Recent Progress in Alzheimer's Disease Research, Part 3: Diagnosis and Treatment

Using Machine Learning to Predict Cognitive Decline in Older Adults From the Chinese Longitudinal Healthy Longevity Survey: Model Development and Validation Study

Background

Cognitive impairment, indicative of Alzheimer disease and other forms of dementia, significantly deteriorates the quality of life of older adult populations and imposes considerable burdens on families and health care systems worldwide. The early identification of individuals at risk for cognitive impairment through a convenient and rapid method is crucial for the timely implementation of interventions.

Objective

The objective of this study was to explore the application of machine learning (ML) to integrate blood biomarkers, life behaviors, and disease history to predict the decline in cognitive function.

Methods

This approach uses data from the Chinese Longitudinal Healthy Longevity Survey. A total of 2688 participants aged 65 years or older from the 2008-2009, 2011-2012, and 2014 Chinese Longitudinal Healthy Longevity Survey waves were included, with cognitive impairment defined as a Mini-Mental State Examination (MMSE) score below 18. The dataset was divided into a training set (n=1331), an internal test set (n=333), and a prospective validation set (n=1024). Participants with a baseline MMSE score of less than 18 were excluded from the cohort to ensure a more accurate assessment of cognitive function. We developed ML models that integrate demographic information, health behaviors, disease history, and blood biomarkers to predict cognitive function at the 3-year follow-up point, specifically identifying individuals who are at risk of experiencing significant declines in cognitive function by that time. Specifically, the models aimed to identify individuals who would experience a significant decline in their MMSE scores (less than 18) by the end of the follow-up period. The performance of these models was evaluated using metrics including accuracy, sensitivity, and the area under the receiver operating characteristic curve.

Results

All ML models outperformed the MMSE alone. The balanced random forest achieved the highest accuracy (88.5% in the internal test set and 88.7% in the prospective validation set), albeit with a lower sensitivity, while logistic regression recorded the highest sensitivity. SHAP (Shapley Additive Explanations) analysis identified instrumental activities of daily living, age, and baseline MMSE scores as the most influential predictors for cognitive impairment.

Conclusions

The incorporation of blood biomarkers, along with demographic, life behavior, and disease history into ML models offers a convenient, rapid, and accurate approach for the early identification of older adult individuals at risk of cognitive impairment. This method presents a valuable tool for health care professionals to facilitate timely interventions and underscores the importance of integrating diverse data types in predictive health models.

Bioinformatics to analyze the differentially expressed genes in different degrees of Alzheimer's disease and their roles in progress of the disease

Employing bioinformatics approaches, this investigation pinpointed pivotal differentially expressed genes (DEGs) across the spectrum of Alzheimer's disease (AD), from incipient to severe stages, using the GSE28146 dataset from the GEO repository. Analytical methods included DEG identification via the limma package in R, coupled with GO and KEGG pathway analyses through clusterProfiler, to discern biological processes and pathway involvements. Key findings spotlighted the roles of proteasome subunits PSMB4, PSMB8, PSMC4, and PSMD6 in the early stage, ribosomal proteins RPS3 and RPL11 during moderate AD, and mitochondrial components COX5B, COX6B2, and COX7A2 in severe AD, underscoring their importance in the disease's pathogenesis. Conclusively, these results not only delineate the dynamic genetic shifts accompanying AD progression but also propose critical biomarkers for potential therapeutic targeting, offering a consolidated basis for future AD research and treatment development. This offered a novel idea for analyzing the pathogenesis and development of AD and investigation of targeted drugs.

Non-Invasive Retinal Biomarkers for Early Diagnosis of Alzheimer's Disease

Alzheimer's disease (AD) is a progressive neurodegenerative disorder of the brain associated with ageing and is the most prevalent form of dementia, affecting an estimated 55 million people worldwide, with projections suggesting this number will exceed 150 million by 2050. With its increasing prevalence, AD represents a significant global health challenge with potentially serious social and economic consequences. Diagnosing AD is particularly challenging as it requires timely recognition. Currently, there is no effective therapy for AD; however, certain medications may help slow its progression. Existing diagnostic methods such as magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), and biomarker analysis in cerebrospinal fluid tend to be expensive and invasive, making them impractical for widespread use. Consequently, research into non-invasive biomarkers that enable early detection and screening for AD is a crucial area of contemporary clinical investigation. One promising approach for the early diagnosis of AD may be retinal imaging. As an extension of the central nervous system, the retina offers a distinctive opportunity for non-invasive brain structure and function assessment. Considering their shared embryological origins and the vascular and immunological similarities between the eye and brain, alterations in the retina may indicate pathological changes in the brain, including those specifically related to AD. Studies suggest that structural and vascular changes in the retina, particularly within the neuronal network and blood vessels, may act as markers of cerebral changes caused by AD. These retinal alterations have the potential to act as biomarkers for early diagnosis. Since AD is typically diagnosed only after a significant neuronal loss has occurred, identifying early diagnostic markers could enable timely intervention and help prevent disease progression. Non-invasive retinal imaging techniques, such as optical coherence tomography (OCT) and OCT angiography, provide accessible methods for the early detection of changes linked to AD. This review article focuses on the potential of retinal imaging as a non-invasive biomarker for early diagnosis of AD. Investigating the ageing of the retina and its connections to neurodegenerative processes could significantly enhance the diagnosis, monitoring, and treatment of AD, paving the way for new diagnostic and therapeutic approaches.

Ghrelin Induces Ferroptosis Resistance and M2 Polarization of Microglia to Alleviate Neuroinflammation and Cognitive Impairment in Alzheimer's Disease

Microglial polarization and ferroptosis are important pathological features in Alzheimer's disease (AD). Ghrelin, a brain-gut hormone, has potential neuroprotective effects in AD. This study aimed to explore the potential mechanisms by which ghrelin regulates the progression of AD, as well as the crosstalk between microglial polarization and ferroptosis. Mouse BV2 microglial cells and male mice were treated with beta-amyloid (Aβ) (1-42) to simulate the AD environment. Microglia ferroptosis was measured by detecting levels of ferroptosis-related proteins (SLC7A11, GPX4, FTL1, and FTH1), metabolic markers (ROS, MDA, GSH, SOD), and observing mitochondrial morphological changes. Microglial polarization was evaluated by measuring levels of inflammatory markers and surface markers. The impact of ghrelin on Aβ1-42-exposed microglia was assessed by coupling with the ferroptosis activator Erastin. Cognitive impairment in AD mice was evaluated through behavioral tests. Tissue staining was applied to determine neuronal damage. In Aβ1-42-exposed microglia, ghrelin upregulated the protein expression of SLC7A11, GPX4, FTL1 and FTH1, reduced ROS and MDA levels, and elevated GSH and SOD levels through the BMP6/SMAD1 pathway. Ghrelin alleviated mitochondrial structural damage. Additionally, ghrelin reduced levels of pro-inflammatory factors and CD86, while increasing levels of anti-inflammatory factors and CD206. Erastin reversed the effects of ghrelin on ferroptosis and phenotypic polarization in Aβ1-42-exposed microglia. In AD mice, ghrelin ameliorated abnormal behavior, neuroinflammation, and plaque deposition. Ghrelin attenuated iNOS/IBA1-positive expression and enhanced Arg-1/IBA1-positive expression in the hippocampus. Ghrelin induces microglial M2 polarization by inhibiting microglia ferroptosis, thereby alleviating neuroinflammation. Our results indicate that ghrelin may serve as a promising potential agent for treating cognitive impairment in AD.

Therapeutic Potential of Polyphenols in Cellular Reversal of Patho-Mechanisms of Alzheimer's Disease Using In Vitro and In Vivo Models: A Comprehensive Review

Alzheimer's disease (AD) is considered one of the most common neurological conditions associated with memory and cognitive impairment and mainly affects people aged 65 or above. Even with tremendous progress in modern neuroscience, a permanent remedy or cure for this crippling disease is still unattainable. Polyphenols are a group of naturally occurring potent compounds that can modulate the neurodegenerative processes typical of AD. The present comprehensive study has been conducted to find out the preclinical and clinical potential of polyphenols and elucidate their possible mechanisms in managing AD. Additionally, we have reviewed different clinical studies investigating polyphenols as single compounds or cotherapies, including those currently recruiting, completed, terminated, withdrawn, or suspended in AD treatment. Natural polyphenols were systematically screened and identified through electronic databases including Google Scholar, PubMed, and Scopus based on in vitro cell line studies and preclinical data demonstrating their potential for neuroprotection. A total of 63 significant polyphenols were identified. A multimechanistic pathway for polyphenol's mode of action has been proposed in the study. Out of 63, four potent polyphenols have been identified as promising potential candidates, based on their reported clinical efficacy. Polyphenols hold tremendous scope for the development of a future drug molecule as a phytopharmaceutical that may be incorporated as an adjuvant to the therapeutic regime. However, more high-quality studies with novel delivery methods and combinatorial approaches are required to overcome obstacles such as bioavailability and blood-brain barrier crossing to underscore the therapeutic potential of these compounds in AD management.

EGB761 ameliorates mild cognitive impairment by inhibiting the pyroptosis and apoptosis in both in vivo and in vitro experiments

Mild cognitive impairment (MCI) is a neurodegenerative condition that is clinically prevalent among the elderly. EGB761 is widely recognized for its promising therapeutic properties in both the prevention and treatment of neurodegenerative disorders. The aim of this study was to investigate the effects of EGB761 in MCI and the underlying molecular mechanism. Four-month-old SAMP8 mice were used as an in vivo MCI model, and BV2 microglial cells were treated with β-amyloid (Aβ) 1-42 to establish an in vitro model. First, the cognitive function was evaluated by the Morris water maze. Then, Aβ levels were measured by enzyme-linked immunosorbent assay. Finally, the underlying molecular mechanism was investigated both in vivo and in vitro. It was found that EGB761 treatment improved the cognitive impairment of SAMP8 mice. In addition, EGB761 inhibited NOD-like receptor protein 3 inflammasome-mediated pyroptosis-related mRNAs and proteins and reduced pyroptosis markers, including gasdermin D fluorescence intensity, propidium iodide-positive cell count, and the lactate dehydrogenase content. Furthermore, EGB761 inhibited extrinsic and intrinsic apoptosis. Thus, EGB761 had protective effects against pyroptosis and apoptosis in BV2 microglial cells induced by Aβ1-42 and SAMP8 mice.

The Benzoxazole Heterocycle: A Comprehensive Review of the Most Recent Medicinal Chemistry Developments of Antiproliferative, Brain-Penetrant, and Anti-inflammatory Agents

The benzoxazole is one of the most widely exploited heterocycles in drug discovery. Natural occurring and synthetic benzoxazoles show a broad range of biological activities. Many benzoxazoles are available for treating several diseases, and, to date, a few are in clinical trials. Moreover, an ever-increasing number of benzoxazole derivatives are under investigation in the early drug discovery phase and as potential hit or lead compounds. This perspective is an attempt to thoroughly review the rational design, the structure-activity relationship, and the biological activity of the most notable benzoxazoles developed during the past 5 years (period 2019-to date) in cancers, neurological disorders, and inflammation. We also briefly overviewed each target and its role in the disease. The huge amount of work examined suggests the great potential of the scaffold and the high interest of the scientific community in novel biologically active compounds containing the benzoxazole core.

Plasma lipidomics in early APP/PS1 female mouse model and its relationship with brain: Is it affected by the estrous cycle?

BACKGROUND

Alzheimer's disease (AD) is the most prevalent dementia, showing higher incidence in women. Besides, lipids play an essential role in brain, and they could be dysregulated in neurodegeneration. Specifically, impaired plasma lipid levels could predict early AD diagnosis. This work aims to identify the main plasma lipids altered in early AD female mouse model and evaluate their relationship with brain lipidome. Also, the possible involvement of the estrous cycle in lipid metabolism has been evaluated.

METHODS

Plasma samples of wild-type (n = 10) and APP/PS1 (n = 10) female mice of 5 months of age were collected, processed, and analysed using a lipidomic mass spectrometry-based method. A statistical analysis involving univariate and multivariate approaches was performed to identify significant lipid differences related to AD between groups. Also, cytology tests were conducted to confirm estrous cycle phases.

RESULTS

Three hundred thirty lipids were detected in plasma, 18 of them showed significant differences between groups; specifically, some triacylglycerols, cholesteryl esters, lysophosphatidylcholines, phosphatidylcholines, and ether-linked phosphatidylcholines, increased in early AD; while other phosphatidylcholines, phosphatidylethanolamines, ceramides, and ether-linked phosphatidylethanolamines decreased in early AD. A multivariate approach was developed from some lipid variables, showing high diagnostic indexes (70% sensitivity, 90% specificity, 80% accuracy). From brain and plasma lipidome, some significant correlations were observed, mainly in the glycerophospholipid family. Also, some differences were found in both plasma and brain lipids, according to the estrous cycle phase.

CONCLUSIONS

Therefore, lipid alterations can be identified in plasma at early AD stages in mice females, with a relationship with brain lipid metabolism for most of the lipid subfamilies, suggesting some lipids as potential AD biomarkers. In addition, the estrous cycle monitoring could be relevant in female studies.

Retinal imaging and Alzheimer's disease: a future powered by Artificial Intelligence

Alzheimer's disease (AD) is a neurodegenerative condition that primarily affects brain tissue. Because the retina and brain share the same embryonic origin, visual deficits have been reported in AD patients. Artificial Intelligence (AI) has recently received a lot of attention due to its immense power to process and detect image hallmarks and make clinical decisions (like diagnosis) based on images. Since retinal changes have been reported in AD patients, AI is being proposed to process images to predict, diagnose, and prognosis AD. As a result, the purpose of this review was to discuss the use of AI trained on retinal images of AD patients. According to previous research, AD patients experience retinal thickness and retinal vessel density changes, which can occasionally occur before the onset of the disease's clinical symptoms. AI and machine vision can detect and use these changes in the domains of disease prediction, diagnosis, and prognosis. As a result, not only have unique algorithms been developed for this condition, but also databases such as the Retinal OCTA Segmentation dataset (ROSE) have been constructed for this purpose. The achievement of high accuracy, sensitivity, and specificity in the classification of retinal images between AD and healthy groups is one of the major breakthroughs in using AI based on retinal images for AD. It is fascinating that researchers could pinpoint individuals with a positive family history of AD based on the properties of their eyes. In conclusion, the growing application of AI in medicine promises its future position in processing different aspects of patients with AD, but we need cohort studies to determine whether it can help to follow up with healthy persons at risk of AD for a quicker diagnosis or assess the prognosis of patients with AD.

Genetic and Epigenetic Biomarkers Linking Alzheimer's Disease and Age-Related Macular Degeneration

Alzheimer's disease (AD) represents a prominent neurodegenerative disorder (NDD), accounting for the majority of dementia cases worldwide. In addition to memory deficits, individuals with AD also experience alterations in the visual system. As the retina is an extension of the central nervous system (CNS), the loss in retinal ganglion cells manifests clinically as decreased visual acuity, narrowed visual field, and reduced contrast sensitivity. Among the extensively studied retinal disorders, age-related macular degeneration (AMD) shares numerous aging processes and risk factors with NDDs such as cognitive impairment that occurs in AD. Histopathological investigations have revealed similarities in pathological deposits found in the retina and brain of patients with AD and AMD. Cellular aging processes demonstrate similar associations with organelles and signaling pathways in retinal and brain tissues. Despite these similarities, there are distinct genetic backgrounds underlying these diseases. This review comprehensively explores the genetic similarities and differences between AMD and AD. The purpose of this review is to discuss the parallels and differences between AMD and AD in terms of pathophysiology, genetics, and epigenetics.

SOCS modulates JAK-STAT pathway as a novel target to mediate the occurrence of neuroinflammation: Molecular details and treatment options

SOCS (Suppressor of Cytokine Signalling) proteins are intracellular negative regulators that primarily modulate and inhibit cytokine-mediated signal transduction, playing a crucial role in immune homeostasis and related inflammatory diseases. SOCS act as inhibitors by regulating the Janus kinase-signal transducer and activator of transcription (JAK-STAT) signaling pathway, thereby intervening in the pathogenesis of inflammation and autoimmune diseases. Recent studies have also demonstrated their involvement in central immunity and neuroinflammation, showing a dual functionality. However, the specific mechanisms of SOCS in the central nervous system remain unclear. This review thoroughly elucidates the specific mechanisms linking the SOCS-JAK-STAT pathway with the inflammatory manifestations of neurodegenerative diseases. Based on this, it proposes the theory that SOCS proteins can regulate the JAK-STAT pathway and inhibit the occurrence of neuroinflammation. Additionally, this review explores in detail the current therapeutic landscape and potential of targeting SOCS in the brain via the JAK-STAT pathway for neuroinflammation, offering insights into potential targets for the treatment of neurodegenerative diseases.

DHEC mesylate attenuates pathologies and aberrant bisecting N-glycosylation in Alzheimer's disease models

Tremendous progress has been made to develop the therapy of Alzheimer's disease (AD). Existing several anti-AD remedies, with certain limitations, are far from adequate. Evidence suggests that dihydroergocristine (DHEC) mesylate, one of the main components of Ergoloid mesylates, can reduce the production of amyloid-β in vitro. However, the therapeutic effect of DHEC mesylate in AD and its underlying mechanism are still largely unknown. Herein, we characterized the pharmacological effect of DHEC mesylate in AD and found that the spatial memory disorders and Alzheimer-type pathologies were alleviated by DHEC mesylate administration. Moreover, we demonstrated that DHEC mesylate improved aberrant bisecting N-glycosylation, which was identified as a potential biomarker of AD. We further explored the underlying mechanism and confirmed that DHEC mesylate protected against AD via AMPK and ERK signaling, in which, AMPK was the dominant down-stream molecule of DHEC mesylate. In summary, our findings provide foundations for development of DHEC mesylate as a therapeutic approach for AD.

Targeting aberrant glycosylation to modulate microglial response and improve cognition in models of Alzheimer's disease

Altered glycosylation profiles have been correlated with potential drug targets in various diseases, including Alzheimer's disease (AD). In this area, the linkage between bisecting N-acetylglucosamine (GlcNAc), a product of N-acetylglucosaminyltransferase III (GnT-III), and AD has been recognized, however, our understanding of the cause and the causative role of this aberrant glycosylation in AD are far from completion. Moreover, the effects and mechanisms of glycosylation-targeting interventions on memory and cognition, and novel targeting strategies are worth further study. Here, we showed the characteristic amyloid pathology-induced and age-related changes of GnT-III, and identified transcription factor 7-like 2 as the key transcription factor responsible for the abnormal expression of GnT-III in AD. Upregulation of GnT-III aggravated cognitive dysfunction and Alzheimer-like pathologies. In contrast, loss of GnT-III could improve cognition and alleviate pathologies. Furthermore, we found that an increase in bisecting GlcNAc modified ICAM-1 resulted in impairment of microglial responses, and genetic inactivation of GnT-III protected against AD mechanistically by blocking the aberrant glycosylation of ICAM-1 and subsequently modulating microglial responses, including microglial motility, phagocytosis ability, homeostatic/reactive state and neuroinflammation. Moreover, by target-based screening of GnT-III inhibitors from FDA-approved drug library, we identified two compounds, regorafenib and dihydroergocristine mesylate, showing pharmacological potential leading to modulation of aberrant glycosylation and microglial responses, and rescue of memory and cognition deficits.

Olfactory identification, cognition, depressive symptoms, and 5-year mortality in patients with subjective cognitive decline, mild cognitive impairment, and Alzheimer's disease

OBJECTIVE

An association between odor and cognitive impairment has been shown in many studies. The objective of the present hospital-based, single-center retrospective study was to assess the impact of odor impairment on the mortality of patients with Alzheimer's disease (AD), subjective cognitive decline (SCD), and mild cognitive impairment (MCI).

METHODS

Odor function was measured by Sniffin Sticks (Burghart Messtechnik, Holm, Germany) and the assessment of self-reported olfactory functioning and olfaction-related quality of life (ASOF) test. Cognitive performance was assessed by an extensive neuropsychological test battery, symptoms of depression were diagnosed with the Geriatric Depressive Scale (GDS). The influence of demographic factors such as gender, age, and education were examined.

RESULTS

Although the univariate analyses and pairwise post hoc comparison showed significant differences for some of the olfactory performance tests/subtests, the multivariate models showed no association between olfactory test performance and mortality among patients with cognitive impairment. "Attention," a domain of the Neuropsychological Test Battery Vienna (NTBV), as well as depressive symptoms, gender, and age, showed a significant influence on the mortality of the patient group.

CONCLUSION

Lower olfactory performance showed no impact on mortality. However, decreased cognitive function of "Attention" can be considered as an influential predictor for mortality.

A review and analysis of key biomarkers in Alzheimer's disease

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that affects over 50 million elderly individuals worldwide. Although the pathogenesis of AD is not fully understood, based on current research, researchers are able to identify potential biomarker genes and proteins that may serve as effective targets against AD. This article aims to present a comprehensive overview of recent advances in AD biomarker identification, with highlights on the use of various algorithms, the exploration of relevant biological processes, and the investigation of shared biomarkers with co-occurring diseases. Additionally, this article includes a statistical analysis of key genes reported in the research literature, and identifies the intersection with AD-related gene sets from databases such as AlzGen, GeneCard, and DisGeNet. For these gene sets, besides enrichment analysis, protein-protein interaction (PPI) networks utilized to identify central genes among the overlapping genes. Enrichment analysis, protein interaction network analysis, and tissue-specific connectedness analysis based on GTEx database performed on multiple groups of overlapping genes. Our work has laid the foundation for a better understanding of the molecular mechanisms of AD and more accurate identification of key AD markers.

Characterization of Hair Metabolome in 5xFAD Mice and Patients with Alzheimer's Disease Using Mass Spectrometry-Based Metabolomics

Hair emerged as a biospecimen for long-term investigation of endogenous metabolic perturbations, reflecting the chemical composition circulating in the blood over the past months. Despite its potential, the use of human hair for metabolomics in Alzheimer's disease (AD) research remains limited. Here, we performed both untargeted and targeted metabolomic approaches to profile the key metabolic pathways in the hair of 5xFAD mice, a widely used AD mouse model. Furthermore, we applied the discovered metabolites to human subjects. Hair samples were collected from 6-month-old 5xFAD mice, a stage marked by widespread accumulation of amyloid plaques in the brain, followed by sample preparation and high-resolution mass spectrometry analysis. Forty-five discriminatory metabolites were discovered in the hair of 6-month-old 5xFAD mice compared to wild-type control mice. Enrichment analysis revealed three key metabolic pathways: arachidonic acid metabolism, sphingolipid metabolism, and alanine, aspartate, and glutamate metabolism. Among these pathways, six metabolites demonstrated significant differences in the hair of 2-month-old 5xFAD mice, a stage prior to the onset of amyloid plaque deposition. These findings suggest their potential involvement in the early stages of AD pathogenesis. When evaluating 45 discriminatory metabolites for distinguishing patients with AD from nondemented controls, a combination of l-valine and arachidonic acid significantly differentiated these two groups, achieving a 0.88 area under the curve. Taken together, these findings highlight the potential of hair metabolomics in identifying disease-specific metabolic alterations and developing biomarkers for improving disease detection and monitoring.

Early Diagnosis of Neurodegenerative Diseases: What Has Been Undertaken to Promote the Transition from PET to Fluorescence Tracers

Alzheimer's Disease (AD) and Parkinson's Disease (PD) represent two among the most frequent neurodegenerative diseases worldwide. A common hallmark of these pathologies is the misfolding and consequent aggregation of amyloid proteins into soluble oligomers and insoluble β-sheet-rich fibrils, which ultimately lead to neurotoxicity and cell death. After a hundred years of research on the subject, this is the only reliable histopathological feature in our hands. Since AD and PD are diagnosed only once neuronal death and the first symptoms have appeared, the early detection of these diseases is currently impossible. At present, there is no effective drug available, and patients are left with symptomatic and inconclusive therapies. Several reasons could be associated with the lack of effective therapeutic treatments. One of the most important factors is the lack of selective probes capable of detecting, as early as possible, the most toxic amyloid species involved in the onset of these pathologies. In this regard, chemical probes able to detect and distinguish among different amyloid aggregates are urgently needed. In this article, we will review and put into perspective results from ex vivo and in vivo studies performed on compounds specifically interacting with such early species. Following a general overview on the three different amyloid proteins leading to insoluble β-sheet-rich amyloid deposits (amyloid β1-42 peptide, Tau, and α-synuclein), a list of the advantages and disadvantages of the approaches employed to date is discussed, with particular attention paid to the translation of fluorescence imaging into clinical applications. Furthermore, we also discuss how the progress achieved in detecting the amyloids of one neurodegenerative disease could be leveraged for research into another amyloidosis. As evidenced by a critical analysis of the state of the art, substantial work still needs to be conducted. Indeed, the early diagnosis of neurodegenerative diseases is a priority, and we believe that this review could be a useful tool for better investigating this field.

Quantitative electroencephalography (qEEG), apolipoprotein A-I (APOA-I), and apolipoprotein epsilon 4 (APOE ɛ4) alleles for the diagnosis of mild cognitive impairment and Alzheimer's disease

INTRODUCTION

Alzheimer's disease (AD) is the most common type of dementia. Amnestic mild cognitive impairment (aMCI), a pre-dementia stage is an important stage for early diagnosis and intervention. This study aimed to investigate the diagnostic value of qEEG, APOA-I, and APOE ɛ4 allele in aMCI and AD patients and found the correlation between qEEG (Delta + Theta)/(Alpha + Beta) ratio (DTABR) and different cognitive domains.

METHODS

All participants were divided into three groups: normal controls (NCs), aMCI, and AD, and all received quantitative electroencephalography (qEEG), neuropsychological scale assessment, apolipoprotein epsilon 4 (APOE ɛ4) alleles, and various blood lipid indicators. Different statistical methods were used for different data.

RESULTS

The cognitive domains except executive ability were all negatively correlated with DTABR in different brain regions while executive ability was positively correlated with DTABR in several brain regions, although without statistical significance. The consequences confirmed that the DTABR of each brain area were related to MMSE, MoCA, instantaneous memory, and the language ability (p < 0.05), and the DTABR in the occipital area was relevant to all cognitive domains (p < 0.01) except executive function (p = 0.272). Also, occipital DTABR was most correlated with language domain when tested by VFT with a moderate level (r = 0.596, p < 0.001). There were significant differences in T3, T5, and P3 DTABR between both AD and NC and aMCI and NCs. As for aMCI diagnosis, the maximum AUC was achieved when using T3 combined with APOA-I and APOE ε4 (0.855) and the maximum AUC was achieved when using T5 combined with APOA-I and APOE ε4 (0.889) for AD diagnosis.

CONCLUSION

These findings highlight that APOA-I, APOE ɛ4, and qEEG play an important role in aMCI and AD diagnosis. During AD continuum, qEEG DTABR should be taken into consideration for the early detection of AD risk.

Gardenia jasminoides J. Ellis extract attenuates memory impairment in rats with Alzheimer's disease by suppressing NLRP3 inflammasome

Alzheimer's disease (AD) is characterized by degeneration of the central nervous system. Recently, many studies have emphasized the beneficial role of Gardenia jasminoides J. Ellis extract (GJ-4) in neuroprotection, which is considered a potential drug for treating AD. However, the mechanism underlying its neuroprotective effects is obscure. This research intended to analyze the effectiveness of GJ-4 to induce neuronal protective role on a rat model of neurotoxicity and probe the potential mechanism. An AD model was established by intraperitoneal injection of aluminum chloride (AlCl3). Then, AlCl3-induced rats were administered 25 mg/kg and 50 mg/kg of GJ-4 orally. This study indicated that GJ-4 (25 and 50 mg/kg) mitigated AD-like behaviors, as evidenced by enhanced ambulation frequency, rearing frequency, and time spent in the target quadrant and decreased grooming frequency, defecation frequency, and escape latency in AlCl3-challenged rats. Also, GJ-4 at 25 and 50 mg/kg exerted an anti-apoptosis effect in the hippocampus of AlCl3-treated rats. Furthermore, GJ-4 (25 and 50 mg/kg) exhibited an anti-inflammatory effect in the hippocampus by repressing the activation of NOD-like receptor thermal protein domain associated protein 3 (NLRP3) inflammasome, further inhibiting the activation of Caspase 1, ASC, IL-1β, and IL-18 in AD hippocampus. Altogether, GJ-4 mitigated AlCl3-triggered impairment of learning and memory in AD rats via repressing NLRP3 inflammasome.

STW-MD: a novel spatio-temporal weighting and multi-step decision tree method for considering spatial heterogeneity in brain gene expression data

Gene expression during brain development or abnormal development is a biological process that is highly dynamic in spatio and temporal. Previous studies have mainly focused on individual brain regions or a certain developmental stage. Our motivation is to address this gap by incorporating spatio-temporal information to gain a more complete understanding of brain development or abnormal brain development, such as Alzheimer's disease (AD), and to identify potential determinants of response. In this study, we propose a novel two-step framework based on spatial-temporal information weighting and multi-step decision trees. This framework can effectively exploit the spatial similarity and temporal dependence between different stages and different brain regions, and facilitate differential gene analysis in brain regions with high heterogeneity. We focus on two datasets: the AD dataset, which includes gene expression data from early, middle and late stages, and the brain development dataset, spanning fetal development to adulthood. Our findings highlight the advantages of the proposed framework in discovering gene classes and elucidating their impact on brain development and AD progression across diverse brain regions and stages. These findings align with existing studies and provide insights into the processes of normal and abnormal brain development.

Prevalence Estimation of Dementia/Alzheimer's Disease Using Health and Retirement Study Database in the United States

BACKGROUND

Updated prevalence estimates along the continuum of Alzheimer's disease (AD) can foster a more nuanced and effective approach to managing AD within the current healthcare landscape.

OBJECTIVES

This study aims to estimate the prevalence and severity distribution of dementia/AD (including mild, moderate, and severe stages) and all-cause mild cognitive impairment (MCI) in the United States using data from the Health and Retirement Study (HRS).

DESIGN

Retrospective study.

SETTING

Data from the bi-annual HRS surveys involving in-depth interviews of a representative sample of Americans aged >50 years.

PARTICIPANTS

Dementia/AD and all-cause MCI patients from the 4 most recent HRS surveys (2014, 2016, 2018 and 2020).

MEASUREMENTS

AD was identified based on diagnosis (self-report). Cognitive performance (modified Telephone Interview of Cognitive Status [TICS-m]) scores in the dementia/AD range were also captured; all-cause MCI was similarly identified using the TICS-m. Dementia/AD and MCI prevalence, as well as the distribution by dementia/AD stage (mild, moderate, or severe), were estimated. Sampling weights developed by HRS were applied to ensure the sample's representativeness of the target population and unbiased estimates for population parameters.

RESULTS

Across the four HRS surveys, the total number of HRS respondents ranged from 15,000 to 21,000 (unweighted); 7,000 to 14,000 had TICS-m scores. The estimated prevalence of AD (all severity categories combined) in the 2014, 2016, 2018, and 2020 HRS surveys was 1.2%, 1.2%, 1.3% and 1.0%, respectively using the diagnosis-based approach; using the cognitive performance-based approach, 23-27% patients had scores in the dementia/AD ranges across the 4 surveys. The estimated prevalence of all-cause MCI was consistently 23% in each survey. In the 2020 survey, the distribution of mild, moderate, and severe disease stages was 34%, 45%, and 21%, respectively, in patients self-reporting an AD diagnosis, and 55%, 40%, and 5%, respectively in all patients meeting TICS-m threshold for dementia/AD.

CONCLUSION

The prevalence of AD diagnosis based on self-report was approximately 1% across the 4 most recent HRS surveys and may reflect the proportion of patients who have actively sought healthcare for AD. Among HRS survey respondents with cognitive scores available, over 20% were in the dementia/AD range. The distribution of disease by stage differed for self-reported AD diagnosis vs dementia/AD based on cognitive scores. Discordance in estimates of dementia/AD and stage distributions underscores a need for better understanding of clinical practice patterns in AD diagnosis, use of clinical assessment tools, and severity classification in the United States. Accurate patient identification is needed, especially early in the AD disease continuum, to allow for timely and appropriate initiation of new anti-amyloid treatments.

Utilities of Isolated Nerve Terminals in Ex Vivo Analyses of Protein Translation in (Patho)physiological Brain States: Focus on Alzheimer's Disease

Synapses are the cellular substrates of higher-order brain functions, and their dysfunction is an early and primary pathogenic mechanism across several neurological disorders. In particular, Alzheimer's disease (AD) is categorized by prodromal structural and functional synaptic deficits, prior to the advent of classical behavioral and pathological features. Recent research has shown that the development, maintenance, and plasticity of synapses depend on localized protein translation. Synaptosomes and synaptoneurosomes are biochemically isolated synaptic terminal preparations which have long been used to examine a variety of synaptic processes ex vivo in both healthy and pathological conditions. These ex vivo preparations preserve the mRNA species and the protein translational machinery. Hence, they are excellent in organello tools for the study of alterations in mRNA levels and protein translation in neuropathologies. Evaluation of synapse-specific basal and activity-driven de novo protein translation activity can be conveniently performed in synaptosomal/synaptoneurosomal preparations from both rodent and human brain tissue samples. This review gives a quick overview of the methods for isolating synaptosomes and synaptoneurosomes before discussing the studies that have utilized these preparations to study localized synapse-specific protein translation in (patho)physiological situations, with an emphasis on AD. While the review is not an exhaustive accumulation of all the studies evaluating synaptic protein translation using the synaptosomal model, the aim is to assemble the most relevant studies that have done so. The hope is to provide a suitable research platform to aid neuroscientists to utilize the synaptosomal/synaptoneurosomal models to evaluate the molecular mechanisms of synaptic dysfunction within the specific confines of mRNA localization and protein translation research.

Hypertension linked to Alzheimer's disease via stroke: Mendelian randomization

This study aimed to investigate the relationship between hypertension and Alzheimer's disease (AD) and demonstrate the key role of stroke in this relationship using mediating Mendelian randomization. AD, a neurodegenerative disease characterized by memory loss, cognitive impairment, and behavioral abnormalities, severely affects the quality of life of patients. Hypertension is an important risk factor for AD. However, the precise mechanism underlying this relationship is unclear. To investigate the relationship between hypertension and AD, we used a mediated Mendelian randomization method and screened for mediating variables between hypertension and AD by setting instrumental variables. The results of the mediated analysis showed that stroke, as a mediating variable, plays an important role in the causal relationship between hypertension and AD. Specifically, the mediated indirect effect value for stroke obtained using multivariate mediated MR analysis was 54.9%. This implies that approximately 55% of the risk of AD owing to hypertension can be attributed to stroke. The results suggest that the increased risk of AD owing to hypertension is mediated through stroke. The finding not only sheds light on the relationship between hypertension and AD but also indicates novel methods for the prevention and treatment of AD. By identifying the critical role of stroke in the link between hypertension and AD, this study provides insights into potential interventions that could mitigate the impact of hypertension on AD. This could help develop personalized treatments and help improve the quality of life of patients with AD who suffer from hypertension.

A review of the flortaucipir literature for positron emission tomography imaging of tau neurofibrillary tangles

Alzheimer's disease is defined by the presence of β-amyloid plaques and neurofibrillary tau tangles potentially preceding clinical symptoms by many years. Previously only detectable post-mortem, these pathological hallmarks are now identifiable using biomarkers, permitting an in vivo definitive diagnosis of Alzheimer's disease. 18F-flortaucipir (previously known as 18F-T807; 18F-AV-1451) was the first tau positron emission tomography tracer to be introduced and is the only Food and Drug Administration-approved tau positron emission tomography tracer (Tauvid™). It has been widely adopted and validated in a number of independent research and clinical settings. In this review, we present an overview of the published literature on flortaucipir for positron emission tomography imaging of neurofibrillary tau tangles. We considered all accessible peer-reviewed literature pertaining to flortaucipir through 30 April 2022. We found 474 relevant peer-reviewed publications, which were organized into the following categories based on their primary focus: typical Alzheimer's disease, mild cognitive impairment and pre-symptomatic populations; atypical Alzheimer's disease; non-Alzheimer's disease neurodegenerative conditions; head-to-head comparisons with other Tau positron emission tomography tracers; and technical considerations. The available flortaucipir literature provides substantial evidence for the use of this positron emission tomography tracer in assessing neurofibrillary tau tangles in Alzheimer's disease and limited support for its use in other neurodegenerative disorders. Visual interpretation and quantitation approaches, although heterogeneous, mostly converge and demonstrate the high diagnostic and prognostic value of flortaucipir in Alzheimer's disease.

The efficacy and safety of anti-Aβ agents for delaying cognitive decline in Alzheimer's disease: a meta-analysis

Background

This meta-analysis evaluates the efficacy and safety of amyloid-β (Aβ) targeted therapies for delaying cognitive deterioration in Alzheimer's disease (AD).

Methods

PubMed, EMBASE, the Cochrane Library, and ClinicalTrials.gov were systematically searched to identify relevant studies published before January 18, 2023.

Results

We pooled 33,689 participants from 42 studies. The meta-analysis showed no difference between anti-Aβ drugs and placebo in the Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog), and anti-Aβ drugs were associated with a high risk of adverse events [ADAS-Cog: MDs = -0.08 (-0.32 to 0.15), p = 0.4785; AEs: RR = 1.07 (1.02 to 1.11), p = 0.0014]. Monoclonal antibodies outperformed the placebo in delaying cognitive deterioration as measured by ADAS-Cog, Clinical Dementia Rating-Sum of Boxes (CDR-SB), Mini-Mental State Examination (MMSE) and Alzheimer's Disease Cooperative Study-Activities of Daily Living (ADCS-ADL), without increasing the risk of adverse events [ADAS-Cog: MDs = -0.55 (-0.89 to 0.21), p = 0.001; CDR-SB: MDs = -0.19 (-0.29 to -0.10), p < 0.0001; MMSE: MDs = 0.19 (0.00 to 0.39), p = 0.05; ADCS-ADL: MDs = 1.26 (0.84 to 1.68), p < 0.00001]. Intravenous immunoglobulin and γ-secretase modulators (GSM) increased cognitive decline in CDR-SB [MDs = 0.45 (0.17 to 0.74), p = 0.002], but had acceptable safety profiles in AD patients. γ-secretase inhibitors (GSI) increased cognitive decline in ADAS-Cog, and also in MMSE and ADCS-ADL. BACE-1 inhibitors aggravated cognitive deterioration in the outcome of the Neuropsychiatric Inventory (NPI). GSI and BACE-1 inhibitors caused safety concerns. No evidence indicates active Aβ immunotherapy, MPAC, or tramiprosate have effects on cognitive function and tramiprosate is associated with serious adverse events.

Conclusion

Current evidence does not show that anti-Aβ drugs have an effect on cognitive performance in AD patients. However, monoclonal antibodies can delay cognitive decline in AD. Development of other types of anti-Aβ drugs should be cautious.

Systematic Review Registration

PROSPERO (https://www.crd.york.ac.uk/prospero/), identifier CRD42023391596.

Salvianolic acid B ameliorates retinal deficits in an early-stage Alzheimer's disease mouse model through downregulating BACE1 and Aβ generation

Alzheimer's disease (AD) is a neurodegenerative disease with subtle onset, early diagnosis remains challenging. Accumulating evidence suggests that the emergence of retinal damage in AD precedes cognitive impairment, and may serve as a critical indicator for early diagnosis and disease progression. Salvianolic acid B (Sal B), a bioactive compound isolated from the traditional Chinese medicinal herb Salvia miltiorrhiza, has been shown promise in treating neurodegenerative diseases, such as AD and Parkinson's disease. In this study we investigated the therapeutic effects of Sal B on retinopathy in early-stage AD. One-month-old transgenic mice carrying five familial AD mutations (5×FAD) were treated with Sal B (20 mg·kg-1·d-1, i.g.) for 3 months. At the end of treatment, retinal function and structure were assessed, cognitive function was evaluated in Morris water maze test. We showed that 4-month-old 5×FAD mice displayed distinct structural and functional deficits in the retinas, which were significantly ameliorated by Sal B treatment. In contrast, untreated, 4-month-old 5×FAD mice did not exhibit cognitive impairment compared to wild-type mice. In SH-SY5Y-APP751 cells, we demonstrated that Sal B (10 μM) significantly decreased BACE1 expression and sorting into the Golgi apparatus, thereby reducing Aβ generation by inhibiting the β-cleavage of APP. Moreover, we found that Sal B effectively attenuated microglial activation and the associated inflammatory cytokine release induced by Aβ plaque deposition in the retinas of 5×FAD mice. Taken together, our results demonstrate that functional impairments in the retina occur before cognitive decline, suggesting that the retina is a valuable reference for early diagnosis of AD. Sal B ameliorates retinal deficits by regulating APP processing and Aβ generation in early AD, which is a potential therapeutic intervention for early AD treatment.

The hidden players: Shedding light on the significance of post-translational modifications and miRNAs in Alzheimer's disease development

Alzheimer's disease (AD) is the most prevalent, expensive, lethal, and burdening neurodegenerative disease of this century. The initial stages of this disease are characterized by a reduced ability to encode and store new memories. Subsequent cognitive and behavioral deterioration occurs during the later stages. Abnormal cleavage of amyloid precursor protein (APP) resulting in amyloid-beta (Aβ) accumulation along with hyperphosphorylation of tau protein are the two characteristic hallmarks of AD. Recently, several post-translational modifications (PTMs) have been identified on both Aβ as well as tau proteins. However, a complete understanding of how different PTMs influence the structure and function of proteins in both healthy and diseased conditions is still lacking. It has been speculated that these PTMs might play vital roles in the progression of AD. In addition, several short non-coding microRNA (miRNA) sequences have been found to be deregulated in the peripheral blood of Alzheimer patients. The miRNAs are single-stranded RNAs that control gene expression by causing mRNA degradation, deadenylation, or translational repression and have been implicated in the regulation of several neuronal and glial activities. The lack of comprehensive understanding regarding disease mechanisms, biomarkers, and therapeutic targets greatly hampers the development of effective strategies for early diagnosis and the identification of viable therapeutic targets. Moreover, existing treatment options for managing the disease have proven to be ineffective and provide only temporary relief. Therefore, understanding the role of miRNAs and PTMs in AD can provide valuable insights into disease mechanisms, aid in the identification of biomarkers, facilitate the discovery of novel therapeutic targets, and inspire innovative treatments for this challenging condition.

Tear Biomarkers and Alzheimer's Disease

Alzheimer's disease (AD) is an age-related progressive neurodegenerative brain disorder that represents the most common type of dementia. It poses a significant diagnostic challenge that requires timely recognition and treatment. Currently, there is no effective therapy for AD; however, certain medications may slow down its progression. The discovery of AD biomarkers, namely, magnetic resonance imaging, positron emission tomography and cerebrospinal fluid molecules (amyloid-β and tau) has advanced our understanding of this disease and has been crucial for identifying early neuropathologic changes prior to clinical changes and cognitive decline. The close interrelationship between the eye and the brain suggests that tears could be an interesting source of biomarkers for AD; however, studies in this area are limited. The identification of biomarkers in tears will enable the development of cost-effective, non-invasive methods of screening, diagnosis and disease monitoring. In order to use tears as a standard method for early and non-invasive diagnosis of AD, future studies need to be conducted on a larger scale.

Advances in diagnosing mild cognitive impairment and Alzheimer's disease using 11C-PIB- PET/CT and common neuropsychological tests

Alzheimer's disease (AD) is a critical health issue worldwide that has a negative impact on patients' quality of life, as well as on caregivers, society, and the environment. Positron emission tomography (PET)/computed tomography (CT) and neuropsychological scales can be used to identify AD and mild cognitive impairment (MCI) early, provide a differential diagnosis, and offer early therapies to impede the course of the illness. However, there are few reports of large-scale ¹¹C-PIB-PET/CT investigations that focus on the pathology of AD and MCI. Therefore, further research is needed to determine how neuropsychological test scales and PET/CT measurements of disease progression interact.

GFAP as a Potential Biomarker for Alzheimer's Disease: A Systematic Review and Meta-Analysis

Blood biomarkers have been considered tools for the diagnosis, prognosis, and monitoring of Alzheimer's disease (AD). Although amyloid-β peptide (Aβ) and tau are primarily blood biomarkers, recent studies have identified other reliable candidates that can serve as measurable indicators of pathological conditions. One such candidate is the glial fibrillary acidic protein (GFAP), an astrocytic cytoskeletal protein that can be detected in blood samples. Increasing evidence suggests that blood GFAP levels can be used to detect early-stage AD. In this systematic review and meta-analysis, we aimed to evaluate GFAP in peripheral blood as a biomarker for AD and provide an overview of the evidence regarding its utility. Our analysis revealed that the GFAP level in the blood was higher in the Aβ-positive group than in the negative groups, and in individuals with AD or mild cognitive impairment (MCI) compared to the healthy controls. Therefore, we believe that the clinical use of blood GFAP measurements has the potential to accelerate the diagnosis and improve the prognosis of AD.

Identifying Hair Biomarker Candidates for Alzheimer's Disease Using Three High Resolution Mass Spectrometry-Based Untargeted Metabolomics Strategies

High-resolution mass spectrometry (HRMS)-based untargeted metabolomics strategies have emerged as an effective tool for discovering biomarkers of Alzheimer's disease (AD). There are various HRMS-based untargeted metabolomics strategies for biomarker discovery, including the data-dependent acquisition (DDA) method, the combination of full scan and target MS/MS, and the all ion fragmentation (AIF) method. Hair has emerged as a potential biospecimen for biomarker discovery in clinical research since it might reflect the circulating metabolic profiles over several months, while the analytical performances of the different data acquisition methods for hair biomarker discovery have been rarely investigated. Here, the analytical performances of three data acquisition methods in HRMS-based untargeted metabolomics for hair biomarker discovery were evaluated. The human hair samples from AD patients (N = 23) and cognitively normal individuals (N = 23) were used as an example. The most significant number of discriminatory features was acquired using the full scan (407), which is approximately 10-fold higher than that using the DDA strategy (41) and 11% higher than that using the AIF strategy (366). Only 66% of discriminatory chemicals discovered in the DDA strategy were discriminatory features in the full scan dataset. Moreover, compared to the deconvoluted MS/MS spectra with coeluted and background ions from the AIF method, the MS/MS spectrum obtained from the targeted MS/MS approach is cleaner and purer. Therefore, an untargeted metabolomics strategy combining the full scan with the targeted MS/MS method could obtain most discriminatory features along with a high quality MS/MS spectrum for discovering the AD biomarkers.

Systematic review of brain and blood lipidomics in Alzheimer's disease mouse models

Alzheimer's disease (AD) diagnosis is based on invasive and expensive biomarkers. Regarding AD pathophysiological mechanisms, there is evidence of a link between AD and aberrant lipid homeostasis. Alterations in lipid composition have been observed in blood and brain samples, and transgenic mouse models represent a promising approach. Nevertheless, there is great variability among studies in mice for the determination of different types of lipids in targeted and untargeted methods. It could be explained by the different variables (model, age, sex, analytical technique), and experimental conditions used. The aim of this work is to review the studies on lipid alteration in brain tissue and blood samples from AD mouse models, focusing on different experimental parameters. As result, great disparity has been observed among the reviewed studies. Brain studies showed an increase in gangliosides, sphingomyelins, lysophospholipids and monounsaturated fatty acids and a decrease in sulfatides. In contrast, blood studies showed an increase in phosphoglycerides, sterols, diacylglycerols, triacylglycerols and polyunsaturated fatty acids, and a decrease in phospholipids, lysophospholipids and monounsaturated fatty acids. Thus, lipids are closely related to AD, and a consensus on lipidomics studies could be used as a diagnostic tool and providing insight into the mechanisms involved in AD.

R1ρ dispersion in white matter correlates with quantitative metrics of cognitive impairment

Much previous neuroimaging research in Alzheimer's disease has focused on the roles of amyloid and tau proteins, but recent studies have implicated microvascular changes in white matter as early indicators of damage related to later dementia. We used MRI to derive novel, non-invasive measurements of R1ρ dispersion using different locking fields to characterize variations of microvascular structure and integrity in brain tissues. We developed a non-invasive 3D R1ρ dispersion imaging technique using different locking fields at 3T. We acquired MR images and cognitive assessments of participants with mild cognitive impairment (MCI) and compared them to age-matched healthy controls in a cross-sectional study. After providing informed consent, 40 adults aged 62 to 82 years (n = 17 MCI) were included in this study. White matter ΔR1ρ-fraction measured by R1ρ dispersion imaging showed a strong correlation with the cognitive status of older adults (βstd = -0.4, p-value < 0.01) independent of age, in contrast to other conventional MRI markers such as T2, R1ρ, and white matter hyperintense lesion volume (WMHs) measured with T2-FLAIR. The correlation of WMHs with cognitive status was no longer significant after adjusting for age and sex in linear regression analysis, and the size of the regression coefficient was substantially decreased (53% lower). This work establishes a new non-invasive method that potentially characterizes impairment of the microvascular structure of white matter in MCI patients compared to healthy controls. The application of this method in longitudinal studies would improve our fundamental understanding of the pathophysiologic changes that accompany abnormal cognitive decline with aging and help identify potential targets for treatment of Alzheimer's disease.

Discovering Hair Biomarkers of Alzheimer's Disease Using High Resolution Mass Spectrometry-Based Untargeted Metabolomics

Hair may be a potential biospecimen to discover biomarkers for Alzheimer's disease (AD) since it reflects the integral metabolic profiles of body burden over several months. Here, we described the AD biomarker discovery in the hair using a high-resolution mass spectrometry (HRMS)-based untargeted metabolomics approach. A total of 24 patients with AD and 24 age- and sex-matched cognitively healthy controls were recruited. The hair samples were collected 0.1-cm away from the scalp and further cut into 3-cm segments. Hair metabolites were extracted by ultrasonication with methanol/phosphate-buffered saline 50/50 (v/v) for 4 h. A total of 25 discriminatory chemicals in hair between the patients with AD and controls were discovered and identified. The AUC value achieved 0.85 (95% CI: 0.72~0.97) in patients with very mild AD compared to healthy controls using a composite panel of the 9 biomarker candidates, indicating high potential for the initiation or promotion phase of AD dementia in the early stage. A metabolic panel combined with the nine metabolites may be used as biomarkers for the early detection of AD. The hair metabolome can be used to reveal metabolic perturbations for biomarker discovery. Investigating perturbations of the metabolites will offer insight into the pathogenesis of AD.

MidCog study: a prospective, observational cohort study investigating health literacy, self-management skills and cognitive function in middle-aged adults

INTRODUCTION

The lack of definitive means to prevent or treat cognitive impairment or dementia is driving intense efforts to identify causal mechanisms. Recent evidence suggests clinically meaningful declines in cognition might present as early as middle age. Studying cognitive changes in middle adulthood could elucidate modifiable factors affecting later cognitive and health outcomes, yet few cognitive ageing studies include this age group. The purpose of the MidCog study is to begin investigations of less-studied and potentially modifiable midlife determinants of later life cognitive outcomes.

METHODS AND ANALYSIS

MidCog is a prospective cohort study of adults ages 35-64, with two in-person interviews 2.5 years apart. Data will be collected from interviews, electronic health records and pharmacy fill data. Measurements will include health literacy, self-management skills, cognitive function, lifestyle and health behaviours, healthcare use, health status and chronic disease outcomes. Associations of health literacy and self-management skills with health behaviours and cognitive/health outcomes will be examined in a series of regression models, and moderating effects of modifiable psychosocial factors.Finally, MidCog data will be linked to an ongoing, parallel cohort study of older adults recruited at ages 55-74 in 2008 ('LitCog'; ages 70-90 in 2023), to explore associations between age, health literacy, self-management skills, chronic diseases, health status and cognitive function among adults ages 35-90.

ETHICS AND DISSEMINATION

The Institutional Review Board at Northwestern University has approved the MidCog study protocol (STU00214736). Results will be published in peer-reviewed journals and summaries will be provided to the funders of the study as well as patients.

Effectiveness of an Individualized Exergame-Based Motor-Cognitive Training Concept Targeted to Improve Cognitive Functioning in Older Adults With Mild Neurocognitive Disorder: Study Protocol for a Randomized Controlled Trial

BACKGROUND

Simultaneous motor-cognitive training is considered promising for preventing the decline in cognitive functioning in older adults with mild neurocognitive disorder (mNCD) and can be highly motivating when applied in the form of exergaming. The literature points to opportunities for improvement in the application of exergames in individuals with mNCD by developing novel exergames and exergame-based training concepts that are specifically tailored to patients with mNCD and ensuring the implementation of effective training components.

OBJECTIVE

This study systematically explores the effectiveness of a newly developed exergame-based motor-cognitive training concept (called "Brain-IT") targeted to improve cognitive functioning in older adults with mNCD.

METHODS

A 2-arm, parallel-group, single-blinded randomized controlled trial with a 1:1 allocation ratio (ie, intervention: control), including 34 to 40 older adults with mNCD will be conducted between May 2022 and December 2023. The control group will proceed with the usual care provided by the (memory) clinics where the patients are recruited. The intervention group will perform a 12-week training intervention according to the "Brain-IT" training concept, in addition to usual care. Global cognitive functioning will be assessed as the primary outcome. As secondary outcomes, domain-specific cognitive functioning, brain structure and function, spatiotemporal parameters of gait, instrumental activities of daily living, psychosocial factors, and resting cardiac vagal modulation will be assessed. Pre- and postintervention measurements will take place within 2 weeks before starting and after completing the intervention. A 2-way analysis of covariance or the Quade nonparametric analysis of covariance will be computed for all primary and secondary outcomes, with the premeasurement value as a covariate for the predicting group factor and the postmeasurement value as the outcome variable. To determine whether the effects are substantive, partial eta-squared (η²_p) effect sizes will be calculated for all primary and secondary outcomes.

RESULTS

Upon the initial submission of this study protocol, 13 patients were contacted by the study team. Four patients were included in the study, 2 were excluded because they were not eligible, and 7 were being informed about the study in detail. Of the 4 included patients, 2 already completed all premeasurements and were in week 2 of the intervention period. Data collection is expected to be completed by December 2023. A manuscript of the results will be submitted for publication in a peer-reviewed open-access journal in 2024.

CONCLUSIONS

This study contributes to the evidence base in the highly relevant area of preventing disability because of cognitive impairment, which has been declared a public health priority by the World Health Organization.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05387057; https://clinicaltrials.gov/ct2/show/NCT05387057.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/41173.

Effect of a dual orexin receptor antagonist on Alzheimer's disease: Sleep disorders and cognition

Orexin is a neuropeptide produced by the lateral hypothalamus that plays an important role in regulating the sleep-wake cycle. The overexpression of the orexinergic system may be related to the pathology of sleep/wakefulness disorders in Alzheimer's disease (AD). In AD patients, the increase in cerebrospinal fluid orexin levels is associated with parallel sleep deterioration. Dual orexin receptor antagonist (DORA) can not only treat the sleep-wakefulness disorder of AD but also improve the performance of patients with cognitive behavior disorder. It is critical to clarify the role of the orexin system in AD, study its relationship with cognitive decline in AD, and evaluate the safety and efficacy of DORA.

Dissociation of Arousal Index Between REM and NREM Sleep in Elderly Adults with Cognitive Impairment, No Dementia: A Pilot Study

BACKGROUND

Sleep disruption in elderly has been associated with an increased risk of cognitive impairment and its transition into Alzheimer's disease (AD). High arousal indices (AIs) during sleep may serve as an early-stage biomarker of cognitive impairment non-dementia (CIND).

OBJECTIVE

Using full-night polysomnography (PSG), we investigated whether CIND is related to different AIs between NREM and REM sleep stages.

METHODS

Fourteen older adults voluntarily participated in this population-based study that included Mini-Mental State Examination, Neuropsi battery, Katz Index of Independence in Activities of Daily Living, and single-night PSG. Subjects were divided into two groups (n = 7 each) according to their results in Neuropsi memory and attention subtests: cognitively unimpaired (CU), with normal results; and CIND, with -2.5 standard deviations in memory and/or attention subtests. AIs per hour of sleep during N1, N2, N3, and REM stages were obtained and correlated with Neuropsi total score (NTS).

RESULTS

AI (REM)  was significantly higher in CU group than in CIND group. For the total sample, a positive correlation between AI (REM)  and NTS was found (r = 0.68, p = 0.006), which remained significant when controlling for the effect of age and education. In CIND group, the AI (N2)  was significantly higher than the AI (REM) .

CONCLUSION

In CIND older adults, this attenuation of normal arousal mechanisms in REM sleep are dissociated from the relative excess of arousals observed in stage N2. We propose as probable etiology an early hypoactivity at the locus coeruleus noradrenergic system, associated to its early pathological damage, present in the AD continuum.

The Interplay Between Cholesterol and Amyloid-β on HT22 Cell Viability, Morphology, and Receptor Tyrosine Kinase Signaling

BACKGROUND

There is a lack of understanding in the molecular and cellular mechanisms of Alzheimer's disease that has hindered progress on therapeutic development. The focus has been on targeting toxic amyloid-β (Aβ) pathology, but these therapeutics have generally failed in clinical trials. Aβ is an aggregation-prone protein that has been shown to disrupt cell membrane structure in molecular biophysics studies and interfere with membrane receptor signaling in cell and animal studies. Whether the lipid membrane or specific receptors are the primary target of attack has not been determined.

OBJECTIVE

This work elucidates some of the interplay between membrane cholesterol and Aβ42 on HT22 neuronal cell viability, morphology, and platelet-derived growth factor (PDGF) signaling pathways.

METHODS

The effects of cholesterol depletion by methyl-β-cyclodextrin followed by treatment with Aβ and/or PDGF-AA were assessed by MTT cell viability assays, western blot, optical and AFM microscopy.

RESULTS

Cell viability studies show that cholesterol depletion was mildly protective against Aβ toxicity. Together cholesterol reduction and Aβ42 treatment compounded the disruption of the PDGFα receptor activation. Phase contrast optical microscopy and live cell atomic force microscopy imaging revealed that cytotoxic levels of Aβ42 caused morphological changes including cell membrane damage, cytoskeletal disruption, and impaired cell adhesion; cell damage was ameliorated by cellular cholesterol depletion.

CONCLUSIONS

Cholesterol depletion impacted the effects of Aβ42 on HT22 cell viability, morphology, and receptor tyrosine kinase signaling.

ALZHEIMER'S DISEASE AND ITS RELATIONSHIP WITH THE MICROBIOTA-GUT-BRAIN AXIS

BACKGROUND

Alzheimer's disease (AD) is a progressive and irreversible neurodegenerative disease, characterized by the accumulation of amyloid plaques and neurofibrillary tangles in the brain. Several pathways enable bidirectional communication between the central nervous system (CNS), the intestine and its microbiota, constituting the microbiota-gut-brain axis.

OBJECTIVE

Review the pathophysiology of AD, relate it to the microbiota-gut-brain axis and discuss the possibility of using probiotics in the treatment and/or prevention of this disease.

METHODS

Search of articles from the PubMed database published in the last 5 years (2017 to 2022) structure the narrative review.

RESULTS

The composition of the gut microbiota influences the CNS, resulting in changes in host behavior and may be related to the development of neurodegenerative diseases. Some metabolites produced by the intestinal microbiota, such as trimethylamine N-oxide (TMAO), may be involved in the pathogenesis of AD, while other compounds produced by the microbiota during the fermentation of food in the intestine, such as D-glutamate and fatty acids short chain, are beneficial in cognitive function. The consumption of live microorganisms beneficial to health, known as probiotics, has been tested in laboratory animals and humans to evaluate the effect on AD.

CONCLUSION

Although there are few clinical trials evaluating the effect of probiotic consumption in humans with AD, the results to date indicate a beneficial contribution of the use of probiotics in this disease.

Leptin ameliorates Aβ1-42-induced Alzheimer's disease by suppressing inflammation via activating p-Akt signaling pathway

Background

Alzheimer's disease (AD) is characterized by progressive neuronal loss, cognitive disorder, and memory decline. Leptin has been reported to have a neuroprotective effect on neurodegenerative diseases.

Objective

Our aim was to investigate whether intraperitoneal injection of leptin has a neuroprotective effect and to explore its underlying mechanisms in the AD mouse model.

Methods

Aβ1-42 was injected into male C57BL/6J mice to construct an AD mouse model, and leptin was injected intraperitoneally to cure AD. The Morris water maze test was used to investigate spatial learning ability. Neuronal loss was tested by tyrosine hydroxylase expression in the hippocampus, and terminal deoxynucleotidyl transferase mediated dUTP nick-end labeling assay was applied to detect neuronal apoptosis. Pro-inflammatory cytokine levels were monitored by RT-PCR and western blotting was selected to explore which signaling pathway leptin acted on.

Results

Leptin ameliorated spatial learning impairment, restored neuronal loss and apoptosis, and inhibited pro-inflammatory cytokine expression by activating the p-Akt signaling pathway in Aβ1-42-induced AD mice.

Conclusion

Leptin ameliorates Aβ1-42-induced AD by suppressing inflammation via activating the p-Akt signaling pathway.

Recognizing novel drugs against Keap1 in Alzheimer's disease using machine learning grounded computational studies

Alzheimer's disease (AD) is the most common neurodegenerative disorder in the world, affecting an estimated 50 million individuals. The nerve cells become impaired and die due to the formation of amyloid-beta (Aβ) plaques and neurofibrillary tangles (NFTs). Dementia is one of the most common symptoms seen in people with AD. Genes, lifestyle, mitochondrial dysfunction, oxidative stress, obesity, infections, and head injuries are some of the factors that can contribute to the development and progression of AD. There are just a few FDA-approved treatments without side effects in the market, and their efficacy is restricted due to their narrow target in the etiology of AD. Therefore, our aim is to identify a safe and potent treatment for Alzheimer's disease. We chose the ursolic acid (UA) and its similar compounds as a compounds' library. And the ChEMBL database was adopted to obtain the active and inactive chemicals against Keap1. The best Quantitative structure-activity relationship (QSAR) model was created by evaluating standard machine learning techniques, and the best model has the lowest RMSE and greatest R2 (Random Forest Regressor). We chose pIC50 of 6.5 as threshold, where the top five potent medicines (DB06841, DB04310, DB11784, DB12730, and DB12677) with the highest predicted pIC50 (7.091184, 6.900866, 6.800155, 6.768965, and 6.756439) based on QSAR analysis. Furthermore, the top five medicines utilize as ligand molecules were docked in Keap1's binding region. The structural stability of the nominated medications was then evaluated using molecular dynamics simulations, RMSD, RMSF, Rg, and hydrogen bonding. All models are stable at 20 ns during simulation, with no major fluctuations observed. Finally, the top five medications are shown as prospective inhibitors of Keap1 and are the most promising to battle AD.

Dementia Detection from Speech Using Machine Learning and Deep Learning Architectures

Dementia affects the patient's memory and leads to language impairment. Research has demonstrated that speech and language deterioration is often a clear indication of dementia and plays a crucial role in the recognition process. Even though earlier studies have used speech features to recognize subjects suffering from dementia, they are often used along with other linguistic features obtained from transcriptions. This study explores significant standalone speech features to recognize dementia. The primary contribution of this work is to identify a compact set of speech features that aid in the dementia recognition process. The secondary contribution is to leverage machine learning (ML) and deep learning (DL) models for the recognition task. Speech samples from the Pitt corpus in Dementia Bank are utilized for the present study. The critical speech feature set of prosodic, voice quality and cepstral features has been proposed for the task. The experimental results demonstrate the superiority of machine learning (87.6 percent) over deep learning (85 percent) models for recognizing Dementia using the compact speech feature combination, along with lower time and memory consumption. The results obtained using the proposed approach are promising compared with the existing works on dementia recognition using speech.

Efficacy of Glucose Metabolism-Related Indexes on the Risk and Severity of Alzheimer’s Disease: A Meta-Analysis

Background: Considering the strong correlation made between Alzheimer’s disease (AD) and the pathology of glucose metabolism disorder, we sought to analyze the effects of fasting blood glucose (FBG) level, fasting plasma insulin (FINS) level, and insulin resistance index (HOMA-IR) on the risk and severity of AD. Objective: Reveal the pathological relationship between AD and insulin resistance. Methods: We searched 5 databases from inception through April 4, 2022. Meta-regression was conducted to identify if there were significant differences between groups. Shapiro-Wilk test and the Q-Q diagram were applied to evaluate the normality of variables. A multiple logistic regression model was employed to explore the association between FBG, FINS, HOMA-IR, and Mini-Mental State Examination scale score (MMSE). Results: 47 qualified articles including 2,981 patients were enrolled in our study. FBG (p < 0.001), FINS (p < 0.001), and HOMA-IR (p < 0.001) were higher in AD patients than in controls. HOMA-IR was negatively correlated with MMSE (p = 0.001) and positively related to the sex ratio (male versus female) (p < 0.05). HOMA-IR obeyed lognormal distribution (p > 0.05), and the 95% bilateral boundary values were 0.73 and 10.67. FBG (p = 0.479) was positively correlated to MMSE, while FINS (p = 0.1657) was negatively correlated with MMSE. Conclusion: The increase in the levels of FBG, FINS, and HOMA-IR served as precise indicators of the risk of AD. HOMA-IR was found to be correlated to the increasing severity of AD, especially in male AD patients.

Changes in Oral Microbial Diversity in a Piglet Model of Traumatic Brain Injury

Dynamic changes in the oral microbiome have gained attention due to their potential diagnostic role in neurological diseases such as Alzheimer's disease and Parkinson's disease. Traumatic brain injury (TBI) is a leading cause of death and disability in the United States, but no studies have examined the changes in oral microbiome during the acute stage of TBI using a clinically translational pig model. Crossbred piglets (4-5 weeks old, male) underwent either a controlled cortical impact (TBI, n = 6) or sham surgery (sham, n = 6). The oral microbiome parameters were quantified from the upper and lower gingiva, both buccal mucosa, and floor of the mouth pre-surgery and 1, 3, and 7 days post-surgery (PS) using the 16S rRNA gene. Faith's phylogenetic diversity was significantly lower in the TBI piglets at 7 days PS compared to those of sham, and beta diversity at 1, 3, and 7 days PS was significantly different between TBI and sham piglets. However, no significant changes in the taxonomic composition of the oral microbiome were observed following TBI compared to sham. Further studies are needed to investigate the potential diagnostic role of the oral microbiome during the chronic stage of TBI with a larger number of subjects.

Is liquid biopsy mature enough for the diagnosis of Alzheimer's disease?

The preclinical diagnosis and clinical practice for Alzheimer's disease (AD) based on liquid biopsy have made great progress in recent years. As liquid biopsy is a fast, low-cost, and easy way to get the phase of AD, continual efforts from intense multidisciplinary studies have been made to move the research tools to routine clinical diagnostics. On one hand, technological breakthroughs have brought new detection methods to the outputs of liquid biopsy to stratify AD cases, resulting in higher accuracy and efficiency of diagnosis. On the other hand, diversiform biofluid biomarkers derived from cerebrospinal fluid (CSF), blood, urine, Saliva, and exosome were screened out and biologically verified. As a result, more detailed knowledge about the molecular pathogenesis of AD was discovered and elucidated. However, to date, how to weigh the reports derived from liquid biopsy for preclinical AD diagnosis is an ongoing question. In this review, we briefly introduce liquid biopsy and the role it plays in research and clinical practice. Then, we summarize the established fluid-based assays of the current state for AD diagnostic such as ELISA, single-molecule array (Simoa), Immunoprecipitation-Mass Spectrometry (IP-MS), liquid chromatography-MS, immunomagnetic reduction (IMR), multimer detection system (MDS). In addition, we give an updated list of fluid biomarkers in the AD research field. Lastly, the current outstanding challenges and the feasibility to use a stand-alone biomarker in the joint diagnostic strategy are discussed.

3-[(1H-Benzo[d][1,2,3]triazol-1-yl)oxy]propyl 9-hydroxy-5a,5b,8,8,11a-pentamethyl-1-(prop-1-en-2-yl)icosahydro-3aH-cyclopenta[a]chrysene-3a-carboxylate

We herein report on the synthesis of a pentacyclic triterpene functionalized through derivation of betulinic acid with hydroxybenzotriazole. The compound was fully characterized by proton (1H-NMR), carbon-13 (13C-NMR), heteronuclear single quantum coherence (HSQC) and distortionless enhancement by polarization transfer (DEPT-135 and DEPT-90) nuclear magnetic resonance. Ultraviolet (UV), and Fourier-transform infrared (FTIR) spectroscopies as well as and high-resolution mass spectrometry (HRMS) were also adopted. Computational studies were conducted to foresee the interactions between compound 3 and phosphodiesterase 9, a relevant target in the field of neurodegenerative diseases. Additionally, preliminary calculation of physico-chemical descriptors was performed to evaluate the drug-likeness of compound 3.

Designing the next-generation clinical care pathway for Alzheimer's disease

The reconceptualization of Alzheimer's disease (AD) as a clinical and biological construct has facilitated the development of biomarker-guided, pathway-based targeted therapies, many of which have reached late-stage development with the near-term potential to enter global clinical practice. These medical advances mark an unprecedented paradigm shift and requires an optimized global framework for clinical care pathways for AD. In this Perspective, we describe the blueprint for transitioning from the current, clinical symptom-focused and inherently late-stage diagnosis and management of AD to the next-generation pathway that incorporates biomarker-guided and digitally facilitated decision-making algorithms for risk stratification, early detection, timely diagnosis, and preventative or therapeutic interventions. We address critical and high-priority challenges, propose evidence-based strategic solutions, and emphasize that the perspectives of affected individuals and care partners need to be considered and integrated.

Amyloid-β protein and MicroRNA-384 in NCAM-Labeled exosomes from peripheral blood are potential diagnostic markers for Alzheimer's disease

Objective

We aimed to establish a method to determine whether amyloid‐β (Aβ) protein and miR‐384 in peripheral blood neural cell adhesion molecule (NCAM)/ATP‐binding cassette transporter A1 (ABCA1) dual‐labeled exosomes may serve as diagnostic markers for the diagnosis of Alzheimer's disease (AD).

Methods

This was a multicenter study using a two‐stage design. The subjects included 45 subjective cognitive decline (SCD) patients, 50 amnesic mild cognitive impairment (aMCI) patients, 40 AD patients, and 30 controls in the discovery stage. The results were validated in the verification stage in 47 SCD patients, 45 aMCI patients, 45 AD patients, and 30 controls. NCAM single‐labeled and NCAM/ABCA1 double‐labeled exosomes in the peripheral blood were captured and detected by immunoassay.

Results

The Aβ42, Aβ_42/40, Tau, P‐T181‐tau, and miR‐384 levels in NCAM single‐labeled and NCAM/ABCA1 double‐labeled exosomes of the aMCI and AD groups were significantly higher than those of the SCD, control, and vascular dementia (VaD) groups (all p < 0.05). The Aβ42 and miR‐384 levels in NCAM/ABCA1 dual‐labeled exosomes of the aMCI and AD groups were higher than those of the control and VaD groups (all p < 0.05). The exosomal Aβ42, Aβ_42/40, Tau, P‐T181‐tau, and miR‐384 levels in peripheral blood were correlated with those in cerebrospinal fluid (all p < 0.05).

Conclusion

This study, for the first time, established a method that sorts specific surface marker exosomes using a two‐step immune capture technology. The plasma NCAM/ABCA1 dual‐labeled exosomal Aβ_42/40 and miR‐384 had potential advantages in the diagnosis of SCD.

Tau-aggregation inhibition: promising role of nanoencapsulated dietary molecules in the management of Alzheimer's disease

Alzheimer's disease (AD) is a cumulative form of dementia associated with memory loss, cognition impairment, and finally leading to death. AD is characterized by abnormal deposits of extracellular beta-amyloid and intracellular Tau-protein tangles throughout the brain. During pathological conditions of AD, Tau protein undergoes various modifications and aggregates over time. A number of clinical trials on patients with AD symptoms have indicated the effectiveness of Tau-based therapies over anti-Aβ treatments. Thus, there is a huge paradigm shift toward Tau aggregation inhibitors. Several bioactives of plants and microbes have been suggested to cross the neuronal cell membrane and play a crucial role in managing neurodegenerative disorders. Bioactives mainly act as active modulators of AD pathology besides having antioxidant and anti-inflammatory potential. Studies also demonstrated the potential role of dietary molecules in inhibiting the formation of Tau aggregates and removing toxic Tau. Further, these molecules in nonencapsulated form exert enhanced Tau aggregation inhibition activity both in in vitro and in vivo studies suggesting a remarkable role of nanoencapsulation in AD management. The present article aims to review and discuss the structure-function relationship of Tau protein, the post-translational modifications that aid Tau aggregation and potential bioactives that inhibit Tau aggregation.