Alzheimer's Disease: Key Insights from Two Decades of Clinical Trial Failures

In-situ nanozyme catalytic amplification coupled with a universal antibody orientation strategy based electrochemical immunosensor for AD-related biomarker

An in-situ nanozyme signal tag combined with a DNA-mediated universal antibody-oriented strategy was proposed to establish a high-performance immunosensing platform for Alzheimer's disease (AD)-related biomarker detection. Briefly, a Zr-based metal-organic framework (MOF) with peroxidase (POD)-like activity was synthesized to encapsulating the electroactive molecule methylene blue (MB), and subsequently modified with a layer of gold nanoparticles on its surface. This led to the creation of double POD-like activity nanozymes surrounding the MB molecule to form a nanozyme signal tag. A large number of hydroxyl radicals were generated by the nanozyme signal tag with the help of H2O2, which catalyzed MB molecules in situ to achieve efficient signal amplification. Subsequently, a DNA-aptamer-mediated universal antibody-oriented strategy was proposed to enhance the binding efficiency for the antigen (target). Meanwhile, a poly adenine was incorporated at the end of the aptamer, facilitating binding to the gold electrode and providing anti-fouling properties due to the hydrophilicity of the phosphate group. Under optimal conditions, this platform was successfully employed for highly sensitive detection of AD-associated tau protein and BACE1, achieving limits of detection with concentrations of 3.34 fg/mL and 1.67 fg/mL, respectively. It is worth mentioning that in the tau immunosensing mode, 20 clinical samples from volunteers of varying ages were analyzed, revealing significantly higher tau expression levels in the blood samples of elderly volunteers compared to young volunteers. This suggests that the developed strategy holds great promise for early AD diagnosis.

A Systematic Online Living Evidence Summary of experimental Alzheimer's disease research

BACKGROUND

Despite extensive investment, the development of effective treatments for Alzheimer's disease (AD) has been largely unsuccessful. To improve translation, it is crucial to ensure the quality and reproducibility of foundational evidence generated from laboratory models. Systematic reviews play a key role in providing an unbiased overview of the evidence, assessing rigour and reporting, and identifying factors that influence reproducibility. However, the sheer pace of evidence generation is prohibitive to evidence synthesis and assessment.

NEW METHOD

To address these challenges, we have developed AD-SOLES, an integrated workflow of automated tools that collect, curate, and visualise the totality of evidence from in vivo experiments.

RESULTS

AD-SOLES is a publicly accessible interactive dashboard aiming to surface and expose data from in vivo experiments. It summarises the latest evidence, tracks reporting quality and transparency, and allows research users to easily locate evidence relevant to their specific research question.

COMPARISON WITH EXISTING METHODS

Using automated screening methodologies within AD-SOLES, systematic reviews can begin at an accelerated starting point compared to traditional approaches. Furthermore, through text-mining approaches within the full-text of publications, users can identify research of interest using specific models, outcomes, or interventions without relying on details in the title and/or abstract.

CONCLUSIONS

By automating the collection, curation, and visualisation of evidence from in vivo experiments, AD-SOLES addresses the challenges posed by the rapid pace of evidence generation. AD-SOLES aims to offer guidance for research improvement, reduce research waste, highlight knowledge gaps, and support informed decision making for researchers, funders, patients, and the public.

Plasma proteomics and lipidomics facilitate elucidation of the link between Alzheimer's disease development and vessel wall fragility

Proximity Extension Assay (PEA) and mass spectrometry (MS) methodologies were utilized for the proteomic and lipidomic characterization of plasma specimens from patients who developed Alzheimer's disease. Proteomics was performed by both PEA and Liquid Chromatography (LC)/MS in this study, but all the more because LC/MS generally tends to be biased towards proteins with high expression and high variability, generating hypotheses proved challenging. Consequently, attempt was made to interpret the results from the PEA data. There were 150 significantly variable proteins and 68 lipids among 1000 proteins and 400 lipids. Pathway analysis was performed for both total and variable proteins measured to reduce bias, and it appeared that vascular fragility was related to AD. Furthermore, a multitude of lipid-associated proteins exhibited statistical changes. In certain instances, the function of individual proteins affected the factors associated with them, whereas others demonstrated trends contrary to anticipated outcomes. These trends seem indicative of diverse feedback mechanisms that provide homeostatic equilibrium. The degree of unsaturation of fatty acids, correlated with cardiovascular risk, warrants specific attention. Certain bile acids exhibited the potential to cause vascular endothelial damage. Contemplating these discoveries in tandem with previously documented phenomena, subtle shifts in homeostatic functions seem to be linked to the fragility of vascular endothelial cells. This is evidenced by the slow and chronic evolution of Alzheimer's disease from preclinical stages to its manifestation.

Speech-related parameters are sensitive measures of acetylcholinesterase inhibitor therapy in mild Alzheimer's disease

Our aim was to find out whether speech-related temporal parameters (SRTPs) are sensitive indicators of the clinical outcome in acetylcholinesterase (AChE) inhibitor therapy with donepezil, compared to the standard cognitive Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog) used in clinical trials. In this 24-week-long, naturalistic, self-control, open-labeled, prospective pilot study with 10 mg donepezil on 20 mild AD patients, cognitive functions were evaluated using 15 different SRTPs analyzed by automatic speech recognition in the Speech-Gap Test® compared to ADAS-Cog test results. Among the SRTPs, the filled pause duration ratio significantly improved after 12 weeks of donepezil treatment. During the 24-week follow-up, additional SRTPs such as the filled pause count ratio and the filled pause frequency showed significant benefits. ADAS-Cog total scores showed a slight but not significant improvement compared to baseline after 12 and 24 weeks of donepezil treatment. Among the ADAS-Cog subtests, only orientation improved significantly after 24 weeks of donepezil treatment. Our results indicate that subtle changes in SRTPs measured by the Speech-Gap Test® could be considered as sensitive indicators of the efficacy of the pharmacotherapy in mild AD. According to our data, other cognitive domains did not show improvement in response to donepezil therapy rating by ADAS-Cog. Based on all of this, it is likely that examining and evaluating speech parameters may play an important role in determining the effects of pharmacological treatment of mild AD. The novelty of our study is that it applies the measurement of linguistic parameters as primary outcomes during a drug trial of mild AD in scientific research for the first time.

AROMHA Brain Health Test: A Remote Olfactory Assessment as a Screen for Cognitive Impairment

Cost-effective, noninvasive screening methods for preclinical Alzheimer's disease (AD) and other neurocognitive disorders remain an unmet need. The olfactory neural circuits develop AD pathological changes prior to symptom onset. To probe these vulnerable circuits, we developed the digital remote AROMHA Brain Health Test (ABHT), an at-home odor identification, discrimination, memory, and intensity assessment. The ABHT was self-administered among cognitively normal (CN) English and Spanish speakers (n=127), participants with subjective cognitive complaints (SCC; n=34), and mild cognitive impairment (MCI; n=19). Self-administered tests took place remotely at home under unobserved (among interested CN participants) and observed modalities (CN, SCC, and MCI), as well as in-person with a research assistant present (CN, SCC, and MCI). Olfactory performance was similar across observed and unobserved remote self-administration and between English and Spanish speakers. Odor memory, identification, and discrimination scores decreased with age, and olfactory identification and discrimination were lower in the MCI group compared to CN and SCC groups, independent of age, sex, and education. The ABHT revealed age-related olfactory decline, and discriminated CN older adults from those with cognitive impairment. Replication of our results in other populations would support the use of the ABHT to identify and monitor individuals at risk for developing dementia.

An Introductory Guide to Using Bloomington Drosophila Stock Center and FlyBase for Aging Research

Studies on numerous species have demonstrated strikingly conserved mechanisms that determine the aging process, from yeasts to worms, flies, zebrafish, mice, and humans. The fruit fly Drosophila melanogaster is an excellent model organism for studying the biological basis of normal aging and etiology of age-related diseases. Since its inception in 1967, the Bloomington Drosophila Stock Center (BDSC) has grown into the largest collection of documented D. melanogaster strains (currently > 91,000). This paper aims to briefly review conserved mechanisms of aging and provides a guide to help users understand the organization of stock listings on the BDSC website and familiarize themselves with the search functions on BDSC and FlyBase, with an emphasis on using genes in conserved pathways as examples to find stocks for aging studies.

Bio-Nano Toolbox for Precision Alzheimer's Disease Gene Therapy

Alzheimer's disease (AD) is the most burdensome aging-associated neurodegenerative disorder, and its treatment encounters numerous failures during drug development. Although there are newly approved in-market β-amyloid targeting antibody solutions, pathological heterogeneity among patient populations still challenges the treatment outcome. Emerging advances in gene therapies offer opportunities for more precise personalized medicine; while, major obstacles including the pathological heterogeneity among patient populations, the puzzled mechanism for druggable target development, and the precision delivery of functional therapeutic elements across the blood-brain barrier remain and limit the use of gene therapy for central neuronal diseases. Aiming for "precision delivery" challenges, nanomedicine provides versatile platforms that may overcome the targeted delivery challenges for AD gene therapy. In this perspective, to picture a toolbox for AD gene therapy strategy development, the most recent advances from benchtop to clinics are highlighted, possibly available gene therapy targets, tools, and delivery platforms are outlined, their challenges as well as rational design elements are addressed, and perspectives in this promising research field are discussed.

Does resistance training in older adults lead to structural brain changes associated with a lower risk of Alzheimer's dementia? A narrative review

Dementia, particularly Alzheimer's Disease (AD), has links to several modifiable risk factors, especially physical inactivity. When considering the relationship between physcial activity and dementia risk, cognitive benefits are generally attributed to aerobic exercise, with resistance exercise (RE) receiving less attention. This review aims to address this gap by evaluating the impact of RE on brain structures and cognitive deficits associated with AD. Drawing insights from randomized controlled trials (RCTs) utilizing structural neuroimaging, the specific influence of RE on AD-affected brain structures and their correlation with cognitive function are discussed. Preliminary findings suggest that RE induces structural brain changes in older adults that could reduce the risk of AD or mitigate AD progression. Importantly, the impacts of RE appear to follow a dose-response effect, reversing pathological structural changes and improving associated cognitive functions if performed at least twice per week for at least six months, with greatest effects in those already experiencing some element of cognitive decline. While more research is eagerly awaited, this review contributes insights into the potential benefits of RE for cognitive health in the context of AD-related changes in brain structure and function.

Transcranial alternating current stimulation (tACS) at gamma frequency: an up-and-coming tool to modify the progression of Alzheimer's Disease

The last decades have witnessed huge efforts devoted to deciphering the pathological mechanisms underlying Alzheimer's Disease (AD) and to testing new drugs, with the recent FDA approval of two anti-amyloid monoclonal antibodies for AD treatment. Beyond these drug-based experimentations, a number of pre-clinical and clinical trials are exploring the benefits of alternative treatments, such as non-invasive stimulation techniques on AD neuropathology and symptoms. Among the different non-invasive brain stimulation approaches, transcranial alternating current stimulation (tACS) is gaining particular attention due to its ability to externally control gamma oscillations. Here, we outline the current knowledge concerning the clinical efficacy, safety, ease-of-use and cost-effectiveness of tACS on early and advanced AD, applied specifically at 40 Hz frequency, and also summarise pre-clinical results on validated models of AD and ongoing patient-centred trials.

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.

3-Hydroxyanthranilic Acid Delays Paralysis in Caenorhabditis elegans Models of Amyloid-Beta and Polyglutamine Proteotoxicity

Age is the primary risk factor for neurodegenerative diseases such as Alzheimer's and Huntington's disease. Alzheimer's disease is the most common form of dementia and a leading cause of death in the elderly population of the United States. No effective treatments for these diseases currently exist. Identifying effective treatments for Alzheimer's, Huntington's, and other neurodegenerative diseases is a major current focus of national scientific resources, and there is a critical need for novel therapeutic strategies. Here, we investigate the potential for targeting the kynurenine pathway metabolite 3-hydroxyanthranilic acid (3HAA) using Caenorhabditis elegans expressing amyloid-beta or a polyglutamine peptide in body wall muscle, modeling the proteotoxicity in Alzheimer's and Huntington's disease, respectively. We show that knocking down the enzyme that degrades 3HAA, 3HAA dioxygenase (HAAO), delays the age-associated paralysis in both models. This effect on paralysis was independent of the protein aggregation in the polyglutamine model. We also show that the mechanism of protection against proteotoxicity from HAAO knockdown is mimicked by 3HAA supplementation, supporting elevated 3HAA as the mediating event linking HAAO knockdown to delayed paralysis. This work demonstrates the potential for 3HAA as a targeted therapeutic in neurodegenerative disease, though the mechanism is yet to be explored.

Passive Anti-Amyloid Beta Immunotherapies in Alzheimer's Disease: From Mechanisms to Therapeutic Impact

Alzheimer's disease, the most common type of dementia worldwide, lacks effective disease-modifying therapies despite significant research efforts. Passive anti-amyloid immunotherapies represent a promising avenue for Alzheimer's disease treatment by targeting the amyloid-beta peptide, a key pathological hallmark of the disease. This approach utilizes monoclonal antibodies designed to specifically bind amyloid beta, facilitating its clearance from the brain. This review offers an original and critical analysis of anti-amyloid immunotherapies by exploring several aspects. Firstly, the mechanisms of action of these therapies are reviewed, focusing on their ability to promote Aβ degradation and enhance its efflux from the central nervous system. Subsequently, the extensive history of clinical trials involving anti-amyloid antibodies is presented, from initial efforts using first-generation molecules leading to mixed results to recent clinically approved drugs. Along with undeniable progress, the authors also highlight the pitfalls of this approach to offer a balanced perspective on this topic. Finally, based on its potential and limitations, the future directions of this promising therapeutic strategy for Alzheimer's disease are emphasized.

Unveiling Gene Interactions in Alzheimer's Disease by Integrating Genetic and Epigenetic Data with a Network-Based Approach

Alzheimer's Disease (AD) is a complex disease and the leading cause of dementia in older people. We aimed to uncover aspects of AD's pathogenesis that may contribute to drug repurposing efforts by integrating DNA methylation and genetic data. Implementing the network-based tool, a dense module search of genome-wide association studies (dmGWAS), we integrated a large-scale GWAS dataset with DNA methylation data to identify gene network modules associated with AD. Our analysis yielded 286 significant gene network modules. Notably, the foremost module included the BIN1 gene, showing the largest GWAS signal, and the GNAS gene, the most significantly hypermethylated. We conducted Web-based Cell-type-Specific Enrichment Analysis (WebCSEA) on genes within the top 10% of dmGWAS modules, highlighting monocyte as the most significant cell type (p < 5 × 10-12). Functional enrichment analysis revealed Gene Ontology Biological Process terms relevant to AD pathology (adjusted p < 0.05). Additionally, drug target enrichment identified five FDA-approved targets (p-value = 0.03) for further research. In summary, dmGWAS integration of genetic and epigenetic signals unveiled new gene interactions related to AD, offering promising avenues for future studies.

Open science in precision medicine for neurodegenerative diseases

Open science initiatives that harness human genomic and genetic data could help increase the likelihood of successfully developing new drugs for neurodegenerative diseases.

Cytokine expression patterns predict suppression of vulnerable neural circuits in a mouse model of Alzheimer's disease

Alzheimer's disease is a neurodegenerative disorder characterized by progressive amyloid plaque accumulation, tau tangle formation, neuroimmune dysregulation, synapse an neuron loss, and changes in neural circuit activation that lead to cognitive decline and dementia. Early molecular and cellular disease-instigating events occur 20 or more years prior to presentation of symptoms, making them difficult to study, and for many years amyloid-β, the aggregating peptide seeding amyloid plaques, was thought to be the toxic factor responsible for cognitive deficit. However, strategies targeting amyloid-β aggregation and deposition have largely failed to produce safe and effective therapies, and amyloid plaque levels poorly correlate with cognitive outcomes. However, a role still exists for amyloid-β in the variation in an individual's immune response to early, soluble forms of aggregates, and the downstream consequences of this immune response for aberrant cellular behaviors and creation of a detrimental tissue environment that harms neuron health and causes changes in neural circuit activation. Here, we perform functional magnetic resonance imaging of awake, unanesthetized Alzheimer's disease mice to map changes in functional connectivity over the course of disease progression, in comparison to wild-type littermates. In these same individual animals, we spatiotemporally profile the immune milieu by measuring cytokines, chemokines, and growth factors across various brain regions and over the course of disease progression from pre-pathology through established cognitive deficit. We identify specific signatures of immune activation predicting hyperactivity followed by suppression of intra- and then inter-regional functional connectivity in multiple disease-relevant brain regions, following the pattern of spread of amyloid pathology.

Prediction of conversion from mild cognitive impairment to Alzheimer's disease and simultaneous feature selection and grouping using Medicaid claim data

BACKGROUND

Due to the heterogeneity among patients with Mild Cognitive Impairment (MCI), it is critical to predict their risk of converting to Alzheimer's disease (AD) early using routinely collected real-world data such as the electronic health record data or administrative claim data.

METHODS

The study used MarketScan Multi-State Medicaid data to construct a cohort of MCI patients. Logistic regression with tree-guided lasso regularization (TGL) was proposed to select important features and predict the risk of converting to AD. A subsampling-based technique was used to extract robust groups of predictive features. Predictive models including logistic regression, generalized random forest, and artificial neural network were trained using the extracted features.

RESULTS

The proposed TGL workflow selected feature groups that were robust, highly interpretable, and consistent with existing literature. The predictive models using TGL selected features demonstrated higher prediction accuracy than the models using all features or features selected using other methods.

CONCLUSIONS

The identified feature groups provide insights into the progression from MCI to AD and can potentially improve risk prediction in clinical practice and trial recruitment.

The need for systems thinking to advance Alzheimer's disease research

Despite extensive research efforts to mechanistically understand late-onset Alzheimer's disease (LOAD) and other complex mental health disorders, curative treatments remain elusive. We emphasize the multiscale multicausality inherent to LOAD, highlighting the interplay between interconnected pathophysiological processes and risk factors. Systems thinking methods, such as causal loop diagrams and systems dynamic models, offer powerful means to capture and study this complexity. Recent studies developed and validated a causal loop diagram and system dynamics model using multiple longitudinal data sets, enabling the simulation of personalized interventions on various modifiable risk factors in LOAD. The results indicate that targeting factors like sleep disturbance and depressive symptoms could be promising and yield synergistic benefits. Furthermore, personalized interventions showed significant potential, with top-ranked intervention strategies differing significantly across individuals. We argue that systems thinking approaches can open new prospects for multifactorial precision medicine. In future research, systems thinking may also guide structured, model-driven data collection on the multiple interactions in LOAD's complex multicausality, facilitating theory development and possibly resulting in effective prevention and treatment options.

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.

Alzheimer's Disease Puzzle: Delving into Pathogenesis Hypotheses

Alzheimer's disease (AD) is a prevalent neurodegenerative disease characterized by both amnestic and non-amnestic clinical manifestations. It accounts for approximately 60-70% of all dementia cases worldwide. With the increasing number of AD patients, elucidating underlying mechanisms and developing corresponding interventional strategies are necessary. Hypotheses about AD such as amyloid cascade, Tau hyper-phosphorylation, neuroinflammation, oxidative stress, mitochondrial dysfunction, cholinergic, and vascular hypotheses are not mutually exclusive, and all of them play a certain role in the development of AD. The amyloid cascade hypothesis is currently the most widely studied; however, other hypotheses are also gaining support. This article summarizes the recent evidence regarding major pathological hypotheses of AD and their potential interplay, as well as the strengths and weaknesses of each hypothesis and their implications for the development of effective treatments. This could stimulate further studies and promote the development of more effective therapeutic strategies for AD.

Lessons Learned from Approval of Aducanumab for Alzheimer's Disease

When the US Food and Drug Administration used the accelerated approval process to authorize the use of the antiamyloid drug aducanumab to treat Alzheimer's disease (AD), many people hoped this signaled a new era of disease-modifying treatment. But 2 years later, aducanumab's failure to launch provides a cautionary tale about the complexities of dementia and the need for a thorough and transparent review of the role that regulatory agencies and various stakeholders play in approving AD drugs. We highlight the events leading to aducanumab's controversial approval and discuss some of the key lessons learned from the drug's failure to deliver the hoped-for benefits. These lessons include the inherent limitations of antiamyloid strategies for a complex disease in which amyloid is only one of several pathological processes, the need for clinical trials that better reflect the diversity of communities affected by AD, the potential pitfalls of futility analyses in clinical trials, the need for greater transparency and other modifications to the approval process, and the dementia field's unreadiness to move from the highly controlled environment of clinical trials to the widespread and chronic use of resource-intensive, disease-modifying drugs in real-world treatment scenarios. People with dementia desperately need effective therapies. We hope that the aducanumab story will inspire changes to the approval process-changes that restore public trust and improve future efforts to deliver disease-modifying therapies to the clinic.

Microfluidic-based human prostate-cancer-on-chip

Lack of adequate models significantly hinders advances in prostate cancer treatment, where resistance to androgen-deprivation therapies and bone metastasis remain as major challenges. Current in vitro models fail to faithfully mimic the complex prostate physiology. In vivo animal models can shed light on the oncogenes involved in prostate cancer development and progression; however, the animal prostate gland is fundamentally different from that of human, and the underlying genetic mechanisms are different. To address this problem, we developed the first in vitro microfluidic human Prostate-Cancer-on-Chip (PCoC) model, where human prostate cancer and stromal fibroblast cells were co-cultivated in two channels separated by a porous membrane under culture medium flow. The established microenvironment enables soluble signaling factors secreted by each culture to locally diffuse through the membrane pores affecting the neighboring culture. We particularly explored the conversion of the stromal fibroblasts into cancer-associated fibroblasts (CAFs) due to the interaction between the 2 cell types. Immunofluorescence microscopy revealed that tumor cells induced CAF biomarkers, αSMA and COL1A1, in stromal fibroblasts. The stromal CAF conversion level was observed to increase along the flow direction in response to diffusion agents, consistent with simulations of solute concentration gradients. The tumor cells also downregulated androgen receptor (AR) expression in stromal fibroblasts, while an adequate level of stromal AR expression is maintained in normal prostate homeostasis. We further investigated tumor invasion into the stroma, an early step in the metastatic cascade, in devices featuring a serpentine channel with orthogonal channel segments overlaying a straight channel and separated by an 8 µm-pore membrane. Both tumor cells and stromal CAFs were observed to cross over into their neighboring channel, and the stroma's role seemed to be proactive in promoting cell invasion. As control, normal epithelial cells neither induced CAF conversion nor promoted cell invasion. In summary, the developed PCoC model allows spatiotemporal analysis of the tumor-stroma dynamic interactions, due to bi-directional signaling and physical contact, recapitulating tissue-level multicellular responses associated with prostate cancer in vivo. Hence, it can serve as an in vitro model to dissect mechanisms in human prostate cancer development and seek advanced therapeutic strategies.

Antiepileptic Drugs as Potential Dementia Prophylactics Following Traumatic Brain Injury

Seizures and other forms of neurovolatility are emerging as druggable prodromal mechanisms that link traumatic brain injury (TBI) to the progression of later dementias. TBI neurotrauma has both acute and long-term impacts on health, and TBI is a leading risk factor for dementias, including chronic traumatic encephalopathy and Alzheimer's disease. Treatment of TBI already considers acute management of posttraumatic seizures and epilepsy, and impressive efforts have optimized regimens of antiepileptic drugs (AEDs) toward that goal. Here we consider that expanding these management strategies could determine which AED regimens best prevent dementia progression in TBI patients. Challenges with this prophylactic strategy include the potential consequences of prolonged AED treatment and that a large subset of patients are refractory to available AEDs. Addressing these challenges is warranted because the management of seizure activity following TBI offers a rare opportunity to prevent the onset or progression of devastating dementias.

Modeling Path Importance for Effective Alzheimer's Disease Drug Repurposing

Recently, drug repurposing has emerged as an effective and resource-efficient paradigm for AD drug discovery. Among various methods for drug repurposing, network-based methods have shown promising results as they are capable of leveraging complex networks that integrate multiple interaction types, such as protein-protein interactions, to more effectively identify candidate drugs. However, existing approaches typically assume paths of the same length in the network have equal importance in identifying the therapeutic effect of drugs. Other domains have found that same length paths do not necessarily have the same importance. Thus, relying on this assumption may be deleterious to drug repurposing attempts. In this work, we propose MPI (Modeling Path Importance), a novel network-based method for AD drug repurposing. MPI is unique in that it prioritizes important paths via learned node embeddings, which can effectively capture a network's rich structural information. Thus, leveraging learned embeddings allows MPI to effectively differentiate the importance among paths. We evaluate MPI against a commonly used baseline method that identifies anti-AD drug candidates primarily based on the shortest paths between drugs and AD in the network. We observe that among the top-50 ranked drugs, MPI prioritizes 20.0% more drugs with anti-AD evidence compared to the baseline. Finally, Cox proportional-hazard models produced from insurance claims data aid us in identifying the use of etodolac, nicotine, and BBB-crossing ACE-INHs as having a reduced risk of AD, suggesting such drugs may be viable candidates for repurposing and should be explored further in future studies.

Aniracetam: An Evidence-Based Model for Preventing the Accumulation of Amyloid-β Plaques in Alzheimer's Disease

 Alzheimer's disease is the leading cause of dementia in the world. It affects 6 million people in the United States and 50 million people worldwide. Alzheimer's disease is characterized by the accumulation of amyloid-β plaques (Aβ), an increase in tau protein neurofibrillary tangles, and a loss of synapses. Since the 1990s, removing and reducing Aβ has been the focus of Alzheimer's treatment and prevention research. The accumulation of Aβ can lead to oxidative stress, inflammation, neurotoxicity, and eventually apoptosis. These insults impair signaling systems in the brain, potentially leading to memory loss and cognitive decline. Aniracetam is a safe, effective, cognitive-enhancing drug that improves memory in both human and animal studies. Aniracetam may prevent the production and accumulation of Aβ by increasing α-secretase activity through two distinct pathways: 1) increasing brain derived neurotrophic factor expression and 2) positively modulating metabotropic glutamate receptors. This is the first paper to propose an evidence-based model for aniracetam reducing the accumulation and production of Aβ.

Biomarkers as Endpoints in Clinical Trials for Alzheimer's Disease

Background

Alzheimer's disease (AD) is a neurodegenerative disease that imposes economic and societal burden. Biomarkers have played a crucial role in the recent approval of aducanumab and lecanemab as disease-modifying therapies which marked a significant milestone for the treatment of AD. The inclusion of biomarkers in AD trials facilitates precise diagnosis, monitors safety, demonstrates target engagement, and supports disease modification.

Objective

This study analyzed the utilization state and trends of biomarkers as endpoints in AD trials.

Methods

In this retrospective study, trials were collected by searching clinicaltrials.gov using the term "Alzheimer". Primary and secondary outcomes were analyzed separately for each phase.

Results

Among the 1,048 analyzed trials, 313 (29.87%) adopted biomarkers as primary endpoints and 364 (34.73%) as secondary endpoints, mainly in phases 1 and 2. The top three biomarkers adopted as primary endpoints in phases 1, 2, and 3 were amyloid-PET, tau-PET, and MRI. The top three biomarkers adopted as secondary endpoints, in phase 1, were cerebrospinal fluid (CSF) amyloid-β (Aβ), blood Aβ and amyloid-PET; in phase 2, they were MRI, CSF Aβ, and CSF phospho-tau; and in phase 3, they were amyloid PET, MRI, and blood Aβ. There was a statistically significant increase in the adoption of biomarkers as primary endpoints in phase 2 trials (p = 0.001) and secondary endpoints in phase 3 trials (p = 0.001).

Conclusions

The growing recognition of the importance of biomarkers in AD trial' design and drug development is evident by the significant steady increase in biomarkers' utilization in phases 2 and 3.

Addressing the Discrepancies Between Animal Models and Human Alzheimer's Disease Pathology: Implications for Translational Research

Animal models, particularly transgenic mice, are extensively used in Alzheimer's disease (AD) research to emulate key disease hallmarks, such as amyloid plaques and neurofibrillary tangles formation. Although these models have contributed to our understanding of AD pathogenesis and can be helpful in testing potential therapeutic interventions, their reliability is dubious. While preclinical studies have shown promise, clinical trials often yield disappointing results, highlighting a notable gap and disparity between animal models and human AD pathology. Existing models frequently overlook early-stage human pathologies and other key AD characteristics, thereby limiting their application in identifying optimal therapeutic interventions. Enhancing model reliability necessitates rigorous study design, comprehensive behavioral evaluations, and biomarker utilization. Overall, a nuanced understanding of each model's neuropathology, its fidelity to human AD, and its limitations is essential for accurate interpretation and successful translation of findings. This article analyzes the discrepancies between animal models and human AD pathology that complicate the translation of findings from preclinical studies to clinical applications. We also delve into AD pathogenesis and attributes to propose a new perspective on this pathology and deliberate over the primary limitations of key experimental models. Additionally, we discuss several fundamental problems that may explain the translational failures and suggest some possible directions for more effective preclinical studies.

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.

Constituents of Uncaria lanosa f. philippinensis and their anti-amyloidogenic activity

The aggregation of amyloid-β (Aβ) remains the most acceptable pathological hallmark of Alzheimer's disease (AD). In search for natural products exhibiting anti-amyloidogenic effects, phytochemical analyses were conducted on Uncaria lanosa f. philippinensis leading to the purification of oxindole alkaloid uncarine E (isopteropodine) (1), the phenylethanoid tyrosol (2), the megastigmane vomifoliol (3), and the previously reported alkaloids mitraphylline and isomitraphylline. This is the first report of compounds 1-3 in the title plant, and tyrosol (2) from the genus Uncaria. Assessment of the anti-amyloidogenic potential using Thioflavin T assay showed 91% (at 50 µM) and 70% (at 25 µM) inhibitions for compound 1. Tyrosol (2) gave 76% (at 50 µM) and 63% (at 25 µM) inhibitions. These compounds may be further tested to elucidate their mechanism in the prevention of Aβ aggregation. To the best of our knowledge, this is the first report on the anti-amyloid aggregation activity of compounds 1 and 2.

Improved multimodal prediction of progression from MCI to Alzheimer's disease combining genetics with quantitative brain MRI and cognitive measures

INTRODUCTION

There is a pressing need for non-invasive, cost-effective tools for early detection of Alzheimer's disease (AD).

METHODS

Using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), Cox proportional models were conducted to develop a multimodal hazard score (MHS) combining age, a polygenic hazard score (PHS), brain atrophy, and memory to predict conversion from mild cognitive impairment (MCI) to dementia. Power calculations estimated required clinical trial sample sizes after hypothetical enrichment using the MHS. Cox regression determined predicted age of onset for AD pathology from the PHS.

RESULTS

The MHS predicted conversion from MCI to dementia (hazard ratio for 80th versus 20th percentile: 27.03). Models suggest that application of the MHS could reduce clinical trial sample sizes by 67%. The PHS alone predicted age of onset of amyloid and tau.

DISCUSSION

The MHS may improve early detection of AD for use in memory clinics or for clinical trial enrichment.

HIGHLIGHTS

A multimodal hazard score (MHS) combined age, genetics, brain atrophy, and memory. The MHS predicted time to conversion from mild cognitive impairment to dementia. MHS reduced hypothetical Alzheimer's disease (AD) clinical trial sample sizes by 67%. A polygenic hazard score predicted age of onset of AD neuropathology.

Modeling Path Importance for Effective Alzheimer's Disease Drug Repurposing

Recently, drug repurposing has emerged as an effective and resource-efficient paradigm for AD drug discovery. Among various methods for drug repurposing, network-based methods have shown promising results as they are capable of leveraging complex networks that integrate multiple interaction types, such as protein-protein interactions, to more effectively identify candidate drugs. However, existing approaches typically assume paths of the same length in the network have equal importance in identifying the therapeutic effect of drugs. Other domains have found that same length paths do not necessarily have the same importance. Thus, relying on this assumption may be deleterious to drug repurposing attempts. In this work, we propose MPI (Modeling Path Importance), a novel network-based method for AD drug repurposing. MPI is unique in that it prioritizes important paths via learned node embeddings, which can effectively capture a network's rich structural information. Thus, leveraging learned embeddings allows MPI to effectively differentiate the importance among paths. We evaluate MPI against a commonly used baseline method that identifies anti-AD drug candidates primarily based on the shortest paths between drugs and AD in the network. We observe that among the top-50 ranked drugs, MPI prioritizes 20.0% more drugs with anti-AD evidence compared to the baseline. Finally, Cox proportional-hazard models produced from insurance claims data aid us in identifying the use of etodolac, nicotine, and BBB-crossing ACE-INHs as having a reduced risk of AD, suggesting such drugs may be viable candidates for repurposing and should be explored further in future studies.

The therapeutic landscape of tauopathies: challenges and prospects

Tauopathies are a group of neurodegenerative disorders characterized by the aggregation of the microtubule-associated protein tau. Aggregates of misfolded tau protein are believed to be implicated in neuronal death, which leads to a range of symptoms including cognitive decline, behavioral change, dementia, and motor deficits. Currently, there are no effective treatments for tauopathies. There are four clinical candidates in phase III trials and 16 in phase II trials. While no effective treatments are currently approved, there is increasing evidence to suggest that various therapeutic approaches may slow the progression of tauopathies or improve symptoms. This review outlines the landscape of therapeutic drugs (indexed through February 28, 2023) that target tau pathology and describes drug candidates in clinical development as well as those in the discovery and preclinical phases. The review also contains information on notable therapeutic programs that are inactive or that have been discontinued from development.

The amyloid cascade hypothesis: an updated critical review

Results from recent clinical trials of antibodies that target amyloid-β (Aβ) for Alzheimer's disease have created excitement and have been heralded as corroboration of the amyloid cascade hypothesis. However, while Aβ may contribute to disease, genetic, clinical, imaging and biochemical data suggest a more complex aetiology. Here we review the history and weaknesses of the amyloid cascade hypothesis in view of the new evidence obtained from clinical trials of anti-amyloid antibodies. These trials indicate that the treatments have either no or uncertain clinical effect on cognition. Despite the importance of amyloid in the definition of Alzheimer's disease, we argue that the data point to Aβ playing a minor aetiological role. We also discuss data suggesting that the concerted activity of many pathogenic factors contribute to Alzheimer's disease and propose that evolving multi-factor disease models will better underpin the search for more effective strategies to treat the disease.

Evidence supportive of a bacterial component in the etiology for Alzheimer's disease and for a temporal-spatial development of a pathogenic microbiome in the brain

Background

Over the last few decades, a growing body of evidence has suggested a role for various infectious agents in Alzheimer's disease (AD) pathogenesis. Despite diverse pathogens (virus, bacteria, fungi) being detected in AD subjects' brains, research has focused on individual pathogens and only a few studies investigated the hypothesis of a bacterial brain microbiome. We profiled the bacterial communities present in non-demented controls and AD subjects' brains.

Results

We obtained postmortem samples from the brains of 32 individual subjects, comprising 16 AD and 16 control age-matched subjects with a total of 130 samples from the frontal and temporal lobes and the entorhinal cortex. We used full-length 16S rRNA gene amplification with Pacific Biosciences sequencing technology to identify bacteria. We detected bacteria in the brains of both cohorts with the principal bacteria comprising Cutibacterium acnes (formerly Propionibacterium acnes) and two species each of Acinetobacter and Comamonas genera. We used a hierarchical Bayesian method to detect differences in relative abundance among AD and control groups. Because of large abundance variances, we also employed a new analysis approach based on the Latent Dirichlet Allocation algorithm, used in computational linguistics. This allowed us to identify five sample classes, each revealing a different microbiota. Assuming that samples represented infections that began at different times, we ordered these classes in time, finding that the last class exclusively explained the existence or non-existence of AD.

Conclusions

The AD-related pathogenicity of the brain microbiome seems to be based on a complex polymicrobial dynamic. The time ordering revealed a rise and fall of the abundance of C. acnes with pathogenicity occurring for an off-peak abundance level in association with at least one other bacterium from a set of genera that included Methylobacterium, Bacillus, Caulobacter, Delftia, and Variovorax. C. acnes may also be involved with outcompeting the Comamonas species, which were strongly associated with non-demented brain microbiota, whose early destruction could be the first stage of disease. Our results are also consistent with a leaky blood-brain barrier or lymphatic network that allows bacteria, viruses, fungi, or other pathogens to enter the brain.

Treatment of Alzheimer's Disease: Beyond Symptomatic Therapies

In an ever-increasing aged world, Alzheimer's disease (AD) represents the first cause of dementia and one of the first chronic diseases in elderly people. With 55 million people affected, the WHO considers AD to be a disease with public priority. Unfortunately, there are no final cures for this pathology. Treatment strategies are aimed to mitigate symptoms, i.e., acetylcholinesterase inhibitors (AChEI) and the N-Methyl-D-aspartate (NMDA) antagonist Memantine. At present, the best approaches for managing the disease seem to combine pharmacological and non-pharmacological therapies to stimulate cognitive reserve. Over the last twenty years, a number of drugs have been discovered acting on the well-established biological hallmarks of AD, deposition of β-amyloid aggregates and accumulation of hyperphosphorylated tau protein in cells. Although previous efforts disappointed expectations, a new era in treating AD has been working its way recently. The Food and Drug Administration (FDA) gave conditional approval of the first disease-modifying therapy (DMT) for the treatment of AD, aducanumab, a monoclonal antibody (mAb) designed against Aβ plaques and oligomers in 2021, and in January 2023, the FDA granted accelerated approval for a second monoclonal antibody, Lecanemab. This review describes ongoing clinical trials with DMTs and non-pharmacological therapies. We will also present a future scenario based on new biomarkers that can detect AD in preclinical or prodromal stages, identify people at risk of developing AD, and allow an early and curative treatment.

Emerging concepts towards a translational framework in Alzheimer's disease

Over the past decades, significant efforts have been made to understand the precise mechanisms underlying the pathogenesis of Alzheimer's disease (AD), the most common cause of dementia. However, clinical trials targeting AD pathological hallmarks have consistently failed. Refinement of AD conceptualization, modeling, and assessment is key to developing successful therapies. Here, we review critical findings and discuss emerging ideas to integrate molecular mechanisms and clinical approaches in AD. We further propose a refined workflow for animal studies incorporating multimodal biomarkers used in clinical studies - delineating critical paths for drug discovery and translation. Addressing unresolved questions with the proposed conceptual and experimental framework may accelerate the development of effective disease-modifying strategies for AD.

Using Stems to Bear Fruit: Deciphering the Role of Alzheimer's Disease Risk Loci in Human-Induced Pluripotent Stem Cell-Derived Microglia

Alzheimer's disease (AD) is the most common neurodegenerative disorder globally. In people aged 65 and older, it is estimated that 1 in 9 currently live with the disease. With aging being the greatest risk factor for disease onset, the physiological, social and economic burden continues to rise. Thus, AD remains a public health priority. Since 2007, genome-wide association studies (GWAS) have identified over 80 genomic loci with variants associated with increased AD risk. Although some variants are beginning to be characterized, the effects of many risk loci remain to be elucidated. One advancement which may help provide a patient-focused approach to tackle this issue is the application of gene editing technology and human-induced pluripotent stem cells (hiPSCs). The relatively non-invasive acquisition of cells from patients with known AD risk loci may provide important insights into the pathological role of these risk variants. Of the risk genes identified, many have been associated with the immune system, including ABCA7, CLU, MEF2C, PICALM and TREM2-genes known to be highly expressed in microglia. This review will detail the potential of using hiPSC-derived microglia to help clarify the role of immune-associated genetic risk variants in AD.

The past and present of therapeutic strategy for Alzheimer's diseases: potential for stem cell therapy

Alzheimer's disease (AD), a progressive neurodegenerative disease characterized by cognitive dysfunction and neuropsychiatric symptoms, is the most prevalent form of dementia among the elderly. Amyloid aggregation, tau hyperphosphorylation, and neural cell loss are the main pathological features. Various hypotheses have been proposed to explain the development of AD. Some therapeutic agents have shown clinical benefits in patients with AD; however, many of these agents have failed. The degree of neural cell loss is associated with the severity of AD. Adult neurogenesis, which governs cognitive and emotional behaviors, occurs in the hippocampus, and some research groups have reported that neural cell transplantation into the hippocampus improves cognitive dysfunction in AD model mice. Based on these clinical findings, stem cell therapy for patients with AD has recently attracted attention. This review provides past and present therapeutic strategies for the management and treatment of AD.

Targeting EP2 Receptor for Drug Discovery: Strengths, Weaknesses, Opportunities, and Threats (SWOT) Analysis

Cyclooxygenase-1 and -2 (COX1 and COX2) derived endogenous ligand prostaglandin-E2 (PGE2) triggers several physiological and pathological conditions. It mediates signaling through four G-protein coupled receptors, EP1, EP2, EP3, and EP4. Among these, EP2 is expressed throughout the body including the brain and uterus. The functional role of EP2 has been extensively studied using EP2 gene knockout mice, cellular models, and selective small molecule agonists and antagonists for this receptor. The efficacy data from in vitro and in vivo animal models indicate that EP2 receptor is a major proinflammatory mediator with deleterious functions in a variety of diseases suggesting a path forward for EP2 inhibitors as the next generation of selective anti-inflammatory and antiproliferative agents. Interestingly in certain diseases, EP2 action is beneficial; therefore, EP2 agonists seem to be clinically useful. Here, we highlight the strengths, weaknesses, opportunities, and potential threats (SWOT analysis) for targeting EP2 receptor for therapeutic development for a variety of unmet clinical needs.

Exploring Rosiglitazone's Potential to Treat Alzheimer's Disease through the Modulation of Brain-Derived Neurotrophic Factor

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that debilitates over 55 million individuals worldwide. Currently, treatments manage and alleviate its symptoms; however, there is still a need to find a therapy that prevents or halts disease progression. Since AD has been labeled as "type 3 diabetes" due to its similarity in pathological hallmarks, molecular pathways, and comorbidity with type 2 diabetes mellitus (T2DM), there is growing interest in using anti-diabetic drugs for its treatment. Rosiglitazone (RSG) is a peroxisome proliferator-activated receptor-gamma agonist that reduces hyperglycemia and hyperinsulinemia and improves insulin signaling. In cellular and rodent models of T2DM-associated cognitive decline and AD, RSG has been reported to improve cognitive impairment and reverse AD-like pathology; however, results from human clinical trials remain consistently unsuccessful. RSG has also been reported to modulate the expression of brain-derived neurotrophic factor (BDNF), a protein that regulates neuroplasticity and energy homeostasis and is implicated in both AD and T2DM. The present review investigates RSG's limitations and potential therapeutic benefits in pre-clinical models of AD through its modulation of BDNF expression.

Transcranial magnetic stimulation effects on cognitive enhancement in mild cognitive impairment and Alzheimer's disease: a systematic review and meta-analysis

Introduction

Transcranial magnetic stimulation (TMS) is a non-invasive intervention that holds promise for improving cognitive function in individuals with Alzheimer's disease (AD). However, the effectiveness of this therapy and the optimal TMS parameters has not reached a consensus. The purpose of the meta-analysis was to systematically discern the effectiveness of different components of TMS protocols on cognitive improvement in patients with mild cognitive impairment (MCI) and AD.

Methods

The meta-analysis was preregistered on Prospero (registration number: CRD42022345482). PubMed, Web of Science, Science Direct, and Cochrane Library databases were used to search, screen and identify eligible studies with the following keywords: Transcranial Magnetic Stimulation OR TMS OR theta burst stimulation AND Alzheimer OR Alzheimers OR Alzheimer's OR mild cognitive impairment OR MCI. Randomized controlled trials (RCTs) of participants with accepted standardized diagnostic criteria were searched by two authors independently. The risk of bias was assessed using an adapted Cochrane Risk of Bias tool. Standardized mean difference (SMD) and 95% confidence interval (CI) were calculated using the random-effects models. Subgroup analyses were performed to investigate the influential factors.

Results

A total of 21 studies and 25 trials were included in this meta-analysis. The findings revealed a significant overall cognition improvement of real stimulation compared with sham stimulation (short-term effects: SMD, 0.91; 95% CI 0.44-1.38; P < 0.01; long-lasting effects: SMD, 0.91; 95% CI 0.27-1.55; P < 0.01). Subgroup analysis demonstrated that stimulation of the left dorsolateral prefrontal cortex and bilateral cerebellums, as well as moderate frequency stimulation (5 Hz and 10 Hz) on mild and moderate cognitive impairment patients, were more effective than other TMS protocols. However, the additional application of cognitive training showed no significant improvement.

Conclusion

Cognitive improvement effect of TMS was demonstrated in MCI and AD patients in both short-term assessment and long-lasting outcomes, and the efficiency of TMS is affected by the stimulation frequency, stimulation site, and participant characteristics. Further RCTs are needed to validate the findings of our subgroup analysis.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022345482, identifier: CRD42022345482.

Effects of Probiotics on Colitis-Induced Exacerbation of Alzheimer's Disease in AppNL-G-F Mice

Alzheimer's disease (AD) is characterized by progressive cognitive decline and is a leading cause of death in the United States. Neuroinflammation has been implicated in the progression of AD, and several recent studies suggest that peripheral immune dysfunction may influence the disease. Continuing evidence indicates that intestinal dysbiosis is an attribute of AD, and inflammatory bowel disease (IBD) has been shown to aggravate cognitive impairment. Previously, we separately demonstrated that an IBD-like condition exacerbates AD-related changes in the brains of the AppNL-G-F mouse model of AD, while probiotic intervention has an attenuating effect. In this study, we investigated the combination of a dietary probiotic and an IBD-like condition for effects on the brains of mice. Male C57BL/6 wild type (WT) and AppNL-G-F mice were randomly divided into four groups: vehicle control, oral probiotic, dextran sulfate sodium (DSS), and DSS given with probiotics. As anticipated, probiotic treatment attenuated the DSS-induced colitis disease activity index in WT and AppNL-G-F mice. Although probiotic feeding significantly attenuated the DSS-mediated increase in WT colonic lipocalin levels, it was less protective in the AppNL-G-F DSS-treated group. In parallel with the intestinal changes, combined probiotic and DSS treatment increased microglial, neutrophil elastase, and 5hmC immunoreactivity while decreasing c-Fos staining compared to DSS treatment alone in the brains of WT mice. Although less abundant, probiotic combined with DSS treatment demonstrated a few similar changes in AppNL-G-F brains with increased microglial and decreased c-Fos immunoreactivity in addition to a slight increase in Aβ plaque staining. Both probiotic and DSS treatment also altered the levels of several cytokines in WT and AppNL-G-F brains, with a unique increase in the levels of TNFα and IL-2 being observed in only AppNL-G-F mice following combined DSS and probiotic treatment. Our data indicate that, while dietary probiotic intervention provides protection against the colitis-like condition, it also influences numerous glial, cytokine, and neuronal changes in the brain that may regulate brain function and the progression of AD.

Localized proteomic differences in the choroid plexus of Alzheimer's disease and epilepsy patients

Introduction

Alzheimer's disease (AD) and epilepsy are reciprocally related. Among sporadic AD patients, clinical seizures occur in 10-22% and subclinical epileptiform abnormalities occur in 22-54%. Cognitive deficits, especially short-term memory impairments, occur in most epilepsy patients. Common neurophysiological and molecular mechanisms occur in AD and epilepsy. The choroid plexus undergoes pathological changes in aging, AD, and epilepsy, including decreased CSF turnover, amyloid beta (Aβ), and tau accumulation due to impaired clearance and disrupted CSF amino acid homeostasis. This pathology may contribute to synaptic dysfunction in AD and epilepsy.

Methods

We evaluated control (n = 8), severe AD (n = 8; A3, B3, C3 neuropathology), and epilepsy autopsy cases (n = 12) using laser capture microdissection (LCM) followed by label-free quantitative mass spectrometry on the choroid plexus adjacent to the hippocampus at the lateral geniculate nucleus level.

Results

Proteomics identified 2,459 proteins in the choroid plexus. At a 5% false discovery rate (FDR), 616 proteins were differentially expressed in AD vs. control, 1 protein in epilepsy vs. control, and 438 proteins in AD vs. epilepsy. There was more variability in the epilepsy group across syndromes. The top 20 signaling pathways associated with differentially expressed proteins in AD vs. control included cell metabolism pathways; activated fatty acid beta-oxidation (p = 2.00 x 10^-7, z = 3.00), and inhibited glycolysis (p = 1.00 x 10^-12, z = -3.46). For AD vs. epilepsy, the altered pathways included cell metabolism pathways, activated complement system (p = 5.62 x 10^-5, z = 2.00), and pathogen-induced cytokine storm (p = 2.19 x 10^-2, z = 3.61). Of the 617 altered proteins in AD and epilepsy vs. controls, 497 (81%) were positively correlated (p < 0.0001, R² = 0.27).

Discussion

We found altered signaling pathways in the choroid plexus of severe AD cases and many correlated changes in the protein expression of cell metabolism pathways in AD and epilepsy cases. The shared molecular mechanisms should be investigated further to distinguish primary pathogenic changes from the secondary ones. These mechanisms could inform novel therapeutic strategies to prevent disease progression or restore normal function. A focus on dual-diagnosed AD/epilepsy cases, specific epilepsy syndromes, such as temporal lobe epilepsy, and changes across different severity levels in AD and epilepsy would add to our understanding.

Extrasynaptic NMDA receptors in acute and chronic excitotoxicity: implications for preventive treatments of ischemic stroke and late-onset Alzheimer's disease

Stroke and late-onset Alzheimer's disease (AD) are risk factors for each other; the comorbidity of these brain disorders in aging individuals represents a significant challenge in basic research and clinical practice. The similarities and differences between stroke and AD in terms of pathogenesis and pathophysiology, however, have rarely been comparably reviewed. Here, we discuss the research background and recent progresses that are important and informative for the comorbidity of stroke and late-onset AD and related dementia (ADRD). Glutamatergic NMDA receptor (NMDAR) activity and NMDAR-mediated Ca²⁺ influx are essential for neuronal function and cell survival. An ischemic insult, however, can cause rapid increases in glutamate concentration and excessive activation of NMDARs, leading to swift Ca²⁺ overload in neuronal cells and acute excitotoxicity within hours and days. On the other hand, mild upregulation of NMDAR activity, commonly seen in AD animal models and patients, is not immediately cytotoxic. Sustained NMDAR hyperactivity and Ca²⁺ dysregulation lasting from months to years, nevertheless, can be pathogenic for slowly evolving events, i.e. degenerative excitotoxicity, in the development of AD/ADRD. Specifically, Ca²⁺ influx mediated by extrasynaptic NMDARs (eNMDARs) and a downstream pathway mediated by transient receptor potential cation channel subfamily M member (TRPM) are primarily responsible for excitotoxicity. On the other hand, the NMDAR subunit GluN3A plays a "gatekeeper" role in NMDAR activity and a neuroprotective role against both acute and chronic excitotoxicity. Thus, ischemic stroke and AD share an NMDAR- and Ca²⁺-mediated pathogenic mechanism that provides a common receptor target for preventive and possibly disease-modifying therapies. Memantine (MEM) preferentially blocks eNMDARs and was approved by the Federal Drug Administration (FDA) for symptomatic treatment of moderate-to-severe AD with variable efficacy. According to the pathogenic role of eNMDARs, it is conceivable that MEM and other eNMDAR antagonists should be administered much earlier, preferably during the presymptomatic phases of AD/ADRD. This anti-AD treatment could simultaneously serve as a preconditioning strategy against stroke that attacks ≥ 50% of AD patients. Future research on the regulation of NMDARs, enduring control of eNMDARs, Ca²⁺ homeostasis, and downstream events will provide a promising opportunity to understand and treat the comorbidity of AD/ADRD and stroke.

Bibliometric analysis of global research on the role of apolipoprotein E in Alzheimer's disease

Alzheimer's disease (AD) has attracted considerable attention from the public and scientific researchers, leading to a rapid growth in relevant research on this disorder in the last 10 years. The present study aimed to conduct a bibliometric analysis to elucidate the trends of global research on the role of apolipoprotein E in AD in the past decade. Three bibliometric software (CiteSpace, VOSviewer, and R Bibliometrix) were used to analyze the active journals, countries/regions, institutes, authors, co-cited references, and keywords in this field. The USA was the most influential country, and the University of California was the most productive institute. Zetterberg H contributed the highest number of publications, and Petersen RC was the most cited author in this field. On the basis of the co-cited reference analysis, knowledge base on biomarkers, risk factors, and mechanisms were updated in the past decade. Current research hotspots are shifting to tau-related mechanisms and identification of genetic risk factors. Our study provides insights into the developing knowledge base and trends related to research on apolipoprotein E in AD, which may provide new directions for further research in this field.

Alzheimer's Disease Treatment: The Search for a Breakthrough

As the search for modalities to cure Alzheimer's disease (AD) has made slow progress, research has now turned to innovative pathways involving neural and peripheral inflammation and neuro-regeneration. Widely used AD treatments provide only symptomatic relief without changing the disease course. The recently FDA-approved anti-amyloid drugs, aducanumab and lecanemab, have demonstrated unclear real-world efficacy with a substantial side effect profile. Interest is growing in targeting the early stages of AD before irreversible pathologic changes so that cognitive function and neuronal viability can be preserved. Neuroinflammation is a fundamental feature of AD that involves complex relationships among cerebral immune cells and pro-inflammatory cytokines, which could be altered pharmacologically by AD therapy. Here, we provide an overview of the manipulations attempted in pre-clinical experiments. These include inhibition of microglial receptors, attenuation of inflammation and enhancement of toxin-clearing autophagy. In addition, modulation of the microbiome-brain-gut axis, dietary changes, and increased mental and physical exercise are under evaluation as ways to optimize brain health. As the scientific and medical communities work together, new solutions may be on the horizon to slow or halt AD progression.

Understanding Barriers Along the Patient Journey in Alzheimer's Disease Using Social Media Data

INTRODUCTION

We speculated that social media data from Alzheimer's disease (AD) stakeholders (patients, caregivers, and clinicians) could identify barriers along the patient journey in AD, and that insights gained may help devise strategies to remove barriers, and ultimately improve the patient journey.

METHODS

Our sample was drawn from a repository of social media posts extracted from 112 public sources between January 1998 and December 2021 using natural language processing text-mining algorithms. The patient journey was classified into three phases: (1) early signs/experiences (Early Signs); (2) screening/assessment/diagnosis (Screening); and (3) treatment/management (Treatment). In the Early Signs phase, issues/challenges derived from a conceptual AD identification framework (ADIF) were examined. In subsequent phases, behavioral/psychiatric challenges, access/barriers to health care, screening/diagnostic methods, and symptomatic treatments for AD were identified. Posts were classified by AD stakeholder type or disease stage, if possible.

RESULTS

We identified 225,977 AD patient journey-related social media posts. Anxiety was a predominant issue/challenge in all patient journey phases. In the Screening and Treatment phases combined, access/barriers to care were described in 16% of posts; unwillingness/resistance to seeking care was a major barrier (≥ 75% of access-related posts across all stakeholders). Commonly identified structural barriers (e.g., affordability/cost, geography/transportation/distance) were more common in patient/caregiver posts than clinician posts. Among Screening-related posts, imaging/scans were commonly mentioned by all stakeholders; biomarkers were more commonly mentioned by patients than clinicians. Treatment-related concerns were identified in 17% of stakeholder-specified posts that named pharmacological agents/classes for the symptomatic management of AD.

CONCLUSION

This descriptive analysis of out-of-clinic experiences reflected in AD social media posts found that unwillingness/resistance to seeking care was a key barrier, followed by structural barriers to health care, such as affordability/cost. Insights from the lived experiences of AD stakeholders are valuable and highlight the need to improve the patient journey in AD and ease patient and caregiver burden.

Development of FERM domain protein-protein interaction inhibitors for MSN and CD44 as a potential therapeutic strategy for Alzheimer's disease

Recent genome-wide association studies have revealed genetic risk factors for Alzheimer's disease (AD) that are exclusively expressed in microglia within the brain. A proteomics approach identified moesin (MSN), a FERM (four-point-one ezrin radixin moesin) domain protein, and the receptor CD44 as hub proteins found within a co-expression module strongly linked to AD clinical and pathological traits as well as microglia. The FERM domain of MSN interacts with the phospholipid PIP2 and the cytoplasmic tails of receptors such as CD44. This study explored the feasibility of developing protein-protein interaction inhibitors that target the MSN-CD44 interaction. Structural and mutational analyses revealed that the FERM domain of MSN binds to CD44 by incorporating a beta strand within the F3 lobe. Phage-display studies identified an allosteric site located close to the PIP2 binding site in the FERM domain that affects CD44 binding within the F3 lobe. These findings support a model in which PIP2 binding to the FERM domain stimulates receptor tail binding through an allosteric mechanism that causes the F3 lobe to adopt an open conformation permissive for binding. High-throughput screening of a chemical library identified two compounds that disrupt the MSN-CD44 interaction, and one compound series was further optimized for biochemical activity, specificity, and solubility. The results suggest that the FERM domain holds potential as a drug development target. The small molecule preliminary leads generated from the study could serve as a foundation for additional medicinal chemistry effort with the goal of controlling microglial activity in AD by modifying the MSN-CD44 interaction.

Revolutionizing the Early Detection of Alzheimer's Disease through Non-Invasive Biomarkers: The Role of Artificial Intelligence and Deep Learning

Alzheimer's disease (AD) is now classified as a silent pandemic due to concerning current statistics and future predictions. Despite this, no effective treatment or accurate diagnosis currently exists. The negative impacts of invasive techniques and the failure of clinical trials have prompted a shift in research towards non-invasive treatments. In light of this, there is a growing need for early detection of AD through non-invasive approaches. The abundance of data generated by non-invasive techniques such as blood component monitoring, imaging, wearable sensors, and bio-sensors not only offers a platform for more accurate and reliable bio-marker developments but also significantly reduces patient pain, psychological impact, risk of complications, and cost. Nevertheless, there are challenges concerning the computational analysis of the large quantities of data generated, which can provide crucial information for the early diagnosis of AD. Hence, the integration of artificial intelligence and deep learning is critical to addressing these challenges. This work attempts to examine some of the facts and the current situation of these approaches to AD diagnosis by leveraging the potential of these tools and utilizing the vast amount of non-invasive data in order to revolutionize the early detection of AD according to the principles of a new non-invasive medicine era.

The Role of Mitochondrial Dysfunction in Alzheimer's: Molecular Defects and Mitophagy-Enhancing Approaches

Alzheimer's disease (AD), a progressive and chronic neurodegenerative syndrome, is categorized by cognitive and memory damage caused by the aggregations of abnormal proteins, specifically including Tau proteins and β-amyloid in brain tissue. Moreover, mitochondrial dysfunctions are the principal causes of AD, which is associated with mitophagy impairment. Investigations exploring pharmacological therapies alongside AD have explicitly concentrated on molecules accomplished in preventing/abolishing the gatherings of the abovementioned proteins and mitochondria damages. Mitophagy is the removal of dead mitochondria by the autophagy process. Damages in mitophagy, the manner of diversified mitochondrial degeneracy by autophagy resulting in an ongoing aggregation of malfunctioning mitochondria, were also suggested to support AD. Recently, plentiful reports have suggested a link between defective mitophagy and AD. This treaty highlights updated outlines of modern innovations and developments on mitophagy machinery dysfunctions in AD brains. Moreover, therapeutic and nanotherapeutic strategies targeting mitochondrial dysfunction are also presented in this review. Based on the significant role of diminished mitophagy in AD, we suggest that the application of different therapeutic approaches aimed at stimulating mitophagy in AD would be beneficial for targeting or reducing the mitochondrial dysfunction induced by AD.

Sigma-2 Receptors—From Basic Biology to Therapeutic Target: A Focus on Age-Related Degenerative Diseases

There is a large unmet medical need to develop disease-modifying treatment options for individuals with age-related degenerative diseases of the central nervous system. The sigma-2 receptor (S2R), encoded by TMEM97, is expressed in brain and retinal cells, and regulates cell functions via its co-receptor progesterone receptor membrane component 1 (PGRMC1), and through other protein–protein interactions. Studies describing functions of S2R involve the manipulation of expression or pharmacological modulation using exogenous small-molecule ligands. These studies demonstrate that S2R modulates key pathways involved in age-related diseases including autophagy, trafficking, oxidative stress, and amyloid-β and α-synuclein toxicity. Furthermore, S2R modulation can ameliorate functional deficits in cell-based and animal models of disease. This review summarizes the current evidence-based understanding of S2R biology and function, and its potential as a therapeutic target for age-related degenerative diseases of the central nervous system, including Alzheimer’s disease, α-synucleinopathies, and dry age-related macular degeneration.