Drug repositioning and repurposing for Alzheimer disease

The role of ACE inhibitors and ARBs in preserving cognitive function via hypertension Management: A critical Update

Hypertension poses a significant risk to cognition-related disorders like dementia. As the global population ages, age-related neurological illnesses such as Alzheimer's disease are becoming increasingly prevalent. The primary hypertension treatments, angiotensin receptor blockers, and angiotensin-converting enzyme inhibitors, exhibit neuroprotective properties. However, observational studies suggest that they may independently contribute to cognitive decline and dementia. Some of these medications have shown promise in reducing cognitive impairment and amyloid buildup in Alzheimer's models. While direct comparisons between the two drug classes are limited, angiotensin receptor blockers have been associated with less brain shrinkage, lower dementia incidence, and slower cognitive decline compared to angiotensin-converting enzyme inhibitors. Both types of medications can influence cognition by passing the blood-brain barrier, with angiotensin receptor blockers potentially offering superior neuroprotective effects due to their selective blockade of the angiotensin type 1 receptor.

Unlocking biological insights from differentially expressed genes: Concepts, methods, and future perspectives

BACKGROUND

Identifying differentially expressed genes (DEGs) is a core task of transcriptome analysis, as DEGs can reveal the molecular mechanisms underlying biological processes. However, interpreting the biological significance of large DEG lists is challenging. Currently, gene ontology, pathway enrichment and protein-protein interaction analysis are common strategies employed by biologists. Additionally, emerging analytical strategies/approaches (such as network module analysis, knowledge graph, drug repurposing, cell marker discovery, trajectory analysis, and cell communication analysis) have been proposed. Despite these advances, comprehensive guidelines for systematically and thoroughly mining the biological information within DEGs remain lacking.

AIM OF REVIEW

This review aims to provide an overview of essential concepts and methodologies for the biological interpretation of DEGs, enhancing the contextual understanding. It also addresses the current limitations and future perspectives of these approaches, highlighting their broad applications in deciphering the molecular mechanism of complex diseases and phenotypes. To assist users in extracting insights from extensive datasets, especially various DEG lists, we developed DEGMiner (https://www.ciblab.net/DEGMiner/), which integrates over 300 easily accessible databases and tools.

KEY SCIENTIFIC CONCEPTS OF REVIEW

This review offers strong support and guidance for exploring DEGs, and also will accelerate the discovery of hidden biological insights within genomes.

Exploring nanoparticular platform in delivery of repurposed drug for Alzheimer's disease: current approaches and future perspectives

INTRODUCTION

Alzheimer's disease (AD) stands as significant challenge in realm of neurodegenerative disorder. It is characterized by gradual decline in cognitive function and memory loss. It has already expanded its prevalence to 55 million people worldwide and is expected to rise significantly. Unfortunately, there exists a limited therapeutic option that would mitigate its progression. Repurposing existing drugs and employing nanoparticle as delivery agent presents a potential solution to address the intricate pathology of AD.

AREAS COVERED

In this review, we delve into utilization of nanoparticular platforms to enhance the delivery of repurposed drugs for treatment of AD. Firstly, the review begins with the elucidation of intricate pathology underpinning AD, subsequently followed by rationale behind drug repurposing in AD. Covered are explorations of nanoparticle-based repurposing of drugs in AD, highlighting their clinical implication. Further, the associated challenges and probable future perspective are delineated.

EXPERT OPINION

The article has highlighted that extensive research has been carried out on the delivery of repurposed nanomedicines against AD. However, there is a need for advanced and long-term research including clinical trials required to shed light upon their safety and toxicity profile. Furthermore, their scalability in pharmaceutical set-up should also be validated.

Heterogeneous graph contrastive learning with gradient balance for drug repositioning

Drug repositioning, which involves identifying new therapeutic indications for approved drugs, is pivotal in accelerating drug discovery. Recently, to mitigate the effect of label sparsity on inferring potential drug-disease associations (DDAs), graph contrastive learning (GCL) has emerged as a promising paradigm to supplement high-quality self-supervised signals through designing auxiliary tasks, then transfer shareable knowledge to main task, i.e. DDA prediction. However, existing approaches still encounter two limitations. The first is how to generate augmented views for fully capturing higher-order interaction semantics. The second is the optimization imbalance issue between auxiliary and main tasks. In this paper, we propose a novel heterogeneous Graph Contrastive learning method with Gradient Balance for DDA prediction, namely GCGB. To handle the first challenge, a fusion view is introduced to integrate both semantic views (drug and disease similarity networks) and interaction view (heterogeneous biomedical network). Next, inter-view contrastive learning auxiliary tasks are designed to contrast the fusion view with semantic and interaction views, respectively. For the second challenge, we adaptively adjust the gradient of GCL auxiliary tasks from the perspective of gradient direction and magnitude for better guiding parameter update toward main task. Extensive experiments conducted on three benchmarks under 10-fold cross-validation demonstrate the model effectiveness.

Emerging paradigms in Alzheimer's therapy

Alzheimer's disease is a neurodegenerative disorder that affects elderly, and its incidence is continuously increasing across the globe. Unfortunately, despite decades of research, a complete cure for Alzheimer's disease continues to elude us. The current medications are mainly symptomatic and slow the disease progression but do not result in reversal of all disease pathologies. The growing body of knowledge on the factors responsible for the onset and progression of the disease has resulted in the identification of new targets that could be targeted for treatment of Alzheimer's disease. This has opened new vistas for treatment of Alzheimer's disease that have moved away from chemotherapeutic agents modulating a single target to biologics and combinations that acted on multiple targets thereby offering better therapeutic outcomes. This review discusses the emerging directions in therapeutic interventions against Alzheimer's disease highlighting their merits that promise to change the treatment paradigm and challenges that limit their clinical translation.

Lung cancer cell-derived exosomes: progress on pivotal role and its application in diagnostic and therapeutic potential

Lung cancer is frequently detected in an advanced stage and has an unfavourable prognosis. Conventional therapies are ineffective for the treatment of metastatic lung cancer. While certain molecular targets have been identified as having a positive response, the absence of appropriate drug carriers prevents their effective utilization. Lung cancer cell-derived exosomes (LCCDEs) have gained attention for their involvement in the development of cancer, as well as their potential for use in diagnosing, treating, and predicting the outcome of lung cancer. This is due to their biological roles and their inherent ability to transport biomolecules from the donor cells. Lung cancer-associated cell-derived extracellular vesicles (LCCDEVs) have the ability to enhance cell proliferation and metastasis, influence angiogenesis, regulate immune responses against tumours during the development of lung cancer, control drug resistance in lung cancer treatment, and are increasingly recognised as a crucial element in liquid biopsy evaluations for the detection of lung cancer. Therapeutic exosomes, which possess inherent intercellular communication capabilities, are increasingly recognised as effective vehicles for targeted drug delivery in precision medicine for tumours. This is due to their exceptional biocompatibility, minimal immunogenicity, low toxicity, prolonged circulation in the bloodstream, biodegradability, and ability to traverse different biological barriers. Currently, multiple studies are being conducted to create new means of diagnosing and predicting outcomes using LCCDEs, as well as to develop techniques for utilizing exosomes as effective carriers for medication delivery. This paper provides an overview of the current state of lung cancer and the wide range of applications of LCCDEs. The encouraging findings and technologies suggest that the utilization of LCCDEs holds promise for the clinical treatment of lung cancer patients.

Inflammatory proteins associated with Alzheimer's disease reduced by a GLP1 receptor agonist: a post hoc analysis of the EXSCEL randomized placebo controlled trial

BACKGROUND

Glucagon-like peptide-1 receptor agonists are a viable option for the prevention of Alzheimer's disease (AD) but the mechanisms of this potential disease modifying action are unclear. We investigated the effects of once-weekly exenatide (EQW) on AD associated proteomic clusters.

METHODS

The Exenatide Study of Cardiovascular Event Lowering study compared the cardiovascular effects of EQW 2 mg with placebo in 13,752 people with type 2 diabetes mellitus. 4,979 proteins were measured (Somascan V0.4) on baseline and 1-year plasma samples of 3,973 participants. C-reactive protein (CRP), ficolin-2 (FCN2), plasminogen activator inhibitor 1 (PAI-1), soluble vascular cell adhesion protein 1 (sVCAM1) and 4 protein clusters were tested in multivariable mixed models.

RESULTS

EQW affected FCN2 (Cohen's d -0.019), PAI-1 (Cohen's d -0.033), sVCAM-1 (Cohen's d 0.035) and a cytokine-cytokine cluster (Cohen's d 0.037) significantly compared with placebo. These effects were sustained in individuals over the age of 65 but not in those under 65.

CONCLUSIONS

EQW treatment was associated with significant change in inflammatory proteins associated with AD.

TRIAL REGISTRATION

EXSCEL is registered on ClinicalTrials.gov: NCT01144338 on 10th of June 2010.

Penfluridol inhibits melanoma growth and metastasis through enhancing von Hippel‒Lindau tumor suppressor-mediated cancerous inhibitor of protein phosphatase 2A (CIP2A) degradation

Melanoma's high metastatic potential, especially to the brain, poses significant challenges to patient survival. The blood‒brain barrier (BBB) is a major obstacle to the effective treatment of melanoma brain metastases. We screened antipsychotic drugs capable of crossing the BBB and identified penfluridol (PF) as the most active candidate. PF reduced melanoma cell viability and induced apoptosis. In animal models, PF effectively inhibited melanoma growth and metastasis to the lung and brain. Using immunoprecipitation combined with high-resolution mass spectrometry, and other techniques such as drug affinity responsive target stability, we identified CIP2A as a direct binding protein of PF. CIP2A is highly expressed in melanoma and its metastases, and is linked to poor prognosis. PF can restore Protein Phosphatase 2A activity by promoting CIP2A degradation, thereby inhibiting several key oncogenic pathways, including AKT and c-Myc. Additionally, von Hippel‒Lindau (VHL) is the endogenous E3 ligase for CIP2A, and PF enhances the interaction between VHL and CIP2A, promoting the ubiquitin‒proteasome degradation of CIP2A, thereby inhibiting melanoma growth and metastasis. Overall, this study not only suggests PF's potential in treating melanoma and its brain metastases but also highlights CIP2A degradation as a therapeutic strategy for melanoma.

The genetic architecture of biological age in nine human organ systems

Investigating the genetic underpinnings of human aging is essential for unraveling the etiology of and developing actionable therapies for chronic diseases. Here, we characterize the genetic architecture of the biological age gap (BAG; the difference between machine learning-predicted age and chronological age) across nine human organ systems in 377,028 participants of European ancestry from the UK Biobank. The BAGs were computed using cross-validated support vector machines, incorporating imaging, physical traits and physiological measures. We identify 393 genomic loci-BAG pairs (P < 5 × 10-8) linked to the brain, eye, cardiovascular, hepatic, immune, metabolic, musculoskeletal, pulmonary and renal systems. Genetic variants associated with the nine BAGs are predominantly specific to the respective organ system (organ specificity) while exerting pleiotropic links with other organ systems (interorgan cross-talk). We find that genetic correlation between the nine BAGs mirrors their phenotypic correlation. Further, a multiorgan causal network established from two-sample Mendelian randomization and latent causal variance models revealed potential causality between chronic diseases (for example, Alzheimer's disease and diabetes), modifiable lifestyle factors (for example, sleep duration and body weight) and multiple BAGs. Our results illustrate the potential for improving human organ health via a multiorgan network, including lifestyle interventions and drug repurposing strategies.

Recent advances in Alzheimer's disease: Mechanisms, clinical trials and new drug development strategies

Alzheimer's disease (AD) stands as the predominant form of dementia, presenting significant and escalating global challenges. Its etiology is intricate and diverse, stemming from a combination of factors such as aging, genetics, and environment. Our current understanding of AD pathologies involves various hypotheses, such as the cholinergic, amyloid, tau protein, inflammatory, oxidative stress, metal ion, glutamate excitotoxicity, microbiota-gut-brain axis, and abnormal autophagy. Nonetheless, unraveling the interplay among these pathological aspects and pinpointing the primary initiators of AD require further elucidation and validation. In the past decades, most clinical drugs have been discontinued due to limited effectiveness or adverse effects. Presently, available drugs primarily offer symptomatic relief and often accompanied by undesirable side effects. However, recent approvals of aducanumab (1) and lecanemab (2) by the Food and Drug Administration (FDA) present the potential in disrease-modifying effects. Nevertheless, the long-term efficacy and safety of these drugs need further validation. Consequently, the quest for safer and more effective AD drugs persists as a formidable and pressing task. This review discusses the current understanding of AD pathogenesis, advances in diagnostic biomarkers, the latest updates of clinical trials, and emerging technologies for AD drug development. We highlight recent progress in the discovery of selective inhibitors, dual-target inhibitors, allosteric modulators, covalent inhibitors, proteolysis-targeting chimeras (PROTACs), and protein-protein interaction (PPI) modulators. Our goal is to provide insights into the prospective development and clinical application of novel AD drugs.

Repurposing Anidulafungin for Alzheimer's Disease via Fragment-Based Drug Discovery

The misfolding and aggregation of beta-amyloid (Aβ) peptides have been implicated as key pathogenic events in the early stages of Alzheimer's disease (AD). Inhibiting Aβ aggregation represents a potential disease-modifying therapeutic approach to AD treatment. Previous studies have identified various molecules that inhibit Aβ aggregation, some of which share common chemical substructures (fragments) that may be key to their inhibitory activity. Employing fragment-based drug discovery (FBDD) methods may facilitate the identification of these fragments, which can subsequently be used to screen new inhibitors and provide leads for further drug development. In this study, we used an in silico FBDD approach to identify 17 fragment clusters that are significantly enriched among Aβ aggregation inhibitors. These fragments were then used to screen anti-infective agents, a promising drug class for repurposing against amyloid aggregation. This screening process identified 16 anti-infective drugs, 5 of which were chosen for further investigation. Among the 5 candidates, anidulafungin, an antifungal compound, showed high efficacy in inhibiting Aβ aggregation in vitro. Kinetic analysis revealed that anidulafungin selectively blocks the primary nucleation step of Aβ aggregation, substantially delaying Aβ fibril formation. Cell viability assays demonstrated that anidulafungin can reduce the toxicity of oligomeric Aβ on BV2 microglia cells. Molecular docking simulations predicted that anidulafungin interacted with various Aβ species, including monomers, oligomers, and fibrils, potentially explaining its activity against Aβ aggregation and toxicity. This study suggests that anidulafungin is a potential drug to be repurposed for AD, and FBDD is a promising approach for discovering drugs to combat Aβ aggregation.

Quantitative 3D histochemistry reveals region-specific amyloid-β reduction by the antidiabetic drug netoglitazone

A hallmark of Alzheimer's disease (AD) is the extracellular aggregation of toxic amyloid-beta (Aβ) peptides in form of plaques. Here, we identify netoglitazone, an antidiabetic compound previously tested in humans, as an Aβ aggregation antagonist. Netoglitazone improved cognition and reduced microglia activity in a mouse model of AD. Using quantitative whole-brain three-dimensional histology (Q3D), we precisely identified brain regions where netoglitazone reduced the number and size of Aβ plaques. We demonstrate the utility of Q3D in preclinical drug evaluation for AD by providing a high-resolution brain-wide view of drug efficacy. Applying Q3D has the potential to improve pre-clinical drug evaluation by providing information that can help identify mechanisms leading to brain region-specific drug efficacy.

Treating cryptosporidiosis: A review on drug discovery strategies

Despite several decades of research on therapeutics, cryptosporidiosis remains a major concern for human and animal health. Even though this field of research to assess antiparasitic drug activity is highly active and competitive, only one molecule is authorized to be used in humans. However, this molecule was not efficacious in immunocompromised people and the lack of animal therapeutics remains a cause of concern. Indeed, the therapeutic arsenal needs to be developed for both humans and animals. Our work aims to clarify research strategies that historically were diffuse and poorly directed. This paper reviews in vitro and in vivo methodologies to assess the activity of future therapeutic compounds by screening drug libraries or through drug repurposing. It focuses on High Throughput Screening methodologies (HTS) and discusses the lack of knowledge of target mechanisms. In addition, an overview of several specific metabolic pathways and enzymatic activities used as targets against Cryptosporidium is provided. These metabolic processes include glycolytic pathways, fatty acid production, kinase activities, tRNA elaboration, nucleotide synthesis, gene expression and mRNA maturation. As a conclusion, we highlight emerging future strategies for screening natural compounds and assessing drug resistance issues.

Pharmacoepidemiology evaluation of bumetanide as a potential candidate for drug repurposing for Alzheimer's disease

INTRODUCTION

Bumetanide, a loop diuretic, was identified as a candidate drug for repurposing for Alzheimer's disease (AD) based on its effects on transcriptomic apolipoprotein E signatures. Cross-sectional analyses of electronic health records suggest that bumetanide is associated with decreased prevalence of AD; however, temporality between bumetanide exposure and AD development has not been established.

METHODS

We evaluated Medicare claims data using Cox proportional hazards regression to evaluate the association between time-dependent use of bumetanide and time to first AD diagnosis while controlling for patient characteristics. Multiple sensitivity analyses were conducted to test the robustness of the findings.

RESULTS

We sampled 833,561 Medicare beneficiaries, 60.8% female, with mean (standard deviation) age of 70.4 (12). Bumetanide use was not significantly associated with AD risk (hazard ratio 1.05; 95% confidence interval, 0.99-1.10).

DISCUSSION

Using a nationwide dataset and a retrospective cohort study design, we were not able to identify a time-dependent effect of bumetanide lowering AD risk.

HIGHLIGHTS

Bumetanide was identified as a candidate for repurposing for Alzheimer's disease (AD). We evaluated the association between bumetanide use and risk of AD. We used Medicare data and accounted for duration of bumetanide use. Bumetanide use was not significantly associated with risk of AD.

CKG-IMC: An inductive matrix completion method enhanced by CKG and GNN for Alzheimer's disease compound-protein interactions prediction

Alzheimer's disease (AD) is one of the most prevalent chronic neurodegenerative disorders globally, with a rapidly growing population of AD patients and currently no effective therapeutic interventions available. Consequently, the development of therapeutic anti-AD drugs and the identification of AD targets represent one of the most urgent tasks. In this study, in addition to considering known drugs and targets, we explore compound-protein interactions (CPIs) between compounds and proteins relevant to AD. We propose a deep learning model called CKG-IMC to predict Alzheimer's disease compound-protein interaction relationships. CKG-IMC comprises three modules: a collaborative knowledge graph (CKG), a principal neighborhood aggregation graph neural network (PNA), and an inductive matrix completion (IMC). The collaborative knowledge graph is used to learn semantic associations between entities, PNA is employed to extract structural features of the relationship network, and IMC is utilized for CPIs prediction. Compared with a total of 16 baseline models based on similarities, knowledge graphs, and graph neural networks, our model achieves state-of-the-art performance in experiments of 10-fold cross-validation and independent test. Furthermore, we use CKG-IMC to predict compounds interacting with two confirmed AD targets, 42-amino-acid β-amyloid (Aβ42) protein and microtubule-associated protein tau (tau protein), as well as proteins interacting with five FDA-approved anti-AD drugs. The results indicate that the majority of predictions are supported by literature, and molecular docking experiments demonstrate a strong affinity between the predicted compounds and targets.

Current View on PPAR-α and Its Relation to Neurosteroids in Alzheimer's Disease and Other Neuropsychiatric Disorders: Promising Targets in a Therapeutic Strategy

Peroxisome proliferator-activated receptors (PPARs) may play an important role in the pathomechanism/pathogenesis of Alzheimer's disease (AD) and several other neurological/neuropsychiatric disorders. AD leads to progressive alterations in the redox state, ion homeostasis, lipids, and protein metabolism. Significant alterations in molecular processes and the functioning of several signaling pathways result in the degeneration and death of synapses and neuronal cells, leading to the most severe dementia. Peroxisome proliferator-activated receptor alpha (PPAR-α) is among the processes affected by AD; it regulates the transcription of genes related to the metabolism of cholesterol, fatty acids, other lipids and neurotransmission, mitochondria biogenesis, and function. PPAR-α is involved in the cholesterol transport to mitochondria, the substrate for neurosteroid biosynthesis. PPAR-α-coding enzymes, such as sulfotransferases, which are responsible for neurosteroid sulfation. The relation between PPAR-α and cholesterol/neurosteroids may have a significant impact on the course and progression of neurodegeneration/neuroprotection processes. Unfortunately, despite many years of intensive studies, the pathogenesis of AD is unknown and therapy for AD and other neurodegenerative diseases is symptomatic, presenting a significant goal and challenge today. This review presents recent achievements in therapeutic approaches for AD, which are targeting PPAR-α and its relation to cholesterol and neurosteroids in AD and neuropsychiatric disorders.

Basic, Translational, and Clinical Research on Dementia

The global impact of dementia is an increasing area of concern and, according to the Alzheimer's Disease International (ADI) World Alzheimer Report 2021, up to 90% of dementia patients in low- and middle-income countries are not diagnosed [...].

Protocol for a double-blind placebo-controlled randomised controlled trial assessing the impact of oral semaglutide in amyloid positivity (ISAP) in community dwelling UK adults

INTRODUCTION

Glucagon-like peptide-1 receptor agonists (GLP-1 RAs), currently marketed for type 2 diabetes and obesity, may offer novel mechanisms to delay or prevent neurotoxicity associated with Alzheimer's disease (AD). The impact of semaglutide in amyloid positivity (ISAP) trial is investigating whether the GLP-1 RA semaglutide reduces accumulation in the brain of cortical tau protein and neuroinflammation in individuals with preclinical/prodromal AD.

METHODS AND ANALYSIS

ISAP is an investigator-led, randomised, double-blind, superiority trial of oral semaglutide compared with placebo. Up to 88 individuals aged ≥55 years with brain amyloid positivity as assessed by positron emission tomography (PET) or cerebrospinal fluid, and no or mild cognitive impairment, will be randomised. People with the low-affinity binding variant of the rs6971 allele of the Translocator Protein 18 kDa (TSPO) gene, which can interfere with interpreting TSPO PET scans (a measure of neuroinflammation), will be excluded.At baseline, participants undergo tau, TSPO PET and MRI scanning, and provide data on physical activity and cognition. Eligible individuals are randomised in a 1:1 ratio to once-daily oral semaglutide or placebo, starting at 3 mg and up-titrating to 14 mg over 8 weeks. They will attend safety visits and provide blood samples to measure AD biomarkers at weeks 4, 8, 26 and 39. All cognitive assessments are repeated at week 26. The last study visit will be at week 52, when all baseline measurements will be repeated. The primary end point is the 1-year change in tau PET signal.

ETHICS AND DISSEMINATION

The study was approved by the West Midlands-Edgbaston Research Ethics Committee (22/WM/0013). The results of the study will be disseminated through scientific presentations and peer-reviewed publications.

TRIAL REGISTRATION NUMBER

ISRCTN71283871.

Tackling neurodegeneration in vitro with omics: a path towards new targets and drugs

Drug discovery is a generally inefficient and capital-intensive process. For neurodegenerative diseases (NDDs), the development of novel therapeutics is particularly urgent considering the long list of late-stage drug candidate failures. Although our knowledge on the pathogenic mechanisms driving neurodegeneration is growing, additional efforts are required to achieve a better and ultimately complete understanding of the pathophysiological underpinnings of NDDs. Beyond the etiology of NDDs being heterogeneous and multifactorial, this process is further complicated by the fact that current experimental models only partially recapitulate the major phenotypes observed in humans. In such a scenario, multi-omic approaches have the potential to accelerate the identification of new or repurposed drugs against a multitude of the underlying mechanisms driving NDDs. One major advantage for the implementation of multi-omic approaches in the drug discovery process is that these overarching tools are able to disentangle disease states and model perturbations through the comprehensive characterization of distinct molecular layers (i.e., genome, transcriptome, proteome) up to a single-cell resolution. Because of recent advances increasing their affordability and scalability, the use of omics technologies to drive drug discovery is nascent, but rapidly expanding in the neuroscience field. Combined with increasingly advanced in vitro models, which particularly benefited from the introduction of human iPSCs, multi-omics are shaping a new paradigm in drug discovery for NDDs, from disease characterization to therapeutics prediction and experimental screening. In this review, we discuss examples, main advantages and open challenges in the use of multi-omic approaches for the in vitro discovery of targets and therapies against NDDs.

The Genetic Architecture of Biological Age in Nine Human Organ Systems

Understanding the genetic basis of biological aging in multi-organ systems is vital for elucidating age-related disease mechanisms and identifying therapeutic interventions. This study characterized the genetic architecture of the biological age gap (BAG) across nine human organ systems in 377,028 individuals of European ancestry from the UK Biobank. We discovered 393 genomic loci-BAG pairs (P-value<5×10-8) linked to the brain, eye, cardiovascular, hepatic, immune, metabolic, musculoskeletal, pulmonary, and renal systems. We observed BAG-organ specificity and inter-organ connections. Genetic variants associated with the nine BAGs are predominantly specific to the respective organ system while exerting pleiotropic effects on traits linked to multiple organ systems. A gene-drug-disease network confirmed the involvement of the metabolic BAG-associated genes in drugs targeting various metabolic disorders. Genetic correlation analyses supported Cheverud's Conjecture1 - the genetic correlation between BAGs mirrors their phenotypic correlation. A causal network revealed potential causal effects linking chronic diseases (e.g., Alzheimer's disease), body weight, and sleep duration to the BAG of multiple organ systems. Our findings shed light on promising therapeutic interventions to enhance human organ health within a complex multi-organ network, including lifestyle modifications and potential drug repositioning strategies for treating chronic diseases. All results are publicly available at https://labs-laboratory.com/medicine.

Optimising the use of electronic medical records for large scale research in psychiatry

The explosion and abundance of digital data could facilitate large-scale research for psychiatry and mental health. Research using so-called "real world data"-such as electronic medical/health records-can be resource-efficient, facilitate rapid hypothesis generation and testing, complement existing evidence (e.g. from trials and evidence-synthesis) and may enable a route to translate evidence into clinically effective, outcomes-driven care for patient populations that may be under-represented. However, the interpretation and processing of real-world data sources is complex because the clinically important 'signal' is often contained in both structured and unstructured (narrative or "free-text") data. Techniques for extracting meaningful information (signal) from unstructured text exist and have advanced the re-use of routinely collected clinical data, but these techniques require cautious evaluation. In this paper, we survey the opportunities, risks and progress made in the use of electronic medical record (real-world) data for psychiatric research.

Effects of antidiabetic agents on platelet characteristics with implications in Alzheimer's disease: Mendelian randomization and colocalization study

Background

Observational studies have found a potential link between the use of thiazolidinediones (TZDs) and a lower risk of Alzheimer's disease (AD) development. Platelets were the great source of amyloid-β (Aβ) and involved in the development of AD. This study aimed to assess the correlation between antidiabetic agents and platelet characteristics, hoping to provide a potential mechanism of TZDs neuroprotection in AD.

Method

Drug-targeted Mendelian randomization (MR) was performed to systematically illustrate the long-term effects of antidiabetic agents on platelet characteristics. Four antidiabetic agent targets were considered. Positive control analysis for type 2 diabetes (T2D) was conducted to validate the selection of instrumental variables (IVs). Colocalization analysis was used to further strengthen the robustness of the results.

Result

Positive control analysis showed an association of four antidiabetic agents with lower risk of T2D, which was consistent with their mechanisms of action and previous evidence from clinical trials. Genetically proxied TZDs were associated with lower platelet count (β[IRNT] = -0.410 [95 % CI -0.533 to -0.288], P = 5.32E-11) and a lower plateletcrit (β[IRNT] = -0.344 [95 % CI -0.481 to -0.206], P = 1.04E-6). Colocalization suggested the posterior probability of hypothesis 4 (PPH4) > 0.8, which further strengthened the MR results.

Conclusion

Genetically proxied TZDs were causally associated with lower platelet characteristics, particularly platelet count and plateletcrit, providing insight into the involvement of platelet-related pathways in the neuroprotection of TZDs against AD. Future studies are warranted to reveal the underlying molecular mechanism of TZDs' neuroprotective effects through platelet pathways.

Artificial intelligence and open science in discovery of disease-modifying medicines for Alzheimer's disease

The high failure rate of clinical trials in Alzheimer's disease (AD) and AD-related dementia (ADRD) is due to a lack of understanding of the pathophysiology of disease, and this deficit may be addressed by applying artificial intelligence (AI) to "big data" to rapidly and effectively expand therapeutic development efforts. Recent accelerations in computing power and availability of big data, including electronic health records and multi-omics profiles, have converged to provide opportunities for scientific discovery and treatment development. Here, we review the potential utility of applying AI approaches to big data for discovery of disease-modifying medicines for AD/ADRD. We illustrate how AI tools can be applied to the AD/ADRD drug development pipeline through collaborative efforts among neurologists, gerontologists, geneticists, pharmacologists, medicinal chemists, and computational scientists. AI and open data science expedite drug discovery and development of disease-modifying therapeutics for AD/ADRD and other neurodegenerative diseases.

Microbiota-gut-brain axis and its therapeutic applications in neurodegenerative diseases

The human gastrointestinal tract is populated with a diverse microbial community. The vast genetic and metabolic potential of the gut microbiome underpins its ubiquity in nearly every aspect of human biology, including health maintenance, development, aging, and disease. The advent of new sequencing technologies and culture-independent methods has allowed researchers to move beyond correlative studies toward mechanistic explorations to shed light on microbiome-host interactions. Evidence has unveiled the bidirectional communication between the gut microbiome and the central nervous system, referred to as the "microbiota-gut-brain axis". The microbiota-gut-brain axis represents an important regulator of glial functions, making it an actionable target to ameliorate the development and progression of neurodegenerative diseases. In this review, we discuss the mechanisms of the microbiota-gut-brain axis in neurodegenerative diseases. As the gut microbiome provides essential cues to microglia, astrocytes, and oligodendrocytes, we examine the communications between gut microbiota and these glial cells during healthy states and neurodegenerative diseases. Subsequently, we discuss the mechanisms of the microbiota-gut-brain axis in neurodegenerative diseases using a metabolite-centric approach, while also examining the role of gut microbiota-related neurotransmitters and gut hormones. Next, we examine the potential of targeting the intestinal barrier, blood-brain barrier, meninges, and peripheral immune system to counteract glial dysfunction in neurodegeneration. Finally, we conclude by assessing the pre-clinical and clinical evidence of probiotics, prebiotics, and fecal microbiota transplantation in neurodegenerative diseases. A thorough comprehension of the microbiota-gut-brain axis will foster the development of effective therapeutic interventions for the management of neurodegenerative diseases.

Synthesis of a Rivastigmine and Insulin Combinational Mucoadhesive Nanoparticle for Intranasal Delivery

Efficient drug delivery remains a critical challenge for treating neurodegenerative diseases, such as Alzheimer's disease (AD). Using innovative nanomaterials, delivering current medications like acetylcholinesterase inhibitors to the brain through the intranasal route is a promising strategy for managing AD. Here, we developed a unique combinational drug delivery system based on N,N,N-trimethyl chitosan nanoparticles (NPs). These NPs encapsulate rivastigmine, the most potent acetylcholinesterase inhibitor, along with insulin, a complementary therapeutic agent. The spherical NPs exhibited a zeta potential of 17.6 mV, a size of 187.00 nm, and a polydispersity index (PDI) of 0.29. Our findings demonstrate significantly improved drug transport efficiency through sheep nasal mucosa using the NPs compared to drug solutions. The NPs exhibited transport efficiencies of 73.3% for rivastigmine and 96.9% for insulin, surpassing the efficiencies of the drug solutions, which showed transport efficiencies of 52% for rivastigmine and 21% for insulin ex vivo. These results highlight the potential of a new drug delivery system as a promising approach for enhancing nasal transport efficiency. These combinational mucoadhesive NPs offer a novel strategy for the simultaneous cerebral delivery of rivastigmine and insulin, which could prove helpful in developing effective treatments of AD and other neurodegenerative conditions.

Exploitation of Autophagy Inducers in the Management of Dementia: A Systematic Review

The social burden of dementia is remarkable since it affects some 57.4 million people all over the world. Impairment of autophagy in age-related diseases, such as dementia, deserves deep investigation for the detection of novel disease-modifying approaches. Several drugs belonging to different classes were suggested to be effective in managing Alzheimer's disease (AD) by means of autophagy induction. Useful autophagy inducers in AD should be endowed with a direct, measurable effect on autophagy, have a safe tolerability profile, and have the capability to cross the blood-brain barrier, at least with poor penetration. According to the PRISMA 2020 recommendations, we propose here a systematic review to appraise the measurable effectiveness of autophagy inducers in the improvement of cognitive decline and neuropsychiatric symptoms in clinical trials and retrospective studies. The systematic search retrieved 3067 records, 10 of which met the eligibility criteria. The outcomes most influenced by the treatment were cognition and executive functioning, pointing at a role for metformin, resveratrol, masitinib and TPI-287, with an overall tolerable safety profile. Differences in sample power, intervention, patients enrolled, assessment, and measure of outcomes prevents generalization of results. Moreover, the domain of behavioral symptoms was found to be less investigated, thus prompting new prospective studies with homogeneous design. PROSPERO registration: CRD42023393456.

Reconsidering repurposing: long-term metformin treatment impairs cognition in Alzheimer's model mice

Metformin, a primary anti-diabetic medication, has been anticipated to provide benefits for Alzheimer's disease (AD), also known as "type 3 diabetes". Nevertheless, some studies have demonstrated that metformin may trigger AD pathology and even elevate AD risk in humans. Despite this, limited research has elucidated the behavioral outcomes of metformin treatment, which would hold significant translational value. Thus, we aimed to perform thorough behavioral research on the prolonged administration of metformin to mice: We administered metformin (300 mg/kg/day) to transgenic 3xTg-AD and non-transgenic (NT) C57BL/6 mice over 1 and 2 years, respectively, and evaluated their behaviors across multiple domains via touchscreen operant chambers, including motivation, attention, memory, visual discrimination, and cognitive flexibility. We found metformin enhanced attention, inhibitory control, and associative learning in younger NT mice (≤16 months). However, chronic treatment led to impairments in memory retention and discrimination learning at older age. Furthermore, metformin caused learning and memory impairment and increased levels of AMPKα1-subunit, β-amyloid oligomers, plaques, phosphorylated tau, and GSK3β expression in AD mice. No changes in potential confounding factors on cognition, including levels of motivation, locomotion, appetite, body weight, blood glucose, and serum vitamin B12, were observed in metformin-treated AD mice. We also identified an enhanced amyloidogenic pathway in db/db mice, as well as in Neuro2a-APP695 cells and a decrease in synaptic markers, such as PSD-95 and synaptophysin in primary neurons, upon metformin treatment. Our findings collectively suggest that the repurposing of metformin should be carefully reconsidered when this drug is used for individuals with AD.

Paradigms and Success Stories of Natural Products in Drug Discovery Against Neurodegenerative Disorders (NDDs)

Neurodegenerative disorders (NDDs) are multifaceted complex disorders that have put a great health and economic burden around the globe nowadays. The multi-factorial nature of NDDs has presented a great challenge in drug discovery and continuous efforts are in progress in search of suitable therapeutic candidates. Nature has a great wealth of active principles in its lap that has cured the human population since ancient times. Natural products have revealed several benefits over conventional synthetic medications and scientists have shifted their vision towards exploring the therapeutic potentials of natural products in the past few years. The structural mimicking of natural compounds to endogenous ligands has presented them as a potential therapeutic candidate to prevent the development of NDDs. In the presented review, authors have summarized demographical facts about various NDDs including Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD) and various types of sclerosis in the brain. The significant findings of new active principles of natural origin along with their therapeutic potentials on NDDs have been included. Also, a description of clinical trials and patents on natural products has been enlisted in this compilation. Although natural products have shown promising success in drug discovery against NDDs, still their use is associated with several ethical issues which need to be solved in the upcoming time.

Sildenafil Reverses the Neuropathological Alzheimer's Disease Phenotype in Cholinergic-Like Neurons Carrying the Presenilin 1 E280A Mutation

Background

Familial Alzheimer's disease (FAD) presenilin 1 E280A (PSEN 1 E280A) is characterized by functional impairment and the death of cholinergic neurons as a consequence of amyloid-β (Aβ) accumulation and abnormal phosphorylation of the tau protein. Currently, there are no available therapies that can cure FAD. Therefore, new therapies are urgently needed for treating this disease.

Objective

To assess the effect of sildenafil (SIL) on cholinergic-like neurons (ChLNs) harboring the PSEN 1 E280A mutation.

Methods

Wild-type (WT) and PSEN 1 E280A ChLNs were cultured in the presence of SIL (25μM) for 24 h. Afterward, proteinopathy, cell signaling, and apoptosis markers were evaluated via flow cytometry and fluorescence microscopy.

Results

We found that SIL was innocuous toward WT PSEN 1 ChLNs but reduced the accumulation of intracellular Aβ fragments by 87%, decreased the non-physiological phosphorylation of the protein tau at residue Ser202/Thr205 by 35%, reduced the phosphorylation of the proapoptotic transcription factor c-JUN at residue Ser63/Ser73 by 63%, decreased oxidized DJ-1 at Cys106-SO3 by 32%, and downregulated transcription factor TP53 (tumor protein p53), BH-3-only protein PUMA (p53 upregulated modulator of apoptosis), and cleaved caspase 3 (CC3) expression by 20%, 32%, and 22%, respectively, compared with untreated mutant ChLNs. Interestingly, SIL also ameliorated the dysregulation of acetylcholine-induced calcium ion (Ca2+) influx in PSEN 1 E280A ChLNs.

Conclusions

Although SIL showed no antioxidant capacity in the oxygen radical absorbance capacity and ferric ion reducing antioxidant power assays, it might function as an anti-amyloid and antiapoptotic agent and functional neuronal enhancer in PSEN 1 E280A ChLNs. Therefore, the SIL has therapeutic potential for treating FAD.

Drug Repositioning: A Monetary Stratagem to Discover a New Application of Drugs

Drug repurposing, also referred to as drug repositioning or drug reprofiling, is a scientific approach to the detection of any new application for an already approved or investigational drug. It is a useful policy for the invention and development of new pharmacological or therapeutic applications of different drugs. The strategy has been known to offer numerous advantages over developing a completely novel drug for certain problems. Drug repurposing has numerous methodologies that can be categorized as target-oriented, drug-oriented, and problem-oriented. The choice of the methodology of drug repurposing relies on the accessible information about the drug molecule and like pharmacokinetic, pharmacological, physicochemical, and toxicological profile of the drug. In addition, molecular docking studies and other computer-aided methods have been known to show application in drug repurposing. The variation in dosage for original target diseases and novel diseases presents a challenge for researchers of drug repurposing in present times. The present review critically discusses the drugs repurposed for cancer, covid-19, Alzheimer's, and other diseases, strategies, and challenges of drug repurposing. Moreover, regulatory perspectives related to different countries like the United States (US), Europe, and India have been delineated in the present review.

Drug Repurposing for Effective Alzheimer's Disease Medicines: Existing Methods and Novel Pharmacoepidemiological Approaches

Drug repurposing is a methodology used to identify new clinical indications for existing drugs developed for other indications and has been successfully applied in the treatment of numerous conditions. Alzheimer's disease (AD) may be particularly well-suited to the application of drug repurposing methods given the absence of effective therapies and abundance of multi-omic data that has been generated in AD patients recently that may facilitate discovery of candidate AD drugs. A recent focus of drug repurposing has been in the application of pharmacoepidemiologic approaches to drug evaluation. Here, real-world clinical datasets with large numbers of patients are leveraged to establish observational efficacy of candidate drugs for further evaluation in disease models and clinical trials. In this review, we provide a selected overview of methods for drug repurposing, including signature matching, network analysis, molecular docking, phenotypic screening, semantic network, and pharmacoepidemiological analyses. Numerous methods have also been applied specifically to AD with the aim of nominating novel drug candidates for evaluation. These approaches, however, are prone to numerous limitations and potential biases that we have sought to address in the Drug Repurposing for Effective Alzheimer's Medicines (DREAM) study, a multi-step framework for selection and validation of potential drug candidates that has demonstrated the promise of STAT3 inhibitors and re-evaluated evidence for other drug candidates, such as phosphodiesterase inhibitors. Taken together, drug repurposing holds significant promise for development of novel AD therapeutics, particularly as the pace of data generation and development of analytical methods continue to accelerate.

Mapping the human brain proteome: opportunities, challenges, and clinical potential

INTRODUCTION

Due to the segmented functions and complexity of the human brain, the characterization of molecular profiles within specific areas such as brain structures and biofluids is essential to unveil the molecular basis for structure specialization as well as the molecular imbalance associated with neurodegenerative and psychiatric diseases.

AREAS COVERED

Much of our knowledge about brain functionality derives from neurophysiological, anatomical, and transcriptomic approaches. More recently, laser capture and imaging proteomics, technological and computational developments in LC-MS/MS, as well as antibody/aptamer-based platforms have allowed the generation of novel cellular, spatial, and posttranslational dimensions as well as innovative facets in biomarker validation and druggable target identification.

EXPERT OPINION

Proteomics is a powerful toolbox to functionally characterize, quantify, and localize the extensive protein catalog of the human brain across physiological and pathological states. Brain function depends on multi-dimensional protein homeostasis, and its elucidation will help us to characterize biological pathways that are essential to properly maintain cognitive functions. In addition, comprehensive human brain pathological proteomes may be the basis in computational drug-repositioning methods as a strategy for unveiling potential new therapies in neurodegenerative and psychiatric disorders.

The Potential of a Stratified Approach to Drug Repurposing in Alzheimer's Disease

Alzheimer's disease (AD) is a complex neurodegenerative condition that is characterized by the build-up of amyloid-beta plaques and neurofibrillary tangles. While multiple theories explaining the aetiology of the disease have been suggested, the underlying cause of the disease is still unknown. Despite this, several modifiable and non-modifiable factors that increase the risk of developing AD have been identified. To date, only eight AD drugs have ever gained regulatory approval, including six symptomatic and two disease-modifying drugs. However, not all are available in all countries and high costs associated with new disease-modifying biologics prevent large proportions of the patient population from accessing them. With the current patient population expected to triple by 2050, it is imperative that new, effective, and affordable drugs become available to patients. Traditional drug development strategies have a 99% failure rate in AD, which is far higher than in other disease areas. Even when a drug does reach the market, additional barriers such as high cost and lack of accessibility prevent patients from benefiting from them. In this review, we discuss how a stratified medicine drug repurposing approach may address some of the limitations and barriers that traditional strategies face in relation to drug development in AD. We believe that novel, stratified drug repurposing studies may expedite the discovery of alternative, effective, and more affordable treatment options for a rapidly expanding patient population in comparison with traditional drug development methods.

Mesenchymal stem cells-derived exosomes: novel carriers for nanoparticle to combat cancer

BACKGROUND

The advancement in novel cancer therapeutics brought a platform combining the properties of exosomes with nanoparticles to precision medicine. The novel therapeutic approach aim is cancer-targeted therapy. Exosomes from mesenchymal stem cells (MSCs-Exo) exhibit unique properties in cancer therapies, which makes them an ideal tool for delivering therapeutic agents into tumor cells. The key role of natural MSCs-Exo is controversial in cancer therapy; however, they can be engineered at their surface or cargo to serve as a smart drug delivery system for cancer-targeted therapy. In the last few years, researchers harnessed nanotechnology to enforce MSCs-Exo for cancer management including, tumor cell tracking, imaging, and tumor cell killing. Different nanoparticles such as gold nanoparticles have particularly been incorporated into MSCs-Exo, which showed an efficient accumulation at the site of tumor with improved anticancer impact. These findings indicate that a hybrid of exosomes-nanoparticles may serve as combination therapy for the effective removal of cancers.

SHORT CONCLUSION

Although exhibiting impressive potential, the use of nanoparticle-loaded MSCs-Exo as a drug-delivery tool has been troubled by some challenges, therefore, translation to clinic prerequisites further scrutiny. In this review, we focus on nanoparticle-loaded MSCs-Exo as a new cancer therapy and discuss engineered MSC-Exo for target therapy.

Fe65-engineered neuronal exosomes encapsulating corynoxine-B ameliorate cognition and pathology of Alzheimer's disease

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by the predominant impairment of neurons in the hippocampus and the formation of amyloid plaques, hyperphosphorylated tau protein, and neurofibrillary tangles in the brain. The overexpression of amyloid-β precursor protein (APP) in an AD brain results in the binding of APP intracellular domain (AICD) to Fe65 protein via the C-terminal Fe65-PTB2 interaction, which then triggers the secretion of amyloid-β and the consequent pathogenesis of AD. Apparently, targeting the interaction between APP and Fe65 can offer a promising therapeutic approach for AD. Recently, exosome, a type of extracellular vesicle with diameter around 30-200 nm, has gained much attention as a potential delivery tool for brain diseases, including AD, due to their ability to cross the blood-brain barrier, their efficient uptake by autologous cells, and their ability to be surface-modified with target-specific receptor ligands. Here, the engineering of hippocampus neuron cell-derived exosomes to overexpress Fe65, enabled the development of a novel exosome-based targeted drug delivery system, which carried Corynoxine-B (Cory-B, an autophagy inducer) to the APP overexpressed-neuron cells in the brain of AD mice. The Fe65-engineered HT22 hippocampus neuron cell-derived exosomes (Fe65-EXO) loaded with Cory-B (Fe65-EXO-Cory-B) hijacked the signaling and blocked the natural interaction between Fe65 and APP, enabling APP-targeted delivery of Cory-B. Notably, Fe65-EXO-Cory-B induced autophagy in APP-expressing neuronal cells, leading to amelioration of the cognitive decline and pathogenesis in AD mice, demonstrating the potential of Fe65-EXO-Cory-B as an effective therapeutic intervention for AD.

Gibson T, McCain S, Stone BC, Gill T, Pickett BE. Pathway2Targets: an open-source pathway-based approach to repurpose therapeutic drugs and prioritize human targets

Background

Recent efforts to repurpose existing drugs to different indications have been accompanied by a number of computational methods, which incorporate protein-protein interaction networks and signaling pathways, to aid with prioritizing existing targets and/or drugs. However, many of these existing methods are focused on integrating additional data that are only available for a small subset of diseases or conditions.

Methods

We have designed and implemented a new R-based open-source target prioritization and repurposing method that integrates both canonical intracellular signaling information from five public pathway databases and target information from public sources including OpenTargets.org. The Pathway2Targets algorithm takes a list of significant pathways as input, then retrieves and integrates public data for all targets within those pathways for a given condition. It also incorporates a weighting scheme that is customizable by the user to support a variety of use cases including target prioritization, drug repurposing, and identifying novel targets that are biologically relevant for a different indication.

Results

As a proof of concept, we applied this algorithm to a public colorectal cancer RNA-sequencing dataset with 144 case and control samples. Our analysis identified 430 targets and ~700 unique drugs based on differential gene expression and signaling pathway enrichment. We found that our highest-ranked predicted targets were significantly enriched in targets with FDA-approved therapeutics for colorectal cancer (p-value < 0.025) that included EGFR, VEGFA, and PTGS2. Interestingly, there was no statistically significant enrichment of targets for other cancers in this same list suggesting high specificity of the results. We also adjusted the weighting scheme to prioritize more novel targets for CRC. This second analysis revealed epidermal growth factor receptor (EGFR), phosphoinositide-3-kinase (PI3K), and two mitogen-activated protein kinases (MAPK14 and MAPK3). These observations suggest that our open-source method with a customizable weighting scheme can accurately prioritize targets that are specific and relevant to the disease or condition of interest, as well as targets that are at earlier stages of development. We anticipate that this method will complement other approaches to repurpose drugs for a variety of indications, which can contribute to the improvement of the quality of life and overall health of such patients.

Aceclofenac/Citronellol Oil Nanoemulsion Repurposing Study: Formulation, In Vitro Characterization, and In Silico Evaluation of Their Antiproliferative and Pro-Apoptotic Activity against Melanoma Cell Line

Aceclofenac (ACF) is a widely used non-steroidal anti-inflammatory drug (NSAID) known for its effectiveness in treating pain and inflammation. Recent studies have demonstrated that ACF possesses antiproliferative properties, inhibiting the growth of cancer cells in various cancer cell lines. Citronellol, a monoterpenoid alcohol found in essential oils, exhibits antioxidant properties and activities such as inhibiting cell growth and acetylcholinesterase inhibition. In this study, the objective was to formulate and evaluate an aceclofenac/citronellol oil nanoemulsion for its antiproliferative effects on melanoma. The optimal concentrations of citronellol oil, Tween 80, and Transcutol HP were determined using a pseudoternary phase diagram. The formulated nanoemulsions were characterized for droplet size, zeta potential, thermophysical stability, and in vitro release. The selected formula (F1) consisted of citronellol oil (1 gm%), Tween 80 (4 gm%), and Transcutol HP (1 gm%). F1 exhibited a spherical appearance with high drug content, small droplet size, and acceptable negative zeta potential. The amorphous state of the drug in the nanoemulsion was confirmed by Differential Scanning Calorimetry, while FTIR analysis indicated its homogenous solubility. The nanoemulsion showed significant antiproliferative activity, with a lower IC50 value compared to aceclofenac or citronellol alone. Flow cytometric analysis revealed cell cycle arrest and increased apoptosis induced by the nanoemulsion. In silico studies provided insights into the molecular mechanism underlying the observed antitumor activity. In conclusion, the developed aceclofenac/citronellol oil nanoemulsion exhibited potent cytotoxicity and pro-apoptotic effects, suggesting its potential as a repurposed antiproliferative agent for melanoma treatment. In a future plan, further animal model research for validation is suggested.

Repurposable Drugs for Immunotherapy and Strategies to Find Candidate Drugs

Conventional drug discovery involves significant steps, time, and expenses; therefore, novel methods for drug discovery remain unmet, particularly for patients with intractable diseases. For this purpose, the drug repurposing method has been recently used to search for new therapeutic agents. Repurposed drugs are mostly previously approved drugs, which were carefully tested for their efficacy for other diseases and had their safety for the human body confirmed following careful pre-clinical trials, clinical trials, and post-marketing surveillance. Therefore, using these approved drugs for other diseases that cannot be treated using conventional therapeutic methods could save time and economic costs for testing their clinical applicability. In this review, we have summarized the methods for identifying repurposable drugs focusing on immunotherapy.

Neurodegenerative Disease Associated Pathways in the Brains of Triple Transgenic Alzheimer's Model Mice Are Reversed Following Two Weeks of Peripheral Administration of Fasudil

The pan Rho-associated coiled-coil-containing protein kinase (ROCK) inhibitor fasudil acts as a vasodilator and has been used as a medication for post-cerebral stroke for the past 29 years in Japan and China. More recently, based on the involvement of ROCK inhibition in synaptic function, neuronal survival, and processes associated with neuroinflammation, it has been suggested that the drug may be repurposed for neurodegenerative diseases. Indeed, fasudil has demonstrated preclinical efficacy in many neurodegenerative disease models. To facilitate an understanding of the wider biological processes at play due to ROCK inhibition in the context of neurodegeneration, we performed a global gene expression analysis on the brains of Alzheimer's disease model mice treated with fasudil via peripheral IP injection. We then performed a comparative analysis of the fasudil-driven transcriptional profile with profiles generated from a meta-analysis of multiple neurodegenerative diseases. Our results show that fasudil tends to drive gene expression in a reverse sense to that seen in brains with post-mortem neurodegenerative disease. The results are most striking in terms of pathway enrichment analysis, where pathways perturbed in Alzheimer's and Parkinson's diseases are overwhelmingly driven in the opposite direction by fasudil treatment. Thus, our results bolster the repurposing potential of fasudil by demonstrating an anti-neurodegenerative phenotype in a disease context and highlight the potential of in vivo transcriptional profiling of drug activity.

Systems pharmacology-based mechanism exploration of Acanthopanax senticosusin for Alzheimer's disease using UPLC-Q-TOF-MS, network analysis, and experimental validation

BACKGROUND

Alzheimer's disease (AD) is a neurodegenerative disease, characterized by progressive cognitive dysfunction and memory loss. However, the disease-modifying treatments for AD are still lacking. Traditional Chinese herbs, have shown their potentials as novel treatments for complex diseases, such as AD.

PURPOSE

This study was aimed at investigating the mechanism of action (MOA) of Acanthopanax senticosusin (AS) for treatment of AD.

METHODS

In this study, we firstly identified the chemical constituents in Acanthopanax senticosusin (AS) utilizing ultra-high performance liquid chromatography coupled with Q-TOF-mass spectrometry (UPLC-Q-TOF-MS), and next built the drug-target network of these compounds. We next performed the systems pharmacology-based analysis to preliminary explore the MOA of AS against AD. Moreover, we applied the network proximity approach to identify the potential anti-AD components in AS. Finally, experimental validations, including animal behavior test, ELISA and TUNEL staining, were conducted to verify our systems pharmacology-based analysis.

RESULTS

60 chemical constituents in AS were identified via the UPLC-Q-TOF-MS approach. The systems pharmacology-based analysis indicated that AS might exert its therapeutic effects on AD via acetylcholinesterase and apoptosis signaling pathway. To explore the material basis of AS against AD, we further identified 15 potential anti-AD components in AS. Consistently, in vivo experiments demonstrated that AS could protect cholinergic nervous system damage and decrease neuronal apoptosis caused by scopolamine.

CONCLUSION

Overall, this study applied systems pharmacology approach, via UPLC-Q-TOF-MS, network analysis, and experimental validation to decipher the potential molecular mechanism of AS against AD.

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.

Thiazolidinedione-triazole conjugates: design, synthesis and probing of the α-amylase inhibitory potential

Aim: The primary objective of this investigation was the synthesis, spectral interpretation and evaluation of the α-amylase inhibition of rationally designed thiazolidinedione-triazole conjugates (7a-7aa). Materials & methods: The designed compounds were synthesized by stirring a mixture of thiazolidine-2,4-dione, propargyl bromide, cinnamaldehyde and azide derivatives in polyethylene glycol-400. The α-amylase inhibitory activity of the synthesized conjugates was examined by integrating in vitro and in silico studies. Results: The investigated derivatives exhibited promising α-amylase inhibitory activity, with IC50 values ranging between 0.028 and 0.088 μmol ml-1. Various computational approaches were employed to get detailed information about the inhibition mechanism. Conclusion: The thiazolidinedione-triazole conjugate 7p, with IC50 = 0.028 μmol ml-1, was identified as the best hit for inhibiting α-amylase.

The Comparative Effectiveness of Monotherapy and Combination Therapies: Impact of Angiotensin Receptor Blockers on the Onset of Alzheimer's Disease

Background

The criteria for use of Alzheimer's disease (AD) drug Leqembi recommended by the Department of Veterans Affairs (VA) include patients aged 65 years or older with mild cognitive impairment (MCI) or mild AD. Comorbidities that include hypertension, hyperlipidemia, and diabetes are common among these patients.

Objectives

Our objective is to investigate the comparative effectiveness of the administration of one, two, or three medications belonging to the categories of angiotensin receptor blockers (ARBs), angiotensin-converting enzyme inhibitors (ACEIs), Beta Blockers, Statins, and Metformin, for their potential to delay the clinical onset of AD and provide a window of opportunity for therapeutic intervention.

Design

Retrospective matched case-control study.

Setting

Data from the Department of Veterans Affairs national corporate data warehouse.

Participants

We conducted an analysis of 122,351 participants (13,611 with AD and 108,740 without AD), aged 65-89, who began at least one of the prescribed medication classes under investigation between October 1998 and April 2018.

Measurements

We utilized Cox proportional hazard regressions, both with and without propensity score weighting, to estimate hazard ratios (HR) associated with the use of different medication combinations for the pre-symptomatic survival time of AD onset. Additionally, we employed a supervised machine learning algorithm (random forest) to assess the relative importance of various therapies in predicting the occurrence of AD.

Result

Adding Metformin to the combination of ACEI+Beta Blocker (HR = 0.56, 95% CI (0.41, 0.77)) reduced the risk of AD onset compared to ACEI monotherapy alone (HR = 0.91, (0.85, 0.98)), Beta Blocker monotherapy (HR = 0.86, 95% CI (0.80, 0.92)), or combined ACEI+Beta Blocker (HR=0.85, 95%CI (0.77, 0.94)), when statin prescribers were used as a reference. Prescriptions of ARB alone or the combination of ARB with Beta Blocker showed an association with a lower risk of AD onset.

Conclusion

Selected medications for the treatment of multiple chronic conditions among elderly individuals with hypertension, hyperlipidemia, and diabetes as monotherapy or combination therapies lengthen the pre-symptomatic period before the onset of AD.

Integrating Comorbidity Knowledge for Alzheimer's Disease Drug Repurposing using Multi-task Graph Neural Network

Alzheimer's Disease (AD) is a multifactorial disease that shares common etiologies with its multiple comorbidities, especially vascular diseases. To predict repurposable drugs for AD utilizing the relatively well-investigated comorbidities' knowledge, we proposed a multi-task graph neural network (GNN)-based pipeline that incorporates the corresponding biomedical interactome of these diseases with their genetic markers and effective therapeutics. Our pipeline can accurately capture the interactions and disease classification in the network. Next, we predicted drugs that might interact with the AD module by the node embedding similarity. Our candidates are mostly BBB permeable, and literature evidence showed their potential for treating AD pathologies, accompanying symptoms, or cotreating AD pathology and its common comorbidities. Our pipeline demonstrated a workable strategy that predicts drug candidates with current knowledge of biological interplays between AD and several vascular diseases.

Elaboration of the Effective Multi-Target Therapeutic Platform for the Treatment of Alzheimer's Disease Based on Novel Monoterpene-Derived Hydroxamic Acids

Novel monoterpene-based hydroxamic acids of two structural types were synthesized for the first time. The first type consisted of compounds with a hydroxamate group directly bound to acyclic, monocyclic and bicyclic monoterpene scaffolds. The second type included hydroxamic acids connected with the monoterpene moiety through aliphatic (hexa/heptamethylene) or aromatic linkers. An in vitro analysis of biological activity demonstrated that some of these molecules had powerful HDAC6 inhibitory activity, with the presence of a linker area in the structure of compounds playing a key role. In particular, it was found that hydroxamic acids containing a hexa- and heptamethylene linker and (-)-perill fragment in the Cap group exhibit excellent inhibitory activity against HDAC6 with IC₅₀ in the submicromolar range from 0.56 ± 0.01 µM to 0.74 ± 0.02 µM. The results of the study of antiradical activity demonstrated the presence of moderate ability for some hydroxamic acids to scavenge 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2ROO^• radicals. The correlation coefficient between the DPPH radical scavenging activity and oxygen radical absorbance capacity (ORAC) value was R² = 0.8400. In addition, compounds with an aromatic linker based on para-substituted cinnamic acids, having a monocyclic para-menthene skeleton as a Cap group, 35a, 38a, 35b and 38b, demonstrated a significant ability to suppress the aggregation of the pathological β-amyloid peptide 1-42. The 35a lead compound with a promising profile of biological activity, discovered in the in vitro experiments, demonstrated neuroprotective effects on in vivo models of Alzheimer's disease using 5xFAD transgenic mice. Together, the results obtained demonstrate a potential strategy for the use of monoterpene-derived hydroxamic acids for treatment of various aspects of Alzheimer's disease.

Designing the 5HT2BR structure and its modulation as a therapeutic target for repurposing approach in drug-resistant epilepsy

The study intends to repurpose FDA drugs and investigate the mechanism of (5HT_2BR) activation by comprehending inter-residue interactions. The 5HT_2BR is a novel thread, and its role in reducing seizures in Dravet syndrome is emerging. The crystal structure (5HT_2BR) is a chimera with mutations; hence 3D-structure is modeled (4IB4: 5HT_2BR_M). The structure is cross-validated to simulate the human receptor using enrichment analysis (ROC: 0.79) and SAVESv6.0. Virtual screening of 2456 approved drugs yielded the best hits that are subjected to MM/GBSA and molecular dynamic (MD) simulations. The 2 top drugs Cabergoline (-53.44 kcal/mol) and Methylergonovine (-40.42 kcal/mol), display strong binding affinity, and ADMET/SAR analysis also suggests their non-mutagenic or non-carcinogenic nature. Methylergonovine has a weaker binding affinity and lower potency than standards [Ergotamine (agonist) and Methysergide (antagonist)] due to its higher K_i (1.32 M) and K_d (6.44 ×10^-8 M) values. Compared to standards, Cabergoline has moderate binding affinity and potency [K_i = 0.85 M and K_d = 5.53 × 10-8 M]. The top 2 drugs primarily interact with conserved residues (ASP135, LEU209, GLY221, ALA225, and THR140) as in agonists, unlike the antagonist. The top 2 drugs, upon binding to the 5HT_2BR_M, modify the helices VI, V, and III and shift the RMSD 2.48 Å and 3.07 Å. LEU209 forms a latch with residues 207-214 (forms a lid) in the 5HT_2BR_M receptor, which enhances agonist binding and prevents drug escape. Methylergonovine and Cabergoline interact more stongly with ALA225 than the antagonist. The post-MD analysis of Cabergoline suggests a better MM/GBSA value (-89.21 kcal/mol) than Methylergonovine (-63.54 kcal/mol). In this study, Cabergoline and Methylergonovine's agonistic mechanism and solid binding properties suggest their strong role in regulating the 5HT_2BR and might target drug-resistant epilepsy.

Pathophysiological Association of Alzheimer's Disease and Hypertension: A Clinical Concern for Elderly Population

Alzheimer's disease (AD), the most common cause of dementia and the fifth leading cause of death in the adult population has a complex pathophysiological link with hypertension (HTN). A growing volume of published literature on a parallel elevation of blood pressure (BP), amyloid plaques, and neurofibrillary tangles formation in post-middle of human brain cells has developed new, widely accepting foundations on this association. In particular, HTN in elderly life mediates cerebral blood flow dysfunction, neuronal dysfunction, and significant decline in cognitive impairment, primarily in the late-life populace, governing the onset of AD. Thus, HTN is an established risk factor for AD. Considering the impact of AD, 1.89 million deaths annually, and the failure of palliative therapies to cure AD, the scientific research community is looking to adopt integrated approaches to target early modified risk factors like HTN to reduce AD burden. The current review highlights the significance and impact of HTN-based prevention in lowering the AD burden in the elderly by providing a comprehensive overview of the physiological relationship between AD and HTN with an in-detail explanation of the role and applications of pathological biomarkers in this clinical association. The review will gain worth in presenting new insights and providing inclusive discussion on the correlation between HTN and cognitive impairment. It will increase across a wider scientific audience to expand understanding of this pathophysiological association.

Emerging therapeutics agents and recent advances in drug repurposing for Alzheimer's disease

Alzheimer's disease (AD) is a multivariate and diversified disease and affects the most sensitive areas of the brain, the cerebral cortex, and the hippocampus. AD is a progressive age-related neurodegenerative disease most often associated with memory deficits and cognition that get more worsen over time. The central theory on the pathophysiological hallmark features of AD is characterized by the accumulation of amyloid β (Aβ) peptides, also associated with tau proteins (τ) dysfunctioning which leads to distorted microtubular structure, affects the cholinergic system, and mitochondrial biogenesis. This review emphasizes how simple it is to find novel treatments for AD and focuses on several recently developed medications through repurposing that can speed up traditional drug development.

Linagliptin and Empagliflozin Inhibit Microtubule Affinity Regulatory Kinase 4: Repurposing Anti-Diabetic Drugs in Neurodegenerative Disorders Using In Silico and In Vitro Approaches

Type 2 diabetes mellitus (T2DM) and Alzheimer's disease (AD) are significant public health burdens. Many studies have revealed the possibility of common pathophysiology between T2DM and AD. Thus, in recent years, studies deciphering the action mechanism of anti-diabetic drugs with their future use in AD and related pathologies are on high demand. Drug repurposing is a safe and effective approach owing to its low cost and time-saving attributes. Microtubule affinity regulating kinase 4 (MARK4) is a druggable target for various diseases and is found to be linked with AD and diabetes mellitus. MARK4 plays a vital role in energy metabolism and regulation and thus serves as an irrefutable target to treat T2DM. The present study was intended to identify the potent MARK4 inhibitors among FDA-approved anti-diabetic drugs. We performed structure-based virtual screening of FDA-approved drugs to identify the top hits against MARK4. We identified five FDA-approved drugs having an appreciable affinity and specificity toward the binding pocket of MARK4. Among these identified hits, two drugs, linagliptin, and empagliflozin, favorably bind to the MARK4 binding pocket, interacting with its critical residues and thus subjected to detailed analysis. All-atom detailed molecular dynamics (MD) simulations revealed the dynamics of binding of linagliptin and empagliflozin with MARK4. Kinase assay showed significant inhibition of MARK4 kinase activity in the presence of these drugs, implying them as potent MARK4 inhibitors. In conclusion, linagliptin and empagliflozin may be promising MARK4 inhibitors, which can further be exploited as potential lead molecules against MARK4-directed neurodegenerative diseases.

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.