Clozapine Improves Memory Impairment and Reduces Aβ Level in the Tg-APPswe/PS1dE9 Mouse Model of Alzheimer’s Disease

Neuroreceptor Inhibition by Clozapine Triggers Mitohormesis and Metabolic Reprogramming in Human Blood Cells

The antipsychotic drug clozapine demonstrates superior efficacy in treatment-resistant schizophrenia, but its intracellular mode of action is not completely understood. Here, we analysed the effects of clozapine (2.5-20 µM) on metabolic fluxes, cell respiration, and intracellular ATP in human HL60 cells. Some results were confirmed in leukocytes of clozapine-treated patients. Neuroreceptor inhibition under clozapine reduced Akt activation with decreased glucose uptake, thereby inducing ER stress and the unfolded protein response (UPR). Metabolic profiling by liquid-chromatography/mass-spectrometry revealed downregulation of glycolysis and the pentose phosphate pathway, thereby saving glucose to keep the electron transport chain working. Mitochondrial respiration was dampened by upregulation of the F0F1-ATPase inhibitory factor 1 (IF1) leading to 30-40% lower oxygen consumption in HL60 cells. Blocking IF1 expression by cotreatment with epigallocatechin-3-gallate (EGCG) increased apoptosis of HL60 cells. Upregulation of the mitochondrial citrate carrier shifted excess citrate to the cytosol for use in lipogenesis and for storage as triacylglycerol in lipid droplets (LDs). Accordingly, clozapine-treated HL60 cells and leukocytes from clozapine-treated patients contain more LDs than untreated cells. Since mitochondrial disturbances are described in the pathophysiology of schizophrenia, clozapine-induced mitohormesis is an excellent way to escape energy deficits and improve cell survival.

Phytochemicals targeting Alzheimer's disease via the AMP-activated protein kinase pathway, effects, and mechanisms of action

Alzheimer's disease (AD), characterized by cognitive dysfunction and other behavioral abnormalities, is a progressive neurodegenerative disease that occurs due to aging. Currently, effective drugs to mitigate or treat AD remain unavailable. AD is associated with several abnormalities in neuronal energy metabolism, such as decreased glucose uptake, mitochondrial dysfunction, and defects in cholesterol metabolism. Amp-activated protein kinase (AMPK) is an important serine/threonine protein kinase that regulates the energy status of cells. AMPK is widely present in eukaryotic cells and can sense and regulate energy metabolism to maintain energy supply and demand balance, making it a promising target for energy metabolism-based AD therapy. Therefore, this review aimed to discuss the molecular mechanism of AMPK in the pathogenesis of AD to provide a theoretical basis for the development of new anti-AD drugs. To review the mechanisms of phytochemicals in the treatment of AD via AMPK pathway regulation, we searched PubMed, Google Scholar, Web of Science, and Embase databases using specific keywords related to AD and phytochemicals in September 2023. Phytochemicals can activate AMPK or regulate the AMPK pathway to exert therapeutic effects in AD. The anti-AD mechanisms of these phytochemicals include inhibiting Aβ aggregation, preventing Tau hyperphosphorylation, inhibiting inflammatory response and glial activation, promoting autophagy, and suppressing anti-oxidative stress. Additionally, several AMPK-related pathways are involved in the anti-AD mechanism, including the AMPK/CaMKKβ/mTOR, AMPK/SIRT1/PGC-1α, AMPK/NF-κB/NLRP3, AMPK/mTOR, and PERK/eIF2α pathways. Notably, urolithin A, artemisinin, justicidin A, berberine, stigmasterol, arctigenin, and rutaecarpine are promising AMPK agonists with anti-AD effects. Several phytochemicals are effective AMPK agonists and may have potential applications in AD treatment. Overall, phytochemical-based drugs may overcome the barriers to the effective treatment of neurodegenerative diseases.

Drug repurposing for neurodegenerative diseases using Zebrafish behavioral profiles

Drug repurposing can accelerate drug development while reducing the cost and risk of toxicity typically associated with de novo drug design. Several disorders lacking pharmacological solutions and exhibiting poor results in clinical trials - such as Alzheimer's disease (AD) - could benefit from a cost-effective approach to finding new therapeutics. We previously developed a neural network model, Z-LaP Tracker, capable of quantifying behaviors in zebrafish larvae relevant to cognitive function, including activity, reactivity, swimming patterns, and optomotor response in the presence of visual and acoustic stimuli. Using this model, we performed a high-throughput screening of FDA-approved drugs to identify compounds that affect zebrafish larval behavior in a manner consistent with the distinct behavior induced by calcineurin inhibitors. Cyclosporine (CsA) and other calcineurin inhibitors have garnered interest for their potential role in the prevention of AD. We generated behavioral profiles suitable for cluster analysis, through which we identified 64 candidate therapeutics for neurodegenerative disorders.

Screening Targets and Therapeutic Drugs for Alzheimer's Disease Based on Deep Learning Model and Molecular Docking

Background

Alzheimer's disease (AD) is a neurodegenerative disorder caused by a complex interplay of various factors. However, a satisfactory cure for AD remains elusive. Pharmacological interventions based on drug targets are considered the most cost-effective therapeutic strategy. Therefore, it is paramount to search potential drug targets and drugs for AD.

Objective

We aimed to provide novel targets and drugs for the treatment of AD employing transcriptomic data of AD and normal control brain tissues from a new perspective.

Methods

Our study combined the use of a multi-layer perceptron (MLP) with differential expression analysis, variance assessment and molecular docking to screen targets and drugs for AD.

Results

We identified the seven differentially expressed genes (DEGs) with the most significant variation (ANKRD39, CPLX1, FABP3, GABBR2, GNG3, PPM1E, and WDR49) in transcriptomic data from AD brain. A newly built MLP was used to confirm the association between the seven DEGs and AD, establishing these DEGs as potential drug targets. Drug databases and molecular docking results indicated that arbaclofen, baclofen, clozapine, arbaclofen placarbil, BML-259, BRD-K72883421, and YC-1 had high affinity for GABBR2, and FABP3 bound with oleic, palmitic, and stearic acids. Arbaclofen and YC-1 activated GABAB receptor through PI3K/AKT and PKA/CREB pathways, respectively, thereby promoting neuronal anti-apoptotic effect and inhibiting p-tau and Aβ formation.

Conclusions

This study provided a new strategy for the identification of targets and drugs for the treatment of AD using deep learning. Seven therapeutic targets and ten drugs were selected by using this method, providing new insight for AD treatment.

Finding Drug Repurposing Candidates for Neurodegenerative Diseases using Zebrafish Behavioral Profiles

Drug repurposing can accelerate drug development while reducing the cost and risk of toxicity typically associated with de novo drug design. Several disorders lacking pharmacological solutions and exhibiting poor results in clinical trials - such as Alzheimer's disease (AD) - could benefit from a cost-effective approach to finding new therapeutics. We previously developed a neural network model, Z-LaP Tracker, capable of quantifying behaviors in zebrafish larvae relevant to cognitive function, including activity, reactivity, swimming patterns, and optomotor response in the presence of visual and acoustic stimuli. Using this model, we performed a high-throughput screening of FDA-approved drugs to identify compounds that affect zebrafish larval behavior in a manner consistent with the distinct behavior induced by calcineurin inhibitors. Cyclosporine (CsA) and other calcineurin inhibitors have garnered interest for their potential role in the prevention of AD. We generated behavioral profiles suitable for cluster analysis, through which we identified 64 candidate therapeutics for neurodegenerative disorders.

Drug repurposing for Alzheimer's disease from 2012-2022-a 10-year literature review

Background: Alzheimer's disease (AD) is a debilitating neurodegenerative condition with few treatment options available. Drug repurposing studies have sought to identify existing drugs that could be repositioned to treat AD; however, the effectiveness of drug repurposing for AD remains unclear. This review systematically analyzes the progress made in drug repurposing for AD throughout the last decade, summarizing the suggested drug candidates and analyzing changes in the repurposing strategies used over time. We also examine the different types of data that have been leveraged to validate suggested drug repurposing candidates for AD, which to our knowledge has not been previous investigated, although this information may be especially useful in appraising the potential of suggested drug repurposing candidates. We ultimately hope to gain insight into the suggested drugs representing the most promising repurposing candidates for AD. Methods: We queried the PubMed database for AD drug repurposing studies published between 2012 and 2022. 124 articles were reviewed. We used RxNorm to standardize drug names across the reviewed studies, map drugs to their constituent ingredients, and identify prescribable drugs. We used the Anatomical Therapeutic Chemical (ATC) Classification System to group drugs. Results: 573 unique drugs were proposed for repurposing in AD over the last 10 years. These suggested repurposing candidates included drugs acting on the nervous system (17%), antineoplastic and immunomodulating agents (16%), and drugs acting on the cardiovascular system (12%). Clozapine, a second-generation antipsychotic medication, was the most frequently suggested repurposing candidate (N = 6). 61% (76/124) of the reviewed studies performed a validation, yet only 4% (5/124) used real-world data for validation. Conclusion: A large number of potential drug repurposing candidates for AD has accumulated over the last decade. However, among these drugs, no single drug has emerged as the top candidate, making it difficult to establish research priorities. Validation of drug repurposing hypotheses is inconsistently performed, and real-world data has been critically underutilized for validation. Given the urgent need for new AD therapies, the utility of real-world data in accelerating identification of high-priority candidates for AD repurposing warrants further investigation.

Activation of the aryl hydrocarbon receptor by clozapine induces preadipocyte differentiation and contributes to endothelial dysfunction

BACKGROUND

The superior therapeutic benefit of clozapine is often associated with metabolic disruptions as obesity, insulin resistance, tachycardia, higher blood pressure, and even hypertension.

AIMS

These adverse vascular/ metabolic events under clozapine are similar to those caused by polycyclic aromatic hydrocarbons (PAHs), and clozapine shows structural similarity to well-known ligands of the aryl hydrocarbon receptor (AhR). Therefore, we speculated that the side effects caused by clozapine might rely on AhR signaling.

METHODS

We examined clozapine-induced AhR activation by luciferase reporter assays in hepatoma HepG2 cells and we proved upregulation of the prototypical AhR target gene Cyp1A1 by realtime-PCR (RT-PCR) analysis and enzyme activity. Next we studied the physiological role of AhR in clozapine's effects on human preadipocyte differentiation and on vasodilatation by myography in wild-type and AhR-/- mice.

RESULTS

In contrast to other antipsychotic drugs (APDs), clozapine triggered AhR activation and Cyp1A1 expression in HepG2 cells and adipocytes. Clozapine induced adipogenesis via AhR signaling. After PGF2α-induced constriction of mouse aortic rings, clozapine strongly reduced the maximal vasorelaxation under acetylcholine in rings from wild-type mice, but only slightly in rings from AhR-/- mice. The reduction was also prevented by pretreatment with the AhR antagonist CH-223191.

CONCLUSION

Identification of clozapine as a ligand for the AhR opens new perspectives to explain common clozapine therapy-associated adverse effects at the molecular level.

Artificial intelligence framework identifies candidate targets for drug repurposing in Alzheimer's disease

BACKGROUND

Genome-wide association studies (GWAS) have identified numerous susceptibility loci for Alzheimer's disease (AD). However, utilizing GWAS and multi-omics data to identify high-confidence AD risk genes (ARGs) and druggable targets that can guide development of new therapeutics for patients suffering from AD has heretofore not been successful.

METHODS

To address this critical problem in the field, we have developed a network-based artificial intelligence framework that is capable of integrating multi-omics data along with human protein-protein interactome networks to accurately infer accurate drug targets impacted by GWAS-identified variants to identify new therapeutics. When applied to AD, this approach integrates GWAS findings, multi-omics data from brain samples of AD patients and AD transgenic animal models, drug-target networks, and the human protein-protein interactome, along with large-scale patient database validation and in vitro mechanistic observations in human microglia cells.

RESULTS

Through this approach, we identified 103 ARGs validated by various levels of pathobiological evidence in AD. Via network-based prediction and population-based validation, we then showed that three drugs (pioglitazone, febuxostat, and atenolol) are significantly associated with decreased risk of AD compared with matched control populations. Pioglitazone usage is significantly associated with decreased risk of AD (hazard ratio (HR) = 0.916, 95% confidence interval [CI] 0.861-0.974, P = 0.005) in a retrospective case-control validation. Pioglitazone is a peroxisome proliferator-activated receptor (PPAR) agonist used to treat type 2 diabetes, and propensity score matching cohort studies confirmed its association with reduced risk of AD in comparison to glipizide (HR = 0.921, 95% CI 0.862-0.984, P = 0.0159), an insulin secretagogue that is also used to treat type 2 diabetes. In vitro experiments showed that pioglitazone downregulated glycogen synthase kinase 3 beta (GSK3β) and cyclin-dependent kinase (CDK5) in human microglia cells, supporting a possible mechanism-of-action for its beneficial effect in AD.

CONCLUSIONS

In summary, we present an integrated, network-based artificial intelligence methodology to rapidly translate GWAS findings and multi-omics data to genotype-informed therapeutic discovery in AD.

Psychedelic-inspired approaches for treating neurodegenerative disorders

Psychedelics are increasingly being recognized for their potential to treat a wide range of brain disorders including depression, post-traumatic stress disorder (PTSD), and substance use disorder. Their broad therapeutic potential might result from an ability to rescue cortical atrophy common to many neuropsychiatric and neurodegenerative diseases by impacting neurotrophic factor gene expression, activating neuronal growth and survival mechanisms, and modulating the immune system. While the therapeutic potential of psychedelics has not yet been extended to neurodegenerative disorders, we provide evidence suggesting that approaches based on psychedelic science might prove useful for treating these diseases. The primary target of psychedelics, the 5-HT_2A receptor, plays key roles in cortical neuron health and is dysregulated in Alzheimer's disease. Moreover, evidence suggests that psychedelics and related compounds could prove useful for treating the behavioral and psychological symptoms of dementia (BPSD). While more research is needed to probe the effects of psychedelics in models of neurodegenerative diseases, the robust effects of these compounds on structural and functional neuroplasticity and inflammation clearly warrant further investigation.

A drug repositioning algorithm based on a deep autoencoder and adaptive fusion

BACKGROUND

Drug repositioning has caught the attention of scholars at home and abroad due to its effective reduction of the development cost and time of new drugs. However, existing drug repositioning methods that are based on computational analysis are limited by sparse data and classic fusion methods; thus, we use autoencoders and adaptive fusion methods to calculate drug repositioning.

RESULTS

In this study, a drug repositioning algorithm based on a deep autoencoder and adaptive fusion was proposed to mitigate the problems of decreased precision and low-efficiency multisource data fusion caused by data sparseness. Specifically, a drug is repositioned by fusing drug-disease associations, drug target proteins, drug chemical structures and drug side effects. First, drug feature data integrated by drug target proteins and chemical structures were processed with dimension reduction via a deep autoencoder to characterize feature representations more densely and abstractly. Then, disease similarity was computed using drug-disease association data, while drug similarity was calculated with drug feature and drug-side effect data. Predictions of drug-disease associations were also calculated using a top-k neighbor method that is commonly used in predictive drug repositioning studies. Finally, a predicted matrix for drug-disease associations was acquired after fusing a wide variety of data via adaptive fusion. Based on experimental results, the proposed algorithm achieves a higher precision and recall rate than the DRCFFS, SLAMS and BADR algorithms with the same dataset.

CONCLUSION

The proposed algorithm contributes to investigating the novel uses of drugs, as shown in a case study of Alzheimer's disease. Therefore, the proposed algorithm can provide an auxiliary effect for clinical trials of drug repositioning.

Drug Repurposing for Alzheimer's Disease Based on Protein-Protein Interaction Network

Alzheimer's disease (AD) is known as a critical neurodegenerative disorder. It worsens as symptoms concerning dementia grow severe over the years. Due to the globalization of Alzheimer's disease, its prevention and treatment are vital. This study proposes a method to extract substantial gene complexes and then introduces potential drugs in Alzheimer's disease. To this end, a protein-protein interaction (PPI) network was utilized to extract five meaningful gene complexes functionally interconnected. An enrichment analysis to introduce the most important biological processes and pathways was accomplished on the obtained genes. The next step is extracting the drugs related to AD and introducing some new drugs which may be helpful for this disease. Finally, a complete network including all the genes associated with each gene complex group and genes' target drug was illustrated. For validating the proposed potential drugs, Connectivity Map (CMAP) analysis was accomplished to determine target genes that are up- or downregulated by proposed drugs. Medical studies and publications were analyzed thoroughly to introduce AD-related drugs. This analysis proves the accuracy of the proposed method in this study. Then, new drugs were introduced that can be experimentally examined as future work. Raloxifene and gentian violet are two new drugs, which have not been introduced as AD-related drugs in previous scientific and medical studies, recommended by the method of this study. Besides the primary goal, five bipartite networks representing the genes of each group and their target miRNAs were constructed to introduce target miRNAs.

Harnessing endophenotypes and network medicine for Alzheimer's drug repurposing

Following two decades of more than 400 clinical trials centered on the "one drug, one target, one disease" paradigm, there is still no effective disease-modifying therapy for Alzheimer's disease (AD). The inherent complexity of AD may challenge this reductionist strategy. Recent observations and advances in network medicine further indicate that AD likely shares common underlying mechanisms and intermediate pathophenotypes, or endophenotypes, with other diseases. In this review, we consider AD pathobiology, disease comorbidity, pleiotropy, and therapeutic development, and construct relevant endophenotype networks to guide future therapeutic development. Specifically, we discuss six main endophenotype hypotheses in AD: amyloidosis, tauopathy, neuroinflammation, mitochondrial dysfunction, vascular dysfunction, and lysosomal dysfunction. We further consider how this endophenotype network framework can provide advances in computational and experimental strategies for drug-repurposing and identification of new candidate therapeutic strategies for patients suffering from or at risk for AD. We highlight new opportunities for endophenotype-informed, drug discovery in AD, by exploiting multi-omics data. Integration of genomics, transcriptomics, radiomics, pharmacogenomics, and interactomics (protein-protein interactions) are essential for successful drug discovery. We describe experimental technologies for AD drug discovery including human induced pluripotent stem cells, transgenic mouse/rat models, and population-based retrospective case-control studies that may be integrated with multi-omics in a network medicine methodology. In summary, endophenotype-based network medicine methodologies will promote AD therapeutic development that will optimize the usefulness of available data and support deep phenotyping of the patient heterogeneity for personalized medicine in AD.

Clozapine-associated secondary antibody deficiency

PURPOSE OF REVIEW

Clozapine has recently been described as a novel cause of secondary antibody deficiency (SAD), associated with long-term therapy. Here we critically review the evidence linking clozapine use to an increased infection risk, describe immunological alterations, and discuss potential mechanisms.

RECENT FINDINGS

Individuals with schizophrenia are at two to five times more likely to develop pneumonia than the general population, in particular, when receiving clozapine. Delayed-onset distinguishes clozapine-associated hypogammaglobulinaemia from agranulocytosis or neutropenia that occur at lesser frequency. Biomarker searches in treatment-resistant schizophrenia highlight an immune signature associated with long-term clozapine use. This includes reduction in class-switched memory B cells, echoing common variable immunodeficiency. Recent identification of a role for dopamine in T follicular helper-B cell interactions may inform future clinical studies.

SUMMARY

The detrimental impact of the increased infection risk associated with clozapine necessitates a re-evaluation of the current monitoring strategies as well as further studies to better understand the underlying mechanisms of SAD in this setting. On the basis of available evidence, we suggest simple modifications to clozapine monitoring including integration of routine vaccination, smoking cessation, and assessment of humoral immunity. Further studies are required to understand the role of clozapine in neuroinflammation as well as other potentially autoantibody-mediated diseases.

Calcium-Sensing Receptor Mediates β-Amyloid-Induced Synaptic Formation Impairment and Cognitive Deficits via Regulation of Cytosolic Phospholipase A2/Prostaglandin E2 Metabolic Pathway

Calcium-sensing receptor (CaSR) is a G protein-coupled receptor (GPCRs). Soluble β-amyloid peptide (Aβ) is one of the orthosteric modulators of CaSR, while, the role and underlying mechanism of CaSR in cognitive decline in Alzheimer’s disease (AD) is unclear. In this study, molecular technology such as live-cell imaging combined with behavioral tests were used to explore the role and the underlying mechanism of CaSR in the cognitive deficits in AD mice. The expression levels of CaSR were increased both in AD mice and Aβ_1–42 (β-amyloid protein)-treated primary cultured neurons. Pharmacological inhibition of CaSR ameliorated recognitive and spatial memory deficits of Aβ_1–42-oligomer-treated mice in a dose-dependent manner. Pharmacological inhibition of CaSR or down-regulation of the expression of CaSR by CaSR-shRNA-lentivirus prevented the impairment of filopodia, and the synapse induced by oligomeric Aβ_1–42. The contents of cytosolic phospholipase A2 (cPLA2) and prostaglandin E2 (PGE2) in hippocampal neurons and tissue were increased after treatment with Aβ_1–42 oligomers. Inhibition or down-regulation of CaSR mediates Aβ-induced synapse formation and cognitive deficits partially, through the activation of the cPLA2/PGE2 pathway. This study provides novel insights on CaSR, which is a promising therapeutic target for AD.

Born to Protect: Leveraging BDNF Against Cognitive Deficit in Alzheimer's Disease

Alzheimer's disease is a chronic neurodegenerative devastating disorder affecting a high percentage of the population over 65 years of age and causing a relevant emotional, social, and economic burden. Clinically, it is characterized by a prominent cognitive deficit associated with language and behavioral impairments. The molecular pathogenesis of Alzheimer's disease is multifaceted and involves changes in neurotransmitter levels together with alterations of inflammatory, oxidative, hormonal, and synaptic pathways, which may represent a drug target for both prevention and treatment; however, an effective treatment for Alzheimer's disease still represents an unmet goal. As neurotrophic factors participate in the modulation of the above-mentioned pathways, they have been highlighted as critical contributors of Alzheimer's disease etiology, whose modulation might be beneficial for Alzheimer's disease. We focused on the neurotrophin brain-derived neurotrophic factor, providing several lines of evidence pointing to brain-derived neurotrophic factor as a plausible endophenotype of cognitive deficits in Alzheimer's disease, illustrating some of the most recent possibilities to modulate the expression of this neurotrophin in the brain in an attempt to ameliorate cognition and delay the progression of Alzheimer's disease. This review shows that otherwise disparate pharmacologic or non-pharmacologic approaches converge on brain-derived neurotrophic factor, providing a means whereby apparently unrelated medical approaches may nevertheless produce similar synaptic and cognitive outcomes in Alzheimer's disease pathogenesis, suggesting that brain-derived neurotrophic factor-based synaptic repair may represent a modifying strategy to ameliorate cognition in Alzheimer's disease.

Animal Models of Psychosis in Alzheimer Disease

Psychosis in Alzheimer Disease (AD) represents a distinct clinicopathologic variant associated with increased cognitive and functional morbidity and an accelerated disease course. To date, extant treatments offer modest benefits with significant risks. The development of new pharmacologic treatments for psychosis in AD would be facilitated by validated preclinical models with which to test candidate interventions. The current review provides a brief summary of the process of validating animal models of human disease together with a critical analysis of the challenges posed in attempting to apply those standards to AD-related behavioral models. An overview of phenotypic analogues of human cognitive and behavioral impairments, with an emphasis on those relevant to psychosis, in AD-related mouse models is provided, followed by an update on recent progress in efforts to translate findings in the pathophysiology of psychotic AD into novel models. Finally, some future directions are suggested to expand the catalogue of psychosis-relevant phenotypes that may provide a sturdier framework for model development and targets for preclinical treatment outcomes.

mTOR-Related Brain Dysfunctions in Neuropsychiatric Disorders

The mammalian target of rapamycin (mTOR) is an ubiquitously expressed serine-threonine kinase, which senses and integrates several intracellular and environmental cues to orchestrate major processes such as cell growth and metabolism. Altered mTOR signalling is associated with brain malformation and neurological disorders. Emerging evidence indicates that even subtle defects in the mTOR pathway may produce severe effects, which are evident as neurological and psychiatric disorders. On the other hand, administration of mTOR inhibitors may be beneficial for a variety of neuropsychiatric alterations encompassing neurodegeneration, brain tumors, brain ischemia, epilepsy, autism, mood disorders, drugs of abuse, and schizophrenia. mTOR has been widely implicated in synaptic plasticity and autophagy activation. This review addresses the role of mTOR-dependent autophagy dysfunction in a variety of neuropsychiatric disorders, to focus mainly on psychiatric syndromes including schizophrenia and drug addiction. For instance, amphetamines-induced addiction fairly overlaps with some neuropsychiatric disorders including neurodegeneration and schizophrenia. For this reason, in the present review, a special emphasis is placed on the role of mTOR on methamphetamine-induced brain alterations.

The antipsychotic agent clozapine induces autophagy via the AMPK-ULK1-Beclin1 signaling pathway in the rat frontal cortex

Clozapine, a representative atypical antipsychotic, has superior efficacy compared to other antipsychotic agents and is used for the treatment of severe psychotic disorders. Therefore, studies on its mechanisms of action are important for understanding the mechanisms of therapeutic approaches to psychosis. Adenosine monophosphate-activated protein kinase (AMPK) is a serine-threonine kinase that plays a major role in maintaining metabolic homeostasis. Unc-51-like kinase 1 (ULK1) and Beclin1 are downstream substrates of AMPK and activate the autophagic process. In this study, we examined the effects of clozapine on the AMPK-ULK1-Beclin1 signaling pathway and autophagy in the frontal cortex of the rat. Clozapine (10mg/kg) administration increased the immunoreactivity of p-Thr172-AMPKα in the rat frontal cortex at 1, 2, and 4h after injection, as we previously reported. The immunoreactivity of p-Ser317-ULK1 and p-Ser93-Beclin1 was also increased at 2 and 4h after clozapine injection. At the same time, the immunoreactivity of LC3-II and the Atg5-Atg12 conjugate, which indicate activation of autophagy, was increased. Transmission electron microscopy clearly showed an increase in autophagosome number in the rat frontal cortex at 2h after clozapine injection. To investigate the role of AMPK in clozapine-induced autophagy, the effects of intracerebroventricular injection of compound C, an AMPK inhibitor, were examined. Administration of compound C attenuated the clozapine-induced increase in ULK1 and Beclin1 phosphorylation, as well the protein levels of LC3-II and the Atg5-Atg12 conjugate in the frontal cortex. In summary, the results showed that clozapine activates autophagy through the AMPK-ULK1-Beclin1 signaling pathway in the frontal cortex of the rat.

Icariside II Effectively Reduces Spatial Learning and Memory Impairments in Alzheimer's Disease Model Mice Targeting Beta-Amyloid Production

Icariside II (ICS II) is a broad-spectrum anti-cancer natural compound extracted from Herba Epimedii Maxim. Recently, the role of ICS II has been investigated in central nervous system, especially have a neuroprotective effect in Alzheimer’s disease (AD). In this study, we attempted to investigate the effects of ICS II, on cognitive deficits and beta-amyloid (Aβ) production in APPswe/PS1dE9 (APP/PS1) double transgenic mice. It was found that chronic ICS II administrated not only effectively ameliorated cognitive function deficits, but also inhibited neuronal degeneration and reduced the formation of plaque burden. ICS II significantly suppressed Aβ production via promoting non-amyloidogenic APP cleavage process by up-regulating a disintegrin and metalloproteinase domain 10 (ADAM10) expression, inhibited amyloidogenic APP processing pathway by down-regulating amyloid precursor protein (APP) and β-site amyloid precursor protein cleavage enzyme 1 (BACE1) expression in APP/PS1 transgenic mice. Meanwhile, ICS II attenuated peroxisome proliferator-activated receptor-γ (PPARγ) degradation as well as inhibition of eukaryotic initiation factor α phosphorylation (p-eIF2α) and PKR endoplasmic reticulum regulating kinase phosphorylation (p-PERK). Moreover, phosphodiesterase type 5 inhibitors (PDE5-Is) have recently emerged as a possible therapeutic target for cognitive enhancement via inhibiting Aβ levels, and we also found that ICS II markedly decreased phosphodiesterase-5A (PDE5A) expression. In conclusion, the present study demonstrates that ICS II could attenuate spatial learning and memory impairments in APP/PS1 transgenic mice. This protection appears to be due to the increased ADAM10 expression and decreased expression of both APP and BACE1, resulting in inhibition of Aβ production in the hippocampus and cortex. Inhibition of PPARγ degradation and PERK/eIF2α phosphorylation are involved in the course, therefore suggesting that ICS II might be a promising potential compound for the treatment of AD.

Haloperidol inactivates AMPK and reduces tau phosphorylation in a tau mouse model of Alzheimer's disease

INTRODUCTION

The use of antipsychotic medications in Alzheimer's disease has been associated with an increased risk of mortality in clinical trials. However, an older postmortem literature suggests that those with schizophrenia treated in an era of exclusively conventional antipsychotic medications had a surprisingly low incidence of tau pathology. No previously published studies have investigated the impact of conventional antipsychotic exposure on tau outcomes in a tau mouse model of AD.

METHODS

In two experiments, transgenic rTg (tauP301L) 4510 tau mice were treated with either haloperidol or vehicle and phosphotau epitopes were quantified using high-sensitivity tau ELISA.

RESULTS

After treatments of 2 and 6 week's duration, mice treated with haloperidol evidenced a significant reduction in tau phosphorylation associated with an inactivation of the tau kinase AMPK.

DISCUSSION

The data suggest that D2 receptor blockade reduces tau phosphorylation in vivo. Future studies are necessary to investigate the impact of this reduction on tau neuropathology.