Alzheimer's disease and blood-based biomarkers - potential contexts of use

Design, synthesis, and biological evaluation of 1,2,4-oxadiazole-based derivatives as multitarget anti-Alzheimer agents

A series of novel 1,2,4-oxadiazole-based derivatives were synthesized and evaluated for their potential anti-Alzheimer disease activity. The results revealed that compounds 2b, 2c, 2d, 3a, 4a, 6, 9a, 9b, and 13b showed excellent inhibitory activity against acetylcholinesterase (AChE) with IC50 values in the range of 0.0158 to 0.121 μM. They were 1.01 to 7.78 times more potent than donepezil (IC50 = 0.123 μM). The newly synthesized compounds exhibited lower activity towards butyrylcholinesterase (BuChE) when compared to rivastigmine. Compounds 4b and 13b showed the most prominent inhibitory potential against BuChE with IC50 values of 11.50 and 15 μM, respectively. Moreover, 4b, and 9b were found to be more potent antioxidant agents (IC50 values of 59.25, and 56.69 μM, respectively) in comparison with ascorbic acid (IC50 = 74.55 μM). Compounds 2b and 2c exhibited monoamine oxidase-B (MAO-B) inhibitory activity with IC50 values of 74.68 and 225.48 μM, respectively. They were 3.55 and 1.17 times more potent than biperiden (IC50 = 265.85 μM). The prominent interactions of the compounds with the AChE active site can be used to computationally explain the high AChE inhibitory activity. The results unveiled 1,2,4-oxadiazole derivatives 2c and 3a as multitarget anti-AD agents. The predicted ADME properties for compounds 2b and 4a were satisfactory, and 4a had the highest likelihood of crossing the blood-brain barrier (BBB), making it the optimum compound for future optimization.

Interventions to Foster Resilience in Family Caregivers of People with Alzheimer's Disease: A Scoping Review

The family caregiver of a person with Alzheimer's disease still experiences, in most cases, negative consequences in their biopsychosocial environment, which are related to the acquisition of this role. However, it has been observed that this fact is not universal in this type of population since benefits can be obtained in the act of caring through the development of resilience. Given this possibility and given that nurses are the health professionals who support people in this illness process, there is an urgent need to identify which non-pharmacological interventions could improve or promote resilience in family caregivers of people with Alzheimer's disease. Therefore, our overall objective was to determine which interventions are useful in promoting resilience in family caregivers of people with Alzheimer's disease through a scoping review. The data were analysed using an adapted version of Arksey and O'Malley's methodological framework, after critically reading the articles with the CasP and MMAT tools. Nine articles were included (five analytical experimental, two quantitative and two mixed). Three types of interventions related to promoting resilience in family caregivers of people with Alzheimer's disease were identified: meditation, multicomponent psychoeducation and creative art; nurses participated as co-therapists in the last two.

Fused thiophene as a privileged scaffold: A review on anti-Alzheimer's disease potentials via targeting cholinesterases, monoamine oxidases, glycogen synthase kinase-3, and Aβ aggregation

As a "silent threat," Alzheimer's disease (AD) is quickly rising to the top of the list of costly and troublesome diseases facing humanity. It is growing to be one of the most troublesome and expensive conditions, with annual health care costs higher than those of cancer and comparable to those of cardiovascular disorders. One of the main pathogenic characteristics of AD is the deficiency of the neurotransmitter acetylcholine (ACh) which plays a vital role in memory, learning, and attention. Acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) play a crucial role in hydrolyzing ACh. Consequently, a frequent therapy approach for AD is the suppression of AChE and BChE to improve cholinergic neurotransmission and reduce cognitive symptoms. The accumulation of amyloid plaques (Aβ) is a primary factor contributing to neurodegenerative diseases, particularly AD. Glycogen synthase kinase-3β (GSK3-β) is regarded as a pivotal player in the pathophysiology of AD since dysregulation of this kinase affects all major hallmarks of the disease, such as tau phosphorylation, Aβ aggregation, memory, neurogenesis, and synaptic function. One of the most challenging and risky issues in modern medicinal chemistry is the urgent and ongoing need for the study and development of effective therapeutic candidates for the treatment of AD. A significant class of heterocyclic molecules that can target the complex and multifactorial pathogenesis of AD are fused thiophene derivatives. The goal of the current review is to demonstrate the advancements made in fused thiophene derivatives' anti-AD activity. It also covers their mechanisms of action and studies of the structure-activity relationships in addition to the compilation of significant synthetic routes for fused thiophene derivatives with anti-AD potential. This review is intended to stimulate new ideas in the search for more rationale designs of derivatives based on fused thiophene, hoping to be more potent in treating AD.

Advanced Overview of Biomarkers and Techniques for Early Diagnosis of Alzheimer's Disease

The development of early non-invasive diagnosis methods and identification of novel biomarkers are necessary for managing Alzheimer's disease (AD) and facilitating effective prognosis and treatment. AD has multi-factorial nature and involves complex molecular mechanism, which causes neuronal degeneration. The primary challenges in early AD detection include patient heterogeneity and lack of precise diagnosis at the preclinical stage. Several cerebrospinal fluid (CSF) and blood biomarkers have been proposed to show excellent diagnosis ability by identifying tau pathology and cerebral amyloid beta (Aβ) for AD. Intense research endeavors are being made to develop ultrasensitive detection techniques and find potent biomarkers for early AD diagnosis. To mitigate AD worldwide, understanding various CSF biomarkers, blood biomarkers, and techniques that can be used for early diagnosis is imperative. This review attempts to provide information regarding AD pathophysiology, genetic and non-genetic factors associated with AD, several potential blood and CSF biomarkers, like neurofilament light, neurogranin, Aβ, and tau, along with biomarkers under development for AD detection. Besides, numerous techniques, such as neuroimaging, spectroscopic techniques, biosensors, and neuroproteomics, which are being explored to aid early AD detection, have been discussed. The insights thus gained would help in finding potential biomarkers and suitable techniques for the accurate diagnosis of early AD before cognitive dysfunction.

Scalar on time-by-distribution regression and its application for modelling associations between daily-living physical activity and cognitive functions in Alzheimer's Disease

Wearable data is a rich source of information that can provide a deeper understanding of links between human behaviors and human health. Existing modelling approaches use wearable data summarized at subject level via scalar summaries in regression, temporal (time-of-day) curves in functional data analysis (FDA), and distributions in distributional data analysis (DDA). We propose to capture temporally local distributional information in wearable data using subject-specific time-by-distribution (TD) data objects. Specifically, we develop scalar on time-by-distribution regression (SOTDR) to model associations between scalar response of interest such as health outcomes or disease status and TD predictors. Additionally, we show that TD data objects can be parsimoniously represented via a collection of time-varying L-moments that capture distributional changes over the time-of-day. The proposed method is applied to the accelerometry study of mild Alzheimer’s disease (AD). We found that mild AD is significantly associated with reduced upper quantile levels of physical activity, particularly during morning hours. In-sample cross validation demonstrated that TD predictors attain much stronger associations with clinical cognitive scales of attention, verbal memory, and executive function when compared to predictors summarized via scalar total activity counts, temporal functional curves, and quantile functions. Taken together, the present results suggest that SOTDR analysis provides novel insights into cognitive function and AD.

Molecular Signaling Pathway Targeted Therapeutic Potential of Thymoquinone in Alzheimer’s disease

Alzheimer’s disease (AD) is a neurodegenerative disease with rapid progression. Black cumin (Nigella sativa) is a nutraceutical that has been investigated as a prophylactic and therapeutic agent for this disease due to its ability to prevent or retard the progression of neurodegeneration. Thymoquinone (TQ) is the main bioactive compound isolated from the seeds of black cumin. Several reports have shown that it has promising potential in the prevention and treatment of AD due to its significant antioxidative, anti-inflammatory, and antiapoptotic properties along with several other mechanisms that target the altered signaling pathways due to the disease pathogenesis. In addition, it shows anticholinesterase activity and prevents α-synuclein induced synaptic damage. The aim of this review is to summarize the potential aspects and mechanisms by which TQ imparts its action in AD.

Antioxidant and Anticholinesterase Properties of the Aqueous Extract of Balanites aegyptiaca L. Delile Fruit Pulp on Monosodium Glutamate-Induced Excitotoxicity in Swiss Mice

Balanites aegyptiaca L. Delile (B. aegyptiaca) is used in traditional medicine for the treatment of memory impairment. This work aims to evaluate the antioxidant and anticholinesterase potential of BA fruit pulp extract on excitotoxicity induced by monosodium glutamate (MSG). MSG was administered 30 minutes after treatment with B. aegyptiaca aqueous fruit pulp extract (50, 125, 250, and 500 mg/kg) and vitamin C (100 mg/kg) for 30 days. The negative control group received only MSG, while the control group was given distilled water daily. Behavioral tests parameters (using the novel object recognition, Y-maze, and Barnes maze tests), oxidative stress biomarkers (malondialdehyde, superoxide dismutase, and catalase), nitric oxide, and acetylcholinesterase activity and hippocampal architecture were evaluated. Results obtained revealed that different doses of B. aegyptiaca significantly reversed the deleterious effect of MSG on memory. This was displayed by a significant ( $p<0.05$ ) increment in the percentage of spontaneous alternation in the Y-maze test and a significant ( $p<0.001$ ) increase in discrimination index in novel object recognition observed with 500 mg/kg extract dose. Moreover, the extract (250 and 500 mg/kg doses) significantly ( $p<0.001$ ) increased direct search strategy and significantly decreased ( $p<0.01$ ) the time taken to find the target hole in the Barnes maze. A modulation of hyperactivity was observed after administration of all extract doses compared to the negative control group in the open arena. Furthermore, the highest dose of the extract caused a significant ( $p<0.001$ ) improvement in antioxidant enzymes activity, associated with a significant ( $p<0.001$ ) decrement in nitric oxide and malondialdehyde concentrations and a significant ( $p<0.01$ ) decrease in acetylcholinesterase activity. Treatment with the extract also restored normal hippocampal cell architecture. B. aegyptiaca fruit pulp extract could thus confer neuroprotection through its antioxidant and anticholinesterase potential.

Alzheimer's Disease-Related Dysbiosis Might Be Triggered by Certain Classes of Antibiotics with Time-Lapse: New Insights into the Pathogenesis?

BACKGROUND

Several putative factors are identified in the literature as causative agents or risk factors for the development of Alzheimer's disease (AD). The amyloid cascade hypothesis has been the main hypothesis about the pathophysiology of AD for decades, but recent studies raised the possible role of dysbiosis in the development of AD, which prevents memory loss.

OBJECTIVE

Finding possible associations between antibiotic consumption patterns and the prevalence of AD in European countries.

METHODS

Antibiotic consumption (European Centre for Disease Prevention and Control, ECDC) for 1997-2007, 2008-2018, and as the whole 1997-2018 period, has been compared to the AD prevalence for 2018 expressed in percentage of the population and statistically analyzed by Pearson calculation.

RESULTS

A significant positive correlation has been found between the AD prevalence (2018) and the average quinolone consumption for the years 1997-2007 (r: 0.37, p: 0.044). A similar association was not observed for the entire 22 years (1997-2018) of the average quinolone consumption, and the years 2008-2018, indicating 10-20 years of time-lapse between the antibiotic exposure and the development of AD. The ratio of broad-spectrum and narrow-spectrum antibiotics (B/N) estimated in the ECDC database for the years of 2008-2018 showed a strong positive association with AD prevalence (2018) (r: 0.406, p: 0.026) and a positive correlation tendency for the entire 22 years 1997-2018 (r: 0.344, p: 0.063), but none for the years 1997-2007 (r: 0.256, p: 0.241).

CONCLUSION

Our study indicated the possible sequential role of certain classes of antibiotics in the development of dysbiosis leading to amyloid deposits of AD, which strengthen the possible role of different mediator molecules (short-chain fatty acids, lipopolysaccharides, etc.) produced by the altered microbiome in the development of AD.

Analysis of behavioral management for dental treatment in patients with dementia using the Korean National Health Insurance data

Background

The global population is aging rapidly, and accordingly, the number of patients with dementia is increasing every year. Although the need for dental treatment increases for various reasons in patients with dementia, they cannot cooperate during dental treatment. Therefore, behavioral management, including sedation (SED) or general anesthesia (GA), is required for patients with dementia. Thus, this study aimed to investigate the trends and effects of SED or GA in patients with dementia undergoing dental treatment in South Korea based on the Korean National Health Insurance claims data.

Methods

This study utilized customized health information data provided by the Health Insurance Review and Assessment Service. Among patients with records of using sedative drugs during dental treatment from January 2007 to September 2019, patients with the International Classification of Diseases-10 code for dementia (F00, F01, F02, F03, and G30) were selected. We then analyzed the full insurance claims data for dental care. Age, sex, sedative use, and dental treatment of patients were analyzed yearly. In addition, the number of cases of GA or SED per year was analyzed, and changes in behavioral management methods with increasing age were investigated.

Results

Between January 2007 and September 2019, a total of 4,383 (male, 1,454; female, 2,929) patients with dementia received dental treatment under SED or GA. The total number of SED and GA cases were 1,515 (male, 528 ; female, 987) and 3,396 (male, 1,119 ; female, 2,277) cases, respectively. The total number of cases of dental treatment for 4,383 patients with dementia was 153,051 cases, of which 2.22% were under GA and 0.98% were under SED. Midazolam was the most commonly used drug for SED.

Conclusion

Although gingivitis and pulpitis were the most common reasons for patients with dementia to visit the dentist, GA or SED for patients with dementia was frequently used in oral and maxillofacial or periodontal surgery.

Influential role of 7-Ketocholesterol in the progression of Alzheimer's disease

Millions of people are affected by neurodegenerative diseases worldwide. They occur due to the loss of brain functions or peripheral nervous system dysfunction. If untreated, prolonged condition ultimately leads to death. Mostly they are associated with stress, altered cholesterol metabolism, inflammation and organelle dysfunction. Endogenous cholesterol and phospholipids in brain undergo auto-oxidation by enzymatic as well as non-enzymatic modes leading to the formation of by-products such as 4-hydroxynonenal and oxysterols. Among various oxysterols, 7-ketocholesterol (7KCh) is one of the major toxic components involved in altering neuronal lipid metabolism, contributing to inflammation and nerve cell damage. More evidently 7KCh is proven to induce oxidative stress and affects membrane permeability. Loss in mitochondrial membrane potential affects metabolism of cell organelles such as lysosomes and peroxisomes which are involved in lipid and protein homeostasis. This in turn could affect amyloidogenesis, tau protein phosphorylation and accumulation in pathological conditions of neurodegenerative diseases. Lipid alterations and the consequent pathogenic protein accumulation, results in the damage of cell organelles and microglial cells. This could be a reason behind disease progression and predominantly reported characteristics of neurodegenerative disorders such as Alzheimer's disease. This review focuses on the role of 7KCh mediated neurodegenerative Alzheimer's disease with emphasis on alterations in the lipid raft microdomain. In addition, current trends in the significant therapies related to 7KCh inhibition are highlighted.

Practical recommendations for timely, accurate diagnosis of symptomatic Alzheimer's disease (MCI and dementia) in primary care: a review and synthesis

The critical role of primary care clinicians (PCCs) in Alzheimer's disease (AD) prevention, diagnosis and management must evolve as new treatment paradigms and disease-modifying therapies (DMTs) emerge. Our understanding of AD has grown substantially: no longer conceptualized as a late-in-life syndrome of cognitive and functional impairments, we now recognize that AD pathology builds silently for decades before cognitive impairment is detectable. Clinically, AD first manifests subtly as mild cognitive impairment (MCI) due to AD before progressing to dementia. Emerging optimism for improved outcomes in AD stems from a focus on preventive interventions in midlife and timely, biomarker-confirmed diagnosis at early signs of cognitive deficits (i.e. MCI due to AD and mild AD dementia). A timely AD diagnosis is particularly important for optimizing patient care and enabling the appropriate use of anticipated DMTs. An accelerating challenge for PCCs and AD specialists will be to respond to innovations in diagnostics and therapy for AD in a system that is not currently well positioned to do so. To overcome these challenges, PCCs and AD specialists must collaborate closely to navigate and optimize dynamically evolving AD care in the face of new opportunities. In the spirit of this collaboration, we summarize here some prominent and influential models that inform our current understanding of AD. We also advocate for timely and accurate (i.e. biomarker-defined) diagnosis of early AD. In doing so, we consider evolving issues related to prevention, detecting emerging cognitive impairment and the role of biomarkers in the clinic.

Classifying Non-Dementia and Alzheimer's Disease/Vascular Dementia Patients Using Kinematic, Time-Based, and Visuospatial Parameters: The Digital Clock Drawing Test

BACKGROUND

Advantages of digital clock drawing metrics for dementia subtype classification needs examination.

OBJECTIVE

To assess how well kinematic, time-based, and visuospatial features extracted from the digital Clock Drawing Test (dCDT) can classify a combined group of Alzheimer's disease/Vascular Dementia patients versus healthy controls (HC), and classify dementia patients with Alzheimer's disease (AD) versus vascular dementia (VaD).

METHODS

Healthy, community-dwelling control participants (n = 175), patients diagnosed clinically with Alzheimer's disease (n = 29), and vascular dementia (n = 27) completed the dCDT to command and copy clock drawing conditions. Thirty-seven dCDT command and 37 copy dCDT features were extracted and used with Random Forest classification models.

RESULTS

When HC participants were compared to participants with dementia, optimal area under the curve was achieved using models that combined both command and copy dCDT features (AUC = 91.52%). Similarly, when AD versus VaD participants were compared, optimal area under the curve was, achieved with models that combined both command and copy features (AUC = 76.94%). Subsequent follow-up analyses of a corpus of 10 variables of interest determined using a Gini Index found that groups could be dissociated based on kinematic, time-based, and visuospatial features.

CONCLUSION

The dCDT is able to operationally define graphomotor output that cannot be measured using traditional paper and pencil test administration in older health controls and participants with dementia. These data suggest that kinematic, time-based, and visuospatial behavior obtained using the dCDT may provide additional neurocognitive biomarkers that may be able to identify and tract dementia syndromes.

Predicting Dementia With Prefrontal Electroencephalography and Event-Related Potential

Objective: To examine whether prefrontal electroencephalography (EEG) can be used for screening dementia.

Methods: We estimated the global cognitive decline using the results of Mini-Mental Status Examination (MMSE), measurements of brain activity from resting-state EEG, responses elicited by auditory stimulation [sensory event-related potential (ERP)], and selective attention tasks (selective-attention ERP) from 122 elderly participants (dementia, 35; control, 87). We investigated that the association between MMSE and each EEG/ERP variable by using Pearson’s correlation coefficient and performing univariate linear regression analysis. Kernel density estimation was used to examine the distribution of each EEG/ERP variable in the dementia and non-dementia groups. Both Univariate and multiple logistic regression analyses with the estimated odds ratios were conducted to assess the associations between the EEG/ERP variables and dementia prevalence. To develop the predictive models, five-fold cross-validation was applied to multiple classification algorithms.

Results: Most prefrontal EEG/ERP variables, previously known to be associated with cognitive decline, show correlations with the MMSE score (strongest correlation has |r| = 0.68). Although variables such as the frontal asymmetry of the resting-state EEG are not well correlated with the MMSE score, they indicate risk factors for dementia. The selective-attention ERP and resting-state EEG variables outperform the MMSE scores in dementia prediction (areas under the receiver operating characteristic curve of 0.891, 0.824, and 0.803, respectively). In addition, combining EEG/ERP variables and MMSE scores improves the model predictive performance, whereas adding demographic risk factors do not improve the prediction accuracy.

Conclusion: Prefrontal EEG markers outperform MMSE scores in predicting dementia, and additional prediction accuracy is expected when combining them with MMSE scores.

Significance: Prefrontal EEG is effective for screening dementia when used independently or in combination with MMSE.

Continuous gait monitoring discriminates community-dwelling mild Alzheimer's disease from cognitively normal controls

INTRODUCTION

Few studies have explored whether gait measured continuously within a community setting can identify individuals with Alzheimer's disease (AD). This study tests the feasibility of this method to identify individuals at the earliest stage of AD.

METHODS

Mild AD (n = 38) and cognitively normal control (CNC; n = 48) participants from the University of Kansas Alzheimer's Disease Center Registry wore a GT3x+ accelerometer continuously for 7 days to assess gait. Penalized logistic regression with repeated five-fold cross-validation followed by adjusted logistic regression was used to identify gait metrics with the highest predictive performance in discriminating mild AD from CNC.

RESULTS

Variability in step velocity and cadence had the highest predictive utility in identifying individuals with mild AD. Metrics were also associated with cognitive domains impacted in early AD.

DISCUSSION

Continuous gait monitoring may be a scalable method to identify individuals at-risk for developing dementia within large, population-based studies.

Accurate Blood-Based Diagnostic Biosignatures for Alzheimer's Disease via Automated Machine Learning

Alzheimer's disease (AD) is the most common form of neurodegenerative dementia and its timely diagnosis remains a major challenge in biomarker discovery. In the present study, we analyzed publicly available high-throughput low-sample -omics datasets from studies in AD blood, by the AutoML technology Just Add Data Bio (JADBIO), to construct accurate predictive models for use as diagnostic biosignatures. Considering data from AD patients and age-sex matched cognitively healthy individuals, we produced three best performing diagnostic biosignatures specific for the presence of AD: A. A 506-feature transcriptomic dataset from 48 AD and 22 controls led to a miRNA-based biosignature via Support Vector Machines with three miRNA predictors (AUC 0.975 (0.906, 1.000)), B. A 38,327-feature transcriptomic dataset from 134 AD and 100 controls led to six mRNA-based statistically equivalent signatures via Classification Random Forests with 25 mRNA predictors (AUC 0.846 (0.778, 0.905)) and C. A 9483-feature proteomic dataset from 25 AD and 37 controls led to a protein-based biosignature via Ridge Logistic Regression with seven protein predictors (AUC 0.921 (0.849, 0.972)). These performance metrics were also validated through the JADBIO pipeline confirming stability. In conclusion, using the automated machine learning tool JADBIO, we produced accurate predictive biosignatures extrapolating available low sample -omics data. These results offer options for minimally invasive blood-based diagnostic tests for AD, awaiting clinical validation based on respective laboratory assays. They also highlight the value of AutoML in biomarker discovery.

Acute cognitive deficits after traumatic brain injury predict Alzheimer's disease-like degradation of the human default mode network

Traumatic brain injury (TBI) and Alzheimer's disease (AD) are prominent neurological conditions whose neural and cognitive commonalities are poorly understood. The extent of TBI-related neurophysiological abnormalities has been hypothesized to reflect AD-like neurodegeneration because TBI can increase vulnerability to AD. However, it remains challenging to prognosticate AD risk partly because the functional relationship between acute posttraumatic sequelae and chronic AD-like degradation remains elusive. Here, functional magnetic resonance imaging (fMRI), network theory, and machine learning (ML) are leveraged to study the extent to which geriatric mild TBI (mTBI) can lead to AD-like alteration of resting-state activity in the default mode network (DMN). This network is found to contain modules whose extent of AD-like, posttraumatic degradation can be accurately prognosticated based on the acute cognitive deficits of geriatric mTBI patients with cerebral microbleeds. Aside from establishing a predictive physiological association between geriatric mTBI, cognitive impairment, and AD-like functional degradation, these findings advance the goal of acutely forecasting mTBI patients' chronic deviations from normality along AD-like functional trajectories. The association of geriatric mTBI with AD-like changes in functional brain connectivity as early as ~6 months post-injury carries substantial implications for public health because TBI has relatively high prevalence in the elderly.

Identification of potential blood biomarkers for early diagnosis of Alzheimer's disease through RNA sequencing analysis

Background

With demographic shifts toward older populations, the number of people with dementia is steadily increasing. Alzheimer’s disease (AD) is the most common cause of dementia, and no curative treatment is available. The current best strategy is to delay disease progression and to practice early intervention to reduce the number of patients that ultimately develop AD. Therefore, promising novel biomarkers for early diagnosis are urgently required.

Methods

To identify blood-based biomarkers for early diagnosis of AD, we performed RNA sequencing (RNA-seq) analysis of 610 blood samples, representing 271 patients with AD, 91 cognitively normal (CN) adults, and 248 subjects with mild cognitive impairment (MCI). We first estimated cell-type proportions among AD, MCI, and CN samples from the bulk RNA-seq data using CIBERSORT and then examined the differentially expressed genes (DEGs) between AD and CN samples. To gain further insight into the biological functions of the DEGs, we performed gene set enrichment analysis (GSEA) and network-based meta-analysis.

Results

In the cell-type distribution analysis, we found a significant association between the proportion of neutrophils and AD prognosis at a false discovery rate (FDR) < 0.05. Furthermore, a similar trend emerged in the results of routine blood tests from a large number of samples (n = 3,099: AD, 1,605; MCI, 994; CN, 500). In addition, GSEA and network-based meta-analysis based on DEGs between AD and CN samples revealed functional modules and important hub genes associated with the pathogenesis of AD. The risk prediction model constructed by using the proportion of neutrophils and the most important hub genes (EEF2 and RPL7) achieved a high AUC of 0.878 in a validation cohort; when further applied to a prospective cohort, the model achieved a high accuracy of 0.727.

Conclusions

Our model was demonstrated to be effective in prospective AD risk prediction. These findings indicate the discovery of potential biomarkers for early diagnosis of AD, and their further improvement may lead to future practical clinical use.

Current and Future of Alzheimer's Therapy with the Best Approach

INTRODUCTION

In spite of the steady progress in the understanding of the etiopathogenesis of Alzheimer's Disease (AD) for the last 50 years, exceptionally few long-standing drugs are, at present, used for AD therapy. New interventions that either prevent, slow or stop the disease are urgently warranted to overcome the growing AD burden. The aim of this narrative review is to summarize the currently existing preclinical and clinical evidence regarding new drug development and biomarkers for better understanding and focused management of AD. This article reviews the various potential and existing targets /receptors with valid biomarkers applied in recent years to address the early-stage tasks of the AD drug discovery process. A comprehensive literature search was conducted in the relevant databases to identify studies published in recent years. In conclusion, the new approaches seem to aim at examining the prospective neuroprotective activity of disease-modifying drugs in the presymptomatic phases of AD, using biomarkers that detect progression of the disease before the growth of overt dementia.

Blood-based systems biology biomarkers for next-generation clinical trials in Alzheimer's disease

Alzheimer's disease (AD)-a complex disease showing multiple pathomechanistic alterations-is triggered by nonlinear dynamic interactions of genetic/epigenetic and environmental risk factors, which, ultimately, converge into a biologically heterogeneous disease. To tackle the burden of AD during early preclinical stages, accessible blood-based biomarkers are currently being developed. Specifically, next-generation clinical trials are expected to integrate positive and negative predictive blood-based biomarkers into study designs to evaluate, at the individual level, target druggability and potential drug resistance mechanisms. In this scenario, systems biology holds promise to accelerate validation and qualification for clinical trial contexts of use-including proof-of-mechanism, patient selection, assessment of treatment efficacy and safety rates, and prognostic evaluation. Albeit in their infancy, systems biology-based approaches are poised to identify relevant AD "signatures" through multifactorial and interindividual variability, allowing us to decipher disease pathophysiology and etiology. Hopefully, innovative biomarker-drug codevelopment strategies will be the road ahead towards effective disease-modifying drugs.
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CLIC1 Protein Accumulates in Circulating Monocyte Membrane during Neurodegeneration

Pathologies that lead to neurodegeneration in the central nervous system (CNS) represent a major contemporary medical challenge. Neurodegenerative processes, like those that occur in Alzheimer’s disease (AD) are progressive, and at the moment, they are unstoppable. Not only is an adequate therapy missing but diagnosis is also extremely complicated. The most reliable method is the measurement of beta amyloid and tau peptides concentration in the cerebrospinal fluid (CSF). However, collecting liquid samples from the CNS is an invasive procedure, thus it is not suitable for a large-scale prevention program. Ideally, blood testing is the most manageable and appropriate diagnostic procedure for a massive population screening. Recently, a few candidates, including proteins or microRNAs present in plasma/serum have been identified. The aim of the present work is to propose the chloride intracellular channel 1 (CLIC1) protein as a potential marker of neurodegenerative processes. CLIC1 protein accumulates in peripheral blood mononuclear cells (PBMCs), and increases drastically when the CNS is in a chronic inflammatory state. In AD patients, both immunolocalization and mRNA quantification are able to show the behavior of CLIC1 during a persistent inflammatory state of the CNS. In particular, confocal microscopy analysis and electrophysiological measurements highlight the significant presence of transmembrane CLIC1 (tmCLIC1) in PBMCs from AD patients. Recent investigations suggest that tmCLIC1 has a very specific role. This provides an opportunity to use blood tests and conventional technologies to discriminate between healthy individuals and patients with ongoing neurodegenerative processes.