Riluzole, a glutamate modulator, slows cerebral glucose metabolism decline in patients with Alzheimer's disease

An Expanded Narrative Review of Neurotransmitters on Alzheimer's Disease: The Role of Therapeutic Interventions on Neurotransmission

Alzheimer's disease (AD) is a progressive neurodegenerative disease. The accumulation of amyloid-β (Aβ) plaques and tau neurofibrillary tangles are the key players responsible for the pathogenesis of the disease. The accumulation of Aβ plaques and tau affect the balance in chemical neurotransmitters in the brain. Thus, the current review examined the role of neurotransmitters in the pathogenesis of Alzheimer's disease and discusses the alterations in the neurochemical activity and cross talk with their receptors and transporters. In the presence of Aβ plaques and neurofibrillary tangles, changes may occur in the expression of neuronal receptors which in turn triggers excessive release of glutamate into the synaptic cleft contributing to cell death and neuronal damage. The GABAergic system may also be affected by AD pathology in a similar way. In addition, decreased receptors in the cholinergic system and dysfunction in the dopamine neurotransmission of AD pathology may also contribute to the damage to cognitive function. Moreover, the presence of deficiencies in noradrenergic neurons within the locus coeruleus in AD suggests that noradrenergic stimulation could be useful in addressing its pathophysiology. The regulation of melatonin, known for its effectiveness in enhancing cognitive function and preventing Aβ accumulation, along with the involvement of the serotonergic system and histaminergic system in cognition and memory, becomes remarkable for promoting neurotransmission in AD. Additionally, nitric oxide and adenosine-based therapeutic approaches play a protective role in AD by preventing neuroinflammation. Overall, neurotransmitter-based therapeutic strategies emerge as pivotal for addressing neurotransmitter homeostasis and neurotransmission in the context of AD. This review discussed the potential for neurotransmitter-based drugs to be effective in slowing and correcting the neurodegenerative processes in AD by targeting the neurochemical imbalance in the brain. Therefore, neurotransmitter-based drugs could serve as a future therapeutic strategy to tackle AD.

Glutamatergic Neurotransmission in Aging and Neurodegenerative Diseases: A Potential Target to Improve Cognitive Impairment in Aging

Aging is characterized by the decline in many of the individual's capabilities. It has been recognized that the brain undergoes structural and functional changes during aging that are occasionally associated with the development of neurodegenerative diseases. In this sense, altered glutamatergic neurotransmission, which involves the release, binding, reuptake, and degradation of glutamate (Glu) in the brain, has been widely studied in physiological and pathophysiological aging. In particular, changes in glutamatergic neurotransmission are exacerbated during neurodegenerative diseases and are associated with cognitive impairment, characterized by difficulties in memory, learning, concentration, and decision-making. Thus, in the present manuscript, we aim to highlight the relevance of glutamatergic neurotransmission during cognitive impairment to develop novel strategies to prevent, ameliorate, or delay cognitive decline. To achieve this goal, we provide a comprehensive review of the changes reported in glutamatergic neurotransmission components, such as Glu transporters and receptors during physiological aging and in the most studied neurodegenerative diseases. Finally, we describe the current therapeutic strategies developed to target glutamatergic neurotransmission.

Genetic deletion of zinc transporter ZnT3 induces progressive cognitive deficits in mice by impairing dendritic spine plasticity and glucose metabolism

Zinc transporter 3 (ZnT3) is abundantly expressed in the brain, residing in synaptic vesicles, where it plays important roles in controlling the luminal zinc levels. In this study, we found that ZnT3 knockout in mice decreased zinc levels in the hippocampus and cortex, and was associated with progressive cognitive impairments, assessed at 2, 6, and 9-month of age. The results of Golgi-Cox staining demonstrated that ZnT3 deficiency was associated with an increase in dendritic complexity and a decrease in the density of mature dendritic spines, indicating potential synaptic plasticity deficit. Since ZnT3 deficiency was previously linked to glucose metabolism abnormalities, we tested the expression levels of genes related to insulin signaling pathway in the hippocampus and cortex. We found that the Expression of glucose transporters, GLUT3, GLUT4, and the insulin receptor in the whole tissue and synaptosome fraction of the hippocampus of the ZnT3 knockout mice were significantly reduced, as compared to wild-type controls. Expression of AKT (A serine/threonine protein kinase) and insulin-induced AKT phosphorylation was also reduced in the hippocampus of ZnT3 knockout mice. We hypothesize that the ZnT3 deficiency and reduced brain zinc levels may cause cognitive impairment by negatively affecting glycose metabolism via decreased expression of key components of insulin signaling, as well as via changes in synaptic plasticity. These finding may provide new therapeutic target for treatments of neurodegenerative disorders.

Feasibility of Using Magnetic Resonance Spectroscopy Test Biomarkers to Diagnose Alzheimer's Disease: Systematic Evaluation and Meta-Analysis

BACKGROUND

Alzheimer's disease (AD) is the leading cause of dementia, resulting in impairments in memory, cognition, decision-making, and social skills. Thus, accurate preclinical diagnosis of Alzheimer's disease is paramount. The identification of biomarkers for Alzheimer's disease through magnetic resonance spectroscopy (MRS) represents a novel adjunctive diagnostic approach.

OBJECTIVE

This study conducted a meta-analysis of the diagnostic results of this technology to explore its feasibility and accuracy.

METHODS

PubMed, Cochrane Library, EMBASE, and Web of Science databases were searched without restrictions, with the search period extending up to July 31, 2022. The search strategy employed a combination of subject headings and keywords. All retrieved documents underwent screening by two researchers, who selected them for meta-analysis. The included literature was analyzed using Review Manager 5.4 software, with corresponding bias maps, forest plots, and summary receiver operating characteristic (SROC) curves generated and analyzed.

RESULTS

A total of 344 articles were retrieved initially, with 11 articles meeting the criteria for inclusion in the analysis. The analysis encompassed data from approximately 1766 patients. In the forest plot, both sensitivity (95% CI) and specificity (95% CI) approached 1. Examining the true positive rate, false positive rate, true negative rate, and false negative rate, all studies on the summary receiver operating characteristic (SROC) curve clustered in the upper left quadrant, suggesting a very high accuracy of biomarkers detected by MRS for diagnosing Alzheimer's disease.

CONCLUSION

The detection of biomarkers by MRS demonstrates feasibility and high accuracy in diagnosing AD. This technology holds promise for widespread adoption in the clinical diagnosis of AD in the future.

Neuroprotective effects of riluzole in Alzheimer's disease: A comprehensive review

BACKGROUND

Despite several hundred clinical trials of drugs that initially showed promise, there has been limited clinical improvement in Alzheimer's disease (AD). This may be attributed to the existence of at least 25 abnormal cellular pathways that underlie the disease. It is improbable for a single drug to address all or most of these pathways, thus even drugs that show promise when administered alone are unlikely to produce significant results. According to previous studies, eight drugs, namely, dantrolene, erythropoietin, lithium, memantine, minocycline, piracetam, riluzole, and silymarin, have been found to target multiple pathways that are involved in the development of AD. Among these drugs, riluzole is currently indicated for the treatment of medical conditions in both adult patients and children and has gained increased attention from scientists due to its potential in the excitotoxic hypothesis of neurodegenerative diseases.

OBJECTIVE

The aim of this study was to investigate the effects of drugs on AD based on cellular and molecular mechanisms.

METHODS

The literature search for this study utilized the Scopus, ScienceDirect, PubMed, and Google Scholar databases to identify relevant articles.

RESULTS

Riluzole exerts its effects in AD through diverse pathways including the inhibition of voltage-dependent sodium and calcium channels, blocking AMPA and NMDA receptors and inhibiting the release of glutamic acid release and stimulation of EAAT1-EAAT2.

CONCLUSION

In this review article, we aimed to review the neuroprotective properties of riluzole, a glutamate modulator, in AD, which could benefit patients with the disease.

Multiparametric hippocampal signatures for early diagnosis of Alzheimer's disease using 18F-FDG PET/MRI Radiomics

PURPOSE

This study aimed to explore the utility of hippocampal radiomics using multiparametric simultaneous positron emission tomography (PET)/magnetic resonance imaging (MRI) for early diagnosis of Alzheimer's disease (AD).

METHODS

A total of 53 healthy control (HC) participants, 55 patients with amnestic mild cognitive impairment (aMCI), and 51 patients with AD were included in this study. All participants accepted simultaneous PET/MRI scans, including 18F-fluorodeoxyglucose (18F-FDG) PET, 3D arterial spin labeling (ASL), and high-resolution T1-weighted imaging (3D T1WI). Radiomics features were extracted from the hippocampus region on those three modal images. Logistic regression models were trained to classify AD and HC, AD and aMCI, aMCI and HC respectively. The diagnostic performance and radiomics score (Rad-Score) of logistic regression models were evaluated from 5-fold cross-validation.

RESULTS

The hippocampal radiomics features demonstrated favorable diagnostic performance, with the multimodal classifier outperforming the single-modal classifier in the binary classification of HC, aMCI, and AD. Using the multimodal classifier, we achieved an area under the receiver operating characteristic curve (AUC) of 0.98 and accuracy of 96.7% for classifying AD from HC, and an AUC of 0.86 and accuracy of 80.6% for classifying aMCI from HC. The value of Rad-Score differed significantly between the AD and HC (p < 0.001), aMCI and HC (p < 0.001) groups. Decision curve analysis showed superior clinical benefits of multimodal classifiers compared to neuropsychological tests.

CONCLUSION

Multiparametric hippocampal radiomics using PET/MRI aids in the identification of early AD, and may provide a potential biomarker for clinical applications.

Kallistatin leads to cognition impairment via downregulating glutamine synthetase

In many neurodegenerative disorders, such as Alzheimer's disease (AD), glutamate-mediated neuronal excitotoxicity is considered the basis for cognitive impairment. The mRNA and protein expression of SERPINA4(Kallistatin) are higher in patients with AD. However, whether Kallistatin plays a regulatory role in glutamate-glutamine cycle homeostasis remains unclear. In this study, we identified impaired cognitive function in Kallistatin transgenic (KAL-TG) mice. Baseline glutamate levels were elevated and miniature excitatory postsynaptic current (mEPSC) frequency was increased in the hippocampus, suggesting the impairment of glutamate homeostasis in KAL-TG mice. Mechanistically, we demonstrated that Kallistatin promoted lysine acetylation and ubiquitination of glutamine synthetase (GS) and facilitated its degradation via the proteasome pathway, thereby downregulating GS. Fenofibrate improved cognitive memory in KAL-TG mice by downregulating serum Kallistatin. Collectively, our study findings provide insights the mechanism by which Kallistatin regulates cognitive impairment, and suggest the potential of fenofibrate to prevente and treat of AD patients with high levels of Kallistatin.

An updated systematic review of neuroprotective agents in the treatment of spinal cord injury

This systematic review aims to summarize the findings from all clinical randomized trials assessing the efficacy of potential neuroprotective agents in influencing the outcomes of acute spinal cord injuries (SCI). Following the PRISMA guidelines, we conducted comprehensive searches in four electronic databases (PubMed, Scopus, Cochrane Library, and Web of Science) up to September 5th, 2023. Our analysis included a total of 30 studies. We examined the effects of 15 substances/drugs: methylprednisolone, tirilazad mesylate, erythropoietin, nimodipine, naloxone, Sygen, Rho protein antagonist, granulocyte colony-stimulating factor, autologous macrophages, autologous bone marrow cells, vitamin D, progesterone, riluzole, minocycline, and blood alcohol concentration. Notable improvements in neurological outcomes were observed with progesterone plus vitamin D and granulocyte colony-stimulating factor. In contrast, results for methylprednisolone, erythropoietin, Sygen, Rho Protein, and Riluzole were inconclusive, primarily due to insufficient sample size or outdated evidence. No significant differences were found in the remaining evaluated drugs. Progesterone plus vitamin D, granulocyte colony-stimulating factor, methylprednisolone, Sygen, Rho Protein, and Riluzole may enhance neurological outcomes in acute SCI cases. It is worth noting that different endpoints or additional subgroup analyses may potentially alter the conclusions of individual trials. Therefore, certain SCI grades may benefit more from these treatments than others, while the overall results may remain inconclusive.

EKGDR: An End-to-End Knowledge Graph-Based Method for Computational Drug Repurposing

The lengthy and expensive process of developing new drugs from scratch, coupled with a high failure rate, has prompted the emergence of drug repurposing/repositioning as a more efficient and cost-effective approach. This approach involves identifying new therapeutic applications for existing approved drugs, leveraging the extensive drug-related data already gathered. However, the diversity and heterogeneity of data, along with the limited availability of known drug-disease interactions, pose significant challenges to computational drug design. To address these challenges, this study introduces EKGDR, an end-to-end knowledge graph-based approach for computational drug repurposing. EKGDR utilizes the power of a drug knowledge graph, a comprehensive repository of drug-related information that encompasses known drug interactions and various categorization information, as well as structural molecular descriptors of drugs. EKGDR employs graph neural networks, a cutting-edge graph representation learning technique, to embed the drug knowledge graph (nodes and relations) in an end-to-end manner. By doing so, EKGDR can effectively learn the underlying causes (intents) behind drug-disease interactions and recursively aggregate and combine relational messages between nodes along different multihop neighborhood paths (relational paths). This process generates representations of disease and drug nodes, enabling EKGDR to predict the interaction probability for each drug-disease pair in an end-to-end manner. The obtained results demonstrate that EKGDR outperforms previous models in all three evaluation metrics: area under the receiver operating characteristic curve (AUROC = 0.9475), area under the precision-recall curve (AUPRC = 0.9490), and recall at the top-200 recommendations (Recall@200 = 0.8315). To further validate EKGDR's effectiveness, we evaluated the top-20 candidate drugs suggested for each of Alzheimer's and Parkinson's diseases.

Combination of fMRI and PET reveals the beneficial effect of three-phase enriched environment on post-stroke memory deficits by enhancing plasticity of brain connectivity between hippocampus and peri-hippocampal cortex

AIM

The three-phase enriched environment (EE) intervention paradigm has been shown to improve learning and memory function after cerebral ischemia, but the neuronal mechanisms are still unclear. This study aimed to investigate the hippocampal-cortical connectivity and the metabolic interactions between neurons and astrocytes to elucidate the underlying mechanisms of EE-induced memory improvement after stroke.

METHODS

Rats were subjected to permanent middle cerebral artery occlusion (pMCAO) or sham surgery and housed in standard environment or EE for 30 days. Memory function was examined by Morris water maze (MWM) test. Magnetic resonance imaging (MRI) was conducted to detect the structural and functional changes. [18 F]-fluorodeoxyglucose (FDG) positron emission tomography (PET) was conducted to detect brain energy metabolism. PET-based brain connectivity and network analysis was performed to study the changes of hippocampal-cortical connectivity. Astrocyte-neuron metabolic coupling, including gap junction protein connexin 43 (Cx43), glucose transporters (GLUTs), and monocarboxylate transporters (MCTs), was detected by histological studies.

RESULTS

Our results showed EE promoted memory function improvement, protected structure integrity, and benefited energy metabolism after stroke. More importantly, EE intervention significantly increased functional connectivity between the hippocampus and peri-hippocampal cortical regions, and specifically regulated the level of Cx43, GLUTs and MCTs in the hippocampus and cortex.

CONCLUSIONS

Our results revealed the three-phase enriched environment paradigm enhanced hippocampal-cortical connectivity plasticity and ameliorated post-stroke memory deficits. These findings might provide some new clues for the development of EE and thus facilitate the clinical transformation of EE.

Mitophagy in Alzheimer's Disease: A Bibliometric Analysis from 2007 to 2022

Background

The investigation of mitophagy in Alzheimer's disease (AD) remains relatively underexplored in bibliometric analysis.

Objective

To delve into the progress of mitophagy, offering a comprehensive overview of research trends and frontiers for researchers.

Methods

Basic bibliometric information, targets, and target-drug-clinical trial-disease extracted from publications identified in the Web of Science Core Collection from 2007 to 2022 were assessed using bibliometric software.

Results

The study encompassed 5,146 publications, displaying a consistent 16-year upward trajectory. The United States emerged as the foremost contributor in publications, with the Journal of Alzheimer's Disease being the most prolific journal. P. Hemachandra Reddy, George Perry, and Xiongwei Zhu are the top 3 most prolific authors. PINK1 and Parkin exhibited an upward trend in the last 6 years. Keywords (e.g., insulin, aging, epilepsy, tauopathy, and mitochondrial quality control) have recently emerged as focal points of interest within the past 3 years. "Mitochondrial dysfunction" is among the top terms in disease clustering. The top 10 drugs/molecules (e.g., curcumin, insulin, and melatonin) were summarized, accompanied by their clinical trials and related targets.

Conclusions

This study presents a comprehensive overview of the mitophagy research landscape in AD over the past 16 years, underscoring mitophagy as an emerging molecular mechanism and a crucial focal point for potential drug in AD. This study pioneers the inclusion of targets and their correlations with drugs, clinical trials, and diseases in bibliometric analysis, providing valuable insights and inspiration for scholars and readers of JADR interested in understanding the potential mechanisms and clinical trials in AD.

omicSynth: An open multi-omic community resource for identifying druggable targets across neurodegenerative diseases

Treatments for neurodegenerative disorders remain rare, but recent FDA approvals, such as lecanemab and aducanumab for Alzheimer disease (MIM: 607822), highlight the importance of the underlying biological mechanisms in driving discovery and creating disease modifying therapies. The global population is aging, driving an urgent need for therapeutics that stop disease progression and eliminate symptoms. In this study, we create an open framework and resource for evidence-based identification of therapeutic targets for neurodegenerative disease. We use summary-data-based Mendelian randomization to identify genetic targets for drug discovery and repurposing. In parallel, we provide mechanistic insights into disease processes and potential network-level consequences of gene-based therapeutics. We identify 116 Alzheimer disease, 3 amyotrophic lateral sclerosis (MIM: 105400), 5 Lewy body dementia (MIM: 127750), 46 Parkinson disease (MIM: 605909), and 9 progressive supranuclear palsy (MIM: 601104) target genes passing multiple test corrections (pSMR_multi < 2.95 × 10-6 and pHEIDI > 0.01). We created a therapeutic scheme to classify our identified target genes into strata based on druggability and approved therapeutics, classifying 41 novel targets, 3 known targets, and 115 difficult targets (of these, 69.8% are expressed in the disease-relevant cell type from single-nucleus experiments). Our novel class of genes provides a springboard for new opportunities in drug discovery, development, and repurposing in the pre-competitive space. In addition, looking at drug-gene interaction networks, we identify previous trials that may require further follow-up such as riluzole in Alzheimer disease. We also provide a user-friendly web platform to help users explore potential therapeutic targets for neurodegenerative diseases, decreasing activation energy for the community.

Nanoplastics induce neuroexcitatory symptoms in zebrafish (Danio rerio) larvae through a manner contrary to Parkinsonian's way in proteomics

Although nanoplastics (NPs) can penetrate the blood-brain barrier and accumulate in the brain, the neurotoxicity of these particles and the mechanisms associated with their unique physio-chemical properties have yet to be sufficiently ascertained. In this study, we assessed the neuroexcitatory symptoms of zebrafish (Danio rerio) larvae treated with polystyrene (PS) NPs based on an examination of locomotory behaviour, dopamine levels, and acetylcholinesterase activity. We found that PS NPs caused oxidative stress and inhibited atoh1a expression in the cerebellum of Tg(atoh1a:dTomato) transgenic zebrafish larvae, thereby indicating damage to the central nervous system. In contrast to the Parkinson's disease (PD) like effects induced by most types of nanoparticles, such as graphene oxide, we established that PS NPs influenced the neuronal proteomic profiles of zebrafish larvae in a manner contrary to the molecular pathways characteristic of PD-like effects, which could be explained by the molecular dynamic simulation. Unlike graphene oxide nanoparticles that promote significant change in the internal structure of neuroproteins, the complex macromolecular polymers of PS NPs promoted the coalescence and increased expression of neuroproteins, thereby plausibly contributing to the neuroexcitatory symptoms observed in treated zebrafish larvae. Consequently, compared with traditional nanoparticles, we believe that the unique physio-chemical properties of NPs could be a potential factor contributing to their toxicity.

Novel benzothiazole derivatives as multitargeted-directed ligands for the treatment of Alzheimer's disease

Neurodegenerative diseases such as Alzheimer's disease (AD) are multifactorial with several different pathologic mechanisms. Therefore, it is assumed that multitargeted-directed ligands (MTDLs) which interact with different biological targets relevant to the diseases, might offer an improved therapeutic alternative than using the traditional "one-target, one-molecule" approach. Herein, we describe new benzothiazole-based derivatives as a privileged scaffold for histamine H₃ receptor ligands (H₃R). The most affine compound, the 3-(azepan-1-yl)propyloxy-linked benzothiazole derivative 4b, displayed a K_i value of 0.012 μM. The multitargeting potential of these H₃R ligands towards AChE, BuChE and MAO-B enzymes was evaluated to yield compound 3s (pyrrolidin-1-yl-(6-((5-(pyrrolidin-1-yl)pentyl)oxy)benzo[d]thiazol-2-yl)methanone) as the most promising MTDL with a K_i value of 0.036 μM at H₃R and IC₅₀ values of 6.7 µM, 2.35 µM, and 1.6 µM towards AChE, BuChE, and MAO-B, respectively. These findings suggest that compound 3s can be a lead structure for developing new multi-targeting anti-AD agents.

From Recognition to Remedy: The Significance of Biomarkers in Neurodegenerative Disease Pathology

With the inexorable aging of the global populace, neurodegenerative diseases (NDs) like Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS) pose escalating challenges, which are underscored by their socioeconomic repercussions. A pivotal aspect in addressing these challenges lies in the elucidation and application of biomarkers for timely diagnosis, vigilant monitoring, and effective treatment modalities. This review delineates the quintessence of biomarkers in the realm of NDs, elucidating various classifications and their indispensable roles. Particularly, the quest for novel biomarkers in AD, transcending traditional markers in PD, and the frontier of biomarker research in ALS are scrutinized. Emergent susceptibility and trait markers herald a new era of personalized medicine, promising enhanced treatment initiation especially in cases of SOD1-ALS. The discourse extends to diagnostic and state markers, revolutionizing early detection and monitoring, alongside progression markers that unveil the trajectory of NDs, propelling forward the potential for tailored interventions. The synergy between burgeoning technologies and innovative techniques like -omics, histologic assessments, and imaging is spotlighted, underscoring their pivotal roles in biomarker discovery. Reflecting on the progress hitherto, the review underscores the exigent need for multidisciplinary collaborations to surmount the challenges ahead, accelerate biomarker discovery, and herald a new epoch of understanding and managing NDs. Through a panoramic lens, this article endeavors to provide a comprehensive insight into the burgeoning field of biomarkers in NDs, spotlighting the promise they hold in transforming the diagnostic landscape, enhancing disease management, and illuminating the pathway toward efficacious therapeutic interventions.

Targeting NLRP3 inflammasome for neurodegenerative disorders

Neuroinflammation is a key pathological feature in neurological diseases, including Alzheimer's disease (AD). The nucleotide-binding domain leucine-rich repeat-containing proteins (NLRs) belong to the pattern recognition receptors (PRRs) family that sense stress signals, which play an important role in inflammation. As a member of NLRs, the NACHT, LRR and PYD domains-containing protein 3 (NLRP3) is predominantly expressed in microglia, the principal innate immune cells in the central nervous system (CNS). Microglia release proinflammatory cytokines to cause pyroptosis through activating NLRP3 inflammasome. The active NLRP3 inflammasome is involved in a variety of neurodegenerative diseases (NDs). Recent studies also indicate the key role of neuronal NLRP3 in the pathogenesis of neurological disorders. In this article, we reviewed the mechanisms of NLRP3 expression and activation and discussed the role of active NLRP3 inflammasome in the pathogenesis of NDs, particularly focusing on AD. The studies suggest that targeting NLRP3 inflammasome could be a novel approach for the disease modification.

Stress and the risk of Alzheimer dementia: Can deconstructed engrams be rebuilt?

The exact neuropathological mechanism by which the dementia process unfolds is under intense scrutiny. The disease affects about 38 million people worldwide, 70% of which are clinically diagnosed with Alzheimer's disease (AD). If the destruction of synapses essential for learning, planning and decision-making is part of the problem, must the restoration of previously lost synapses be part of the solution? It is plausible that neuronal capacity to restitute information corresponds with the adaptive capacity of its connectivity reserve. A challenge will be to promote the functional connectivity that can compensate for the lost one. This will require better clarification of the remodeling of functional connectivity during the progression of AD dementia and its reversal upon experimental treatment. A major difficulty is to promote the neural pathways that are atrophied in AD dementia while suppressing others that are bolstered. Therapeutic strategies should aim at scaling functional connectivity to a just balance between the atrophic and hypertrophic systems. However, the exact factors that can help reach this objective are still unclear. Similarities between the effects of chronic stress and some neuropathological mechanisms underlying AD dementia support the idea that common components deserve prime attention as therapeutic targets.

From Answers to Insights: Unveiling the Strengths and Limitations of ChatGPT and Biomedical Knowledge Graphs

Purpose

Large Language Models (LLMs) have shown exceptional performance in various natural language processing tasks, benefiting from their language generation capabilities and ability to acquire knowledge from unstructured text. However, in the biomedical domain, LLMs face limitations that lead to inaccurate and inconsistent answers. Knowledge Graphs (KGs) have emerged as valuable resources for organizing structured information. Biomedical Knowledge Graphs (BKGs) have gained significant attention for managing diverse and large-scale biomedical knowledge. The objective of this study is to assess and compare the capabilities of ChatGPT and existing BKGs in question-answering, biomedical knowledge discovery, and reasoning tasks within the biomedical domain.

Methods

We conducted a series of experiments to assess the performance of ChatGPT and the BKGs in various aspects of querying existing biomedical knowledge, knowledge discovery, and knowledge reasoning. Firstly, we tasked ChatGPT with answering questions sourced from the "Alternative Medicine" sub-category of Yahoo! Answers and recorded the responses. Additionally, we queried BKG to retrieve the relevant knowledge records corresponding to the questions and assessed them manually. In another experiment, we formulated a prediction scenario to assess ChatGPT's ability to suggest potential drug/dietary supplement repurposing candidates. Simultaneously, we utilized BKG to perform link prediction for the same task. The outcomes of ChatGPT and BKG were compared and analyzed. Furthermore, we evaluated ChatGPT and BKG's capabilities in establishing associations between pairs of proposed entities. This evaluation aimed to assess their reasoning abilities and the extent to which they can infer connections within the knowledge domain.

Results

The results indicate that ChatGPT with GPT-4.0 outperforms both GPT-3.5 and BKGs in providing existing information. However, BKGs demonstrate higher reliability in terms of information accuracy. ChatGPT exhibits limitations in performing novel discoveries and reasoning, particularly in establishing structured links between entities compared to BKGs.

Conclusions

To address the limitations observed, future research should focus on integrating LLMs and BKGs to leverage the strengths of both approaches. Such integration would optimize task performance and mitigate potential risks, leading to advancements in knowledge within the biomedical field and contributing to the overall well-being of individuals.

The Disruption of NMDAR/TRPM4 Death Signaling with TwinF Interface Inhibitors: A New Pharmacological Principle for Neuroprotection

With the discovery that the acquisition of toxic features by extrasynaptic NMDA receptors (NMDARs) involves their physical interaction with the non-selective cation channel, TRPM4, it has become possible to develop a new pharmacological principle for neuroprotection, namely the disruption of the NMDAR/TRPM4 death signaling complex. This can be accomplished through the expression of the TwinF domain, a 57-amino-acid-long stretch of TRPM4 that mediates its interaction with NMDARs, but also using small molecule TwinF interface (TI) inhibitors, also known as NMDAR/TRPM4 interaction interface inhibitors. Both TwinF and small molecule TI inhibitors detoxify extrasynaptic NMDARs without interfering with synaptic NMDARs, which serve important physiological functions in the brain. As the toxic signaling of extrasynaptic NMDARs contributes to a wide range of neurodegenerative conditions, TI inhibitors may offer therapeutic options for currently untreatable human neurodegenerative diseases including Amyotrophic Lateral Sclerosis, Alzheimer's disease, and Huntington's disease.

Therapeutic Strategies Aimed at Improving Neuroplasticity in Alzheimer Disease

Alzheimer disease (AD) is the most prevalent form of dementia among elderly people. Owing to its varied and multicausal etiopathology, intervention strategies have been highly diverse. Despite ongoing advances in the field, efficient therapies to mitigate AD symptoms or delay their progression are still of limited scope. Neuroplasticity, in broad terms the ability of the brain to modify its structure in response to external stimulation or damage, has received growing attention as a possible therapeutic target, since the disruption of plastic mechanisms in the brain appear to correlate with various forms of cognitive impairment present in AD patients. Several pre-clinical and clinical studies have attempted to enhance neuroplasticity via different mechanisms, for example, regulating glucose or lipid metabolism, targeting the activity of neurotransmitter systems, or addressing neuroinflammation. In this review, we first describe several structural and functional aspects of neuroplasticity. We then focus on the current status of pharmacological approaches to AD stemming from clinical trials targeting neuroplastic mechanisms in AD patients. This is followed by an analysis of analogous pharmacological interventions in animal models, according to their mechanisms of action.

An In Vivo Electroencephalographic Analysis of the Effect of Riluzole against Limbic and Absence Seizure and Comparison with Glutamate Antagonists

BACKGROUND

Riluzole (RLZ) has demonstrated neuroprotective effects in several neurological disorders. These neuroprotective effects seem to be mainly due to its ability to inhibit the excitatory glutamatergic neurotransmission, acting on different targets located both at the presynaptic and postsynaptic levels.

METHODS

In the present study, we evaluated the effects of Riluzole (RLZ) against limbic seizures, induced by AMPA, kainate, and NMDA receptor agonists in Sprague-Dawley rats, and in a well-validated genetic model of absence epilepsy, the WAG/Rij rat. Furthermore, in this latter model, we also studied the effect of RLZ in co-administration with the competitive NMDA receptor antagonist, CPP, or the non-competitive AMPA receptor antagonist, THIQ-10c, on spike-wave discharges (SWDs) in WAG/Rij rats, to understand the potential involvement of AMPA and NMDA receptors in the anti-absence effect of RLZ.

RESULTS

In Sprague-Dawley rats, RLZ pretreatment significantly reduced the limbic seizure severity induced by glutamatergic agonists, suggesting an antagonism of RLZ mainly on NMDA rather than non-NMDA receptors. RLZ also reduced SWD parameters in WAG/Rij rats. Interestingly, the co-administration of RLZ with CPP did not increase the anti-absence activity of RLZ in this model, advocating a competitive effect on the NMDA receptor. In contrast, the co-administration of RLZ with THIQ-10c induced an additive effect against absence seizure in WAG/Rij rats.

CONCLUSIONS

these results suggest that the antiepileptic effects of RLZ, in both seizure models, can be mainly due to the antagonism of the NMDA glutamatergic receptors.

omicSynth: an Open Multi-omic Community Resource for Identifying Druggable Targets across Neurodegenerative Diseases

Treatments for neurodegenerative disorders remain rare, although recent FDA approvals, such as Lecanemab and Aducanumab for Alzheimer's Disease, highlight the importance of the underlying biological mechanisms in driving discovery and creating disease modifying therapies. The global population is aging, driving an urgent need for therapeutics that stop disease progression and eliminate symptoms. In this study, we create an open framework and resource for evidence-based identification of therapeutic targets for neurodegenerative disease. We use Summary-data-based Mendelian Randomization to identify genetic targets for drug discovery and repurposing. In parallel, we provide mechanistic insights into disease processes and potential network-level consequences of gene-based therapeutics. We identify 116 Alzheimer's disease, 3 amyotrophic lateral sclerosis, 5 Lewy body dementia, 46 Parkinson's disease, and 9 Progressive supranuclear palsy target genes passing multiple test corrections (pSMR_multi < 2.95×10-6 and pHEIDI > 0.01). We created a therapeutic scheme to classify our identified target genes into strata based on druggability and approved therapeutics - classifying 41 novel targets, 3 known targets, and 115 difficult targets (of these 69.8% are expressed in the disease relevant cell type from single nucleus experiments). Our novel class of genes provides a springboard for new opportunities in drug discovery, development and repurposing in the pre-competitive space. In addition, looking at drug-gene interaction networks, we identify previous trials that may require further follow-up such as Riluzole in AD. We also provide a user-friendly web platform to help users explore potential therapeutic targets for neurodegenerative diseases, decreasing activation energy for the community [https://nih-card-ndd-smr-home-syboky.streamlit.app/].

Advances in the discovery of heterocyclic-based drugs against Alzheimer's disease

INTRODUCTION

Alzheimer's disease is a multifactorial neurodegenerative disorder characterized by beta-amyloid accumulation and tau protein hyperphosphorylation. The disease involves interconnected mechanisms, which can be clustered into two target-packs based on the affected proteins. Pack-1 focuses on beta-amyloid accumulation, oxidative stress, and metal homeostasis dysfunction, and Pack-2 involves tau protein, calcium homeostasis, and neuroinflammation. Against this background heterocyclic system, there is a powerful source of pharmacophores to develop effective small drugs to treat multifactorial diseases like Alzheimer's.

AREAS COVERED

This review highlights the most promising heterocyclic systems as potential hit candidates with multi-target capacity for the development of new drugs targeting Alzheimer's disease. The selection of these heterocyclic systems was based on two crucial factors: their synthetic versatility and their well-documented biological properties of therapeutic potential in neurodegenerative diseases.

EXPERT OPINION

The synthesis of small drugs against Alzheimer's disease requires a multifactorial approach that targets the key pathological proteins. In this context, the utilization of heterocyclic systems, with well-established synthetic processes and facile functionalization, becomes a crucial element in the design phases. Furthermore, the selection of hit heterocyclic should be guided by a full understanding of their biological activities. Thus, the identification of promising heterocyclic scaffolds with known biological effects increases the potential to develop effective molecules against Alzheimer's disease.

MRS in neurodegenerative dementias, prodromal syndromes and at-risk states: A systematic review of the literature

BACKGROUND

In recent years, MRS has benefited from increased MRI field strengths, new acquisition protocols and new processing techniques. This review aims to determine how this has altered our understanding of MRS neurometabolic markers in neurodegenerative dementias.

METHODS

Our systematic review of human in vivo MRS literature since 2002 pertains to Alzheimer's disease (AD), dementia with Lewy bodies (DLB), Parkinson's disease dementia, frontotemporal dementia (FTD), prodromal and 'at-risk' states. Studies using field strengths of 3 T or more were included.

RESULTS

Of 85 studies, AD and/or mild cognitive impairment (MCI) were the most common conditions of interest (58 papers, 68%). Only 14 (16%) studies included other dementia syndromes and 13 (15%) investigated 'at-risk' cohorts. Earlier findings of lower N-acetylaspartate and higher myo-inositol were confirmed. Additionally, lower choline and creatine in AD and MCI were reported, though inconsistently. Previously challenging-to-measure metabolites (glutathione, glutamate and gamma-aminobutyric acid) were reportedly lower in AD, FTD and DLB compared with controls.

DISCUSSION

Increasing field strength alongside targeted acquisition protocols has revealed additional metabolite changes. Most studies were small and regional metabolite differences between dementia types may not have been captured due to the predominant placement of voxels in the posterior cingulate cortex. The standard of data collection, quality control and analysis is improving due to greater consensus regarding acquisition and processing techniques. Ongoing harmonization of techniques, creation of larger and longitudinal cohorts, and placement of MRS voxels in more diverse regions will strengthen future research.

From Answers to Insights: Unveiling the Strengths and Limitations of ChatGPT and Biomedical Knowledge Graphs

Large Language Models (LLMs) have demonstrated exceptional performance in various natural language processing tasks, utilizing their language generation capabilities and knowledge acquisition potential from unstructured text. However, when applied to the biomedical domain, LLMs encounter limitations, resulting in erroneous and inconsistent answers. Knowledge Graphs (KGs) have emerged as valuable resources for structured information representation and organization. Specifically, Biomedical Knowledge Graphs (BKGs) have attracted significant interest in managing large-scale and heterogeneous biomedical knowledge. This study evaluates the capabilities of ChatGPT and existing BKGs in question answering, knowledge discovery, and reasoning. Results indicate that while ChatGPT with GPT-4.0 surpasses both GPT-3.5 and BKGs in providing existing information, BKGs demonstrate superior information reliability. Additionally, ChatGPT exhibits limitations in performing novel discoveries and reasoning, particularly in establishing structured links between entities compared to BKGs. To overcome these limitations, future research should focus on integrating LLMs and BKGs to leverage their respective strengths. Such an integrated approach would optimize task performance and mitigate potential risks, thereby advancing knowledge in the biomedical field and contributing to overall well-being.

Drug repositioning targeting glutaminase reveals drug candidates for the treatment of Alzheimer's disease patients

BACKGROUND

Despite numerous clinical trials and decades of endeavour, there is still no effective cure for Alzheimer's disease. Computational drug repositioning approaches may be employed for the development of new treatment strategies for Alzheimer's patients since an extensive amount of omics data has been generated during pre-clinical and clinical studies. However, targeting the most critical pathophysiological mechanisms and determining drugs with proper pharmacodynamics and good efficacy are equally crucial in drug repurposing and often imbalanced in Alzheimer's studies.

METHODS

Here, we investigated central co-expressed genes upregulated in Alzheimer's disease to determine a proper therapeutic target. We backed our reasoning by checking the target gene's estimated non-essentiality for survival in multiple human tissues. We screened transcriptome profiles of various human cell lines perturbed by drug induction (for 6798 compounds) and gene knockout using data available in the Connectivity Map database. Then, we applied a profile-based drug repositioning approach to discover drugs targeting the target gene based on the correlations between these transcriptome profiles. We evaluated the bioavailability, functional enrichment profiles and drug-protein interactions of these repurposed agents and evidenced their cellular viability and efficacy in glial cell culture by experimental assays and Western blotting. Finally, we evaluated their pharmacokinetics to anticipate to which degree their efficacy can be improved.

RESULTS

We identified glutaminase as a promising drug target. Glutaminase overexpression may fuel the glutamate excitotoxicity in neurons, leading to mitochondrial dysfunction and other neurodegeneration hallmark processes. The computational drug repurposing revealed eight drugs: mitoxantrone, bortezomib, parbendazole, crizotinib, withaferin-a, SA-25547 and two unstudied compounds. We demonstrated that the proposed drugs could effectively suppress glutaminase and reduce glutamate production in the diseased brain through multiple neurodegeneration-associated mechanisms, including cytoskeleton and proteostasis. We also estimated the human blood-brain barrier permeability of parbendazole and SA-25547 using the SwissADME tool.

CONCLUSIONS

This study method effectively identified an Alzheimer's disease marker and compounds targeting the marker and interconnected biological processes by use of multiple computational approaches. Our results highlight the importance of synaptic glutamate signalling in Alzheimer's disease progression. We suggest repurposable drugs (like parbendazole) with well-evidenced activities that we linked to glutamate synthesis hereby and novel molecules (SA-25547) with estimated mechanisms for the treatment of Alzheimer's patients.

Riluzole and its prodrugs for the treatment of Alzheimer's disease

Current medications for Alzheimer's disease help manage symptoms and behavioral problems. Nevertheless, they do not slow the progression of cognitive decline or dementia. A potential approach for treating Alzheimer's disease is to target neurons that are sensitive to disease pathobiology such as glutamatergic neurons. Several patents disclosed methods for treating Alzheimer's disease by administering riluzole or its prodrugs. Clinical trials revealed that 6 months treatment using riluzole or troriluzole is associated with a slower decline in the tomographic measures of the positron emissions of cerebral glucose metabolism in Alzheimer's patients. The proposed strategy claims to prevent and/or slow the cognitive decline of Alzheimer's patients and to enhance global functioning. These claims may also pave the way for other glutamate modulators to be used for Alzheimer's disease.

Multiple Bioenergy-Linked OCT Biomarkers Suggest Greater-Than-Normal Rod Mitochondria Activity Early in Experimental Alzheimer's Disease

Purpose

In Alzheimer's disease, central brain neurons show evidence for early hyperactivity. It is unclear if this occurs in the retina, another disease target. Here, we tested for imaging biomarker manifestation of prodromal hyperactivity in rod mitochondria in vivo in experimental Alzheimer's disease.

Methods

Light- and dark-adapted 4-month-old 5xFAD and wild-type (WT) mice, both on a C57BL/6J background, were studied with optical coherence tomography (OCT). We measured the reflectivity profile shape of the inner segment ellipsoid zone (EZ) as a proxy for mitochondria distribution. Two additional indices responsive to mitochondria activity were also measured: the thickness of the external limiting membrane-retinal pigment epithelium (ELM-RPE) region and the signal magnitude of a hyporeflective band (HB) between photoreceptor tips and apical RPE. Retinal laminar thickness and visual performance were evaluated.

Results

In response to low energy demand (light), WT mice showed the expected elongation in EZ reflectivity profile shape, relatively thicker ELM-RPE, and greater HB signal. Under high energy demand (dark), the EZ reflectivity profile shape was rounder, the ELM-RPE was thinner, and the HB was reduced. These OCT biomarker patterns for light-adapted 5xFAD mice did not match those of light-adapted WT mice but rather that of dark-adapted WT mice. Dark-adapted 5xFAD and WT mice showed the same biomarker pattern. The 5xFAD mice exhibited modest nuclear layer thinning and lower-than-normal contrast sensitivity.

Conclusions

Results from three OCT bioenergy biomarkers raise the novel possibility of early rod hyperactivity in vivo in a common Alzheimer's disease model.

A Medicinal Chemistry Perspective on Excitatory Amino Acid Transporter 2 Dysfunction in Neurodegenerative Diseases

The excitatory amino acid transporter 2 (EAAT2) plays a key role in the clearance and recycling of glutamate - the major excitatory neurotransmitter in the mammalian brain. EAAT2 loss/dysfunction triggers a cascade of neurodegenerative events, comprising glutamatergic excitotoxicity and neuronal death. Nevertheless, our current knowledge regarding EAAT2 in neurodegenerative diseases, such as amyotrophic lateral sclerosis (ALS) and Alzheimer's disease (AD), is restricted to post-mortem analysis of brain tissue and experimental models. Thus, detecting EAAT2 in the living human brain might be crucial to improve diagnosis/therapy for ALS and AD. This perspective article describes the role of EAAT2 in physio/pathological processes and provides a structure-activity relationship of EAAT2-binders, bringing two perspectives: therapy (activators) and diagnosis (molecular imaging tools).

In-silico docking and molecular dynamic introspective study of multiple targets of AChE with Rivastigmine and NMDA receptors with Riluzole for Alzheimer's disease

The present study was initiated with PDB selection and validation where 11 acetylcholinesterase (AChE) and 4 N-methyl-D-aspartate receptor (NMDAR) proteins were considered for docking with Rivastigmine and Riluzole respectively. Out of the 15 proteins, selected significant binding was observed for AChE, with 5FPQ, and NMDA receptors with 5I2K. Molecular docking studies of 5FPQ/Rivastigmine complex displayed a binding score of -8.6 kcal/mol, and the predicted inhibitory concentration (Ki) was found to be 31 nM, whereas the 5I2K/Riluzole complex showed a binding score of -9.6 kcal/mol, with an inhibitory concentration (Ki) of 21 nM. Riluzole in complex with 5I2K formed predominant π-π stacking interactions with Tyr144, pi-alkyl interaction with Pro129, and conventional hydrogen bond with Phe130. In contrast, Rivastigmine in a complex with 5FPQ formed a hydrogen bond with Gln413 and pi-alkyl with Pro537. Molecular dynamics simulation study of both complexes 5FPQ/Rivastigmine and 5I2K/Riluzole exhibited stable RMSD, RMSF, Rg, and significant numbers of hydrogen bonds. From free energy landscape (FEL) analysis both complexes were observed to achieve global minima. Overall, molecular docking and MD simulation with subsequent binding free energies studies (MM-PBSA) elucidate the binding conformations and stability of these reprogrammed drugs in the AChE and NMDAR targets. From these in-silico predictions, it can be suggested that both Rivastigmine and Riluzole combination may provide better insights as a starting point combination therapy for the treatment of Alzheimer's disease.Communicated by Ramaswamy H. Sarma.

Prodromal Glutamatergic Modulation with Riluzole Impacts Glucose Homeostasis and Spatial Cognition in Alzheimer's Disease Mice

BACKGROUND

Prior research supports a strong link between Alzheimer's disease (AD) and metabolic dysfunction that involves a multi-directional interaction between glucose, glutamatergic homeostasis, and amyloid pathology. Elevated soluble amyloid-β (Aβ) is an early biomarker for AD-associated cognitive decline that contributes to concurrent glutamatergic and metabolic dyshomeostasis in humans and male transgenic AD mice. Yet, it remains unclear how primary time-sensitive targeting of hippocampal glutamatergic activity may impact glucose regulation in an amyloidogenic mouse model. Previous studies have illustrated increased glucose uptake and metabolism using a neuroprotective glutamate modulator (riluzole), supporting the link between glucose and glutamatergic homeostasis.

OBJECTIVE

We hypothesized that targeting early glutamatergic hyperexcitation through riluzole treatment could aid in attenuating co-occurring metabolic and amyloidogenic pathologies with the intent of ameliorating cognitive decline.

METHODS

We conducted an early intervention study in male and female transgenic (AβPP/PS1) and knock-in (APPNL - F/NL - F) AD mice to assess the on- and off-treatment effects of prodromal glutamatergic modulation (2-6 months of age) on glucose homeostasis and spatial cognition through riluzole treatment.

RESULTS

Results indicated a sex- and genotype-specific effect on glucose homeostasis and spatial cognition with riluzole intervention that evolved with disease progression and time since treatment.

CONCLUSION

These findings support the interconnected nature of glucose and glutamatergic homeostasis with amyloid pathology and petition for further investigation into the targeting of this relationship to improve cognitive performance.

Identification and immune characteristics of molecular subtypes related to protein glycosylation in Alzheimer's disease

BACKGROUND

Protein glycosylation has been confirmed to be involved in the pathological mechanisms of Alzheimer's disease (AD); however, there is still a lack of systematic analysis of the immune processes mediated by protein glycosylation-related genes (PGRGs) in AD.

MATERIALS AND METHODS

Transcriptomic data of AD patients were obtained from the Gene Expression Omnibus database and divided into training and verification datasets. The core PGRGs of the training set were identified by weighted gene co-expression network analysis, and protein glycosylation-related subtypes in AD were identified based on k-means unsupervised clustering. Protein glycosylation scores and neuroinflammatory levels of different subtypes were compared, and functional enrichment analysis and drug prediction were performed based on the differentially expressed genes (DEGs) between the subtypes. A random forest model was used to select important DEGs as diagnostic markers between subtypes, and a line chart model was constructed and verified in other datasets. We evaluated the differences in immune cell infiltration between the subtypes through the single-sample gene set enrichment analysis, analyzed the correlation between core diagnostic markers and immune cells, and explored the expression regulation network of the core diagnostic markers.

RESULTS

Eight core PGRGs were differentially expressed between the training set and control samples. AD was divided into two subtypes with significantly different biological processes, such as vesicle-mediated transport in synapses and neuroactive ligand-receptor interactions. The high protein glycosylation subtype had a higher level of neuroinflammation. Riluzole and sulfasalazine were found to have potential clinical value in this subtype. A reliable construction line chart model was constructed based on nine diagnostic markers, and SERPINA3 was identified as the core diagnostic marker. There were significant differences in immune cell infiltration between the two subtypes. SERPINA3 was found to be closely related to immune cells, and the expression of SERPINA3 in AD was found to be regulated by a competing endogenous RNA network that involves eight long non-coding RNAs and seven microRNAs.

CONCLUSION

Protein glycosylation and its corresponding immune process play an important role in the occurrence and development of AD. Understanding the role of PGRGs in AD may provide a new potential therapeutic target for AD.

Neue Hinweise auf Effektivität von Riluzol bei Alzheimer-Demenz

Glutamaterge pyramidale Neuron bilden Verbindungen unter anderem zwischen kortikalen Regionen und exzitatorischen hippokampalen Bahnen. Die Dysregulation glutamaterger neuraler Schaltkreise mit ihrer nachfolgenden Toxizität könnte auch zur Neurobiologie der Alzheimer-Demenz (AD) beitragen.

In Silico and In Vitro Studies of Benzothiazole-Isothioureas Derivatives as a Multitarget Compound for Alzheimer's Disease

Alzheimer's disease (AD) is a progressive neurodegenerative disorder. Inhibiting acetylcholinesterase (AChE), amyloid beta (Aβ1-42) aggregation and avoiding the oxidative stress could prevent the progression of AD. Benzothiazole groups have shown neuroprotective activity whereas isothioureas groups act as AChE inhibitors and antioxidants. Therefore, 22 benzothiazole-isothiourea derivatives (3a-v) were evaluated by docking simulations as inhibitors of AChE and Aβ1-42 aggregation. In silico studies showed that 3f, 3r and 3t had a delta G (ΔG) value better than curcumin and galantamine on Aβ1-42 and AChE, respectively. The physicochemical and pharmacokinetics predictions showed that only 3t does not violate Lipinski's rule of five, though it has moderated cytotoxicity activity. Then, 3f, 3r and 3t were synthetized and chemically characterized for their in vitro evaluation including their antioxidant activity and their cytotoxicity in PC12 cells. 3r was able to inhibit AChE, avoid Aβ1-42 aggregation and exhibit antioxidant activity; nevertheless, it showed cytotoxic against PC12 cells. Compound 3t showed the best anti-Aβ1-42 aggregation and inhibitory AChE activity and, despite that predictor, showed that it could be cytotoxic; in vitro with PC12 cell was negative. Therefore, 3t could be employed as a scaffold to develop new molecules with multitarget activity for AD and, due to physicochemical and pharmacokinetics predictions, it could be administered in vivo using liposomes due to is not able to cross the BBB.

The Pharmacorank Search Tool for the Retrieval of Prioritized Protein Drug Targets and Drug Repositioning Candidates According to Selected Diseases

We present the Pharmacorank search tool as an objective means to obtain prioritized protein drug targets and their associated medications according to user-selected diseases. This tool could be used to obtain prioritized protein targets for the creation of novel medications or to predict novel indications for medications that already exist. To prioritize the proteins associated with each disease, a gene similarity profiling method based on protein functions is implemented. The priority scores of the proteins are found to correlate well with the likelihoods that the associated medications are clinically relevant in the disease's treatment. When the protein priority scores are plotted against the percentage of protein targets that are known to bind medications currently indicated to treat the disease, which we termed the pertinency score, a strong correlation was observed. The correlation coefficient was found to be 0.9978 when using a weighted second-order polynomial fit. As the highly predictive fit was made using a broad range of diseases, we were able to identify a general threshold for the pertinency score as a starting point for considering drug repositioning candidates. Several repositioning candidates are described for proteins that have high predicated pertinency scores, and these provide illustrative examples of the applications of the tool. We also describe focused reviews of repositioning candidates for Alzheimer's disease. Via the tool's URL, https://protein.som.geisinger.edu/Pharmacorank/, an open online interface is provided for interactive use; and there is a site for programmatic access.

Landscape of immune infiltration in entorhinal cortex of patients with Alzheimerʼs disease

Alzheimer’s disease (AD) is one of the most common neurodegenerative diseases and manifests as progressive memory loss and cognitive dysfunction. Neuroinflammation plays an important role in the development of Alzheimer’s disease and anti-inflammatory drugs reduce the risk of the disease. However, the immune microenvironment in the brains of patients with Alzheimer’s disease remains unclear, and the mechanisms by which anti-inflammatory drugs improve Alzheimer’s disease have not been clearly elucidated. This study aimed to provide an overview of the immune cell composition in the entorhinal cortex of patients with Alzheimer’s disease based on the transcriptomes and signature genes of different immune cells and to explore potential therapeutic targets based on the relevance of drug targets. Transcriptomics data from the entorhinal cortex tissue, derived from GSE118553, were used to support our study. We compared the immune-related differentially expressed genes (irDEGs) between patients and controls by using the limma R package. The difference in immune cell composition between patients and controls was detected via the xCell algorithm based on the marker genes in immune cells. The correlation between marker genes and immune cells and the interaction between genes and drug targets were evaluated to explore potential therapeutic target genes and drugs. There were 81 irDEGs between patients and controls that participated in several immune-related pathways. xCell analysis showed that most lymphocyte scores decreased in Alzheimer’s disease, including CD4⁺ Tc, CD4⁺ Te, Th1, natural killer (NK), natural killer T (NKT), pro-B cells, eosinophils, and regulatory T cells, except for Th2 cells. In contrast, most myeloid cell scores increased in patients, except in dendritic cells. They included basophils, mast cells, plasma cells, and macrophages. Correlation analysis suggested that 37 genes were associated with these cells involved in innate immunity, of which eight genes were drug targets. Taken together, these results delineate the profile of the immune components of the entorhinal cortex in Alzheimer’s diseases, providing a new perspective on the development and treatment of Alzheimer’s disease.

The synapse as a treatment avenue for Alzheimer's Disease

Alzheimer's disease (AD) is a neurodegenerative disorder with devastating symptoms, including memory impairments and cognitive deficits. Hallmarks of AD pathology are amyloid-beta (Aβ) deposition forming neuritic plaques and neurofibrillary tangles (NFTs). For many years, AD drug development has mainly focused on directly targeting the Aβ aggregation or the formation of tau tangles, but this disease has no cure so far. Other common characteristics of AD are synaptic abnormalities and dysfunctions such as synaptic damage, synaptic loss, and structural changes in the synapse. Those anomalies happen in the early stages of the disease before behavioural symptoms have occurred. Therefore, better understanding the mechanisms underlying the synaptic dysfunction found in AD and targeting the synapse, especially using early treatment windows, can lead to finding novel and more effective treatments that could improve the lives of AD patients. Researchers have recently started developing different disease-modifying treatments targeting the synapse to rescue and prevent synaptic dysfunction in AD. The main objectives of these new strategies are to halt synaptic loss, strengthen synaptic connections, and improve synaptic density, potentially leading to the rescue or prevention of cognitive impairments. This article aims to address the mechanisms of synaptic degeneration in AD and discuss current strategies that focus on the synapse for AD therapy. Alzheimer's disease (AD) is a neurodegenerative disorder that significantly impairs memory and causes cognitive and behavioural deficits. Scientists worldwide have tried to find a treatment that can reverse or rescue AD symptoms, but there is no cure so far. One prominent characteristic of AD is the brain atrophy caused by significant synaptic loss and overall neuronal damage, which starts at the early stages of the disease before other AD hallmarks such as neuritic plaques and NFTs. The present review addresses the underlying mechanisms behind synaptic loss and dysfunction in AD and discusses potential strategies that target the synapse.

The combination of autologous mesenchymal stem cell-derived exosomes and neurotrophic factors as an intervention for amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis is a chronic progressive degeneration of motor neurons and has a high mortality. Riluzole and edaravone are the only approved medications currently being used for amyotrophic lateral sclerosis in clinical settings. However, they can lead to serious complications, such as injuries to the liver and kidney. To date, there is no effective treatment for amyotrophic lateral sclerosis. In this regard, investigations concerning the employment of exosomes, mesenchymal stem cells, and neurotrophic factors to ameliorate amyotrophic lateral sclerosis are attracting considerable attention in the scientific community. Herein, we systematically analyze the relationship relevant to autologous mesenchymal stem cell derived-exosomes, neurotrophic factors and amyotrophic lateral sclerosis. Mesenchymal stem cells modulate immune response, mitigate oxidative stress, promote neuronal regeneration, and differentiate into neuronal and glial cells. Furthermore, exosomes from mesenchymal stem cells exert beneficial effects on their mother cells by preventing abnormal differentiation of mesenchymal stem cells. Similarly, neurotrophic factors regulate inflammatory response, stimulate the neuron repair, and the recovery of neuronal functioning. Therefore, autologous mesenchymal stem cells-derived exosomes combined with neurotrophic factors could potentially be an effective interventional medium for amyotrophic lateral sclerosis.

Connecting the biology of stress, allostatic load and epigenetics to social structures and processes

How do sociology and stress biology connect in efforts to understand the impact of early childhood adversity on health and life chances? This memorial article describes the collaboration between Bruce and Craig McEwen in bringing stress neurobiology to sociologists. It attempts, in turn, to bring sociology to stress neurobiologists, the second goal of this collaboration. It frames the social sources of human stress in terms of the social determinants of health as well as more proximal childhood adversities. It also underlines the importance of supportive adult and community relationships in preventing toxic stress. Bruce was hopeful that stress biology research could inform public health efforts aimed at improving population health and more equitable life trajectories. To strengthen our understanding of stress and to contribute to that goal, stress neurobiologists can help tease out the complex social causes of stress by expanding the range of variables employed to identify its sources as well as the protections against it in human populations.

Saturation Transfer MRI for Detection of Metabolic and Microstructural Impairments Underlying Neurodegeneration in Alzheimer's Disease

Alzheimer's disease (AD) is one of the most common causes of dementia and difficult to study as the pool of subjects is highly heterogeneous. Saturation transfer (ST) magnetic resonance imaging (MRI) methods are quantitative modalities with potential for non-invasive identification and tracking of various aspects of AD pathology. In this review we cover ST-MRI studies in both humans and animal models of AD over the past 20 years. A number of magnetization transfer (MT) studies have shown promising results in human brain. Increased computing power enables more quantitative MT studies, while access to higher magnetic fields improves the specificity of chemical exchange saturation transfer (CEST) techniques. While much work remains to be done, results so far are very encouraging. MT is sensitive to patterns of AD-related pathological changes, improving differential diagnosis, and CEST is sensitive to particular pathological processes which could greatly assist in the development and monitoring of therapeutic treatments of this currently incurable disease.

Glutamate and GABA in Microglia-Neuron Cross-Talk in Alzheimer's Disease

The physiological balance between excitation and inhibition in the brain is significantly affected in Alzheimer’s disease (AD). Several neuroactive compounds and their signaling pathways through various types of receptors are crucial in brain homeostasis, among them glutamate and γ-aminobutyric acid (GABA). Activation of microglial receptors regulates the immunological response of these cells, which in AD could be neuroprotective or neurotoxic. The novel research approaches revealed the complexity of microglial function, including the interplay with other cells during neuroinflammation and in the AD brain. The purpose of this review is to describe the role of several proteins and multiple receptors on microglia and neurons, and their involvement in a communication network between cells that could lead to different metabolic loops and cell death/survival. Our review is focused on the role of glutamatergic, GABAergic signaling in microglia–neuronal cross-talk in AD and neuroinflammation. Moreover, the significance of AD-related neurotoxic proteins in glutamate/GABA-mediated dialogue between microglia and neurons was analyzed in search of novel targets in neuroprotection, and advanced pharmacological approaches.

Alzheimer's disease clinical trial update 2019-2021

The current clinical trial landscape targeting Alzheimer's disease (AD) is reviewed in the context of studies completed from 2019 to 2021. This review focuses on available data for observational and phase II/III clinical trial results, which will have the most impact on the field. ClinicalTrials.gov, the United States (US) comprehensive federal registry, was queried to identify completed trials. There are currently 226 interventional clinical trials and 51 observational studies completed, suspended, terminated, or withdrawn within our selected time frame. This review reveals that the role of biomarkers is expanding and although many lessons have been learned, many challenges remain when targeting disease modification of AD through amyloid and tau. In addition, to halt or slow clinical progression of AD, new clinical and observational trials are focusing on prevention as well as the role of more diverse biological processes known to influence AD pathology.