tau protein manifest. These changes lead to tau protein aggregation and the formation of paired helical filaments (PHF) and neurofibrillary tangles (NFT), which are common hallmarks of Alzheimer's disease and other tauopathies. The accumulation of PHFs and NFTs results in impairment of physiological functions, apoptosis, and neuronal loss, which is reflected as cognitive impairment, and in the late stages of the disease, leads to death. The causes of this pathological transformation of tau protein haven't been fully understood yet. In both physiological and pathological conditions, tau interacts with several proteins which maintain their proper function or can participate in their pathological modifications. Interaction partners of tau protein and associated molecular pathways can either initiate and drive the tau pathology or can act neuroprotective, by reducing pathological tau proteins or inflammation. In this review, we focus on the tau as a multifunctional protein and its known interacting partners active in regulations of different processes and the roles of these proteins in Alzheimer's disease and tauopathies.

Tau: A Signaling Hub Protein

Over four decades ago, in vitro experiments showed that tau protein interacts with and stabilizes microtubules in a phosphorylation-dependent manner. This observation fueled the widespread hypotheses that these properties extend to living neurons and that reduced stability of microtubules represents a major disease-driving event induced by pathological forms of tau in Alzheimer’s disease and other tauopathies. Accordingly, most research efforts to date have addressed this protein as a substrate, focusing on evaluating how specific mutations, phosphorylation, and other post-translational modifications impact its microtubule-binding and stabilizing properties. In contrast, fewer efforts were made to illuminate potential mechanisms linking physiological and disease-related forms of tau to the normal and pathological regulation of kinases and phosphatases. Here, we discuss published work indicating that, through interactions with various kinases and phosphatases, tau may normally act as a scaffolding protein to regulate phosphorylation-based signaling pathways. Expanding on this concept, we also review experimental evidence linking disease-related tau species to the misregulation of these pathways. Collectively, the available evidence supports the participation of tau in multiple cellular processes sustaining neuronal and glial function through various mechanisms involving the scaffolding and regulation of selected kinases and phosphatases at discrete subcellular compartments. The notion that the repertoire of tau functions includes a role as a signaling hub should widen our interpretation of experimental results and increase our understanding of tau biology in normal and disease conditions.

From Pyrazolones to Azaindoles: Evolution of Active-Site SHP2 Inhibitors Based on Scaffold Hopping and Bioisosteric Replacement

The tyrosine phosphatase SHP2 controls the activity of pivotal signaling pathways, including MAPK, JAK-STAT, and PI3K-Akt. Aberrant SHP2 activity leads to uncontrolled cell proliferation, tumorigenesis, and metastasis. SHP2 signaling was recently linked to drug resistance against cancer medications such as MEK and BRAF inhibitors. In this work, we present the development of a novel class of azaindole SHP2 inhibitors. We applied scaffold hopping and bioisosteric replacement concepts to eliminate unwanted structural motifs and to improve the inhibitor characteristics of the previously reported pyrazolone SHP2 inhibitors. The most potent azaindole 45 inhibits SHP2 with an IC₅₀ = 0.031 μM in an enzymatic assay and with an IC₅₀ = 2.6 μM in human pancreas cells (HPAF-II). Evaluation in a series of cellular assays for metastasis and drug resistance demonstrated efficient SHP2 blockade. Finally, 45 inhibited proliferation of two cancer cell lines that are resistant to cancer drugs and diminished ERK signaling.

Data-Driven Modeling of Knowledge Assemblies in Understanding Comorbidity Between Type 2 Diabetes Mellitus and Alzheimer's Disease

Background:

Recent studies have suggested comorbid association between Alzheimer’s disease (AD) and type 2 diabetes mellitus (T2DM) through identification of shared molecular mechanisms. However, the inference is pre-dominantly literature-based and lacks interpretation of pre-disposed genomic variants and transcriptomic measurables.

Objective:

In this study, we aim to identify shared genetic variants and dysregulated genes in AD and T2DM and explore their functional roles in the comorbidity between the diseases.

Methods:

The genetic variants for AD and T2DM were retrieved from GWAS catalog, GWAS central, dbSNP, and DisGeNet and subjected to linkage disequilibrium analysis. Next, shared variants were prioritized using RegulomeDB and Polyphen-2. Afterwards, a knowledge assembly embedding prioritized variants and their corresponding genes was created by mining relevant literature using Biological Expression Language. Finally, coherently perturbed genes from gene expression meta-analysis were mapped to the knowledge assembly to pinpoint biological entities and processes and depict a mechanistic link between AD and T2DM.

Results:

Our analysis identified four genes (i.e., ABCG1, COMT, MMP9, and SOD2) that could have dual roles in both AD and T2DM. Using cartoon representation, we have illustrated a set of causal events surrounding these genes which are associated to biological processes such as oxidative stress, insulin resistance, apoptosis and cognition.

Conclusion:

Our approach of using data as the driving force for unraveling disease etiologies eliminates literature bias and enables identification of novel entities that serve as the bridge between comorbid conditions.

First person – Yohan Kim

First Person is a series of interviews with the first authors of a selection of papers published in Journal of Cell Science, helping early-career researchers promote themselves alongside their papers. Yohan Kim is first author on ‘Tau interacts with SHP2 in neuronal systems and in Alzheimer's disease brains’, published in JCS. Yohan conducted the research described in this article while a graduate student in Gloria Lee's lab at the University of Iowa Carver College of Medicine, IA, USA . He is now a postdoctoral fellow in the lab of Efrat Levy at the Center for Dementia Research, Nathan S. Kline Institute, NY, USA, investigating the pathogenesis of Alzheimer's disease and developing therapeutic strategies.