The "rights" of precision drug development for Alzheimer's disease

Secreted endogenous macrosomes reduce Aβ burden and ameliorate Alzheimer's disease

Innovative therapeutic strategies are urgently needed for Alzheimer's disease (AD) due to the increasing size of the aging population and the lack of effective drug treatment. Here, we report the therapeutic effects of extracellular vesicles (EVs) secreted by microglia, including macrosomes and small EVs, on AD-associated pathology. Macrosomes strongly inhibited β-amyloid (Aβ) aggregation and rescued cells from Aβ misfolding-induced cytotoxicity. Furthermore, macrosome administration reduced Aβ plaques and ameliorated cognitive impairment in mice with AD. In contrast, small EVs slightly promoted Aβ aggregation and did not improve AD pathology. Proteomic analysis of small EVs and macrosomes revealed that macrosomes harbor several important neuroprotective proteins that inhibit Aβ misfolding. In particular, the small integral membrane protein 10-like protein 2B in macrosomes has been shown to inhibit Aβ aggregation. Our observations provide an alternative therapeutic strategy for the treatment of AD over conventional ineffective drug treatments.

Probiotics as functional foods: How probiotics can alleviate the symptoms of neurological disabilities

Neurological disorders are diseases of the central nervous system with progressive loss of nervous tissue. One of the most difficult problems associated with neurological disorders is that there is no clear treatment for these diseases. In this review, the physiopathology of some neurodegenerative diseases, etiological causes, drugs used and their side effects, and finally the role of probiotics in controlling the symptoms of these neurodegenerative diseases are presented. Recently, researchers have focused more on the microbiome and the gut-brain axis, which may play a critical role in maintaining brain health. Probiotics are among the most important bacteria that have positive effects on the balance of homeostasis via influencing the microbiome. Other important functions of probiotics in alleviating symptoms of neurological disorders include anti-inflammatory properties, short-chain fatty acid production, and the production of various neurotransmitters. The effects of probiotics on the control of abnormalities seen in neurological disorders led to probiotics being referred to as "psychobiotic. Given the important role of the gut-brain axis and the imbalance of the gut microbiome in the etiology and symptoms of neurological disorders, probiotics could be considered safe agents that positively affect the balance of the microbiome as complementary treatment options for neurological disorders.

Ginsenoside Rg1 in neurological diseases: From bench to bedside

Ginseng has been used in China as a superior medicinal material for thousands of years that can nourish the five internal organs, calm the mind and benefit wisdom. Due to its anti-inflammatory, antioxidant and neuroprotective activities, one of the active components of ginseng, ginsenoside Rg1, has been extensively investigated in the remedy of brain disorders, especially dementia and depression. In this review, we summarized the research progress on the action mechanisms of Rg1 ameliorating depression-like behaviors, including inhibition of hyperfunction of hypothalamic-pituitary-adrenal (HPA) axis, regulation of synaptic plasticity and gut flora. Rg1 may alleviate Alzheimer's disease in the early phase, as well as in the middle-late phases through repairing dendrite, axon and microglia- and astrocyte-related inflammations. We also proposed that Rg1 could regulate memory state (the imbalance of working and aversive memory) caused by distinct stimuli. These laboratory studies would further the clinical trials on Rg1. From the prospective of drug development, we discussed the limitations of the present investigations and proposed our ideas to increase permeability and bioavailability of Rg1. Taken together, Rg1 has the potential to treat neuropsychiatric disorders, but a future in-depth investigation of the mechanisms is still required. In addition, drug development will benefit from the clinical trials in one specific neuropsychiatric disorder.

Alzheimer's disease drug development pipeline: 2023

Introduction

Drugs that prevent the onset, slow progression, or improve cognitive and behavioral symptoms of Alzheimer's disease (AD) are needed.

Methods

We searched ClinicalTrials.gov for all current Phase 1, 2 and 3 clinical trials for AD and mild cognitive impairment (MCI) attributed to AD. We created an automated computational database platform to search, archive, organize, and analyze the derived data. The Common Alzheimer's Disease Research Ontology (CADRO) was used to identify treatment targets and drug mechanisms.

Results

On the index date of January 1, 2023, there were 187 trials assessing 141 unique treatments for AD. Phase 3 included 36 agents in 55 trials; 87 agents were in 99 Phase 2 trials; and Phase 1 had 31 agents in 33 trials. Disease-modifying therapies were the most common drugs comprising 79% of drugs in trials. Twenty-eight percent of candidate therapies are repurposed agents. Populating all current Phase 1, 2, and 3 trials will require 57,465 participants.

Discussion

The AD drug development pipeline is advancing agents directed at a variety of target processes.

HIGHLIGHTS

There are currently 187 trials assessing 141 drugs for the treatment of Alzheimer's disease (AD).Drugs in the AD pipeline address a variety of pathological processes.More than 57,000 participants will be required to populate all currently registered trials.

Clinical utility of an antibody-free LC-MS method to detect brain amyloid deposition in cognitively unimpaired individuals from the screening visit of the A4 Study

INTRODUCTION

This study explored the ability of plasma amyloid beta (Aβ)42/Aβ40 to identify brain amyloid deposition in cognitively unimpaired (CU) individuals.

METHODS

Plasma Aβ was quantified with an antibody-free high-performance liquid chromatography tandem mass spectrometry method from Araclon Biotech (ABtest-MS) in a subset of 731 CU individuals from the screening visit of the Anti-Amyloid Treatment in Asymptomatic Alzheimer's (A4) Study, to assess associations of Aβ42/Aβ40 with Aβ positron emission tomography (PET).

RESULTS

A model including Aβ42/Aβ40, age, apolipoprotein E ε4, and recruitment site identified Aβ PET status with an area under the curve of 0.88 and an overall accuracy of 81%. A plasma-based pre-screening step could save up to 42% of the total number of Aβ PET scans.

DISCUSSION

ABtest-MS accurately identified brain amyloid deposition in a population of CU individuals, supporting its implementation in AD secondary prevention trials to reduce recruitment time and costs. Although a certain degree of heterogeneity is inherent to large and multicentric trials, ABtest-MS could be more robust to pre-analytical bias compared to other immunoprecipitation mass spectrometry methods.

HIGHLIGHTS

Plasma amyloid beta (Aβ)42/Aβ40 accurately identified brain Aβ deposition in cognitively unimpaired individuals from the Anti-Amyloid Treatment in Asymptomatic Alzheimer's (A4) Study.The inclusion of the recruitment site in the predictive models has a non-negligible effect.A plasma biomarker-based model could reduce recruitment costs in Alzheimer's disease secondary prevention trials.Antibody-free liquid chromatography mass spectrometry methods may be more robust to pre-analytical variability than other platforms.

Poor Translatability of Biomedical Research Using Animals - A Narrative Review

The failure rate for the translation of drugs from animal testing to human treatments remains at over 92%, where it has been for the past few decades. The majority of these failures are due to unexpected toxicity - that is, safety issues revealed in human trials that were not apparent in animal tests - or lack of efficacy. However, the use of more innovative tools, such as organs-on-chips, in the preclinical pipeline for drug testing, has revealed that these tools are more able to predict unexpected safety events prior to clinical trials and so can be used for this, as well as for efficacy testing. Here, we review several disease areas, and consider how the use of animal models has failed to offer effective new treatments. We also make some suggestions as to how the more human-relevant new approach methodologies might be applied to address this.

Forecasting individual progression trajectories in Alzheimer's disease

The anticipation of progression of Alzheimer's disease (AD) is crucial for evaluations of secondary prevention measures thought to modify the disease trajectory. However, it is difficult to forecast the natural progression of AD, notably because several functions decline at different ages and different rates in different patients. We evaluate here AD Course Map, a statistical model predicting the progression of neuropsychological assessments and imaging biomarkers for a patient from current medical and radiological data at early disease stages. We tested the method on more than 96,000 cases, with a pool of more than 4,600 patients from four continents. We measured the accuracy of the method for selecting participants displaying a progression of clinical endpoints during a hypothetical trial. We show that enriching the population with the predicted progressors decreases the required sample size by 38% to 50%, depending on trial duration, outcome, and targeted disease stage, from asymptomatic individuals at risk of AD to subjects with early and mild AD. We show that the method introduces no biases regarding sex or geographic locations and is robust to missing data. It performs best at the earliest stages of disease and is therefore highly suitable for use in prevention trials.

Biomarkers for dementia in Latin American countries: Gaps and opportunities

Limited knowledge on dementia biomarkers in Latin American and Caribbean (LAC) countries remains a serious barrier. Here, we reported a survey to explore the ongoing work, needs, interests, potential barriers, and opportunities for future studies related to biomarkers. The results show that neuroimaging is the most used biomarker (73%), followed by genetic studies (40%), peripheral fluids biomarkers (31%), and cerebrospinal fluid biomarkers (29%). Regarding barriers in LAC, lack of funding appears to undermine the implementation of biomarkers in clinical or research settings, followed by insufficient infrastructure and training. The survey revealed that despite the above barriers, the region holds a great potential to advance dementia biomarkers research. Considering the unique contributions that LAC could make to this growing field, we highlight the urgent need to expand biomarker research. These insights allowed us to propose an action plan that addresses the recommendations for a biomarker framework recently proposed by regional experts.

Why a clinical trial is as good as its outcome measure: A framework for the selection and use of cognitive outcome measures for clinical trials of Alzheimer's disease

A crucial aspect of any clinical trial is using the right outcome measure to assess treatment efficacy. Compared to the rapidly evolved understanding and measurement of pathophysiology in preclinical and early symptomatic stages of Alzheimer's disease (AD), relatively less progress has been made in the evolution of clinical outcome assessments (COAs) for those stages. The current paper aims to provide a benchmark for the design and evaluation of COAs for use in early AD trials. We discuss lessons learned on capturing cognitive changes in predementia stages of AD, including challenges when validating novel COAs for those early stages and necessary evidence for their implementation in clinical trials. Moving forward, we propose a multi-step framework to advance the use of more effective COAs to assess clinically meaningful changes in early AD, which will hopefully contribute to the much-needed consensus around more appropriate outcome measures to assess clinical efficacy of putative treatments. HIGHLIGHTS: We discuss lessons learned on capturing cognitive changes in predementia stages of AD. We propose a framework for the design and evaluation of performance based cognitive tests for use in early AD trials. We provide recommendations to facilitate the implementation of more effective cognitive outcome measures in AD trials.

Three-dimensional chromatin architecture datasets for aging and Alzheimer's disease

Recently, increasing studies are indicating a close association between dysregulated enhancers and neurodegenerative diseases, such as Alzheimer's disease (AD). However, their contributions were poorly defined for lacking direct links to disease genes. To bridge this gap, we presented the Hi-C datasets of 4 AD patients, 4 dementia-free aged and 3 young subjects, including 30 billion reads. As applications, we utilized them to link the AD risk SNPs and dysregulated epigenetic marks to the target genes. Combining with epigenetic data, we observed more detailed interactions among regulatory regions and found that many known AD risk genes were under long-distance promoter-enhancer interactions. For future AD and aging studies, our datasets provide a reference landscape to better interpret findings of association and epigenetic studies for AD and aging process.

Gait Indicators Contribute to Screening Cognitive Impairment: A Single- and Dual-Task Gait Study

Background: Screening cognitive impairment is complex and not an appliance for early screening. Gait performance is strongly associated with cognitive impairment. Objectives: We aimed to explore gait indicators that could potentially screen cognitive dysfunction. Methods: A total of 235 subjects were recruited from June 2021 to June 2022. Four gait tasks, including the walking test, the timed “Up & Go” test (TUG), foot pressure balance (FPB), and one-legged standing with eyes closed test (OLS-EC), were performed. Moreover, in the walking test, participants were instructed to walk at their usual pace for the single-gait test. For the dual-task tests, participants walked at their usual pace while counting backward from 100 by 1s. The data were analyzed by the independent sample t-test, univariate and multivariate logistic regression, a linear trend, stratified and interaction analysis, the receiver operating characteristic (ROC) curve, and Pearson’s correlations. Results: Among the 235 participants, 81 (34.5%) were men and 154 (65.5%) were women. The mean age of participants was 72 ± 7.836 years. The control, MCI, mild AD, and severe AD groups had means of 71, 63, 71, and 30, respectively. After adjusting for age, sex, education, and body mass index (BMI), the dual-task toe-off-ground angle (TOA) (odds ratio (OR) = 0.911, 95% confidence interval (CI): 0.847, 0.979), single-task TOA (OR = 0.904, 95% CI: 0.841−0.971), and the timed “Up & Go” time (TUGT) (OR = 1.515, 95% CI: 1.243−1.846) were significantly associated with an increased risk of cognitive impairment. In addition, the trend test and stratified analysis results had no significant differences (all p > 0.05). The area under the roc curve (AUC) values of TOA in the dual-task and TUGT were 0.812 and 0.847, respectively. Additionally, TOA < 36.75° in the dual-task, TOA < 38.90° in the single-task, and TUGT > 9.83 seconds (s) are likely to indicate cognitive impairment. The cognitive assessment scale scores were significantly correlated with TOA (all r > 0.3, p < 0.001) and TUGT (all r > 0.2), respectively. Conclusion: TOA and TUGT scores are, in some circumstances, associated with cognitive impairment; therefore, they can be used as simple initial screenings to identify patients at risk.

Recommendations for robust and reproducible preclinical research in personalised medicine

BACKGROUND

Personalised medicine is a medical model that aims to provide tailor-made prevention and treatment strategies for defined groups of individuals. The concept brings new challenges to the translational step, both in clinical relevance and validity of models. We have developed a set of recommendations aimed at improving the robustness of preclinical methods in translational research for personalised medicine.

METHODS

These recommendations have been developed following four main steps: (1) a scoping review of the literature with a gap analysis, (2) working sessions with a wide range of experts in the field, (3) a consensus workshop, and (4) preparation of the final set of recommendations.

RESULTS

Despite the progress in developing innovative and complex preclinical model systems, to date there are fundamental deficits in translational methods that prevent the further development of personalised medicine. The literature review highlighted five main gaps, relating to the relevance of experimental models, quality assessment practices, reporting, regulation, and a gap between preclinical and clinical research. We identified five points of focus for the recommendations, based on the consensus reached during the consultation meetings: (1) clinically relevant translational research, (2) robust model development, (3) transparency and education, (4) revised regulation, and (5) interaction with clinical research and patient engagement. Here, we present a set of 15 recommendations aimed at improving the robustness of preclinical methods in translational research for personalised medicine.

CONCLUSIONS

Appropriate preclinical models should be an integral contributor to interventional clinical trial success rates, and predictive translational models are a fundamental requirement to realise the dream of personalised medicine. The implementation of these guidelines is ambitious, and it is only through the active involvement of all relevant stakeholders in this field that we will be able to make an impact and effectuate a change which will facilitate improved translation of personalised medicine in the future.

Therapeutic Potential of Natural Compounds in Neurodegenerative Diseases: Insights from Clinical Trials

Neurodegenerative diseases are caused by the gradual loss of neurons' function. These neurological illnesses remain incurable, and current medicines only alleviate the symptoms. Given the social and economic burden caused by the rising frequency of neurodegenerative diseases, there is an urgent need for the development of appropriate therapeutics. Natural compounds are gaining popularity as alternatives to synthetic drugs due to their neuroprotective properties and higher biocompatibility. While natural compounds' therapeutic effects for neurodegenerative disease treatment have been investigated in numerous in vitro and in vivo studies, only few have moved to clinical trials. This article provides the first systematic review of the clinical trials evaluating natural compounds' safety and efficacy for the treatment of the five most prevalent neurodegenerative disorders: Alzheimer's disease, Parkinson's disease, multiple sclerosis, amyotrophic lateral sclerosis, and Huntington's disease.

Experimental Medicine Approaches in Early-Phase CNS Drug Development

Traditionally, Phase 1 clinical trials were largely conducted in healthy normal volunteers and focused on collection of safety, tolerability, and pharmacokinetic data. However, in the CNS therapeutic area, with more drugs failing in later phase development, Phase 1 trials have undergone an evolution that includes incorporation of novel approaches involving novel study designs, inclusion of biomarkers, and early inclusion of patients to improve the pharmacologic understanding of novel CNS-active compounds early in clinical development with the hope of improving success in later phase pivotal trials. In this chapter, the authors will discuss the changing landscape of Phase 1 clinical trials in CNS, including novel trial methodology, inclusion of pharmacodynamic biomarkers, and experimental medicine approaches to inform early decision-making in clinical development.

Capturing Measures That Matter: The Potential Value of Digital Measures of Physical Behavior for Alzheimer's Disease Drug Development

Alzheimer's disease (AD) is a devastating neurodegenerative disease and the primary cause of dementia worldwide. Despite the magnitude of AD's impact on patients, caregivers, and society, nearly all AD clinical trials fail. A potential contributor to this high rate of failure is that established clinical outcome assessments fail to capture subtle clinical changes, entail high burden for patients and their caregivers, and ineffectively address the aspects of health deemed important by patients and their caregivers. AD progression is associated with widespread changes in physical behavior that have impacts on the ability to function independently, which is a meaningful aspect of health for patients with AD and important for diagnosis. However, established assessments of functional independence remain underutilized in AD clinical trials and are limited by subjective biases and ceiling effects. Digital measures of real-world physical behavior assessed passively, continuously, and remotely using digital health technologies have the potential to address some of these limitations and to capture aspects of functional independence in patients with AD. In particular, measures of real-world gait, physical activity, and life-space mobility captured with wearable sensors may offer value. Additional research is needed to understand the validity, feasibility, and acceptability of these measures in AD clinical research.

The Case for a Novel Therapeutic Approach to Dementia: Small Molecule Hepatocyte Growth Factor (HGF/MET) Positive Modulators

An estimated 6.5 million Americans aged 65 years or older have Alzheimer's disease (AD), which will grow to 13.8 million Americans by 2060. Despite the growing burden of dementia, no fundamental change in drug development for AD has been seen in > 20 years. Currently approved drugs for AD produce only modest symptomatic improvements in cognition with small effect sizes. A growing mismatch exists between the urgent need to develop effective drugs for symptomatic AD and the largely failed search for disease modification. The failure rate of clinical trials in AD is high overall, and in particular for disease-modifying therapies. Research efforts in AD have focused predominantly on amyloid-β and tau pathologies, but limiting clinical research to these "classical hallmarks" of the disease does not address the most urgent patient, caregiver, or societal needs. Rather, clinical research should consider the complex pathophysiology of AD. Innovative approaches are needed that provide outside-the-box thinking, and re-imagine trial design, interventions, and outcomes as well as progress in proteomics and fluid biomarker analytics for both diagnostics and disease monitoring. A new approach offering a highly specific, yet multi-pronged intervention that exerts positive modulation on the HGF/MET neurotrophic system is currently being tested in mid-to-late-stage clinical trials in mild to moderate AD. Findings from such trials may provide data to support novel approaches for development of innovative drugs for treating AD at various disease stages, including among patients already symptomatic, and may offer benefits for other neurodegenerative diseases.

Amyloid Cascade Hypothesis for the Treatment of Alzheimer's Disease: Progress and Challenges

The amyloid cascade hypothesis has always been a research focus in the therapeutic field of Alzheimer's disease (AD) since it was put forward. Numerous researchers attempted to find drugs for AD treatment based on this hypothesis. To promote the research of anti-AD drugs development, the current hypothesis and pathogenesis were reviewed with expounding of β-amyloid generation from its precursor protein and related transformations. Meanwhile, the present drug development strategies aimed at each stage in this hypothesis were also summarized. Several strategies especially immunotherapy showed the optimistic results in clinical trials, but only a small percentage of them eventually succeeded. In this review, we also tried to point out some common problems of drug development in preclinical and clinical studies which might be settled through multidisciplinary cooperation as well as the understanding that reinforces the amyloid cascade hypothesis.

Antibacterial and β-amyloid precursor protein-cleaving enzyme 1 inhibitory polyketides from the fungus Aspergillus chevalieri

One new prenylated benzenoid, (±)-chevalieric acid (1), and four new anthraquinone derivatives, (10S,12S)-, (10S,12R)-, (10R,12S)-, and (10R,12R)-chevalierone (2-5), together with ten previously described compounds (6-15), were isolated from the fungus Aspergillus chevalieri (L. Mangin) Thom and Church. The structures of new compounds were elucidated by extensive 1D and 2D nuclear magnetic resonance (NMR), and HRESIMS spectroscopic analysis. The absolute configurations of 2-5 were determined by experimental and calculated electronic circular dichroism (ECD) and DP4+ analysis. Compound 10 showed weak cytotoxicity against human lung cancer cell line A549 with IC50 39.68 μM. Compounds 2-5 exhibited antibacterial activities against the methicillin-resistant Staphylococcus aureus (MRSA) and opportunistic pathogenic bacterium Pseudomonas aeruginosa. The MIC value for compound 6 against MRSA is 44.02 μM. Additionally, Compounds 8, 10, 11 showed weak to moderate inhibitory activities against the β-secretase (BACE1), with IC50 values of 36.1, 40.9, 34.9 μM, respectively.

Photobiomodulation for Hypertension and Alzheimer's Disease

Although the cause(s) of Alzheimer's disease in the majority of cases remains elusive, it has long been associated with hypertension. In animal models of the disease, hypertension has been shown to exacerbate Alzheimer-like pathology and behavior, while in humans, hypertension during mid-life increases the risk of developing the disease later in life. Unfortunately, once individuals are diagnosed with the disease, there are few therapeutic options available. There is neither an effective symptomatic treatment, one that treats the debilitating cognitive and memory deficits, nor, more importantly, a neuroprotective treatment, one that stops the relentless progression of the pathology. Further, there is no specific preventative treatment that offsets the onset of the disease. A key factor or clue in this quest for an effective preventative and therapeutic treatment may lie in the contribution of hypertension to the disease. In this review, we explore the idea that photobiomodulation, the application of specific wavelengths of light onto body tissues, can reduce the neuropathology and behavioral deficits in Alzheimer's disease by controlling hypertension. We suggest that treatment with photobiomodulation can be an effective preventative and therapeutic option for this neurodegenerative disease.

Role of chronic neuroinflammation in neuroplasticity and cognitive function: A hypothesis

OBJECTIVE

Evaluating the efficacy of 3,6'-dithioPomalidomide in 5xFAD Alzheimer's disease (AD) mice to test the hypothesis that neuroinflammation is directly involved in the development of synaptic/neuronal loss and cognitive decline.

BACKGROUND

Amyloid-β (Aβ) or tau-focused clinical trials have proved unsuccessful in mitigating AD-associated cognitive impairment. Identification of new drug targets is needed. Neuroinflammation is a therapeutic target in neurodegenerative disorders, and TNF-α a pivotal neuroinflammatory driver.

NEW HYPOTHESIS

AD-associated chronic neuroinflammation directly drives progressive synaptic/neuronal loss and cognitive decline. Pharmacologically mitigating microglial/astrocyte activation without altering Aβ generation will define the role of neuroinflammation in AD progression.

MAJOR CHALLENGES

Difficulty of TNF-α-lowering compounds reaching brain, and identification of a therapeutic-time window to preserve the beneficial role of neuroinflammatory processes.

LINKAGE TO OTHER MAJOR THEORIES

Microglia/astroglia are heavily implicated in maintenance of synaptic plasticity/function in healthy brain and are disrupted by Aβ. Mitigation of chronic gliosis can restore synaptic homeostasis/cognitive function.

Promising Blood Biomarkers for Clinical Use in Alzheimer's Disease: A Focused Update

Alzheimer’s disease (AD) is the most-common cause of neurodegenerative dementia, and it is characterized by abnormal amyloid and tau accumulation, which indicates neurodegeneration. AD has mostly been diagnosed clinically. However, ligand-specific positron emission tomography (PET) imaging, such as amyloid PET, and cerebrospinal fluid (CSF) biomarkers are needed to accurately diagnose AD, since they supplement the shortcomings of clinical diagnoses. Using biomarkers that represent the pathology of AD is essential (particularly when disease-modifying treatment is available) to identify the corresponding pathology of targeted therapy and for monitoring the treatment response. Although imaging and CSF biomarkers are useful, their widespread use is restricted by their high cost and the discomfort during the lumbar puncture, respectively. Recent advances in AD blood biomarkers shed light on their future use for clinical purposes. The amyloid β (Aβ)42/Aβ40 ratio and the concentrations of phosphorylated tau at threonine 181 and at threonine 217, and of neurofilament light in the blood were found to represent the pathology of Aβ, tau, and neurodegeneration in the brain when using automatic electrochemiluminescence technologies, single-molecule arrays, immunoprecipitation coupled with mass spectrometry, etc. These blood biomarkers are imminently expected to be incorporated into clinical practice to predict, diagnose, and determine the stage of AD. In this review we focus on advancements in the measurement technologies for blood biomarkers and the promising biomarkers that are approaching clinical application. We also discuss the current limitations, the needed further investigations, and the perspectives on their use.

Committee on High-quality Alzheimer's Disease Studies (CHADS) consensus report

BACKGROUND

Consensus guidance for the development and identification of high-quality Alzheimer's disease clinical trials is needed for protocol development and conduct of clinical trials.

METHODS

An ad hoc consensus committee was convened in conjunction with the Alzheimer's Association to develop consensus recommendations.

RESULTS

Consensus was readily reached for the need to provide scientific justification, registration of trials, institutional review board oversight, conflict of interest disclosure, funding source disclosure, defined trial population, recruitment resources, definition of the intervention, specification of trial duration, appropriate payment for participant engagement, risk-benefit disclosure as part of the consent process, and the requirement to disseminate and/or publish trial results even if the study is negative.

CONCLUSIONS

This consensus guidance should prove useful for the protocol development and conduct of clinical trials, and may further provide a platform for the development of education materials that may help guide appropriate clinical trial participation decisions for potential trial participants and the general public.

Blood-brain barrier-on-a-chip for brain disease modeling and drug testing

The blood-brain barrier (BBB) is an interface between cerebral blood and the brain parenchyma. As a gate keeper, BBB regulates passage of nutrients and exogeneous compounds. Owing to this highly selective barrier, many drugs targeting brain diseases are not likely to pass through the BBB. Thus, a large amount of time and cost have been paid for the development of BBB targeted therapeutics. However, many drugs validated in in vitro models and animal models have failed in clinical trials primarily due to the lack of an appropriate BBB model. Human BBB has a unique cellular architecture. Different physiologies between human and animal BBB hinder the prediction of drug responses. Therefore, a more physiologically relevant alternative BBB model needs to be developed. In this review, we summarize major features of human BBB and current BBB models and describe organ-on-chip models for BBB modeling and their applications in neurological complications.

β-Amyloid in blood neuronal-derived extracellular vesicles is elevated in cognitively normal adults at risk of Alzheimer's disease and predicts cerebral amyloidosis

Background

Blood biomarkers that can be used for preclinical Alzheimer’s disease (AD) diagnosis would enable trial enrollment at a time when the disease is potentially reversible. Here, we investigated plasma neuronal-derived extracellular vesicle (nEV) cargo in patients along the Alzheimer’s continuum, focusing on cognitively normal controls (NCs) with high brain β-amyloid (Aβ) loads (Aβ+).

Methods

The study was based on the Sino Longitudinal Study on Cognitive Decline project. We enrolled 246 participants, including 156 NCs, 45 amnestic mild cognitive impairment (aMCI) patients, and 45 AD dementia (ADD) patients. Brain Aβ loads were determined using positron emission tomography. NCs were classified into 84 Aβ− NCs and 72 Aβ+ NCs. Baseline plasma nEVs were isolated by immunoprecipitation with an anti-CD171 antibody. After verification, their cargos, including Aβ, tau phosphorylated at threonine 181, and neurofilament light, were quantified using a single-molecule array. Concentrations of these cargos were compared among the groups, and their receiver operating characteristic (ROC) curves were constructed. A subset of participants underwent follow-up cognitive assessment and magnetic resonance imaging. The relationships of nEV cargo levels with amyloid deposition, longitudinal changes in cognition, and brain regional volume were explored using correlation analysis. Additionally, 458 subjects in the project had previously undergone plasma Aβ quantification.

Results

Only nEV Aβ was included in the subsequent analysis. We focused on Aβ₄₂ in the current study. After normalization of nEVs, the levels of Aβ₄₂ were found to increase gradually across the cognitive continuum, with the lowest in the Aβ− NC group, an increase in the Aβ+ NC group, a further increase in the aMCI group, and the highest in the ADD group, contributing to their diagnoses (Aβ− NCs vs. Aβ+ NCs, area under the ROC curve values of 0.663; vs. aMCI, 0.857; vs. ADD, 0.957). Furthermore, nEV Aβ₄₂ was significantly correlated with amyloid deposition, as well as longitudinal changes in cognition and entorhinal volume. There were no differences in plasma Aβ levels among NCs, aMCI, and ADD individuals.

Conclusions

Our findings suggest the potential use of plasma nEV Aβ₄₂ levels in diagnosing AD-induced cognitive impairment and Aβ+ NCs. This biomarker reflects cortical amyloid deposition and predicts cognitive decline and entorhinal atrophy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13195-022-01010-x.

Blood-brain barrier-on-a-chip for brain disease modeling and drug testing

The blood-brain barrier (BBB) is an interface between cerebral blood and the brain parenchyma. As a gate keeper, BBB regulates passage of nutrients and exogeneous compounds. Owing to this highly selective barrier, many drugs targeting brain diseases are not likely to pass through the BBB. Thus, a large amount of time and cost have been paid for the development of BBB targeted therapeutics. However, many drugs validated in in vitro models and animal models have failed in clinical trials primarily due to the lack of an appropriate BBB model. Human BBB has a unique cellular architecture. Different physiologies between human and animal BBB hinder the prediction of drug responses. Therefore, a more physiologically relevant alternative BBB model needs to be developed. In this review, we summarize major features of human BBB and current BBB models and describe organ-on-chip models for BBB modeling and their applications in neurological complications. [BMB Reports 2022; 55(5): 213-219].

Neuroinflammation as a Potential Therapeutic Target in Alzheimer’s Disease

Although amyloid-β (Aβ) peptide accumulation is considered as a key early event in the pathogenesis of Alzheimer’s disease (AD), the precise pathophysiology of this deadly illness remains unclear and no effective remedies capable of inhibiting disease progression have been discovered. In addition to deposition of extracellular Aβ plaques and intracellular neurofibrillary tangles, neuroinflammation has been identified as the third core characteristic crucial in the pathogenesis of AD. More and more evidence from laboratory and clinical studies have suggested that anti-inflammatory treatments could defer or prevent the occurrence of AD. In this review, we will discuss multifaceted evidence of neuroinflammation presented in AD and the newly emerged anti-inflammatory targets both in pre-clinical and clinical AD.

Effects of multisite anodal transcranial direct current stimulation combined with cognitive stimulation in patients with Alzheimer's disease and its neurophysiological correlates: A double-blind randomized clinical trial

OBJECTIVES

We aimed to examine the effects of multisite anodal transcranial direct current stimulation (tDCS) combined with cognitive stimulation (CS) over 2 months on cognitive performance and brain activity, and the relationship between them, in patients with Alzheimer's disease (AD).

METHODS

Patients with AD were randomly assigned to an active tDCS+CS (n=18) or a sham tDCS+CS (n=18) group. Cognitive performance was assessed using the Alzheimer Disease Assessment Scale-cognitive subscale (ADAS-cog) and brain activity using EEG (spectral power and coherence analysis) before and after the intervention. Multisite anodal tDCS (2 mA, 30 min) was applied over six brain regions [left and right dorsolateral prefrontal cortex (F3 and F4), Broca's area (F5), Wernicke's area (CP5), left and right somatosensory association cortex (P3 and P4)] for 24 sessions (three times a week). Both groups performed CS during tDCS.

RESULTS

Anodal tDCS+CS delays cognitive decline (ADAS-cog change) to a greater extent than sham tDCS+CS (-3.4±1.1 vs. -1.7±0.4; p=.03). Bilateral EEG coherence at high and low frequencies was greater for the active tDCS+CS than sham+CS group for most electrode pairs assessed (p < .05). The post-intervention ADAS-cog change score was predictive for EEG coherence at different sites (R²=.59 to .68; p < .05) in the active but not in the sham tDCS+CS group.

CONCLUSION

Anodal tDCS+CS improved overall cognitive function and changed EEG brain activity compared to sham tDCS+CS. Changes in cognitive performance were associated with changes in EEG measures of brain activity. Anodal tDCS+CS appears to be a promising therapeutic strategy to modulate cortical activity and improve cognitive function in patients with AD.

Intratarget Microdosing for Deep Phenotyping of Multiple Drug Effects in the Live Brain

A main impediment to effective development of new therapeutics for central nervous system disorders, and for the in vivo testing of biological hypotheses in the brain, is the ability to rapidly measure the effect of novel agents and treatment combinations on the pathophysiology of native brain tissue. We have developed a miniaturized implantable microdevice (IMD) platform, optimized for direct stereotactic insertion into the brain, which enables the simultaneous measurement of multiple drug effects on the native brain tissue in situ. The IMD contains individual reservoirs which release microdoses of single agents or combinations into confined regions of the brain, with subsequent spatial analysis of phenotypic, transcriptomic or metabolomic effects. Using murine models of Alzheimer’s disease (AD), we demonstrate that microdoses of various approved and investigational CNS drugs released from the IMD within a local brain region exhibit in situ phenotypes indicative of therapeutic responses, such as neuroprotection, reduction of hyperphosphorylation, immune cell modulation, and anti-inflammatory effects. We also show that local treatments with drugs affecting metabolism provide evidence for regulation of metabolite profiles and immune cell function in hMAPT AD mice. The platform should prove useful in facilitating the rapid testing of pharmacological or biological treatment hypotheses directly within native brain tissues (of various animal models and in patients) and help to confirm on-target effects, in situ pharmacodynamics and drug-induced microenvironment remodeling, much more efficiently than currently feasible.

Dual Reversible Coumarin Inhibitors Mutually Bound to Monoamine Oxidase B and Acetylcholinesterase Crystal Structures

Multitarget directed ligands (MTDLs) represent a promising frontier in tackling the complexity of multifactorial pathologies. The synergistic inhibition of monoamine oxidase B (MAO B) and acetylcholinesterase (AChE) is believed to provide a potentiated effect in the treatment of Alzheimer’s disease. Among previously reported micromolar or sub-micromolar coumarin-bearing dual inhibitors, compound 1 returned a tight-binding inhibition of MAO B (K_i = 4.5 μM) and a +5.5 °C increase in the enzyme T_m value. Indeed, the X-ray crystal structure revealed that binding of 1 produces unforeseen conformational changes at the MAO B entrance cavity. Interestingly, 1 showed great shape complementarity with the AChE enzymatic gorge, being deeply buried from the catalytic anionic subsite (CAS) to the peripheral anionic subsite (PAS) and causing significant structural changes in the active site. These findings provide structural templates for further development of dual MAO B and AChE inhibitors.

Development and Biological Characterization of a Novel Selective TrkA Agonist with Neuroprotective Properties against Amyloid Toxicity

Neurotrophins are growth factors that exert important neuroprotective effects by preventing neuronal death and synaptic loss. Nerve Growth Factor (NGF) acts through the activation of its high-affinity, pro-survival TrkA and low-affinity, pro-apoptotic p75NTR receptors. NGF has been shown to slow or prevent neurodegenerative signals in Alzheimer's Disease (AD) progression. However, its low bioavailability and its blood-brain-barrier impermeability limit the use of NGF as a potential therapeutic agent against AD. Based on our previous findings on synthetic dehydroepiandrosterone derivatives, we identified a novel NGF mimetic, named ENT-A013, which selectively activates TrkA and exerts neuroprotective, anti-amyloid-β actions. We now report the chemical synthesis, in silico modelling, metabolic stability, CYP-mediated reaction phenotyping and biological characterization of ENT-A013 under physiological and neurodegenerative conditions. We show that ENT-A013 selectively activates the TrkA receptor and its downstream kinases Akt and Erk1/2 in PC12 cells, protecting these cells from serum deprivation-induced cell death. Moreover, ENT-A013 promotes survival of primary Dorsal Root Ganglion (DRG) neurons upon NGF withdrawal and protects hippocampal neurons against Amyloid β-induced apoptosis and synaptic loss. Furthermore, this neurotrophin mimetic partially restores LTP impairment. In conclusion, ENT-A013 represents a promising new lead molecule for developing therapeutics against neurodegenerative disorders, such as Alzheimer's Disease, selectively targeting TrkA-mediated pro-survival signals.

Promoter Hypomethylation of TGFBR3 as a Risk Factor of Alzheimer’s Disease: An Integrated Epigenomic-Transcriptomic Analysis

Alzheimer’s disease (AD) is characterized by the abnormal deposition of amyloid-β (Aβ) plaques and tau tangles in the brain and accompanied with cognitive impairment. However, the fundamental cause of this disease remains elusive. To elucidate the molecular processes related to AD, we carried out an integrated analysis utilizing gene expression microarrays (GSE36980 and GSE5281) and DNA methylation microarray (GSE66351) in temporal cortex of AD patients from the Gene Expression Omnibus (GEO) database. We totally discovered 409 aberrantly methylated and differentially expressed genes. These dysregulated genes were significantly enriched in biological processes including cell part morphogenesis, chemical synaptic transmission and regulation of Aβ formation. Through convergent functional genomic (CFG) analysis, expression cross-validation and clinicopathological correlation analysis, higher TGFBR3 level was observed in AD and positively correlated with Aβ accumulation. Meanwhile, the promoter methylation level of TGFBR3 was reduced in AD and negatively associated with Aβ level and advanced Braak stage. Mechanically, TGFBR3 might promote Aβ production by enhancing β- and γ-secretase activities. Further investigation revealed that TGFBR3 may exert its functions via Synaptic vesicle cycle, Calcium signaling pathway and MAPK signal pathway by regulating hub genes GNB1, GNG3, CDC5L, DYNC1H1 and FBXW7. Overall, our findings highlighted TGFBR3 as an AD risk gene and might be used as a diagnostic biomarker and therapeutic target for AD treatment.

Role of miRNAs in Neurodegeneration: From Disease Cause to Tools of Biomarker Discovery and Therapeutics

Neurodegenerative diseases originate from neuronal loss in the central nervous system (CNS). These debilitating diseases progress with age and have become common due to an increase in longevity. The National Institute of Environmental Health Science’s 2021 annual report suggests around 6.2 million Americans are living with Alzheimer’s disease, and there is a possibility that there will be 1.2 million Parkinson’s disease patients in the USA by 2030. There is no clear-cut universal mechanism for identifying neurodegenerative diseases, and therefore, they pose a challenge for neurobiology scientists. Genetic and environmental factors modulate these diseases leading to familial or sporadic forms. Prior studies have shown that miRNA levels are altered during the course of the disease, thereby suggesting that these noncoding RNAs may be the contributing factor in neurodegeneration. In this review, we highlight the role of miRNAs in the pathogenesis of neurodegenerative diseases. Through this review, we aim to achieve four main objectives: First, we highlight how dysregulation of miRNA biogenesis led to these diseases. Second, we highlight the computational or bioinformatics tools required to identify the putative molecular targets of miRNAs, leading to biological molecular pathways or mechanisms involved in these diseases. Third, we focus on the dysregulation of miRNAs and their target genes leading to several neurodegenerative diseases. In the final section, we highlight the use of miRNAs as potential diagnostic biomarkers in the early asymptomatic preclinical diagnosis of these age-dependent debilitating diseases. Additionally, we discuss the challenges and advances in the development of miRNA therapeutics for brain targeting. We list some of the innovative strategies employed to deliver miRNA into target cells and the relevance of these viral and non-viral carrier systems in RNA therapy for neurodegenerative diseases. In summary, this review highlights the relevance of studying brain-enriched miRNAs, the mechanisms underlying their regulation of target gene expression, their dysregulation leading to progressive neurodegeneration, and their potential for biomarker marker and therapeutic intervention. This review thereby highlights ways for the effective diagnosis and prevention of these neurodegenerative disorders in the near future.

Grey matter network markers identify individuals with prodromal Alzheimer's disease who will show rapid clinical decline

Individuals with prodromal Alzheimer's disease show considerable variability in rates of cognitive decline, which hampers the ability to detect potential treatment effects in clinical trials. Prognostic markers to select those individuals who will decline rapidly within a trial time frame are needed. Brain network measures based on grey matter covariance patterns have been associated with future cognitive decline in Alzheimer's disease. In this longitudinal cohort study, we investigated whether cut-offs for grey matter networks could be derived to detect fast disease progression at an individual level. We further tested whether detection was improved by adding other biomarkers known to be associated with future cognitive decline [i.e. CSF tau phosphorylated at threonine 181 (p-tau181) levels and hippocampal volume]. We selected individuals with mild cognitive impairment and abnormal CSF amyloid β1-42 levels from the Amsterdam Dementia Cohort and the Alzheimer's Disease Neuroimaging Initiative, when they had available baseline structural MRI and clinical follow-up. The outcome was progression to dementia within 2 years. We determined prognostic cut-offs for grey matter network properties (gamma, lambda and small-world coefficient) using time-dependent receiver operating characteristic analysis in the Amsterdam Dementia Cohort. We tested the generalization of cut-offs in the Alzheimer's Disease Neuroimaging Initiative, using logistic regression analysis and classification statistics. We further tested whether combining these with CSF p-tau181 and hippocampal volume improved the detection of fast decliners. We observed that within 2 years, 24.6% (Amsterdam Dementia Cohort, n = 244) and 34.0% (Alzheimer's Disease Neuroimaging Initiative, n = 247) of prodromal Alzheimer's disease patients progressed to dementia. Using the grey matter network cut-offs for progression, we could detect fast progressors with 65% accuracy in the Alzheimer's Disease Neuroimaging Initiative. Combining grey matter network measures with CSF p-tau and hippocampal volume resulted in the best model fit for classification of rapid decliners, increasing detecting accuracy to 72%. These data suggest that single-subject grey matter connectivity networks indicative of a more random network organization can contribute to identifying prodromal Alzheimer's disease individuals who will show rapid disease progression. Moreover, we found that combined with p-tau and hippocampal volume this resulted in the highest accuracy. This could facilitate clinical trials by increasing chances to detect effects on clinical outcome measures.

Challenges and hopes for Alzheimer's disease

Recent drug development efforts targeting Alzheimer's disease (AD) have failed to produce effective disease-modifying agents for many reasons, including the substantial presymptomatic neuronal damage that is caused by the accumulation of the amyloid β (Aβ) peptide and tau protein abnormalities, deleterious adverse effects of drug candidates, and inadequate design of clinical trials. New molecular targets, biomarkers, and diagnostic techniques, as well as alternative nonpharmacological approaches, are sorely needed to detect and treat early pathological events. This article analyzes the successes and debacles of pharmaceutical endeavors to date, and highlights new technologies that may lead to the more effective diagnosis and treatment of the pathologies that underlie AD. The use of focused ultrasound, deep brain stimulation, stem cell therapy, and gene therapy, in parallel with pharmaceuticals and judicious lifestyle adjustments, holds promise for the deceleration, prevention, or cure of AD and other neurodegenerative disorders.

Converging multi-modality datasets to build efficient drug repositioning pipelines against Alzheimer's disease and related dementias

Alzheimer's disease and related dementias (AD/ADRD) affects more than 50 million people worldwide but there is no clear therapeutic option affordable for the general patient population. Recently, drug repositioning studies featuring collaborations between academic institutes, medical centers, and hospitals are generating novel therapeutics candidates against these devastating diseases and filling in an important area for healthcare that is poorly represented by pharmaceutical companies. Such drug repositioning studies converge expertise from bioinformatics, chemical informatics, medical informatics, artificial intelligence, high throughput and high-content screening and systems biology. They also take advantage of multi-scale, multi-modality datasets, ranging from transcriptomic and proteomic data, electronical medical records, and medical imaging to social media information of patient behaviors and emotions and epidemiology profiles of disease populations, in order to gain comprehensive understanding of disease mechanisms and drug effects. We proposed a recursive drug repositioning paradigm involving the iteration of three processing steps of modeling, prediction, and validation to identify known drugs and bioactive compounds for AD/ADRD. This recursive paradigm has the potential of quickly obtaining a panel of robust novel drug candidates for AD/ADRD and gaining in-depth understanding of disease mechanisms from those repositioned drug candidates, subsequently improving the success rate of predicting novel hits.

An integrated brain-specific network identifies genes associated with neuropathologic and clinical traits of Alzheimer's disease

Alzheimer's disease (AD) has a strong genetic predisposition. However, its risk genes remain incompletely identified. We developed an Alzheimer's brain gene network-based approach to predict AD-associated genes by leveraging the functional pattern of known AD-associated genes. Our constructed network outperformed existing networks in predicting AD genes. We then systematically validated the predictions using independent genetic, transcriptomic, proteomic data, neuropathological and clinical data. First, top-ranked genes were enriched in AD-associated pathways. Second, using external gene expression data from the Mount Sinai Brain Bank study, we found that the top-ranked genes were significantly associated with neuropathological and clinical traits, including the Consortium to Establish a Registry for Alzheimer's Disease score, Braak stage score and clinical dementia rating. The analysis of Alzheimer's brain single-cell RNA-seq data revealed cell-type-specific association of predicted genes with early pathology of AD. Third, by interrogating proteomic data in the Religious Orders Study and Memory and Aging Project and Baltimore Longitudinal Study of Aging studies, we observed a significant association of protein expression level with cognitive function and AD clinical severity. The network, method and predictions could become a valuable resource to advance the identification of risk genes for AD.

In Silico and Ex Vivo Analyses of the Inhibitory Action of the Alzheimer Drug Posiphen and Primary Metabolites with Human Acetyl- and Butyrylcholinesterase Enzymes

Alzheimer’s disease (AD) is the most common neurodegenerative disorder worldwide. Ongoing research to develop AD treatments has characterized multiple drug targets including the cholinergic system, amyloid-β peptide, phosphorylated tau, and neuroinflammation. These systems have the potential to interact to either drive or slow AD progression. Promising agents that simultaneously impact many of these drug targets are the AD experimental drug Posiphen and its enantiomer phenserine that, currently, are separately being evaluated in clinical trials. To define the cholinergic component of these agents, the anticholinesterase activities of a ligand dataset comprising Posiphen and primary metabolites ((+)-N1-norPosiphen, (+)-N8-norPosiphen, and (+)-N1,N8-bisnorPosiphen) were characterized and compared to those of the enantiomer phenserine. The “target” dataset involved the human cholinesterase enzymes acetylcholinesterase (AChE) and butyrylcholinesterase (BChE). Binding interactions between the ligands and targets were analyzed using Autodock 4.2. The computationally determined inhibitory action of these ligands was then compared to ex vivo laboratory-measured values versus human AChE and BChE. While Posiphen lacked AChE inhibitory action, its major and minor metabolites (+)-N1-norPosiphen and (+)-N1,N8-bisnorPosiphen, respectively, possessed modest AChE inhibitory activity, and Posiphen and all metabolites lacked BChE action. Phenserine, as a positive control, demonstrated AChE-selective inhibitory action. In light of AChE inhibitory action deriving from a major and minor Posiphen metabolite, current Posiphen clinical trials in AD and related disorders should additionally evaluate AChE inhibition; particularly if Posiphen should be combined with a known anticholinesterase, since this drug class is clinically approved and the standard of care for AD subjects, and excessive AChE inhibition may impact drug tolerability.

A Review of the Current Mammalian Models of Alzheimer's Disease and Challenges That Need to Be Overcome

Alzheimer's disease (AD) is one of the looming health crises of the near future. Increasing lifespans and better medical treatment for other conditions mean that the prevalence of this disease is expected to triple by 2050. The impact of AD includes both the large toll on individuals and their families as well as a large financial cost to society. So far, we have no way to prevent, slow, or cure the disease. Current medications can only alleviate some of the symptoms temporarily. Many animal models of AD have been created, with the first transgenic mouse model in 1995. Mouse models have been beset by challenges, and no mouse model fully captures the symptomatology of AD without multiple genetic mutations and/or transgenes, some of which have never been implicated in human AD. Over 25 years later, many mouse models have been given an AD-like disease and then 'cured' in the lab, only for the treatments to fail in clinical trials. This review argues that small animal models are insufficient for modelling complex disorders such as AD. In order to find effective treatments for AD, we need to create large animal models with brains and lifespan that are closer to humans, and underlying genetics that already predispose them to AD-like phenotypes.

Concatenation of molecular docking and molecular simulation of BACE-1, γ-secretase targeted ligands: in pursuit of Alzheimer's treatment

INTRODUCTION

Alzheimer's disease (AD), the most predominant cause of dementia, has evolved tremendously with an escalating frequency, mainly affecting the elderly population. An effective means of delaying, preventing, or treating AD is yet to be achieved. The failure rate of dementia drug trials has been relatively higher than in other disease-related clinical trials. Hence, multi-targeted therapeutic approaches are gaining attention in pharmacological developments.

AIMS

As an extension of our earlier reports, we have performed docking and molecular dynamic (MD) simulation studies for the same 13 potential ligands against beta-site APP cleaving enzyme 1 (BACE-1) and γ-secretase as a therapeutic target for AD. The In-silico screening of these ligands as potential inhibitors of BACE-1 and γ-secretase was performed using AutoDock enabled PyRx v-0.8. The protein-ligand interactions were analyzed in Discovery Studio 2020 (BIOVIA). The stability of the most promising ligand against BACE-1 and γ-secretase was evaluated by MD simulation using Desmond-2018 (Schrodinger, LLC, NY, USA).

RESULTS

The computational screening revealed that the docking energy values for each of the ligands against both the target enzymes were in the range of -7.0 to -10.1 kcal/mol. Among the 13 ligands, 8 (55E, 6Z2, 6Z5, BRW, F1B, GVP, IQ6, and X37) showed binding energies of ≤-8 kcal/mol against BACE-1 and γ-secretase. For the selected enzyme targets, BACE-1 and γ-secretase, 6Z5 displayed the lowest binding energy of -10.1 and -9.8 kcal/mol, respectively. The MD simulation study confirmed the stability of BACE-6Z5 and γ-secretase-6Z5 complexes and highlighted the formation of a stable complex between 6Z5 and target enzymes.

CONCLUSION

The virtual screening, molecular docking, and molecular dynamics simulation studies revealed the potential of these multi-enzyme targeted ligands. Among the studied ligands, 6Z5 seems to have the best binding potential and forms a stable complex with BACE-1 and γ-secretase. We recommend the synthesis of 6Z5 for future in-vitro and in-vivo studies.

On the design of early-phase Alzheimer's disease clinical trials with cerebrospinal fluid tau outcomes

BACKGROUND/AIMS

The focus of Alzheimer's disease studies has shifted to earlier disease stages, including mild cognitive impairment. Biomarker inclusion criteria are often incorporated into mild cognitive impairment clinical trials to identify individuals with "prodromal Alzheimer's disease" to ensure appropriate drug targets and enrich for participants likely to develop Alzheimer's disease dementia. The use of these eligibility criteria may affect study power.

METHODS

We investigated outcome variability and study power in the setting of proof-of-concept prodromal Alzheimer's disease trials that incorporate cerebrospinal fluid levels of total tau (t-tau) and phosphorylated (p-tau) as primary outcomes and how differing biomarker inclusion criteria affect power. We used data from the Alzheimer's Disease Neuroimaging Initiative to model trial scenarios and to estimate the variance and within-subject correlation of total and phosphorylated tau. These estimates were then used to investigate the differences in study power for trials considering these two surrogate outcomes.

RESULTS

Patient characteristics were similar for all eligibility criteria. The lowest outcome variance and highest within-subject correlation were obtained when phosphorylated tau was used as an eligibility criterion, compared to amyloid beta or total tau, regardless of whether total tau or phosphorylated tau were used as primary outcomes. Power increased when eligibility criteria were broadened to allow for enrollment of subjects with either low amyloid beta or high phosphorylated tau.

CONCLUSION

Specific biomarker inclusion criteria may impact statistical power in trials using total tau or phosphorylated tau as the primary outcome. In concert with other important considerations such as treatment target and population of clinical interest, these results may have implications to the integrity and efficiency of prodromal Alzheimer's disease trial designs.

Beyond the average patient: how neuroimaging models can address heterogeneity in dementia

Dementia is a highly heterogeneous condition, with pronounced individual differences in age of onset, clinical presentation, progression rates and neuropathological hallmarks, even within a specific diagnostic group. However, the most common statistical designs used in dementia research studies and clinical trials overlook this heterogeneity, instead relying on comparisons of group average differences (e.g. patient versus control or treatment versus placebo), implicitly assuming within-group homogeneity. This one-size-fits-all approach potentially limits our understanding of dementia aetiology, hindering the identification of effective treatments. Neuroimaging has enabled the characterization of the average neuroanatomical substrates of dementias; however, the increasing availability of large open neuroimaging datasets provides the opportunity to examine patterns of neuroanatomical variability in individual patients. In this update, we outline the causes and consequences of heterogeneity in dementia and discuss recent research that aims to tackle heterogeneity directly, rather than assuming that dementia affects everyone in the same way. We introduce spatial normative modelling as an emerging data-driven technique, which can be applied to dementia data to model neuroanatomical variation, capturing individualized neurobiological 'fingerprints'. Such methods have the potential to detect clinically relevant subtypes, track an individual's disease progression or evaluate treatment responses, with the goal of moving towards precision medicine for dementia.

Blood-based biomarkers for Alzheimer's disease: towards clinical implementation

For many years, blood-based biomarkers for Alzheimer's disease seemed unattainable, but recent results have shown that they could become a reality. Convincing data generated with new high-sensitivity assays have emerged with remarkable consistency across different cohorts, but also independent of the precise analytical method used. Concentrations in blood of amyloid and phosphorylated tau proteins associate with the corresponding concentrations in CSF and with amyloid-PET or tau-PET scans. Moreover, other blood-based biomarkers of neurodegeneration, such as neurofilament light chain and glial fibrillary acidic protein, appear to provide information on disease progression and potential for monitoring treatment effects. Now the question emerges of when and how we can bring these biomarkers to clinical practice. This step would pave the way for blood-based biomarkers to support the diagnosis of, and development of treatments for, Alzheimer's disease and other dementias.

Cerebrovascular microRNA Expression Profile During Early Development of Alzheimer's Disease in a Mouse Model

BACKGROUND

Emerging evidence demonstrates association of Alzheimer's disease (AD) with impaired delivery of blood oxygen and nutrients to and throughout the brain. The cerebral circulation plays multiple roles underscoring optimal brain perfusion and cognition entailing moment-to-moment blood flow control, vascular permeability, and angiogenesis. With currently no effective treatment to prevent or delay the progression of AD, cerebrovascular microRNA (miRNA) markers corresponding to post-transcriptional regulation may distinguish phases of AD.

OBJECTIVE

We tested the hypothesis that cerebrovascular miRNA expression profiles indicate developmental stages of AD pathology.

METHODS

Total RNA was isolated from total brain vessel segments of male and female 3xTg-AD mice [young, 1-2 mo; cognitive impairment (CI), 4-5 mo; extracellular amyloid-β plaques (Aβ), 6-8 mo; plaques+neurofibrillary tangles (AβT), 12-15 mo]. NanoString technology nCounter miRNA Expression panel for mouse was used to screen for 599 miRNAs.

RESULTS

Significant (p < 0.05) downregulation of various miRNAs indicated transitions from young to CI (e.g., let-7g & miR-1944, males; miR-133a & miR-2140, females) and CI to Aβ (e.g., miR-99a, males) but not from Aβ to AβT. In addition, altered expression of select miRNAs from overall Pre-AD (young + CI) versus AD (Aβ+ AβT) were detected in both males (let-7d, let-7i, miR-23a, miR-34b-3p, miR-99a, miR-126-3p, miR-132, miR-150, miR-151-5p, miR-181a) and females (miR-150, miR-539). Altogether, at least 20 cerebrovascular miRNAs effectively delineate AD versus Pre-AD pathology.

CONCLUSION

Using the 3xTg-AD mouse model, these data demonstrate that cerebrovascular miRNAs pertaining to endothelial function, vascular permeability, angiogenesis, inflammation, and Aβ/tau metabolism can track early development of AD.

The Alzheimer's disease drug development landscape

Background

Alzheimer’s disease (AD) is a devastating neurodegenerative disease leading to dementia. The field has made significant progress over the last 15 years. AD diagnosis has shifted from syndromal, based on signs and symptoms, to a biomarker construct based on the pathological hallmarks of the disease: amyloid β deposition, pathologic tau, and neurodegeneration. Numerous genetic risk factors for sporadic AD have been identified, providing further insight into the molecular underpinnings of the disease. For the last two decades, however, drug development for AD has been proven to be particularly challenging. Here, we provide a unique overview of the drug development landscape for AD. By comparing preclinical and clinical drug development pipelines, we aim to describe trends and differences regarding target classes and therapeutic modalities in preclinical and clinical development.

Methods

We analyzed proprietary and public databases and company websites for drugs in preclinical development for AD by the pharmaceutical industry and major clinical trial registries for drugs in clinical development for AD. Drugs were categorized by target class and treatment modality.

Results

We found a higher proportion of preclinical interventions targeting molecular pathways associated with sporadic AD genetic risk variants, compared to clinical stage interventions. These include apolipoprotein E (ApoE) and lipids, lysosomal/endosomal targets, and proteostasis. Further, we observed a trend suggesting that more traditional therapeutic modalities are developed for these novel targets, while more novel treatment modalities such as gene therapies and enzyme treatments are in development for more traditional targets such as amyloid β and tau. Interestingly, the percentage of amyloid β targeting therapies in preclinical development (19.2%) is even higher than the percentage in clinical development (10.7%), indicating that diversification away from interventions targeting amyloid-beta has not materialized. Inflammation is the second most popular target class in both preclinical and clinical development.

Conclusions

Our observations show that the AD drug development pipeline is diversifying in terms of targets and treatment modalities, while amyloid-targeting therapies remain a prominent avenue of development as well. To further advance AD drug development, novel companion diagnostics are needed that are directed at disease mechanisms related to genetic risk factors of AD, both for patient stratification and assessment of therapeutic efficacy in clinical trials.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13195-021-00927-z.

The promise of microRNA-based therapies in Alzheimer's disease: challenges and perspectives

Multi-pathway approaches for the treatment of complex polygenic disorders are emerging as alternatives to classical monotarget therapies and microRNAs are of particular interest in that regard. MicroRNA research has come a long way from their initial discovery to the cumulative appreciation of their regulatory potential in healthy and diseased brain. However, systematic interrogation of putative therapeutic or toxic effects of microRNAs in (models of) Alzheimer's disease is currently missing and fundamental research findings are yet to be translated into clinical applications. Here, we review the literature to summarize the knowledge on microRNA regulation in Alzheimer's pathophysiology and to critically discuss whether and to what extent these increasing insights can be exploited for the development of microRNA-based therapeutics in the clinic.

Female specific risk factors for the development of Alzheimer's disease neuropathology and cognitive impairment: Call for a precision medicine approach

Alzheimer's disease (AD) includes a long asymptomatic stage, which precedes the formal diagnosis of dementia. AD biomarker models provide a framework for precision medicine approaches during this stage. However, such approaches have ignored the possible influence of sex on cognition and brain health, despite female sex noted as a major risk factor. Since AD-related changes may emerge in midlife, intervention efforts are being redirected around this period. Midlife coincides with several endocrinological changes, such as the menopausal transition experienced by women. In this narrative review, we discuss evidence for sex-differences in AD neuropathological burden and outline key endocrinological mechanisms for both sexes, focussing on hormonal events throughout the lifespan that may influence female susceptibility to AD neuropathology and dementia onset. We further consider common non-modifiable (genetic) and modifiable (lifestyle and health) risk factors, highlighting possible sex-dependent differential effects for the AD disease course. Finally, we evaluate the studies selected for this review demonstrating sex-differences in cognitive, pathological and health factors, summarising the state of sex differences in AD risk factors. We further provide recommendations for targeted research on female-specific risk factors, to inform personalised strategies for AD-prevention and the promotion of female brain health.

Influence of in vitro neuronal membranes on the anti-amyloidogenic activity of gallic acid: Implication for the therapy of Alzheimer's disease

Molecules inhibiting the amyloid beta (Aβ) peptide aggregation and/or disaggregating mature fibrils are a promising approach for the Alzheimer's disease (AD) therapy, as the Aβ fibrillation is one of the key triggers of the disease. Gallic acid (GA) is a phenolic acid with anti-amyloidogenic activity against Aβ in buffered solutions. However, there is still no evidence of these properties in vivo. Given the rate of failures of AD drug development, there is a huge demand of replicating the in vivo environment in in vitro studies, thus allowing to stop earlier the study of molecules with no effect in vivo. Thus, this study aims to evaluate the effect of in vitro neuronal membranes on the GA's ability in preventing Aβ_1-42 aggregation and disrupting preformed fibrils. To this end, liposomes were employed to mimic the cell membrane environment. The results reveal that the lipid membranes did not affect the GA's ability in inhibiting Aβ_1-42 fibrillation. However, in vitro neuronal membranes modulate the GA-induced Aβ fibrils disaggregation, which may be related with the moderate affinity of the compound for the lipid membrane. Even so, GA presented strong anti-amyloidogenic properties in the cell membrane-like environment. This work highlights the promising value of GA on preventing and treating AD, thus justifying its study in animal models.