Significance of Blood and Cerebrospinal Fluid Biomarkers for Alzheimer's Disease: Sensitivity, Specificity and Potential for Clinical Use

Advancements in Immunity and Dementia Research: Highlights from the 2023 AAIC Advancements: Immunity Conference

The immune system is a key player in the onset and progression of neurodegenerative disorders. While brain resident immune cell-mediated neuroinflammation and peripheral immune cell (eg, T cell) infiltration into the brain have been shown to significantly contribute to Alzheimer's disease (AD) pathology, the nature and extent of immune responses in the brain in the context of AD and related dementias (ADRD) remain unclear. Furthermore, the roles of the peripheral immune system in driving ADRD pathology remain incompletely elucidated. In March of 2023, the Alzheimer's Association convened the Alzheimer's Association International Conference (AAIC), Advancements: Immunity, to discuss the roles of the immune system in ADRD. A wide range of topics were discussed, such as animal models that replicate human pathology, immune-related biomarkers and clinical trials, and lessons from other fields describing immune responses in neurodegeneration. This manuscript presents highlights from the conference and outlines avenues for future research on the roles of immunity in neurodegenerative disorders. HIGHLIGHTS: The immune system plays a central role in the pathogenesis of Alzheimer's disease. The immune system exerts numerous effects throughout the brain on amyloid-beta, tau, and other pathways. The 2023 AAIC, Advancements: Immunity, encouraged discussions and collaborations on understanding the role of the immune system.

AlzGenPred - CatBoost-based gene classifier for predicting Alzheimer's disease using high-throughput sequencing data

AD is a progressive neurodegenerative disorder characterized by memory loss. Due to the advancement in next-generation sequencing, an enormous amount of AD-associated genomics data is available. However, the information about the involvement of these genes in AD association is still a research topic. Therefore, AlzGenPred is developed to identify the AD-associated genes using machine-learning. A total of 13,504 features derived from eight sequence-encoding schemes were generated and evaluated using 16 machine learning algorithms. Network-based features significantly outperformed sequence-based features, effectively distinguishing AD-associated genes. In contrast, sequence-based features failed to classify accurately. To improve performance, we generated 24 fused features (6020 D) from sequence-based encodings, increasing accuracy by 5-7% using a two-step lightGBM-based recursive feature selection method. However, accuracy remained below 70% even after hyperparameter tuning. Therefore, network-based features were used to generate the CatBoost-based ML method AlzGenPred with 96.55% accuracy and 98.99% AUROC. The developed method is tested on the AlzGene dataset where it showed 96.43% accuracy. Then the model was validated using the transcriptomics dataset. AlzGenPred provides a reliable and user-friendly tool for identifying potential AD biomarkers, accelerating biomarker discovery, and advancing our understanding of AD. It is available at https://www.bioinfoindia.org/alzgenpred/ and https://github.com/shuklarohit815/AlzGenPred .

Clinical Insights on Caloric Restriction Mimetics for Mitigating Brain Aging and Related Neurodegeneration

Aging, an inevitable physiological process leading to a progressive decline in bodily functions, has been an abundantly researched domain with studies attempting to slow it down and reduce its debilitating effects. Investigations into the cellular and molecular pathways associated with aging have allowed the formulation of therapeutic strategies. Of these, caloric restriction (CR) has been implicated for its role in promoting healthy aging by modulating key molecular targets like Insulin/IGF-1, mTOR, and sirtuins. However, CR requires dedication and commitment to a strict regimen which poses a difficulty in maintaining consistency. To maneuver around cumbersome diets, Caloric Restriction Mimetics (CRMs) have emerged as promising alternatives by mimicking the beneficial effects of CR. This review elucidates the molecular foundations enabling CRMs like rapamycin, metformin, resveratrol, spermidine, and many more to function as suitable anti-aging molecules. Moreover, it explores clinical trials (retrieved from the clinicaltrials.gov database) aimed at demonstrating the efficacy of CRMs as effective candidates against age-related neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease.

Psychosis in Alzheimer Disease and Elevations in Disease-Relevant Biomarkers

Importance

The emergence of psychotic symptoms in Alzheimer disease (AD) is associated with accelerated cognitive and functional decline that may be related to disease pathology.

Objective

To investigate the longitudinal dynamics of plasma tau phosphorylated at threonine 181 (p-tau181) and neurofilament light chain protein (NfL) levels in association with the emergence of psychotic symptoms (delusions and hallucinations) in the context of AD.

Design, Setting, and Participants

This cohort study used longitudinal data from the Alzheimer Disease Neuroimaging Initiative (ADNI). Baseline analyses compared patients with mild cognitive impairment (MCI) and AD (both with psychosis [AD+P] and without psychosis [AD-P]) and participants who were cognitively unimpaired (CU). For the longitudinal analysis, participants with MCI and AD were subdivided into patients with evidence of psychosis at baseline (AD+P baseline) and patients free of psychosis at baseline who showed incidence of psychosis over the course of the study (AD+P incident). Study data were analyzed between June and November 2023.

Exposures

Plasma p-tau181 and NfL measures in individuals with MCI and AD, both with and without psychosis.

Main Outcomes and Measures

Plasma p-tau181 and NfL quantifications up to 48 months and concurrent assessments of presence or absence of delusions and hallucinations via the Neuropsychiatric Inventory (NPI) questionnaire.

Results

The cohort included 752 participants with AD (mean [SD] age, 74.2 [7.7] years; 434 male [57.7%]). A total of 424 CU participants had a mean (SD) age of 75.4 (6.6) years of whom 222 were female (52.4%). In the longitudinal analysis of p-tau181 trajectories of the AD+P group, the group of patients who showed incidence of psychosis over the course of follow-up (AD+P incident) demonstrated an associated increase in plasma p-tau181 levels compared with the group of patients who had psychosis at baseline (AD+P baseline) and showed an associated decrease in plasma p-tau181 levels (F4, 117 = 3.24; P = .01). The mean slope of p-tau181 change was significantly different in AD+P incident and AD+P baseline groups (F5,746 = 86.76, P < .0001) and when only individuals with amyloid-β positivity (Aβ+), which was determined using positron emission tomography, were compared (F5,455 = 84.60, P < .001). Patients who experienced psychosis at any time had increased levels of NfL relative to those who never experienced psychosis.

Conclusions and Relevance

Results of this cohort study suggest that the emergence of psychosis in AD was associated with elevations in plasma levels of p-tau181, highlighting the potential utility of plasma p-tau181 as a biomarker of neuropsychiatric illness in AD, which could have implications for predictive and treatment response strategies.

Long Non-Coding RNAs and Alzheimer's Disease: Towards Personalized Diagnosis

Alzheimer's disease (AD), a neurodegenerative disorder characterized by progressive cognitive decline, is the most common form of dementia. Currently, there is no single test that can diagnose AD, especially in understudied populations and developing countries. Instead, diagnosis is based on a combination of medical history, physical examination, cognitive testing, and brain imaging. Exosomes are extracellular nanovesicles, primarily composed of RNA, that participate in physiological processes related to AD pathogenesis such as cell proliferation, immune response, and neuronal and cardiovascular function. However, the identification and understanding of the potential role of long non-coding RNAs (lncRNAs) in AD diagnosis remain largely unexplored. Here, we clinically, cognitively, and genetically characterized a sample of 15 individuals diagnosed with AD (cases) and 15 controls from Barranquilla, Colombia. Advanced bioinformatics, analytics and Machine Learning (ML) techniques were used to identify lncRNAs differentially expressed between cases and controls. The expression of 28,909 lncRNAs was quantified. Of these, 18 were found to be differentially expressed and harbored in pivotal genes related to AD. Two lncRNAs, ENST00000608936 and ENST00000433747, show promise as diagnostic markers for AD, with ML models achieving > 95% sensitivity, specificity, and accuracy in both the training and testing datasets. These findings suggest that the expression profiles of lncRNAs could significantly contribute to advancing personalized AD diagnosis in this community, offering promising avenues for early detection and follow-up.

Exploratory Tau PET/CT with [11C]PBB3 in Patients with Suspected Alzheimer's Disease and Frontotemporal Lobar Degeneration: A Pilot Study on Correlation with PET Imaging and Cerebrospinal Fluid Biomarkers

Accurately diagnosing Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD) is challenging due to overlapping symptoms and limitations of current imaging methods. This study investigates the use of [11C]PBB3 PET/CT imaging to visualize tau pathology and improve diagnostic accuracy. Given diagnostic challenges with symptoms and conventional imaging, [11C]PBB3 PET/CT's potential to enhance accuracy was investigated by correlating tau pathology with cerebrospinal fluid (CSF) biomarkers, positron emission tomography (PET), computed tomography (CT), amyloid-beta, and Mini-Mental State Examination (MMSE). We conducted [11C]PBB3 PET/CT imaging on 24 patients with suspected AD or FTLD, alongside [11C]PiB PET/CT (13 patients) and [18F]FDG PET/CT (15 patients). Visual and quantitative assessments of [11C]PBB3 uptake using standardized uptake value ratios (SUV-Rs) and correlation analyses with clinical assessments were performed. The scans revealed distinct tau accumulation patterns; 13 patients had no or faint uptake (PBB3-negative) and 11 had moderate to pronounced uptake (PBB3-positive). Significant inverse correlations were found between [11C]PBB3 SUV-Rs and MMSE scores, but not with CSF-tau or CSF-amyloid-beta levels. Here, we show that [11C]PBB3 PET/CT imaging can reveal distinct tau accumulation patterns and correlate these with cognitive impairment in neurodegenerative diseases. Our study demonstrates the potential of [11C]PBB3-PET imaging for visualizing tau pathology and assessing disease severity, offering a promising tool for enhancing diagnostic accuracy in AD and FTLD. Further research is essential to validate these findings and refine the use of tau-specific PET imaging in clinical practice, ultimately improving patient care and treatment outcomes.

SIMOA Diagnostics on Alzheimer's Disease and Frontotemporal Dementia

BACKGROUND

Accurate diagnosis of Alzheimer's disease (AD) and frontotemporal dementia (FTD) represents a health issue due to the absence of disease traits. We assessed the performance of a SIMOA panel in cerebrospinal fluid (CSF) from 43 AD and 33 FTD patients with 60 matching Control subjects in combination with demographic-clinical characteristics.

METHODS

136 subjects (AD: n = 43, FTD: n = 33, Controls: n = 60) participated. Single-molecule array (SIMOA), glial fibrillary acidic protein (GFAP), neurofilament light (NfL), TAU, and ubiquitin carboxy-terminal hydrolase L1 (UCH-L1) in CSF were analyzed with a multiplex neuro 4plex kit. Receiver operating characteristic (ROC) curve analysis compared area under the curve (AUC), while the principal of the sparse partial least squares discriminant analysis (sPLS-DA) was used with the intent to strengthen the identification of confident disease clusters.

RESULTS

CSF exhibited increased levels of all SIMOA biomarkers in AD compared to Controls (AUCs: 0.71, 0.86, 0.92, and 0.94, respectively). Similar patterns were observed in FTD with NfL, TAU, and UCH-L1 (AUCs: 0.85, 0.72, and 0.91). sPLS-DA revealed two components explaining 19% and 9% of dataset variation.

CONCLUSIONS

CSF data provide high diagnostic accuracy among AD, FTD, and Control discrimination. Subgroups of demographic-clinical characteristics and biomarker concentration highlighted the potential of combining different kinds of data for successful and more efficient cohort clustering.

Skin-brain axis in Alzheimer's disease - Pathologic, diagnostic, and therapeutic implications: A Hypothetical Review

The dynamic interaction between the brain and the skin is termed the 'skin-brain axis.' Changes in the skin not only reflect conditions in the brain but also exert direct and indirect effects on the brain. Interestingly, the connection between the skin and brain is crucial for understanding aging and neurodegenerative diseases. Several studies have shown an association between Alzheimer's disease (AD) and various skin disorders, such as psoriasis, bullous pemphigoid, and skin cancer. Previous studies have shown a significantly increased risk of new-onset AD in patients with psoriasis. In contrast, skin cancer may reduce the risk of developing AD. Accumulating evidence suggests an interaction between skin disease and AD; however, AD-associated pathological changes mediated by the skin-brain axis are not yet clearly defined. While some studies have reported on the diagnostic implications of the skin-brain axis in AD, few have discussed its potential therapeutic applications. In this review, we address the pathological changes mediated by the skin-brain axis in AD. Furthermore, we summarize (1) the diagnostic implications elucidated through the role of the skin-brain axis in AD and (2) the therapeutic implications for AD based on the skin-brain axis. Our review suggests that a potential therapeutic approach targeting the skin-brain axis will enable significant advances in the treatment of AD.

A data-driven approach to complement the A/T/(N) classification system using CSF biomarkers

AIMS

The AT(N) classification system not only improved the biological characterization of Alzheimer's disease (AD) but also raised challenges for its clinical application. Unbiased, data-driven techniques such as clustering may help optimize it, rendering informative categories on biomarkers' values.

METHODS

We compared the diagnostic and prognostic abilities of CSF biomarkers clustering results against their AT(N) classification. We studied clinical (patients from our center) and research (Alzheimer's Disease Neuroimaging Initiative) cohorts. The studied CSF biomarkers included Aβ(1-42), Aβ(1-42)/Aβ(1-40) ratio, tTau, and pTau.

RESULTS

The optimal solution yielded three clusters in both cohorts, significantly different in diagnosis, AT(N) classification, values distribution, and survival. We defined these three CSF groups as (i) non-defined or unrelated to AD, (ii) early stages and/or more delayed risk of conversion to dementia, and (iii) more severe cognitive impairment subjects with faster progression to dementia.

CONCLUSION

We propose this data-driven three-group classification as a meaningful and straightforward approach to evaluating the risk of conversion to dementia, complementary to the AT(N) system classification.

Non-invasive Biomarkers for Early Detection of Alzheimer's Disease: a New-Age Perspective

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that primarily affects the elderly population. It gradually leads to memory loss, loss of thinking ability, and an overall cognitive decline. However, exhaustive literature is available to suggest that pathological changes in the brain occur decades before the first clinical symptoms appear. This review provides insight into the non-invasive biomarkers for early detection of AD that have been successfully studied in populations across the globe. These biomarkers have been detected in the blood, saliva, breath, and urine samples. Retinal imaging techniques are also reported. In this study, PubMed and Google scholar were the databases employed using keywords "Alzheimer's disease," "neurodegeneration," "non-invasive biomarkers," "early diagnosis," "blood-based biomarkers," and "preclinical AD," among others. The evaluation of these biomarkers will provide early diagnosis of AD in the preclinical stages due to their positive correlation with brain pathology in AD. Early diagnosis with reliable and timely intervention can effectively manage this disease.

Multilayered Bioorthogonal SERS Nanoprobes Selectively Aggregating in Human Fluids: A Smart Optical Assay for β-Amyloid Peptide Quantification

Alzheimer's disease (AD) is a debilitating neurological condition characterized by cognitive decline, memory loss, and behavioral skill impairment, features that worsen with time. Early diagnosis will likely be the most effective therapy for Alzheimer's disease since it can ensure timely pharmacological treatments that can reduce the irreversible progression and delay the symptoms. Amyloid β-peptide 1-42 (Aβ (1-42)) is considered one of the key pathological AD biomarkers that is present in different biological fluids. However, Aβ (1-42) detection still relies on colorimetric and enzyme-linked immunoassays as the gold standard characterized by low accuracy or high costs, respectively. In this context, optical detection techniques based on surface-enhanced Raman spectroscopy (SERS) through advanced nanoconstructs are promising alternatives for the development of novel rapid and low-cost methods for the targeting of Aβ pathological biomarkers in fluids. Here, a multilayered nanoprobe constituted by bioorthogonal Raman reporters (RRs) embedded within two layers of gold nanoparticles (Au@RRs@AuNPs) has been developed and successfully validated for specific detection of Aβ (1-42) in the human cerebrospinal fluid (CSF) with sensitivity down to pg/mL. The smart double-layer configuration enables us to exploit the outer gold NP surfaces for selective absorption of targeted peptide whose concentration controls the aggregation behavior of Au@RRs@AuNPs, proportionally reflected in Raman intensity changes, providing high specificity and sensitivity and representing a significant step ahead of the state of the art on SERS for clinical analyses.

Peripheral Blood and Cerebrospinal Fluid Levels of YKL-40 in Alzheimer's Disease: A Systematic Review and Meta-Analysis

The pathogenesis associated with Alzheimer's disease (AD) is particularly complicated, and early diagnosis and course monitoring of the disease are not ideal based on the available core biomarkers. As a biomarker closely related to neuroinflammation, YKL-40 provides a potential scalable approach in AD, but its association remains controversial and inconclusive with AD. We conducted this study to assess the utility of YKL-40 levels in peripheral blood and cerebrospinal fluid (CSF) of AD patients and healthy controls (HCs) by meta-analysis. We systematically searched and screened relevant trials for comparing YKL-40 levels between AD patients and HCs in PubMed, Embase, Cochrane, and Web of Science, with a search deadline of 14 March 2023 for each database. A total of 17 eligible and relevant studies involving 1811 subjects, including 949 AD patients and 862 HCs, were included. The results showed that YKL-40 levels in the peripheral blood of AD patients and HCs did not possess significant differences. Subgroup analysis showed YKL-40 significantly differed in plasma (SMD = 0.527, 95%CI: [0.302, 0.752]; p = 0.000), but did not in serum. In the case of comparison with HCs, YKL-40 was significantly higher in CSF of AD patients (SMD = 0.893, 95%CI: [0.665, 1.121]; p = 0.000). Besides that, when we performed a combined analysis of total YKL-40 in both peripheral blood and CSF, overall YKL-40 concentrations were also significantly increased among AD patients (SMD = 0.608, 95%CI: [0.272, 0.943]; p = 0.000). YKL-40 provides support and rationale for the neuroinflammatory pathogenesis of AD. The significance of CSF levels of YKL-40 for early screening of AD is definite. Plasma levels of YKL-40 also appear to assist in discriminating AD patients from HCs, which facilitates early screening and monitoring of the natural course of AD.

Chiral Amino Acid Profiling in Serum Reveals Potential Biomarkers for Alzheimer's Disease

BACKGROUND

Alzheimer's disease (AD) is a complex neurodegenerative disease, and increasing evidence has linked dysregulation of amino acids to AD pathogenesis. However, the existing studies often ignore the chirality of amino acids, and some results are inconsistent and controversial. The changes of amino acid profiles in AD from the perspective of enantiomers remain elusive.

OBJECTIVE

The purpose of this study is to investigate whether the levels of amino acids, especially D-amino acids, are deregulated in the peripheral serum of AD patients, with the ultimate goal of discovering novel biomarkers for AD.

METHODS

The chiral amino acid profiles were determined by HPLC-MS/MS with a pre-column derivatization method. Experimental data obtained from 37 AD patients and 34 healthy controls (HC) were statistically analyzed.

RESULTS

Among the 35 amino acids detected, D-proline, D/total-proline ratio, D-aspartate, and D/total-aspartate ratio were decreased, while D-phenylalanine was elevated in AD compared to HC. Significant age-dependent increases in D-proline, D/total-proline ratio, and D-phenylalanine were observed in HC, but not in AD. Receiver operator characteristic analyses of the combination of D-proline, D-aspartate, D-phenylalanine, and age for discriminating AD from HC provided satisfactory area under the curve (0.87), specificity (97.0%), and sensitivity (83.8%). Furthermore, the D-aspartate level was significantly decreased with the progression of AD, as assessed by the Clinical Dementia Rating Scale and Mini-Mental State Examination.

CONCLUSION

The panels of D-proline, D-phenylalanine, and D-aspartate in peripheral serum may serve as novel biomarker candidates for AD. The latter parameter is further associated with the severity of AD.

Dynamic changes in metabolites of the kynurenine pathway in Alzheimer’s disease, Parkinson’s disease, and Huntington’s disease: A systematic Review and meta-analysis

Background

Tryptophan (TRP) is an essential amino acid that must be provided in the diet. The kynurenine pathway (KP) is the main route of TRP catabolism into nicotinamide adenosine dinucleotide (NAD⁺), and metabolites of this pathway may have protective or degenerative effects on the nervous system. Thus, the KP may be involved in neurodegenerative diseases.

Objectives

The purpose of this systematic review and meta-analysis is to assess the changes in KP metabolites such as TRP, kynurenine (KYN), kynurenic acid (KYNA), Anthranilic acid (AA), 3-hydroxykynurenine (3-HK), 5-Hydroxyindoleacetic acid (5-HIAA), and 3-Hydroxyanthranilic acid (3-HANA) in Alzheimer’s disease (AD), Parkinson’s disease (PD), and Huntington’s disease (HD) patients compared to the control group.

Methods

We conducted a literature search using PubMed/Medline, Scopus, Google Scholar, Web of Science, and EMBASE electronic databases to find articles published up to 2022. Studies measuring TRP, KYN, KYNA, AA, 3-HK, 5-HIAA, 3-HANA in AD, PD, or HD patients and controls were identified. Standardized mean differences (SMDs) were used to determine the differences in the levels of the KP metabolites between the two groups.

Results

A total of 30 studies compromising 689 patients and 774 controls were included in our meta-analysis. Our results showed that the blood levels of TRP was significantly lower in the AD (SMD=-0.68, 95% CI=-0.97 to -0.40, p=0.000, I2 = 41.8%, k=8, n=382), PD (SMD=-0.77, 95% CI=-1.24 to -0.30, p=0.001, I2 = 74.9%, k=4, n=352), and HD (SMD=-0.90, 95% CI=-1.71 to -0.10, p=0.028, I2 = 91.0%, k=5, n=369) patients compared to the controls. Moreover, the CSF levels of 3-HK in AD patients (p=0.020) and the blood levels of KYN in HD patients (p=0.020) were lower compared with controls.

Conclusion

Overall, the findings of this meta-analysis support the hypothesis that the alterations in the KP may be involved in the pathogenesis of AD, PD, and HD. However, additional research is needed to show whether other KP metabolites also vary in AD, PD, and HD patients. So, the metabolites of KP can be used for better diagnosing these diseases.

Effects of Electroacupuncture on the Correlation between Serum and Central Immunity in AD Model Animals

Objective

The goal was to investigate the connection between neuroinflammation in the brain and serum inflammatory markers as Alzheimer's disease progressed. We also sought to determine whether electroacupuncture had an effect on inflammatory markers found in blood and other brain regions.

Methods

As an animal model for AD, we used senescence-accelerated mouse prone 8 (SAMP8) mice. To examine the effects and probable mechanism of electroacupuncture, we used HE staining, immunofluorescence staining, western blotting, and enzyme-linked immunosorbent assay.

Results

Electroacupuncture therapy protected neurons, significantly downregulated the Iba-1 level in the hippocampus (p value was 0.003), frontal lobe cortex (p value was 0.042), and temporal lobe cortex (p value was 0.013) of the AD animal model, all of which had significantly lower levels of IL-6 (p value was 0.001), IL-1β (p value was 0.001), and TNF-α (p value was 0.001) in their serum.

Conclusion

The amounts of IL-6, IL-1β, and TNF-α detected in the serum were strongly linked to the levels discovered in the hippocampus and the frontal lobes of the brain, respectively. A better understanding of the electroacupuncture process as well as the course of Alzheimer's disease and the therapeutic benefits of electroacupuncture may be gained by using biomarkers such as serum inflammatory marker biomarkers.

Clinical relevance of biomarkers, new therapeutic approaches, and role of post-translational modifications in the pathogenesis of Alzheimer's disease

Alzheimer's disease (AD) is a neurodegenerative disorder that causes progressive loss of cognitive functions like thinking, memory, reasoning, behavioral abilities, and social skills thus affecting the ability of a person to perform normal daily functions independently. There is no definitive cure for this disease, and treatment options available for the management of the disease are not very effective as well. Based on histopathology, AD is characterized by the accumulation of insoluble deposits of amyloid beta (Aβ) plaques and neurofibrillary tangles (NFTs). Although several molecular events contribute to the formation of these insoluble deposits, the aberrant post-translational modifications (PTMs) of AD-related proteins (like APP, Aβ, tau, and BACE1) are also known to be involved in the onset and progression of this disease. However, early diagnosis of the disease as well as the development of effective therapeutic approaches is impeded by lack of proper clinical biomarkers. In this review, we summarized the current status and clinical relevance of biomarkers from cerebrospinal fluid (CSF), blood and extracellular vesicles involved in onset and progression of AD. Moreover, we highlight the effects of several PTMs on the AD-related proteins, and provide an insight how these modifications impact the structure and function of proteins leading to AD pathology. Finally, for disease-modifying therapeutics, novel approaches, and targets are discussed for the successful treatment and management of AD.

Neuroproteomics Chip-Based Mass Spectrometry and Other Techniques for Alzheimer´S Disease Biomarkers – Update

Background:

Alzheimer's disease (AD) is a progressive neurodegenerative disease of growing interest given that there is cognitive damage and symptom onset acceleration. Therefore, it is important to find AD biomarkers for early diagnosis, disease progression, and discrimination of AD and other diseases.

Objective:

To update the relevance of mass spectrometry for the identification of peptides and proteins involved in AD useful as discriminating biomarkers.

Methods:

Proteomics and peptidomics technologies that show the highest possible specificity and selectivity for AD biomarkers are analyzed, together with the biological fluids used. In addition to positron emission tomography and magnetic resonance imaging, MALDI-TOF mass spectrometry is widely used to identify proteins and peptides involved in AD. The use of protein chips in SELDI technology and electroblotting chips for peptides makes feasible small amounts (L) of samples for analysis.

Results:

Suitable biomarkers are related to AD pathology, such as intracellular neurofibrillary tangles; extraneuronal senile plaques; neuronal and axonal degeneration; inflammation and oxidative stress. Recently, peptides were added to the candidate list, which are not amyloid-b or tau fragments, but are related to coagulation, brain plasticity, and complement/neuroinflammation systems involving the neurovascular unit.

Conclusion:

The progress made in the application of mass spectrometry and recent chip techniques is promising for discriminating between AD, mild cognitive impairment, and matched healthy controls. The application of this technique to blood samples from patients with AD has shown to be less invasive and fast enough to determine the diagnosis, stage of the disease, prognosis, and follow-up of the therapeutic response.

Biomarkers and Tools for Predicting Alzheimer's Disease in the Preclinical Stage

Alzheimer's disease (AD) is the only leading cause of death for which no disease-modifying therapy is currently available. Over the past decade, a string of disappointing clinical trial results has forced us to shift our focus to the preclinical stage of AD, which represents the most promising therapeutic window. However, the accurate diagnosis of preclinical AD requires the presence of brain β- amyloid deposition determined by cerebrospinal fluid or amyloid-positron emission tomography, significantly limiting routine screening and diagnosis in non-tertiary hospital settings. Thus, an easily accessible marker or tool with high sensitivity and specificity is highly needed. Recently, it has been discovered that individuals in the late stage of preclinical AD may not be truly "asymptomatic" in that they may have already developed subtle or subjective cognitive decline. In addition, advances in bloodderived biomarker studies have also allowed the detection of pathologic changes in preclinical AD. Exosomes, as cell-to-cell communication messengers, can reflect the functional changes of their source cell. Methodological advances have made it possible to extract brain-derived exosomes from peripheral blood, making exosomes an emerging biomarker carrier and liquid biopsy tool for preclinical AD. The eye and its associated structures have rich sensory-motor innervation. In this regard, studies have indicated that they may also provide reliable markers. Here, our report covers the current state of knowledge of neuropsychological and eye tests as screening tools for preclinical AD and assesses the value of blood and brain-derived exosomes as carriers of biomarkers in conjunction with the current diagnostic paradigm.

Neuroimaging of Mouse Models of Alzheimer’s Disease

Magnetic resonance imaging (MRI) and positron emission tomography (PET) have made great strides in the diagnosis and our understanding of Alzheimer’s Disease (AD). Despite the knowledge gained from human studies, mouse models have and continue to play an important role in deciphering the cellular and molecular evolution of AD. MRI and PET are now being increasingly used to investigate neuroimaging features in mouse models and provide the basis for rapid translation to the clinical setting. Here, we provide an overview of the human MRI and PET imaging landscape as a prelude to an in-depth review of preclinical imaging in mice. A broad range of mouse models recapitulate certain aspects of the human AD, but no single model simulates the human disease spectrum. We focused on the two of the most popular mouse models, the 3xTg-AD and the 5xFAD models, and we summarized all known published MRI and PET imaging data, including contrasting findings. The goal of this review is to provide the reader with broad framework to guide future studies in existing and future mouse models of AD. We also highlight aspects of MRI and PET imaging that could be improved to increase rigor and reproducibility in future imaging studies.

Prospects for the use of graphene-based biological sensors in the early diagnosis of Alzheimer's disease (review of literature)

Among the most significant challenges presented to modern medicine is the problem of cognitive disorders. The relevance of her research is determined by the wide spread of disorders of the higher cortical functions, their significant negative impact on the quality of life of patients, as well as high economic costs on the part of the state and the patient's relatives aimed at organizing medical, diagnostic and rehabilitation processes. The main cause of cognitive impairment in the elderly is Alzheimer's disease. Currently, the criteria for the diagnosis of this nosological form have been developed and are widely used in practice. However, it should be noted that their use is most effective if the patient has a detailed clinical picture, at the stage of dementia. In addition, they provide for the study of biomarkers in a number of cases in the cerebrospinal fluid or using positron emission tomography, which presents certain technical difficulties. Especially significant problems arise in the pre-dement stages. This situation dictates the need to search for new promising diagnostic methods that will have high sensitivity and specificity, as well as the possibility of application in the early stages of Alzheimer's disease, including in outpatient settings. The article provides information about modern methods of computer neuroimaging, discusses the research directions of individual biomarkers, and also shows the prospects for using diagnostic test panels developed on the basis of graphene biosensors, taking into account the latest achievements of nanotechnology and their integration into medical science.

Sleep Quality Improvement Enhances Neuropsychological Recovery and Reduces Blood Aβ42/40 Ratio in Patients with Mild-Moderate Cognitive Impairment

Background and objectives: Alzheimer's disease is a progressive brain degeneration and is associated with a high prevalence of sleep disorders. Amyloid β peptide-42/40 (Aβ42/40) and Tau-pT181 are the core biomarkers in cerebrospinal fluid and blood. Accumulated data from studies in mouse models and humans demonstrated an aberrant elevation of these biomarkers due to sleep disturbance, especially sleep-disordered breathing (SDB). However, it is not clear if sleep quality improvement reduces the blood levels of Ab42/40 ratio and Tau-pT181 in Alzheimer's disease patients. Materials and Methods: In this prospective study, a longitudinal analysis was conducted on 64 patients with mild-moderate cognition impairment (MCI) due to Alzheimer's disease accompanied by SDB. Another 33 MCI cases without sleep-disordered breathing were included as the control group. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI) score system. Neuropsychological assessments were conducted using the Montreal Cognitive Assessment (MoCA), Geriatric Depression Scale (GDS), Clinical Dementia Rating (CDR), 24-h Hamilton Rating Scale for Depression (HRSD-24), and Hamilton Anxiety Rating Scale (HAMA) scoring systems. Aβ42, Aβ40, and Tau-pT181 protein levels in blood specimens were measured using ELISA assays. All patients received donepezil treatment for Alzheimer's disease. SDB was managed with continuous pressure ventilation. Results: A significant correlation was found among PSQI, HRSD-24, HAMA, Aβ42/40 ratio, and Tau-pT181 level in all cases. In addition, a very strong and negative correlation was discovered between education level and dementia onset age. Compared to patients without SDB (33 non-SD cases), patients with SDB (64 SD cases) showed a significantly lower HRSD-24 score and a higher Aβ42/40 ratio Tau-pT181 level. Sleep treatment for patients with SDB significantly improved all neuropsychological scores, Aβ42/40 ratio, and Tau-pT181 levels. However, 11 patients did not completely recover from a sleep disorder (PSQI > 5 post-treatment). In this subgroup of patients, although HAMA score and Tau-pT181 levels were significantly reduced, MoCA and HRSD-24 scores, as well as Aβ42/40 ratio, were not significantly improved. ROC analysis found that the blood Aβ42/40 ratio held the highest significance in predicting sleep disorder occurrence. Conclusions: This is the first clinical study on sleep quality improvement in Alzheimer's disease patients. Sleep quality score was associated with patient depression and anxiety scores, as well as Aβ42/40 ratio and Tau-pT181 levels. A complete recovery is critical for fully improving all neuropsychological assessments, Aβ42/40 ratio, and Tau-pT181 levels. Blood Aβ42/40 ratio is a feasible prognostic factor for predicting sleep quality.

Plasma neurofilament L to amyloid β42 ratio in differentiating Alzheimer's type from non-Alzheimer's dementia: A cross-sectional pilot study from India

Based on the reduction of amyloid β plaques, US FDA has recently approved Aducanumab as a disease modifying treatment for Alzheimer's disease (AD). With high pricing and the potential risks likely with this treatment, certainty of AD diagnosis becomes crucial. The current pilot study evaluated plasma levels of neurofilament L, an axonal injury marker and amyloid β42, a major component of amyloid plaques for discriminating AD from non-AD dementia (NAD). Results with Simoa assays indicate that a combination of neurofilament L and amyloid β42 can be considered as a screening tool in identifying eligible subjects for AD treatment/ clinical trials.

Biomarkers of neurodegeneration and glial activation validated in Alzheimer's disease assessed in longitudinal cerebrospinal fluid samples of Parkinson's disease

Aim

Several pathophysiological processes are involved in Parkinson’s disease (PD) and could inform in vivo biomarkers. We assessed an established biomarker panel, validated in Alzheimer’s Disease, in a PD cohort.

Methods

Longitudinal cerebrospinal fluid (CSF) samples from PPMI (252 PD, 115 healthy controls, HC) were analyzed at six timepoints (baseline, 6, 12, 24, 36, and 48 months follow-up) using Elecsys® electrochemiluminescence immunoassays to quantify neurofilament light chain (NfL), soluble TREM2 receptor (sTREM2), chitinase-3-like protein 1 (YKL40), glial fibrillary acidic protein (GFAP), interleukin-6 (IL-6), S100, and total α-synuclein (αSyn).

Results

αSyn was significantly lower in PD (mean 103 pg/ml vs. HC: 127 pg/ml, p<0.01; area under the curve [AUC]: 0.64), while all other biomarkers were not significantly different (AUC NfL: 0.49, sTREM2: 0.54, YKL40: 0.57, GFAP: 0.55, IL-6: 0.53, S100: 0.54, p>0.05) and none showed a significant difference longitudinally. We found significantly higher levels of all these markers between PD patients who developed cognitive decline during follow-up, except for αSyn and IL-6.

Conclusion

Except for αSyn, the additional biomarkers did not differentiate PD and HC, and none showed longitudinal differences, but most markers predict cognitive decline in PD during follow-up.

Circulating 4-F4t-Neuroprostane and 10-F4t-Neuroprostane Are Related to MECP2 Gene Mutation and Natural History in Rett Syndrome

Neuroprostanes, a family of non-enzymatic metabolites of the docosahexaenoic acid, have been suggested as potential biomarkers for neurological diseases. Objective biological markers are strongly needed in Rett syndrome (RTT), which is a progressive X-linked neurodevelopmental disorder that is mainly caused by mutations in the methyl-CpG binding protein 2 (MECP2) gene with a predominant multisystemic phenotype. The aim of the study is to assess a possible association between MECP2 mutations or RTT disease progression and plasma levels of 4(RS)-4-F_4t-neuroprostane (4-F_4t-NeuroP) and 10(RS)-10-F_4t-neuroprostane (10-F_4t-NeuroP) in typical RTT patients with proven MECP2 gene mutation. Clinical severity and disease progression were assessed using the Rett clinical severity scale (RCSS) in n = 77 RTT patients. The 4-F_4t-NeuroP and 10-F_4t-NeuroP molecules were totally synthesized and used to identify the contents of the plasma of the patients. Neuroprostane levels were related to MECP2 mutation category (i.e., early truncating, gene deletion, late truncating, and missense), specific hotspot mutations (i.e., R106W, R133C, R168X, R255X, R270X, R294X, R306C, and T158M), and disease stage (II through IV). Circulating 4-F_4t-NeuroP and 10-F_4t-NeuroP were significantly related to (i) the type of MECP2 mutations where higher levels were associated to gene deletions (p ≤ 0.001); (ii) severity of common hotspot MECP2 mutation (large deletions, R168X, R255X, and R270X); (iii) disease stage, where higher concentrations were observed at stage II (p ≤ 0.002); and (iv) deficiency in walking (p ≤ 0.0003). This study indicates the biological significance of 4-F_4t-NeuroP and 10-F_4t-NeuroP as promising molecules to mark the disease progression and potentially gauge genotype-phenotype associations in RTT.

Machine Learning and Novel Biomarkers for the Diagnosis of Alzheimer's Disease

Background: Alzheimer’s disease (AD) is a complex and severe neurodegenerative disease that still lacks effective methods of diagnosis. The current diagnostic methods of AD rely on cognitive tests, imaging techniques and cerebrospinal fluid (CSF) levels of amyloid-β1-42 (Aβ42), total tau protein and hyperphosphorylated tau (p-tau). However, the available methods are expensive and relatively invasive. Artificial intelligence techniques like machine learning tools have being increasingly used in precision diagnosis. Methods: We conducted a meta-analysis to investigate the machine learning and novel biomarkers for the diagnosis of AD. Methods: We searched PubMed, the Cochrane Central Register of Controlled Trials, and the Cochrane Database of Systematic Reviews for reviews and trials that investigated the machine learning and novel biomarkers in diagnosis of AD. Results: In additional to Aβ and tau-related biomarkers, biomarkers according to other mechanisms of AD pathology have been investigated. Neuronal injury biomarker includes neurofiliament light (NFL). Biomarkers about synaptic dysfunction and/or loss includes neurogranin, BACE1, synaptotagmin, SNAP-25, GAP-43, synaptophysin. Biomarkers about neuroinflammation includes sTREM2, and YKL-40. Besides, d-glutamate is one of coagonists at the NMDARs. Several machine learning algorithms including support vector machine, logistic regression, random forest, and naïve Bayes) to build an optimal predictive model to distinguish patients with AD from healthy controls. Conclusions: Our results revealed machine learning with novel biomarkers and multiple variables may increase the sensitivity and specificity in diagnosis of AD. Rapid and cost-effective HPLC for biomarkers and machine learning algorithms may assist physicians in diagnosing AD in outpatient clinics.

Progress regarding the context-of-use of tau as biomarker of Alzheimer's disease and other neurodegenerative diseases

Introduction: Tau protein misfolding and accumulation in toxic species is a critical pathophysiological process of Alzheimer's disease (AD) and other neurodegenerative disorders (NDDs). Tau biomarkers, namely cerebrospinal fluid (CSF) total-tau (t-tau), 181-phosphorylated tau (p-tau), and tau-PET tracers, have been recently embedded in the diagnostic criteria for AD. Nevertheless, the role of tau as a diagnostic and prognostic biomarker for other NDDs remains controversial.Areas covered: We performed a systematical PubMed-based review of the most recent advances in tau-related biomarkers for NDDs. We focused on papers published from 2015 to 2020 assessing the diagnostic or prognostic value of each biomarker.Expert opinion: The assessment of tau biomarkers in alternative easily accessible matrices, through the development of ultrasensitive techniques, represents the most significant perspective for AD-biomarker research. In NDDs, novel tau isoforms (e.g. p-tau217) or proteolytic fragments (e.g. N-terminal fragments) may represent candidate diagnostic and prognostic biomarkers and may help monitoring disease progression. Protein misfolding amplification assays, allowing the identification of different tau strains (e.g. 3 R- vs. 4 R-tau) in CSF, may constitute a breakthrough for the in vivo stratification of NDDs. Tau-PET may help tracking the spatial-temporal evolution of tau pathophysiology in AD but its application outside the AD-spectrum deserves further studies.

Integrated Learning: Screening Optimal Biomarkers for Identifying Preeclampsia in Placental mRNA Samples

Preeclampsia (PE) is a maternal disease that causes maternal and child death. Treatment and preventive measures are not sound enough. The problem of PE screening has attracted much attention. The purpose of this study is to screen placental mRNA to obtain the best PE biomarkers for identifying patients with PE. We use Limma in the R language to screen out the 48 differentially expressed genes with the largest differences and used correlation-based feature selection algorithms to reduce the dimensionality and avoid attribute redundancy arising from too many mRNA samples participating in the classification. After reducing the mRNA attributes, the mRNA samples are sorted from large to small according to information gain. In this study, a classifier model is designed to identify whether samples had PE through mRNA in the placenta. To improve the accuracy of classification and avoid overfitting, three classifiers, including C4.5, AdaBoost, and multilayer perceptron, are used. We use the majority voting strategy integrated with the differentially expressed genes and the genes filtered by the best subset method as comparison methods to train the classifier. The results show that the classification accuracy rate has increased from 79% to 82.2%, and the number of mRNA features has decreased from 48 to 13. This study provides clues for the main PE biomarkers of mRNA in the placenta and provides ideas for the treatment and screening of PE.

Cerebrospinal Fluid and Serum d-Serine Levels in Patients with Alzheimer's Disease: A Systematic Review and Meta-Analysis

OBJECTIVE

Alzheimer's disease (AD) is a complex and severe neurodegenerative disease and still lacks effective methods of diagnosis. Dysfunction of the N-methyl-D-aspartate receptor (NMDAR) has been found to be involved in synapse dysfunction and neurotoxicity of AD mechanisms. d-Serine, an NMDAR receptor coagonist, is reported as a potential new biomarker for AD. However, the results of serum and cerebrospinal fluid (CSF) d-serine levels are conflicting. We conducted a meta-analysis to investigate the serum and CSF d-serine levels in patients with AD.

METHODS

We searched PubMed, the Cochrane central register of controlled trials, and the Cochrane database of systematic reviews for trials that measured d-serine levels both in patients with AD and in controls. We included controlled trials that analyzed d-serine levels in human samples (e.g., serum and CSF). Studies were pooled using a random-effect model for comparisons between AD and control group. We used effect size (ES; expressed as d-serine levels) in each selected meta-analysis to calculate standardized mean difference (SMD). Positive values indicated increased d-serine levels in AD group. We presented results with 95% confidence intervals (CIs). The heterogeneity of the included trials was evaluated through visually inspecting funnel plots and using the I2 statistic. Moderators of effects were explored using metaregression.

RESULTS

Seven trials with more than 1186 participants were included in this meta-analysis. d-serine levels in patients with AD were significantly higher than those in controls (SMD = 0.679, 95% CI = 0.335 to 1.022, p < 0.001). Subgroup analyses showed that the AD group had significantly higher d-serine levels in serum and CSF compared with the control group (SMD = 0.566 (serum) and 1.008 (CSF); 95% CI = 0.183 to 0.948 (serum) and 0.168 to 1.849 (CSF)). Moreover, a metaregression revealed a significant negative association between ES and mean mini-mental state examination score in AD group (slope = -0.1203, p = 0.0004).

CONCLUSIONS

Our results revealed higher d-serine levels in the serum and CSF of patients with AD relative to the controls. Further studies with a larger sample size and longer follow-up are recommended to clarify this association.

Biomarkers for Alzheimer's Disease: Where Do We Stand and Where Are We Going?

Alzheimer's disease (AD) is an age-related neurodegenerative and progressive disorder representing the most common form of dementia in older adults [...].