scholarly journals MiR-29c-3p May Promote the Progression of Alzheimer’s Disease through BACE1

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yanqun Cao ◽  
Xiangxiang Tan ◽  
Quzhe Lu ◽  
Kai Huang ◽  
Xiaoer Tang ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cell Proliferation ◽  
Animal Models ◽  
Binding Sites ◽  
Target Genes ◽  
Specific Binding ◽  
Cell Models ◽  
Proliferation Activity ◽  
Bace1 Level

The aim of this study was to explore the specific role of miR-29c-3p in Alzheimer’s disease (AD). Animal models of AD were established by injecting streptozotocin (STZ) into mice through the lateral ventricle, while cell models of AD were induced by 10 μM β-amyloid (Aβ). We detected miR-29c-3p and β-site amyloid precursor protein cleaving enzyme 1 (BACE1) contents and measured AD cell proliferation and apoptosis. A low miR-29c-3p level and a high BACE1 level were detected in the brain tissue of AD animal models and AD cell models. Aβ-processed cells had markedly lower proliferation activity, higher apoptosis, increased phosphorylation of tau protein was over phosphorylated, but the overexpression of miR-29c-3p or the silencing of BACE1 significantly enhanced the cell proliferation activity and reduced cell apoptosis by regulating the contents of related proteins. Inhibition of miR-29c-3p or overexpression of BACE1 aggravated Aβ-induced side effects. We used Targetscan7.2 to predict the downstream target genes of miR-29c-3p. Then, we detected that there were target binding sites between miR-29c-3p and BACE1. The rescue experiment identified BACE1 as a functional target for miR-29c-3p. AD leads to decreased miR-29c-3p level and increased BACE1 level. MiR-29c-3p has specific binding sites with the 3′-untranslated region (3′-UTR) of BACE1 and thus negatively regulates the BACE1 level, thereby affecting the progression of AD.

scholarly journals Dynamic changes of autophagic flux induced by Abeta in the brain of postmortem Alzheimer’s disease patients, animal models and cell models

Aging ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 10912-10930
Author(s):  
Zhimin Long ◽  
Jingfei Chen ◽  
Yueyang Zhao ◽  
Wen Zhou ◽  
Qiuhui Yao ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Animal Models ◽  
Autophagic Flux ◽  
Cell Models ◽  
Dynamic Changes ◽  
The Brain

Differential Expression of miR-381-3p in Alzheimer’s Disease Patients and Its Role in Beta-Amyloid-Induced Neurotoxicity and Inflammation

2021 ◽  
pp. 1-9
Author(s):  
Meng Zhang ◽  
Yonglei Liu ◽  
Pingping Teng ◽  
Qing Yang
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cell Proliferation ◽  
Inflammatory Cytokines ◽  
Roc Curve ◽  
Pearson Correlation ◽  
Luciferase Reporter ◽  
Cell Models ◽  
Gene Assay ◽  
Proliferation And Apoptosis

<b><i>Introduction:</i></b> This study aimed to explore the diagnostic value and effect of miR-381-3p on Alzheimer’s disease (AD). <b><i>Methods:</i></b> RT-qPCR was used for the measurement of miR-381-3p levels. Pearson correlation coefficient was used for the correlation analysis. Receiver operating characteristic (ROC) curve was constructed to assess the distinct ability of miR-381-3p for AD. SH-SY5Y cells were treated with Aβ25-35 to establish an AD cell model. The role of miR-381-3p on cell proliferation and apoptosis was detected. ELISA was applied to detect the protein levels of inflammatory cytokine expression. The target relationship of miR-381-3p with PTGS2 was verified by luciferase reporter gene assay. <b><i>Results:</i></b> Low expression of miR-381-3p was detected in the serum of AD patients and cell models. There was a negative association of serum miR-381-3p with the serum inflammatory cytokines. The ROC curve demonstrated the distinct ability of serum miR-381-3p for AD, with the AUC value of 0.898, with a sensitivity of 87.5%, and a specificity of 77.7%. Overexpression of miR-381-3p reversed the influence of Aβ25-35 on cell proliferation and apoptosis, but miR-381-3p downregulation exacerbated the influence. miR-381-3p overexpression inhibited the release of IL-6, IL-1β, and TNF-α induced by Aβ25-35 treatment, whereas miR-381-3p downregulation further promoted the release of inflammatory cytokines. PTGS2 was the target gene of miR-381-3p and was upregulated in AD cell models. <b><i>Conclusion:</i></b> miR-381-3p is less expressed in the serum of AD patients and has potential diagnostic values for AD. Overexpression of miR-381-3p may attenuate Aβ25-35-induced neurotoxicity and inflammatory responses via targeting PTGS2 in SH-SY5Y cells.

scholarly journals Astroglial tracer BU99008 detects multiple binding sites in Alzheimer’s disease brain

2021 ◽  
Author(s):  
Amit Kumar ◽  
Niina A. Koistinen ◽  
Mona-Lisa Malarte ◽  
Inger Nennesmo ◽  
Martin Ingelsson ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Binding Sites ◽  
Specific Binding ◽  
Brain Regions ◽  
Binding Studies ◽  
Reactive Astrogliosis ◽  
High Affinity ◽  
Pet Tracer ◽  
Multiple Binding

AbstractWith reactive astrogliosis being established as one of the hallmarks of Alzheimer’s disease (AD), there is high interest in developing novel positron emission tomography (PET) tracers to detect early astrocyte reactivity. BU99008, a novel astrocytic PET ligand targeting imidazoline-2 binding sites (I2BS) on astrocytes, might be a suitable candidate. Here we demonstrate for the first time that BU99008 could visualise reactive astrogliosis in postmortem AD brains and propose a multiple binding site [Super-high-affinity (SH), High-affinity (HA) and Low-affinity (LA)] model for BU99008, I2BS specific ligands (2-BFI and BU224) and deprenyl in AD and control (CN) brains. The proportion (%) and affinities of these sites varied significantly between the BU99008, 2-BFI, BU224 and deprenyl in AD and CN brains. Regional binding studies demonstrated significantly higher 3H-BU99008 binding in AD brain regions compared to CN. Comparative autoradiography studies reinforced these findings, showing higher specific binding for 3H-BU99008 than 3H-Deprenyl in sporadic AD brain compared to CN, implying that they might have different targets. The data clearly shows that BU99008 could detect I2BS expressing reactive astrocytes with good selectivity and specificity and hence be a potential attractive clinical astrocytic PET tracer for gaining further insight into the role of reactive astrogliosis in AD.

scholarly journals Enhanced Autolysosomal Function Ameliorates the Inflammatory Response Mediated by the NLRP3 Inflammasome in Alzheimer’s Disease

2021 ◽  
Vol 13 ◽  
Author(s):  
Wen Zhou ◽  
Deng Xiao ◽  
Yueyang Zhao ◽  
Botao Tan ◽  
Zhimin Long ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Animal Models ◽  
Inflammatory Response ◽  
Nlrp3 Inflammasome ◽  
Amyloid Β ◽  
Amyloid Β Peptide ◽  
Cell Models ◽  
Exogenous Addition ◽  
Related Proteins

The pathogenesis of Alzheimer’s disease (AD) involves activation of many NLRP3 inflammatory bodies, which may be related to amyloid β peptide and aggregation of misfolded proteins. Autophagy is an important regulator of inflammatory bodies. However, autophagy shows dynamic changes in the development of AD, and its role in inflammation remains controversial. In this study, the key link between autophagic disorders and the NLRP3 inflammasome in AD was investigated. APP/PS1 double transgenic mice and C57 mice with Aβ25–35 injected into the lateral ventricle were used as two animal models of AD. Immunofluorescence staining and Western blot analysis showed that NLRP3 inflammasome-related proteins and inflammatory cytokines, such as IL-1α, IL-1β, IL-6, IL-12, and TNF-α, were increased and microglia were activated in the brains of both AD animal models. Endogenous overexpression of the APPswe gene and exogenous addition of Aβ25–35 increased the expression of NLRP3 inflammasome-related proteins, while exogenous Aβ25–35 intervention more significantly activated inflammation. Furthermore, LC3 was increased in the AD animal and cell models, and the level of Lamp1 decreased. After overexpression of the primary regulator of lysosomal biogenesis, TFEB, the lysosome protein Lamp1 was increased, and LC3 and inflammatory protein expression were decreased. These results suggest that the NLRP3 inflammasome-mediated inflammatory response is activated in AD animal and cell models, which may be related to the decline in autolysosome function. Overexpression of the TFEB protein can reduce the inflammatory response by improving autolysosome function in AD model cells.

Consideration of a Pharmacological Combinatorial Approach to Inhibit Chronic Inflammation in Alzheimer’s Disease

2019 ◽  
Vol 16 (11) ◽  
pp. 1007-1017 ◽  
Author(s):  
James G. McLarnon
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Animal Models ◽  
Chronic Inflammation ◽  
Preventive Strategy ◽  
Subsequent Work ◽  
Activated Microglia ◽  
Starting Point ◽  
Anti Inflammatory ◽  
Cocktail Approach

A combinatorial cocktail approach is suggested as a rationale intervention to attenuate chronic inflammation and confer neuroprotection in Alzheimer’s disease (AD). The requirement for an assemblage of pharmacological compounds follows from the host of pro-inflammatory pathways and mechanisms present in activated microglia in the disease process. This article suggests a starting point using four compounds which present some differential in anti-inflammatory targets and actions but a commonality in showing a finite permeability through Blood-brain Barrier (BBB). A basis for firstchoice compounds demonstrated neuroprotection in animal models (thalidomide and minocycline), clinical trial data showing some slowing in the progression of pathology in AD brain (ibuprofen) and indirect evidence for putative efficacy in blocking oxidative damage and chemotactic response mediated by activated microglia (dapsone). It is emphasized that a number of candidate compounds, other than ones suggested here, could be considered as components of the cocktail approach and would be expected to be examined in subsequent work. In this case, systematic testing in AD animal models is required to rigorously examine the efficacy of first-choice compounds and replace ones showing weaker effects. This protocol represents a practical approach to optimize the reduction of microglial-mediated chronic inflammation in AD pathology. Subsequent work would incorporate the anti-inflammatory cocktail delivery as an adjunctive treatment with ones independent of inflammation as an overall preventive strategy to slow the progression of AD.

Neuropeptides in Alzheimer’s Disease: An Update

2019 ◽  
Vol 16 (6) ◽  
pp. 544-558 ◽  
Author(s):  
Carla Petrella ◽  
Maria Grazia Di Certo ◽  
Christian Barbato ◽  
Francesca Gabanella ◽  
Massimo Ralli ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Animal Models ◽  
Potential Role ◽  
Brain Distribution ◽  
Brain Areas ◽  
Small Proteins ◽  
Current Review ◽  
The Central Nervous System ◽  
Available Information

Neuropeptides are small proteins broadly expressed throughout the central nervous system, which act as neurotransmitters, neuromodulators and neuroregulators. Growing evidence has demonstrated the involvement of many neuropeptides in both neurophysiological functions and neuropathological conditions, among which is Alzheimer’s disease (AD). The role exerted by neuropeptides in AD is endorsed by the evidence that they are mainly neuroprotective and widely distributed in brain areas responsible for learning and memory processes. Confirming this point, it has been demonstrated that numerous neuropeptide-containing neurons are pathologically altered in brain areas of both AD patients and AD animal models. Furthermore, the levels of various neuropeptides have been found altered in both Cerebrospinal Fluid (CSF) and blood of AD patients, getting insights into their potential role in the pathophysiology of AD and offering the possibility to identify novel additional biomarkers for this pathology. We summarized the available information about brain distribution, neuroprotective and cognitive functions of some neuropeptides involved in AD. The main focus of the current review was directed towards the description of clinical data reporting alterations in neuropeptides content in both AD patients and AD pre-clinical animal models. In particular, we explored the involvement in the AD of Thyrotropin-Releasing Hormone (TRH), Cocaine- and Amphetamine-Regulated Transcript (CART), Cholecystokinin (CCK), bradykinin and chromogranin/secretogranin family, discussing their potential role as a biomarker or therapeutic target, leaving the dissertation of other neuropeptides to previous reviews.

scholarly journals Artificial intelligence-based computational framework for drug-target prioritization and inference of novel repositionable drugs for Alzheimer’s disease

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Shingo Tsuji ◽  
Takeshi Hase ◽  
Ayako Yachie-Kinoshita ◽  
Taiko Nishino ◽  
Samik Ghosh ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Deep Learning ◽  
Drug Target ◽  
Target Genes ◽  
Drug Repositioning ◽  
Therapeutic Targets ◽  
Machine Learning Techniques ◽  
Computational Framework ◽  
Novel Therapeutic

Abstract Background Identifying novel therapeutic targets is crucial for the successful development of drugs. However, the cost to experimentally identify therapeutic targets is huge and only approximately 400 genes are targets for FDA-approved drugs. As a result, it is inevitable to develop powerful computational tools that can identify potential novel therapeutic targets. Fortunately, the human protein-protein interaction network (PIN) could be a useful resource to achieve this objective. Methods In this study, we developed a deep learning-based computational framework that extracts low-dimensional representations of high-dimensional PIN data. Our computational framework uses latent features and state-of-the-art machine learning techniques to infer potential drug target genes. Results We applied our computational framework to prioritize novel putative target genes for Alzheimer’s disease and successfully identified key genes that may serve as novel therapeutic targets (e.g., DLG4, EGFR, RAC1, SYK, PTK2B, SOCS1). Furthermore, based on these putative targets, we could infer repositionable candidate-compounds for the disease (e.g., tamoxifen, bosutinib, and dasatinib). Conclusions Our deep learning-based computational framework could be a powerful tool to efficiently prioritize new therapeutic targets and enhance the drug repositioning strategy.

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