High performance plasma amyloid-β biomarkers for Alzheimer's disease

Optical nanomaterial-based detection of biomarkers in liquid biopsy

Liquid biopsy, which is a minimally invasive procedure as an alternative to tissue biopsy, has been introduced as a new diagnostic/prognostic measure. By screening disease-related markers from the blood or other biofluids, it promises early diagnosis, timely prognostication, and effective treatment of the diseases. However, there will be a long way until its realization due to its conceptual and practical challenges. The biomarkers detected by liquid biopsy, such as circulating tumor cell (CTC) and circulating tumor DNA (ctDNA), are extraordinarily rare and often obscured by an abundance of normal cellular components, necessitating ultra-sensitive and accurate detection methods for the advancement of liquid biopsy techniques. Optical biosensors based on nanomaterials open an important opportunity in liquid biopsy because of their enhanced sensing performance with simple and practical properties. In this review article, we summarized recent innovations in optical nanomaterials to demonstrate the sensitive detection of protein, peptide, ctDNA, miRNA, exosome, and CTCs. Each study prepares the optical nanomaterials with a tailored design to enhance the sensing performance and to meet the requirements of each biomarker. The unique optical characteristics of metallic nanoparticles (NPs), quantum dots, upconversion NPs, silica NPs, polymeric NPs, and carbon nanomaterials are exploited for sensitive detection mechanisms. These recent advances in liquid biopsy using optical nanomaterials give us an opportunity to overcome challenging issues and provide a resource for understanding the unknown characteristics of the biomarkers as well as the mechanism of the disease.

Predicting early Alzheimer's with blood biomarkers and clinical features

Alzheimer's disease (AD) is an incurable neurodegenerative disorder that leads to dementia. This study employs explainable machine learning models to detect dementia cases using blood gene expression, single nucleotide polymorphisms (SNPs), and clinical data from Alzheimer's Disease Neuroimaging Initiative (ADNI). Analyzing 623 ADNI participants, we found that the Support Vector Machine classifier with Mutual Information (MI) feature selection, trained on all three data modalities, achieved exceptional performance (accuracy = 0.95, AUC = 0.94). When using gene expression and SNP data separately, we achieved very good performance (AUC = 0.65, AUC = 0.63, respectively). Using SHapley Additive exPlanations (SHAP), we identified significant features, potentially serving as AD biomarkers. Notably, genetic-based biomarkers linked to axon myelination and synaptic vesicle membrane formation could aid early AD detection. In summary, this genetic-based biomarker approach, integrating machine learning and SHAP, shows promise for precise AD diagnosis, biomarker discovery, and offers novel insights for understanding and treating the disease. This approach addresses the challenges of accurate AD diagnosis, which is crucial given the complexities associated with the disease and the need for non-invasive diagnostic methods.

Effect of blood collection tube containing protease inhibitors on the pre-analytical stability of Alzheimer's disease plasma biomarkers

INTRODUCTION

The reliability of plasma Alzheimer's disease (AD) biomarkers can be compromised by protease-induced degradation. This limits the feasibility of conducting plasma biomarker studies in environments that lack the capacity for immediate processing and appropriate storage of blood samples. We hypothesized that blood collection tube supplementation with protease inhibitors can improve the stability of plasma biomarkers at room temperatures (RT). This study conducted a comparative analysis of blood biomarker stability in traditional ethylenediaminetetraacetic acid (EDTA) tubes versus BD™ P100 collection tubes, the latter being coated with a protease inhibitor cocktail. The stability of six plasma AD biomarkers was evaluated over time under RT conditions.

METHODS

We evaluated three experimental approaches. In Approach 1, pooled plasma samples underwent storage at RT for up to 96 hours. In Approach 2, plasma samples isolated upfront from whole blood collected into EDTA or P100 tubes were stored at RT for 0h or 24h before biomarker measurements. In Approach 3, whole blood samples were collected into paired EDTA or P100 tubes, followed by storage at RT for 0h or 24h before isolating the plasma for analyses. Biomarkers were measured with Single Molecule Array (Simoa) and immunoprecipitation-mass spectrometry (IP-MS) assays.

RESULTS

Both the IP-MS and Simoa methods revealed that the use of P100 tubes significantly improved the stability of Aβ42 and Aβ40 across all approaches. Additionally, the Aβ42/Aβ40 ratio levels were significantly stabilized only in the IP-MS assay in Approach 3. No significant differences were observed in the levels of plasma p-tau181, GFAP, and NfL for samples collected using either tube type in any of the approaches.

CONCLUSION

Supplementation of blood collection tubes with protease inhibitors could reduce the protease-induced degradation of plasma Aβ42 and Aβ40, and the Aβ ratio for IP-MS assay. This has crucial implications for preanalytical procedures, particularly in resource-limited settings.

Palladium nanoballs coupled with smartphone-thermal reader for photothermal lateral flow immunoassay of Aβ 1-40

Amyloid beta 1-40 (Aβ 1-40) is one of the most abundant substances in the body with the capacity to form insoluble aggregates and is a universal biomarker for the prediction of Alzheimer's disease. Here, a palladium nanoball (PNB)-strip was developed and coupled with a smartphone-thermal reader as an ultrasensitive and cost-effective platform for Aβ 1-40 detection. In this study, PNB was synthesized and introduced into lateral flow strips as an alternative signal source to gold nanoparticles to improve sensitivity because the PNB has a better heat generation ability. Quantitative analysis was performed using a self-developed smartphone-thermal reader, which is portable and cost-effective. The detection limit of the system was determined to be 20 pg mL-1, which fulfils the need for clinical diagnosis at the point-of-care. This work highlights a PNB-strip coupled smartphone-thermal reader for ultrasensitive and cost-effective Aβ 1-40 detection.

High-resolution omics of vascular ageing and inflammatory pathways in neurodegeneration

High-resolution omics, particularly single-cell and spatial transcriptomic profiling, are rapidly enhancing our comprehension of the normal molecular diversity of gliovascular cells, as well as their age-related changes that contribute to neurodegeneration. With more omic profiling studies being conducted, it is becoming increasingly essential to synthesise valuable information from the rapidly accumulating findings. In this review, we present an overview of the molecular features of neurovascular and glial cells that have been recently discovered through omic profiling, with a focus on those that have potentially significant functional implications and/or show cross-species differences between human and mouse, and that are linked to vascular deficits and inflammatory pathways in ageing and neurodegenerative disorders. Additionally, we highlight the translational applications of omic profiling, and discuss omic-based strategies to accelerate biomarker discovery and facilitate disease course-modifying therapeutics development for neurodegenerative conditions.

Physical activity and amyloid beta in middle-aged and older adults: A systematic review and meta-analysis

BACKGROUND

One of the pathological hallmarks distinguishing Alzheimer's disease from other dementias is the accumulation of amyloid beta (Aβ). Higher physical activity is associated with decreased dementia risk, and one potential path could be through Aβ levels modulation. We aimed to explore the relationship between physical activity and Aβ in middle-aged and older adults.

METHODS

A systematic search of PubMed, Web of Science, PsycINFO, Cochrane Central Register of Controlled Trials, and SPORTDiscus was performed from inception to April 28, 2022. Studies were eligible if they included physical activity and Aβ data in adults aged 45 years or older. Multi-level meta-analyses of intervention and observational studies were performed to examine the role of physical activity in modulating Aβ levels.

RESULTS

In total, 37 articles were included (8 randomized controlled trials, 3 non-randomized controlled trials, 4 prospective longitudinal studies, and 22 cross-sectional studies). The overall effect size of physical activity interventions on changes in blood Aβ was medium (pooled standardized mean difference = -0.69, 95% confidence interval (95%CI): -1.41 to 0.03; I2 = 74.6%). However, these results were not statistically significant, and there were not enough studies to explore the effects of physical activity on cerebrospinal fluid (CSF) and brain Aβ. Data from observational studies were examined based on measurements of Aβ in the brain using positron emission tomography scans, CSF, and blood. Higher physical activity was positively associated with Aβ only in the CSF (Estimate r = 0.12; 95%CI: 0.05-0.18; I2 = 38.00%).

CONCLUSION

Physical activity might moderately reduce blood Aβ in middle-aged and older adults. However, results were only near statistical significance and might be interpreted with caution given the methodological limitations observed in some of the included studies. In observational studies, higher levels of physical activity were positively associated with Aβ only in CSF. Therefore, further research is needed to understand the modulating role of physical activity in the brain, CSF, and blood Aβ, as well as its implication for cognitive health.

Neuropsychiatric symptoms in Alzheimer's continuum and their association with plasma biomarkers

BACKGROUND

Little is known about association between neuropsychiatric symptoms and plasma biomarkers across the entire Alzheimer's continuum.

METHODS

A total of 305 individuals with amyloid-β (Aβ) deposition (determined by 18F-florbetapir PET) participated in this study, including cognitively normal controls (n = 53), subjective cognitive decline (SCD, n = 75), mild cognitive impairment (MCI, n = 74), and dementia (n = 103). Plasma biomarkers (Aβ1-42, Aβ1-40, total tau [t-tau], phosphorylated tau 181 [p-tau181], and neurofilament light [NfL]), apolipoprotein E (APOE) genotyping and Neuropsychiatric Inventory Questionnaire (NPI-Q) were completed. Neuropsychiatric symptoms were classified into four subsymdromes (hyperactivity, psychosis, affective, and apathy). Logistic regression analysis was conducted to investigate relationships between neuropsychiatric symptoms and plasma biomarkers.

RESULTS

About one-third of cognitively unimpaired individuals (normal controls: 34.0 %, SCD: 28.0 %) reported one or more neuropsychiatric symptoms, and more in symptomatic stages such as MCI (40.5 %) and dementia (81.0 %). Plasma NfL significantly increased in dementia group compared to SCD and healthy controls, relating to a higher risk of aberrant motor behavior, anxiety, sleep disturbance, disinhibition, and euphoria. Older age (odds ratio [OR] = 1.079, 95 % confidence interval [CI] = 1.022-1.140, p = 0.006), lower cognitive score (OR = 0.846, 95%CI = 0.791-0.905, p < 0.001) and increased plasma NfL (OR = 1.021, 95%CI = 1.00-1.042, p = 0.041) could predict psychosis. No significant differences were found in plasma Aβ1-42/Aβ1-40, t-tau or p-tau181 across all groups, and none correlated with neuropsychiatric symptoms.

LIMITATIONS

The cross-sectional design, small sample size and use of NPI-Q.

CONCLUSIONS

This study supported neuropsychiatric symptoms as early manifestations of preclinical Alzheimer's disease, and suggested plasma NfL to be a potential biomarker for detecting neuropsychiatric symptoms in Alzheimer's continuum.

Odor identification score as an alternative method for early identification of amyloidogenesis in Alzheimer's disease

A simple screening test to identify the early stages of Alzheimer's disease (AD) is urgently needed. We investigated whether odor identification impairment can be used to differentiate between stages of the A/T/N classification (amyloid,  tau, neurodegeneration) in individuals with amnestic mild cognitive impairment or AD and in healthy controls. We collected data from 132 Japanese participants visiting the Toranomon Hospital dementia outpatient clinic. The odor identification scores correlated significantly with major neuropsychological scores, regardless of apolipoprotein E4 status, and with effective cerebrospinal fluid (CSF) biomarkers [amyloid β 42 (Aβ42) and the Aβ42/40 and phosphorylated Tau (p-Tau)/Aβ42 ratios] but not with ineffective biomarkers [Aβ40 and the p-Tau/total Tau ratio]. A weak positive correlation was observed between the corrected odor identification score (adjusted for age, sex, ApoE4 and MMSE), CSF Aβ42, and the Aβ42/40 ratio. The odor identification score demonstrated excellent discriminative power for the amyloidogenesis stage , according to the A/T/N classification, but was unsuitable for differentiating between the p-Tau accumulation and the neurodegeneration stages. After twelve odor species were analyzed, a version of the score comprising only four odors-India ink, wood, curry, and sweaty socks-proved highly effective in identifying AD amyloidogenesis, showing promise for the screening of preclinical AD.

Novel Development and Prospects in Pathogenesis, Diagnosis, and Therapy of Alzheimer's Disease

Alzheimer's disease (AD) is the most prevalent neurodegenerative disease with cognitive decline and behavioral dysfunction. AD will become a global public health concern due to its increasing prevalence brought on by the severity of global aging. It is critical to understand the pathogenic mechanisms of AD and investigate or pursue a viable therapy strategy in clinic. Amyloid-β (Aβ) accumulation and abnormally hyperphosphorylated tau protein are the main regulating variables in the pathological phase of AD. And neuroinflammation brought on by activated microglia was found to be one risk factor contributing to changes in Aβ and tau pathology. It is important to investigate the unique biomarkers of early diagnosis and advanced stage, which may help to elucidate the specific pathological process of AD and provide potential novel therapeutic targets or preventative measures.

Assessment of immunoprecipitation with subsequent immunoassays for the blood-based diagnosis of Alzheimer's disease

The Aβ42/40 ratio and the concentration of phosphorylated Tau181 in blood plasma represent attractive biomarkers for Alzheimer's disease. As a means for reducing potential matrix effects, which may interfere with plasma immunoassays, we have previously developed a pre-analytical sample workup by semi-automated immunoprecipitation. Here we test the compatibility of pre-analytical immunoprecipitations with automated Aβ1-40, Aβ1-42 and phosphorylated Tau181 immunoassays on the Lumipulse platform and compare the diagnostic performance of the respective immunoprecipitation immunoassay approaches with direct plasma measurements. 71 participants were dichotomized according to their Aβ42/40 ratios in cerebrospinal fluid into the diagnostic groups amyloid-positive (n = 32) and amyloid-negative (n = 39). The plasma Aβ1-42/1-40 ratio and phosphorylated Tau181 levels were determined on the Lumipulse G600II platform (Fujirebio) by direct measurements in EDTA-plasma or after Aβ- or Tau-immunoprecipitation, respectively. Pre-analytical immunoprecipitation of Aβ turned out to be compatible with the Lumipulse Aβ assays and resulted in a numerical, yet statistically not significant increase in the area under the ROC curve for plasma Aβ1-42/1-40. Additionally, we observed a significant increase in the standardised effect size (Cohen's D). Pre-analytical immunoprecipitation of Tau resulted in increased differences between the diagnostic groups in terms of median and mean phosphorylated Tau 181 levels. Furthermore, we observed a greater Cohen's d (p < 0.001) and a larger area under the ROC curve (p = 0.038) after Tau-IP. Our preliminary findings in a small, preselected sample indicate that pre-analytical immunoprecipitation may have the potential to improve the diagnostic performance of plasma biomarker immunoassays for Aβ1-42/1-40 and phosphorylated Tau181 to predict brain amyloid deposition.

Self-calibrating surface-enhanced Raman scattering-lateral flow immunoassay for determination of amyloid-β biomarker of Alzheimer's disease

Rapid early diagnosis of Alzheimer's disease (AD) is critical for its effective and prompt treatment since the clinically available treatments can only relieve the symptoms or slow the disease progression. However, it is still a grand challenge to accurately diagnose AD at its early stage because of the indiscernible early symptoms and the lack of sensitive detection tools. Here, we develop a self-calibrating surface-enhanced Raman scattering (SERS)-lateral flow immunoassay (LFIA) biosensor for quantitative analysis of amyloid-β1-42 (Aβ1-42) biomarker in biofluids, enabling accurate AD diagnosis. The designed SERS-LFIA biosensor makes full use of the unique aspects of the LFIA format and the SERS technique to quantify the Aβ1-42 level in complex biofluids with high sensitivity, excellent anti-interference capability, low-cost, and operation simplicity. The key aspect of the design of this biosensor is that internal standard (IS)-SERS nanoparticles are embedded in the test line of the test strip as a self-calibration unit for correction of fluctuations of SERS signals caused by various external factors such as test parameters and sample heterogeneity. We demonstrate significant improvement of the detection performance of the SERS-LFIA biosensor for ratiometric quantification of Aβ1-42 owing to the built-in IS in the test line. We expect that the present IS-based biosensing strategy provides a promising tool for accurate AD diagnosis and longitudinal monitoring of therapeutic response with great promises for clinical translation.

In-vivo diagnosis of cerebral amyloid angiopathy: an updated review

PURPOSE OF REVIEW

Sporadic cerebral amyloid angiopathy (CAA) is a highly prevalent small vessel disease in ageing population with potential severe complications including lobar intracerebral hemorrhage (ICH), cognitive impairment, and dementia. Although diagnosis of CAA was made only with postmortem neuropathological examination a few decades ago, diagnosing CAA without pathological proof is now allowed in living patients. This review focuses on recently identified biomarkers of CAA and current diagnostic criteria.

RECENT FINDINGS

Over the past few years, clinicians and researchers have shown increased interest for CAA, and important advances have been made. Thanks to recent insights into mechanisms involved in CAA and advances in structural and functional neuroimaging, PET amyloid tracers, cerebrospinal fluid and plasma biomarkers analysis, a growing number of biomarkers of CAA have been identified. Imaging-based diagnostic criteria including emerging biomarkers have been recently developed or updated, enabling accurate and earlier diagnosis of CAA in living patients.

SUMMARY

Recent advances in neuroimaging allow diagnosing CAA in the absence of pathological examination. Current imaging-based criteria have high diagnostic performance in patients presenting with ICH, but is more limited in other clinical context such as cognitively impaired patients or asymptomatic individuals. Further research is still needed to improve diagnostic accuracy.

Biological variation estimates of Alzheimer's disease plasma biomarkers in healthy individuals

INTRODUCTION

Blood biomarkers have proven useful in Alzheimer's disease (AD) research. However, little is known about their biological variation (BV), which improves the interpretation of individual-level data.

METHODS

We measured plasma amyloid beta (Aβ42, Aβ40), phosphorylated tau (p-tau181, p-tau217, p-tau231), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL) in plasma samples collected weekly over 10 weeks from 20 participants aged 40 to 60 years from the European Biological Variation Study. We estimated within- (CVI ) and between-subject (CVG ) BV, analytical variation, and reference change values (RCV).

RESULTS

Biomarkers presented considerable variability in CVI and CVG . Aβ42/Aβ40 had the lowest CVI (≈ 3%) and p-tau181 the highest (≈ 16%), while others ranged from 6% to 10%. Most RCVs ranged from 20% to 30% (decrease) and 25% to 40% (increase).

DISCUSSION

BV estimates for AD plasma biomarkers can potentially refine their clinical and research interpretation. RCVs might be useful for detecting significant changes between serial measurements when monitoring early disease progression or interventions. Highlights Plasma amyloid beta (Aβ42/Aβ40) presents the lowest between- and within-subject biological variation, but also changes the least in Alzheimer's disease (AD) patients versus controls. Plasma phosphorylated tau variants significantly vary in their within-subject biological variation, but their substantial fold-changes in AD likely limits the impact of their variability. Plasma neurofilament light chain and glial fibrillary acidic protein demonstrate high between-subject variation, the impact of which will depend on clinical context. Reference change values can potentially be useful in monitoring early disease progression and the safety/efficacy of interventions on an individual level. Serial sampling revealed that unexpectedly high values in heathy individuals can be observed, which urges caution when interpreting AD plasma biomarkers based on a single test result.

Plasma Aβ42/Aβ40 and phospho-tau217 concentration ratios increase the accuracy of amyloid PET classification in preclinical Alzheimer's disease

INTRODUCTION

Incorporating blood-based Alzheimer's disease biomarkers such as tau and amyloid beta (Aβ) into screening algorithms may improve screening efficiency.

METHODS

Plasma Aβ, phosphorylated tau (p-tau)181, and p-tau217 concentration levels from AHEAD 3-45 study participants were measured using mass spectrometry. Tau concentration ratios for each proteoform were calculated to normalize for inter-individual differences. Receiver operating characteristic (ROC) curve analysis was performed for each biomarker against amyloid positivity, defined by > 20 Centiloids. Mixture of experts analysis assessed the value of including tau concentration ratios into the existing predictive algorithm for amyloid positron emission tomography status.

RESULTS

The area under the receiver operating curve (AUC) was 0.87 for Aβ42/Aβ40, 0.74 for phosphorylated variant p-tau181 ratio (p-tau181/np-tau181), and 0.92 for phosphorylated variant p-tau217 ratio (p-tau217/np-tau217). The Plasma Predicted Centiloid (PPC), a predictive model including p-tau217/np-tau217, Aβ42/Aβ40, age, and apolipoprotein E improved AUC to 0.95.

DISCUSSION

Including plasma p-tau217/np-tau217 along with Aβ42/Aβ40 in predictive algorithms may streamline screening preclinical individuals into anti-amyloid clinical trials.

CLINICALTRIALS

gov Identifier: NCT04468659 HIGHLIGHTS: The addition of plasma phosphorylated variant p-tau217 ratio (p-tau217/np-tau217) significantly improved plasma biomarker algorithms for identifying preclinical amyloid positron emission tomography positivity. Prediction performance at higher NAV Centiloid levels was improved with p-tau217/np-tau217. All models generated for this study are incorporated into the Plasma Predicted Centiloid (PPC) app for public use.

Alzheimer's disease and inflammatory biomarkers positively correlate in plasma in the UK-ADRC cohort

INTRODUCTION

Protein-based plasma assays provide hope for improving accessibility and specificity of molecular diagnostics to diagnose dementia.

METHODS

Plasma was obtained from participants (N = 837) in our community-based University of Kentucky Alzheimer's Disease Research Center cohort. We evaluated six Alzheimer's disease (AD)- and neurodegeneration-related (Aβ40, Aβ42, Aβ42/40, p-tau181, total tau, and NfLight) and five inflammatory biomarkers (TNF𝛼, IL6, IL8, IL10, and GFAP) using the SIMOA-based protein assay platform. Statistics were performed to assess correlations.

RESULTS

Our large cohort reflects previous plasma biomarker findings. Relationships between biomarkers to understand AD-inflammatory biomarker correlations showed significant associations between AD and inflammatory biomarkers suggesting peripheral inflammatory interactions with increasing AD pathology. Biomarker associations parsed out by clinical diagnosis (normal, MCI, and dementia) reveal changes in strength of the correlations across the cognitive continuum.

DISCUSSION

Unique AD-inflammatory biomarker correlations in a community-based cohort reveal a new avenue for utilizing plasma-based biomarkers in the assessment of AD and related dementias.

HIGHLIGHTS

Large community cohorts studying sex, age, and APOE genotype effects on biomarkers are few. It is unknown how biomarker-biomarker associations vary through aging and dementia. Six AD (Aβ40, Aβ42, Aβ42/40, p-tau181, total tau, and NfLight) and five inflammatory biomarkers (TNFα, IL6, IL8, IL10, and GFAP) were used to examine associations between biomarkers. Plasma biomarkers suggesting increasing cerebral AD pathology corresponded to increases in peripheral inflammatory markers, both pro-inflammatory and anti-inflammatory. Strength of correlations, between pairs of classic AD and inflammatory plasma biomarker, changes throughout cognitive progression to dementia.

Comparative methods for quantifying plasma biomarkers in Alzheimer's disease: Implications for the next frontier in cerebral amyloid angiopathy diagnostics

Plasma amyloid beta (Aβ) and tau are emerging as accessible biomarkers for Alzheimer's disease (AD). However, many assays exist with variable test performances, highlighting the need for a comparative assessment to identify the most valid assays for future use in AD and to apply to other settings in which the same biomarkers may be useful, namely, cerebral amyloid angiopathy (CAA). CAA is a progressive cerebrovascular disease characterized by deposition of Aβ40 and Aβ42 in cortical and leptomeningeal vessels. Novel immunotherapies for AD can induce amyloid-related imaging abnormalities resembling CAA-related inflammation. Few studies have evaluated plasma biomarkers in CAA. Identifying a CAA signature could facilitate diagnosis, prognosis, and a safer selection of patients with AD for emerging immunotherapies. This review evaluates studies that compare the diagnostic test performance of plasma biomarker techniques in AD and cerebrovascular and plasma biomarker profiles of CAA; it also discusses novel hypotheses and future avenues for plasma biomarker research in CAA.

Plasma proteomic profiles predict future dementia in healthy adults

The advent of proteomics offers an unprecedented opportunity to predict dementia onset. We examined this in data from 52,645 adults without dementia in the UK Biobank, with 1,417 incident cases and a follow-up time of 14.1 years. Of 1,463 plasma proteins, GFAP, NEFL, GDF15 and LTBP2 consistently associated most with incident all-cause dementia (ACD), Alzheimer's disease (AD) and vascular dementia (VaD), and ranked high in protein importance ordering. Combining GFAP (or GDF15) with demographics produced desirable predictions for ACD (area under the curve (AUC) = 0.891) and AD (AUC = 0.872) (or VaD (AUC = 0.912)). This was also true when predicting over 10-year ACD, AD and VaD. Individuals with higher GFAP levels were 2.32 times more likely to develop dementia. Notably, GFAP and LTBP2 were highly specific for dementia prediction. GFAP and NEFL began to change at least 10 years before dementia diagnosis. Our findings strongly highlight GFAP as an optimal biomarker for dementia prediction, even more than 10 years before the diagnosis, with implications for screening people at high risk for dementia and for early intervention.

Liquid-liquid phase separation in Alzheimer's disease

The pathological aggregation and misfolding of tau and amyloid-β play a key role in Alzheimer's disease (AD). However, the underlying pathological mechanisms remain unclear. Emerging evidences indicate that liquid-liquid phase separation (LLPS) has great impacts on regulating human health and diseases, especially neurodegenerative diseases. A series of studies have revealed the significance of LLPS in AD. In this review, we summarize the latest progress of LLPS in AD, focusing on the impact of metal ions, small-molecule inhibitors, and proteinaceous partners on tau LLPS and aggregation, as well as toxic oligomerization, the role of LLPS on amyloid-β (Aβ) aggregation, and the cross-interactions between amyloidogenic proteins in AD. Eventually, the fundamental methods and techniques used in LLPS study are introduced. We expect to present readers a deeper understanding of the relationship between LLPS and AD.

Alzheimer's Disease Biomarker Analysis Using Targeted Mass Spectrometry

Alzheimer's disease (AD) is characterized by several neuropathological changes, mainly extracellular amyloid aggregates (plaques), intraneuronal inclusions of phosphorylated tau (tangles), as well as neuronal and synaptic degeneration, accompanied by tissue reactions to these processes (astrocytosis and microglial activation) that precede neuronal network disturbances in the symptomatic phase of the disease. A number of biomarkers for these brain tissue changes have been developed, mainly using immunoassays. In this review, we discuss how targeted mass spectrometry (TMS) can be used to validate and further characterize classes of biomarkers reflecting different AD pathologies, such as tau- and amyloid-beta pathologies, synaptic dysfunction, lysosomal dysregulation, and axonal damage, and the prospect of using TMS to measure these proteins in clinical research and diagnosis. TMS advantages and disadvantages in relation to immunoassays are discussed, and complementary aspects of the technologies are discussed.

Consensus on rapid screening for prodromal Alzheimer's disease in China

Alzheimer's disease (AD) is a common cause of dementia, characterised by cerebral amyloid-β deposition, pathological tau and neurodegeneration. The prodromal stage of AD (pAD) refers to patients with mild cognitive impairment (MCI) and evidence of AD's pathology. At this stage, disease-modifying interventions should be used to prevent the progression to dementia. Given the inherent heterogeneity of MCI, more specific biomarkers are needed to elucidate the underlying AD's pathology. Although the uses of cerebrospinal fluid and positron emission tomography are widely accepted methods for detecting AD's pathology, their clinical applications are limited by their high costs and invasiveness, particularly in low-income areas in China. Therefore, to improve the early detection of Alzheimer's disease (AD) pathology through cost-effective screening methods, a panel of 45 neurologists, psychiatrists and gerontologists was invited to establish a formal consensus on the screening of pAD in China. The supportive evidence and grades of recommendations are based on a systematic literature review and focus group discussion. National meetings were held to allow participants to review, vote and provide their expert opinions to reach a consensus. A majority (two-thirds) decision was used for questions for which consensus could not be reached. Recommended screening methods are presented in this publication, including neuropsychological assessment, peripheral biomarkers and brain imaging. In addition, a general workflow for screening pAD in China is established, which will help clinicians identify individuals at high risk and determine therapeutic targets.

Application of blood-based biomarkers of Alzheimer's disease in clinical practice: Recommendations from Taiwan Dementia Society

Blood-based biomarkers (BBM) are potentially powerful tools that assist in the biological diagnosis of Alzheimer's disease (AD) in vivo with minimal invasiveness, relatively low cost, and good accessibility. This review summarizes current evidence for using BBMs in AD, focusing on amyloid, tau, and biomarkers for neurodegeneration. Blood-based phosphorylated tau and the Aβ42/Aβ40 ratio showed consistent concordance with brain pathology measured by CSF or PET in the research setting. In addition, glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) are neurodegenerative biomarkers that show the potential to assist in the differential diagnosis of AD. Other pathology-specific biomarkers, such as α-synuclein and TAR DNA-binding protein 43 (TDP-43), can potentially detect AD concurrent pathology. Based on current evidence, the working group from the Taiwan Dementia Society (TDS) achieved consensus recommendations on the appropriate use of BBMs for AD in clinical practice. BBMs may assist clinical diagnosis and prognosis in AD subjects with cognitive symptoms; however, the results should be interpreted by dementia specialists and combining biochemical, neuropsychological, and neuroimaging information. Further studies are needed to evaluate BBMs' real-world performance and potential impact on clinical decision-making.

Protein Misfolding in Pregnancy: Current Insights, Potential Mechanisms, and Implications for the Pathogenesis of Preeclampsia

Protein misfolding disorders are a group of diseases characterized by supra-physiologic accumulation and aggregation of pathogenic proteoforms resulting from improper protein folding and/or insufficiency in clearance mechanisms. Although these processes have been historically linked to neurodegenerative disorders, such as Alzheimer's disease, evidence linking protein misfolding to other pathologies continues to emerge. Indeed, the deposition of toxic protein aggregates in the form of oligomers or large amyloid fibrils has been linked to type 2 diabetes, various types of cancer, and, in more recent years, to preeclampsia, a life-threatening pregnancy-specific disorder. While extensive physiological mechanisms are in place to maintain proteostasis, processes, such as aging, genetic factors, or environmental stress in the form of hypoxia, nutrient deprivation or xenobiotic exposures can induce failure in these systems. As such, pregnancy, a natural physical state that already places the maternal body under significant physiological stress, creates an environment with a lower threshold for aberrant aggregation. In this review, we set out to discuss current evidence of protein misfolding in pregnancy and potential mechanisms supporting a key role for this process in preeclampsia pathogenesis. Improving our understanding of this emerging pathophysiological process in preeclampsia can lead to vital discoveries that can be harnessed to create better diagnoses and treatment modalities for the disorder.

Detection of Femtomolar Amyloid-β Peptides for Early-Stage Identification of Alzheimer's Amyloid-β Aggregation with Functionalized Gold Nanoparticles

Progressive amyloid-β (Aβ) fibrillar aggregates have long been considered as the pathogenesis of Alzheimer's disease (AD). Biocompatible and stable cysteine-Aβ peptide-conjugated gold nanoparticles (Cys-Aβ@AuNP) are demonstrated as suitable materials for detecting subfemtomolar Aβ peptides in human plasma. Incubation with Aβ peptides causes the Cys-Aβ@AuNP to aggregate and changes its absorption spectra. The spectral change is especially apparent and noticeable when detecting subfemtomolar Aβ peptides, and the aggregates contain only two or three AuNPs. Cys-Aβ@AuNP can also be used to identify early-stage Aβ oligomerization, which is not possible using the conventional method, in which the fluorescence of thioflavin-T is measured. The ability to detect Aβ oligomerization can facilitate therapeutics for AD. In addition, the binding of Aβ peptides by Cys-Aβ@AuNP in combination with centrifugation redirects the conventional Aβ aggregation pathway and can effectively inhibit the formation of toxic Aβ oligomers or fibrils. Therefore, the proposed Cys-Aβ@AuNP can also be used to develop effective therapeutic agents to inhibit Aβ aggregation. The results obtained in this study are expected to open revolutionary ways to both detect and inhibit Aβ aggregation at an early stage.

Association of Plasma Claudin-5 with Age and Alzheimer Disease

The blood-brain barrier (BBB) plays pivotal roles in synaptic and neuronal functioning by sealing the space between adjacent microvascular endothelial cells. BBB breakdown is present in patients with mild cognitive impairment (MCI) or Alzheimer disease (AD). Claudin-5 (CLDN-5) is a tetra-spanning protein essential for sealing the intercellular space between adjacent endothelial cells in the BBB. In this study, we developed a blood-based assay for CLDN-5 and investigated its diagnostic utility using 100 cognitively normal (control) subjects, 100 patients with MCI, and 100 patients with AD. Plasma CLDN-5 levels were increased in patients with AD (3.08 ng/mL) compared with controls (2.77 ng/mL). Plasma levels of phosphorylated tau (pTau181), a biomarker of pathological tau, were elevated in patients with MCI or AD (2.86 and 4.20 pg/mL, respectively) compared with control subjects (1.81 pg/mL). In patients with MCI or AD, plasma levels of CLDN-5-but not pTau181-decreased with age, suggesting some age-dependent BBB changes in MCI and AD. These findings suggest that plasma CLDN-5 may a potential biochemical marker for the diagnosis of AD.

High-Performance Plasma Biomarker Panel for Alzheimer's Disease Screening Using a Femtomolar-Level Label-Free Biosensing System

Alzheimer's disease (AD) is the most common cause of dementia in older people. However, diagnosing AD through noncognitive methods, such as invasive cerebrospinal fluid sampling or radioactive positron emission tomography, has limited applications. Herein, the femtomolar levels of AD biomarkers amyloid β 40 (Aβ40), amyloid β 42 (Aβ42), phosphorylated tau 181 (P-tau181), phosphorylated tau 217 (P-tau217), and neurofilament light chain (NfL) were determined in human plasma in multicenter clinical cohorts using an ultrasensitive graphene field-effect transistor sensor. A machine-learning algorithm was also used to assemble these plasma biomarkers and optimize their performance in discriminating individual stages of Alzheimer's dementia progression. The "composite-info" biomarker panel, which combines these biomarkers and clinical information, considerably improved the staging performance in AD progression. It achieved an area under the curve of >0.94 in the receiver operator characteristic (ROC) curve. In addition, the panel demonstrated an advantage in the individual-based stage assessment compared with that of the Mini-Mental State Examination/Montreal Cognitive Assessment and nuclear magnetic resonance imaging. This study provides a composite biomarker panel for the screening and early diagnosis of AD using a rapid detection system.

Multi-Omic Blood Biomarkers as Dynamic Risk Predictors in Late-Onset Alzheimer's Disease

Late-onset Alzheimer's disease is the leading cause of dementia worldwide, accounting for a growing burden of morbidity and mortality. Diagnosing Alzheimer's disease before symptoms are established is clinically challenging, but would provide therapeutic windows for disease-modifying interventions. Blood biomarkers, including genetics, proteins and metabolites, are emerging as powerful predictors of Alzheimer's disease at various timepoints within the disease course, including at the preclinical stage. In this review, we discuss recent advances in such blood biomarkers for determining disease risk. We highlight how leveraging polygenic risk scores, based on genome-wide association studies, can help stratify individuals along their risk profile. We summarize studies analyzing protein biomarkers, as well as report on recent proteomic- and metabolomic-based prediction models. Finally, we discuss how a combination of multi-omic blood biomarkers can potentially be used in memory clinics for diagnosis and to assess the dynamic risk an individual has for developing Alzheimer's disease dementia.

Definition of a Threshold for the Plasma Aβ42/Aβ40 Ratio Measured by Single-Molecule Array to Predict the Amyloid Status of Individuals without Dementia

Alzheimer's disease (AD) is characterized by amyloid beta (Aβ) plaques and hyperphosphorylated tau in the brain. Aβ plaques precede cognitive impairments and can be detected through amyloid-positron emission tomography (PET) or in cerebrospinal fluid (CSF). Assessing the plasma Aβ42/Aβ40 ratio seems promising for non-invasive and cost-effective detection of brain Aβ accumulation. This approach involves some challenges, including the accuracy of blood-based biomarker measurements and the establishment of clear, standardized thresholds to categorize the risk of developing brain amyloid pathology. Plasma Aβ42/Aβ40 ratio was measured in 277 volunteers without dementia, 70 AD patients and 18 non-AD patients using single-molecule array. Patients (n = 88) and some volunteers (n = 66) were subject to evaluation of amyloid status by CSF Aβ quantification or PET analysis. Thresholds of plasma Aβ42/Aβ40 ratio were determined based on a Gaussian mixture model, a decision tree, and the Youden's index. The 0.0472 threshold, the one with the highest sensitivity, was retained for general population without dementia screening, and the 0.0450 threshold was retained for research and clinical trials recruitment, aiming to minimize the need for CSF or PET analyses to identify amyloid-positive individuals. These findings offer a promising step towards a cost-effective method for identifying individuals at risk of developing AD.

Exploring small non-coding RNAs as blood-based biomarkers to predict Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) diagnosis relies on clinical symptoms complemented with biological biomarkers, the Amyloid Tau Neurodegeneration (ATN) framework. Small non-coding RNA (sncRNA) in the blood have emerged as potential predictors of AD. We identified sncRNA signatures specific to ATN and AD, and evaluated both their contribution to improving AD conversion prediction beyond ATN alone.

METHODS

This nested case-control study was conducted within the ACE cohort and included MCI patients matched by sex. Patients free of type 2 diabetes underwent cerebrospinal fluid (CSF) and plasma collection and were followed-up for a median of 2.45-years. Plasma sncRNAs were profiled using small RNA-sequencing. Conditional logistic and Cox regression analyses with elastic net penalties were performed to identify sncRNA signatures for A+(T|N)+ and AD. Weighted scores were computed using cross-validation, and the association of these scores with AD risk was assessed using multivariable Cox regression models. Gene ontology (GO) and Kyoto encyclopaedia of genes and genomes (KEGG) enrichment analysis of the identified signatures were performed.

RESULTS

The study sample consisted of 192 patients, including 96 A+(T|N)+ and 96 A-T-N- patients. We constructed a classification model based on a 6-miRNAs signature for ATN. The model could classify MCI patients into A-T-N- and A+(T|N)+ groups with an area under the curve of 0.7335 (95% CI, 0.7327 to 0.7342). However, the addition of the model to conventional risk factors did not improve the prediction of AD beyond the conventional model plus ATN status (C-statistic: 0.805 [95% CI, 0.758 to 0.852] compared to 0.829 [95% CI, 0.786, 0.872]). The AD-related 15-sncRNAs signature exhibited better predictive performance than the conventional model plus ATN status (C-statistic: 0.849 [95% CI, 0.808 to 0.890]). When ATN was included in this model, the prediction further improved to 0.875 (95% CI, 0.840 to 0.910). The miRNA-target interaction network and functional analysis, including GO and KEGG pathway enrichment analysis, suggested that the miRNAs in both signatures are involved in neuronal pathways associated with AD.

CONCLUSIONS

The AD-related sncRNA signature holds promise in predicting AD conversion, providing insights into early AD development and potential targets for prevention.

Association of amyloid-beta with depression or depressive symptoms in older adults without dementia: a systematic review and meta-analysis

Several lines of evidence have indicated that depression might be a prodromal symptom of Alzheimer's disease (AD). This systematic review and meta-analysis investigated the cross-sectional association between amyloid-beta, one of the key pathologies defining AD, and depression or depressive symptoms in older adults without dementia. A systematic search in PubMed yielded 689 peer-reviewed articles. After full-text screening, nine CSF studies, 11 PET studies, and five plasma studies were included. No association between amyloid-beta and depression or depressive symptoms were found using cerebrospinal fluid (CSF) (0.15; 95% CI: -0.08; 0.37), positron emission topography (PET) (Cohen's d: 0.09; 95% CI: -0.05; 0.24), or plasma (-0.01; 95% CI: -0.23; 0.22). However, subgroup analyses revealed an association in plasma studies of individuals with cognitive impairment. A trend of an association was found in the studies using CSF and PET. This systematic review and meta-analysis suggested that depressive symptoms may be part of the prodromal stage of dementia.

Identified Small Open Reading Frame-Encoded Peptides in Human Serum with Nanoparticle Protein Coronas

The low-molecular-weight proteins (LMWP) in serum and plasma are related to various human diseases and can be valuable biomarkers. A small open reading frame-encoded peptide (SEP) is one kind of LMWP, which has been found to function in many bioprocesses and has also been found in human blood, making it a potential biomarker. The detection of LMWP by a mass spectrometry (MS)-based proteomic assay is often inhibited by the wide dynamic range of serum/plasma protein abundance. Nanoparticle protein coronas are a newly emerging protein enrichment method. To analyze SEPs in human serum, we have developed a protocol integrated with nanoparticle protein coronas and liquid chromatography (LC)/MS/MS. With three nanoparticles, TiO2, Fe3O4@SiO2, and Fe3O4@SiO2@TiO2, we identified 164 new SEPs in the human serum sample. Fe3O4@SiO2 and a nanoparticle mixture obtained the maximum number and the largest proportion of identified SEPs, respectively. Compared with acetonitrile-based extraction, nanoparticle protein coronas can cover more small proteins and SEPs. The magnetic nanoparticle is also fit for high-throughput parallel protein separation before LC/MS. This method is fast, efficient, reproducible, and easy to operate in 96-well plates and centrifuge tubes, which will benefit the research on SEPs and biomarkers.

Peripheral blood amyloid-β involved in the pathogenesis of Alzheimer's disease via impacting on peripheral innate immune cells

A key pathological factor of Alzheimer's disease (AD), the most prevalent form of age-related dementia in the world, is excessive β-amyloid protein (Aβ) in extracellular aggregation in the brain. And in the peripheral blood, a large amount of Aβ is derived from platelets. So far, the causality between the levels of peripheral blood Aβ and its aggregation in the brain, particularly the role of the peripheral blood Aβ in the pathology of AD, is still unclear. And the relation between the peripheral blood Aβ and tau tangles of brain, another crucial pathologic factor contributing to the pathogenesis of AD, is also ambiguous. More recently, the anti-Aβ monoclonal antibodies are approved for treatment of AD patients through declining the peripheral blood Aβ mechanism of action to enhance plasma and central nervous system (CNS) Aβ clearance, leading to a decrease Aβ burden in brain and improving cognitive function, which clearly indicates that the levels of the peripheral blood Aβ impacted on the Aβ burden in brain and involved in the pathogenesis of AD. In addition, the role of peripheral innate immune cells in AD remains mostly unknown and the results obtained were controversial. In the present review, we summarize recent studies on the roles of peripheral blood Aβ and the peripheral innate immune cells in the pathogenesis of AD. Finally, based on the published data and our own work, we believe that peripheral blood Aβ plays an important role in the development and progression of AD by impacting on the peripheral innate immune cells.

Drug repositioning with adaptive graph convolutional networks

MOTIVATION

Drug repositioning is an effective strategy to identify new indications for existing drugs, providing the quickest possible transition from bench to bedside. With the rapid development of deep learning, graph convolutional networks (GCNs) have been widely adopted for drug repositioning tasks. However, prior GCNs based methods exist limitations in deeply integrating node features and topological structures, which may hinder the capability of GCNs.

RESULTS

In this study, we propose an adaptive GCNs approach, termed AdaDR, for drug repositioning by deeply integrating node features and topological structures. Distinct from conventional graph convolution networks, AdaDR models interactive information between them with adaptive graph convolution operation, which enhances the expression of model. Concretely, AdaDR simultaneously extracts embeddings from node features and topological structures and then uses the attention mechanism to learn adaptive importance weights of the embeddings. Experimental results show that AdaDR achieves better performance than multiple baselines for drug repositioning. Moreover, in the case study, exploratory analyses are offered for finding novel drug-disease associations.

AVAILABILITY AND IMPLEMENTATION

The soure code of AdaDR is available at: https://github.com/xinliangSun/AdaDR.

Specific serum autoantibodies predict the development and progression of Alzheimer's disease with high accuracy

Autoimmunity plays a key role in the pathogenesis of Alzheimer's disease (AD). However, whether autoantibodies in peripheral blood can be used as biomarkers for AD has been elusive. Serum samples were obtained from 1,686 participants, including 767 with AD, 146 with mild cognitive impairment (MCI), 255 with other neurodegenerative diseases, and 518 healthy controls. Specific autoantibodies were measured using a custom-made immunoassay. Multivariate support vector machine models were employed to investigate the correlation between serum autoantibody levels and disease states. As a result, seven candidate AD-specific autoantibodies were identified, including MAPT, DNAJC8, KDM4D, SERF1A, CDKN1A, AGER, and ASXL1. A classification model with high accuracy (area under the curve (AUC) = 0.94) was established. Importantly, these autoantibodies could distinguish AD from other neurodegenerative diseases and out-performed amyloid and tau protein concentrations in cerebrospinal fluid in predicting cognitive decline (P < 0.001). This study indicated that AD onset and progression are possibly accompanied by an unappreciated serum autoantibody response. Therefore, future studies could optimize its application as a convenient biomarker for the early detection of AD.

Harmonization of CSF and imaging biomarkers in Alzheimer's disease: Need and practical applications for genetics studies and preclinical classification

In Alzheimer's disease (AD) research, cerebrospinal fluid (CSF) Amyloid beta (Aβ), Tau and pTau are the most accepted and well validated biomarkers. Several methods and platforms exist to measure those biomarkers, leading to challenges in combining data across studies. Thus, there is a need to identify methods that harmonize and standardize these values. We used a Z-score based approach to harmonize CSF and amyloid imaging data from multiple cohorts and compared GWAS results using this approach with currently accepted methods. We also used a generalized mixture model to calculate the threshold for biomarker-positivity. Based on our findings, our normalization approach performed as well as meta-analysis and did not lead to any spurious results. In terms of dichotomization, cutoffs calculated with this approach were very similar to those reported previously. These findings show that the Z-score based harmonization approach can be applied to heterogeneous platforms and provides biomarker cut-offs consistent with the classical approaches without requiring any additional data.

FTIR Spectroscopy and Blood-Derived Extracellular Vesicles Duo in Alzheimer's Disease

Background

Alzheimer's disease (AD) diagnosis is difficult, and new accurate tools based on peripheral biofluids are urgently needed. Extracellular vesicles (EVs) emerged as a valuable source of biomarker profiles for AD, since their cargo is disease-specific and these can be easily isolated from easily accessible biofluids, as blood. Fourier Transform Infrared (FTIR) spectroscopy can be employed to analyze EVs and obtain the spectroscopic profiles from different regions of the spectra, simultaneously characterizing carbohydrates, nucleic acids, proteins, and lipids.

Objective

The aim of this study was to identify blood-derived EVs (bdEVs) spectroscopic signatures with AD discriminatory potential.

Methods

Herein, FTIR spectra of bdEVs from two biofluids (serum and plasma) and distinct sets of Controls and AD cases were acquired, and EVs' spectra analyzed.

Results

Analysis of bdEVs second derivative peaks area revealed differences between Controls and AD cases in distinct spectra regions, assigned to carbohydrates and nucleic acids, amides, and lipids.

Conclusions

EVs' spectroscopic profiles presented AD discriminatory value, supporting the use of bdEVs combined with FTIR as a screening or complementary tool for AD diagnosis.

Blood-Based Biomarkers for Early Alzheimer's Disease Diagnosis in Real-World Settings

As our knowledge about the biology of Alzheimer's disease (AD) expands and we recognize the significance of early intervention for effective treatment, there is a shift in focus toward detecting the disease at an early stage. AD is characterized by the accumulation of misfolded amyloid-β (Aβ) and phosphorylated tau proteins in the brain, leading to the formation of senile plaques and neurofibrillary tangles. While a definitive diagnosis of AD can only be confirmed through autopsy by examining these pathological features, there are now reliable methods available for diagnosing the disease in living individuals. These methods involve analyzing cerebrospinal fluid and using positron emission tomography to accurately assess the presence of Aβ and tau proteins. While these diagnostic markers have shown high accuracy in memory-clinic populations, they do have limitations such as the requirement for invasive lumbar puncture or exposure to ionizing radiation. Additionally, they are not easily accessible outside of specialized healthcare settings. Blood-based biomarkers of the core pathological features of AD are being developed, showing promise for less invasive, scalable identification of AD cases in the community. The advantages for the healthcare systems of this development are obvious, but the diagnostic performance of blood-based biomarkers in broader, non-selected populations outside of retrospective analyses and research cohorts still requires further investigation, including the combination with more effective neuropsychological assessments such as digital cognitive test solutions.

The Clinical Aspects of COVID and Alzheimer's Disease: A Round-Up of Where Things Stand and Are Headed

 The link between long COVID-19 and brain/cognitive impairments is concerning and may foster a worrisome worldwide emergence of novel cases of neurodegenerative diseases with aging. This review aims to update the knowledge, crosstalk, and possible intersections between the Post-COVID Syndrome (PCS) and Alzheimer's disease (AD). References included in this review were obtained from PubMed searches conducted between October 2023 and November 2023. PCS is a very heterogenous and poorly understood disease with recent evidence of a possible association with chronic diseases such as AD. However, more scientific data is required to establish the link between PCS and AD.

2D nanostructures: Potential in diagnosis and treatment of Alzheimer's disease

Two-dimensional (2D) nanomaterials have garnered enormous attention seemingly due to their unusual architecture and properties. Graphene and graphene oxide based 2D nanomaterials remained the most sought after for several years but the quest to design superior 2D nanomaterials which can find wider application gave rise to development of non-graphene 2D materials as well. Consequently, in addition to graphene based 2D nanomaterials, 2D nanostructures designed using macromolecules (such as DNAs, proteins, peptides and peptoids), transition metal dichalcogenides, transition-metal carbides and/or nitrides (MXene), black phosphorous, chitosan, hexagonal boron nitrides, and graphitic carbon nitride, and covalent organic frameworks have been developed. Interestingly, these 2D nanomaterials have found applications in diagnosis and treatment of various diseases including Alzheimer's disease (AD). Although AD is one of the most debilitating neurodegenerative conditions across the globe; unfortunately, there remains a paucity of effective diagnostic and/or therapeutic intervention for it till date. In this scenario, nanomaterial-based biosensors, or therapeutics especially 2D nanostructures are emerging to be promising in this regard. This review summarizes the diagnostic and therapeutic platforms developed for AD using 2D nanostructures. Collectively, it is worth mentioning that these 2D nanomaterials would seemingly provide an alternative and intriguing platform for biomedical interventions.

Aqueous and Plasma Levels of Phosphorylated Tau 181 in Individuals with Normal Cognition

Background

Plasma and cerebrospinal fluid (CSF) levels of p-tau181 have been associated with Alzheimer's disease (AD). The retina and vitreous have shown measurable quantities of phosphorylated tau 181 (p-tau181). The aqueous humor, which can be collected during cataract surgery, may have measurable concentrations of p-tau181.

Objective

To determine whether p-tau181 is detectable in the aqueous humor and if so, whether it is associated with other measures that might be consistent with AD such as higher plasma p-tau181 concentration and lower Montreal Cognitive Assessment (MoCA-BLIND version 7.1) score.

Methods

Aqueous humor samples, blood samples, and MoCA-BLIND scores were collected from patients who did not carry a clinical diagnosis of cognitive impairment at the time of cataract surgery. Aqueous p-tau181 concentrations and plasma p-tau181 concentrations were then measured using ultra-sensitive single-molecule assay ELISA technology. A rank-transformed mixed-effects multivariate regression model was used to determine associations between aqueous concentrations, plasma concentrations, and MoCA-BLIND scores.

Results

16 eyes of 16 participants were enrolled with an average age of 71.6. Average MoCA-BLIND score was 20.6/22, average aqueous p-tau181 concentration was 6.4 pg/mL, and average plasma p-tau181 concentration was 3.1 pg/mL. Higher plasma p-tau181 was significantly associated with higher aqueous p-tau181 (p = 0.02). Aqueous p-tau181 and plasma p-tau181 were negatively associated with MoCA-BLIND scores (p = 0.005 and p = 0.001 respectively) in these patients.

Conclusions

Aqueous p-tau181 is positively correlated with plasma p-tau181 and is negatively correlated with MoCA-BLIND scores. Further study in individuals with mild cognitive impairment or AD characterized by cerebrospinal fluid and volumetric MRI metrics may yield further insights.

Relationship between topological efficiency of white matter structural connectome and plasma biomarkers across the Alzheimer's disease continuum

Both plasma biomarkers and brain network topology have shown great potential in the early diagnosis of Alzheimer's disease (AD). However, the specific associations between plasma AD biomarkers, structural network topology, and cognition across the AD continuum have yet to be fully elucidated. This retrospective study evaluated participants from the Sino Longitudinal Study of Cognitive Decline cohort between September 2009 and October 2022 with available blood samples or 3.0-T MRI brain scans. Plasma biomarker levels were measured using the Single Molecule Array platform, including β-amyloid (Aβ), phosphorylated tau181 (p-tau181), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL). The topological structure of brain white matter was assessed using network efficiency. Trend analyses were carried out to evaluate the alterations of the plasma markers and network efficiency with AD progression. Correlation and mediation analyses were conducted to further explore the relationships among plasma markers, network efficiency, and cognitive performance across the AD continuum. Among the plasma markers, GFAP emerged as the most sensitive marker (linear trend: t = 11.164, p = 3.59 × 10-24 ; quadratic trend: t = 7.708, p = 2.25 × 10-13 ; adjusted R2  = 0.475), followed by NfL (linear trend: t = 6.542, p = 2.9 × 10-10 ; quadratic trend: t = 3.896, p = 1.22 × 10-4 ; adjusted R2  = 0.330), p-tau181 (linear trend: t = 8.452, p = 1.61 × 10-15 ; quadratic trend: t = 6.316, p = 1.05 × 10-9 ; adjusted R2  = 0.346) and Aβ42/Aβ40 (linear trend: t = -3.257, p = 1.27 × 10-3 ; quadratic trend: t = -1.662, p = 9.76 × 10-2 ; adjusted R2  = 0.101). Local efficiency decreased in brain regions across the frontal and temporal cortex and striatum. The principal component of local efficiency within these regions was correlated with GFAP (Pearson's R = -0.61, p = 6.3 × 10-7 ), NfL (R = -0.57, p = 6.4 × 10-6 ), and p-tau181 (R = -0.48, p = 2.0 × 10-4 ). Moreover, network efficiency mediated the relationship between general cognition and GFAP (ab = -0.224, 95% confidence interval [CI] = [-0.417 to -0.029], p = .0196 for MMSE; ab = -0.198, 95% CI = [-0.42 to -0.003], p = .0438 for MOCA) or NfL (ab = -0.224, 95% CI = [-0.417 to -0.029], p = .0196 for MMSE; ab = -0.198, 95% CI = [-0.42 to -0.003], p = .0438 for MOCA). Our findings suggest that network efficiency mediates the association between plasma biomarkers, specifically GFAP and NfL, and cognitive performance in the context of AD progression, thus highlighting the potential utility of network-plasma approaches for early detection, monitoring, and intervention strategies in the management of AD.

Optimized Pre-analytical Handling Protocol for Blood-Based Biomarkers of Alzheimer's Disease

The therapeutic management of patients with Alzheimer's disease (AD) has been hindered by poor diagnostic accuracy. As such, there is an unmet clinical need for tools that can detect and diagnose the disease in its early stages. Compared with cerebrospinal fluid (CSF)-based biomarkers or positron emission tomography (PET), the use of reliable blood-based biomarkers could offer an accessible and minimally invasive method of streamlining diagnosis in the clinical setting. However, the influence of pre-analytical processing and sample handling parameters on the accurate measurement of protein biomarkers is well established, especially for AD CSF-based biomarkers. In this chapter, we provide recommendations for an optimal sample handling protocol for the analysis of blood-based biomarkers specifically for amyloid pathology in AD.

Visual Functions Are Associated with Biomarker Changes in Alzheimer's Disease

Background

While various biomarkers of Alzheimer's disease (AD) have been associated with general cognitive function, their association to visual-perceptive function across the AD spectrum warrant more attention due to its significant impact on quality of life. Thus, this study explores how AD biomarkers are associated with decline in this cognitive domain.

Objective

To explore associations between various fluid and imaging biomarkers and visual-based cognitive assessments in participants across the AD spectrum.

Methods

Data from participants (N = 1,460) in the Alzheimer's Disease Neuroimaging Initiative were analyzed, including fluid and imaging biomarkers. Along with the Mini-Mental State Examination (MMSE), three specific visual-based cognitive tests were investigated: Trail Making Test (TMT) A and TMT B, and the Boston Naming Test (BNT). Locally estimated scatterplot smoothing curves and Pearson correlation coefficients were used to examine associations.

Results

MMSE showed the strongest correlations with most biomarkers, followed by TMT-B. The p-tau181/Aβ1-42 ratio, along with the volume of the hippocampus and entorhinal cortex, had the strongest associations among the biomarkers.

Conclusions

Several biomarkers are associated with visual processing across the disease spectrum, emphasizing their potential in assessing disease severity and contributing to progression models of visual function and cognition.

Plasma/Serum Proteomics based on Mass Spectrometry

Human blood is a window of physiology and disease. Examination of biomarkers in blood is a common clinical procedure, which can be informative in diagnosis and prognosis of diseases, and in evaluating treatment effectiveness. There is still a huge demand on new blood biomarkers and assays for precision medicine nowadays, therefore plasma/serum proteomics has attracted increasing attention in recent years. How to effectively proceed with the biomarker discovery and clinical diagnostic assay development is a question raised to researchers who are interested in this area. In this review, we comprehensively introduce the background and advancement of technologies for blood proteomics, with a focus on mass spectrometry (MS). Analyzing existing blood biomarkers and newly-built diagnostic assays based on MS can shed light on developing new biomarkers and analytical methods. We summarize various protein analytes in plasma/serum which include total proteome, protein post-translational modifications, and extracellular vesicles, focusing on their corresponding sample preparation methods for MS analysis. We propose screening multiple protein analytes in the same set of blood samples in order to increase success rate for biomarker discovery. We also review the trends of MS techniques for blood tests including sample preparation automation, and further provide our perspectives on their future directions.

RNA Analysis of Circulating Leukocytes in Patients with Alzheimer's Disease

Background

One of the key symptoms of Alzheimer's disease (AD) is the impairment of short-term memory. Hippocampal neurogenesis is essential for short-term memory and is known to decrease in patients with AD. Impaired short-term memory and impaired neurogenesis are observed in aged mice alongside changes in RNA expression of gap junction and metabolism-related genes in circulating leukocytes. Moreover, after penetrating the blood-brain barrier via the SDF1/CXCR4 axis, circulating leukocytes directly interact with hippocampal neuronal stem cells via gap junctions.

Objective

Evaluation of RNA expression profiles in circulating leukocytes in patients with AD.

Methods

Patients with AD (MMSE≧23, n = 10) and age-matched controls (MMSE≧28, n = 10) were enrolled into this study. RNA expression profiles of gap junction and metabolism-related genes in circulating leukocytes were compared between the groups (jRCT: 1050210166).

Results

The ratios of gap junction and metabolism-related genes were significantly different between patients with AD and age-matched controls. However, due to large inter-individual variations, there were no statistically significant differences in the level of single RNA expression between these groups.

Conclusions

Our findings suggest a potential connection between the presence of circulating leukocytes and the process of hippocampal neurogenesis in individuals with AD. Analyzing RNA in circulating leukocytes holds promise as a means to offer novel insights into the pathology of AD, distinct from conventional markers.

Association of Plasma Amyloid-β and Dementia Among Black and White Older Adults

Background

Plasma amyloid-β (Aβ) has emerged as an important tool to detect risks of Alzheimer's disease and related dementias, although research in diverse populations is lacking.

Objective

We compared plasma Aβ42/40 by race with dementia risk over 15 years among Black and White older adults.

Methods

In a prospective cohort of 997 dementia-free participants (mean age 74±2.9 years, 55% women, 54% Black), incident dementia was identified based on hospital records, medication, and neurocognitive test over 15 years. Plasma Aβ42/40 was measured at Year 2 and categorized into low, medium, and high tertile. We used linear regression to estimate mean Aβ42/40 by race and race-stratified Cox proportional hazards models to assess the association between Aβ42/40 tertile and dementia risk.

Results

Black participants had a lower age-adjusted mean Aβ 42/40 compared to White participants, primarily among APOE ɛ4 non-carriers (Black: 0.176, White: 0.185, p = 0.035). Among Black participants, lower Aβ 42/40 was associated with increased dementia risk: 33% in low (hazard ratios [HR] = 1.77, 95% confidence interval 1.09-2.88) and 27% in medium tertile (HR = 1.67, 1.01-2.78) compared with 18% in high Aβ 42/40 tertile; Increased risks were attenuated among White participants: 21% in low (HR = 1.43, 0.81-2.53) and 23% in medium tertile (HR = 1.27, 0.68-2.36) compared with 15% in high Aβ 42/40 tertile. The interaction by race was not statistically significant.

Conclusions

Among community-dwelling, non-demented older adults, especially APOE ɛ4 non-carriers, Black individuals had lower plasma Aβ 42/40 and demonstrated a higher dementia risk with low Aβ42/40 compared with White individuals.

Clinical utility of plasma Aβ42/40 ratio by LC-MS/MS in Alzheimer's disease assessment

INTRODUCTION

Plasma Aβ42/40 ratio can be used to help predict amyloid PET status, but its clinical utility in Alzheimer's disease (AD) assessment is unclear.

METHODS

Aβ42/40 ratio was measured by LC-MS/MS in 250 specimens with associated amyloid PET imaging, diagnosis, and demographic data, and 6,192 consecutive clinical specimens submitted for Aβ42/40 testing.

RESULTS

High diagnostic sensitivity and negative predictive value (NPV) for Aβ-PET positivity were observed, consistent with the clinical performance of other plasma LC-MS/MS assays, but with greater separation between Aβ42/40 values for individuals with positive vs negative Aβ-PET results. Assuming a moderate prevalence of Aβ-PET positivity, a cutpoint was identified with 99% NPV, which could help predict that AD is likely not the cause of patients' cognitive impairment and help reduce PET evaluation by about 40%.

DISCUSSION

Using high-throughput plasma Aβ42/40 LC-MS/MS assays can help reduce PET evaluations in patients with low likelihood of AD pathology, allowing for cost savings.

Diagnostic performance of plasma pTau 217, pTau 181, Aβ 1-42 and Aβ 1-40 in the LUMIPULSE automated platform for the detection of Alzheimer disease

BACKGROUND

Recently developed blood markers for Alzheimer's disease (AD) detection have high accuracy but usually require ultra-sensitive analytic tools not commonly available in clinical laboratories, and their performance in clinical practice is unknown.

METHODS

We analyzed plasma samples from 290 consecutive participants that underwent lumbar puncture in routine clinical practice in a specialized memory clinic (66 cognitively unimpaired, 130 participants with mild cognitive impairment, and 94 with dementia). Participants were classified as amyloid positive (A+) or negative (A-) according to CSF Aβ1-42/Aβ1-40 ratio. Plasma pTau217, pTau181, Aβ1-42 and Aβ1-40 were measured in the fully-automated LUMIPULSE platform. We used linear regression to compare plasma biomarkers concentrations between A + and A- groups, evaluated Spearman's correlation between plasma and CSF and performed ROC analyses to assess their diagnostic accuracy to detect brain amyloidosis as determined by CSF Aβ1-42/Aβ1-40 ratio. We analyzed the potential of pTau217 to predict amyloidosis in CSF.

RESULTS

Plasma pTau217 and pTau181 concentration were higher in A + than A- while the plasma Aβ1-42/Aβ1-40 ratio was lower in A + compared to A-. pTau181 and the Aβ1-42/Aβ1-40 ratio showed moderate correlation between plasma and CSF (Rho = 0.66 and 0.69, respectively). The areas under the ROC curve to discriminate A + from A- participants were 0.94 (95% CI 0.92-0.97) for pTau217, and 0.88 (95% CI 0.84-0.92) for both pTau181 and Aβ1-42/Aβ1-40. Chronic kidney disease (CKD) was related to increased plasma biomarker concentrations, but ratios were less affected. Plasma pTau217 had the highest fold change (x4.2) and showed high predictive capability in discriminating A + from A-, having 4-7% misclassification rate. The global accuracy of plasma pTau217 using a two-threshold approach was robust in symptomatic groups, exceeding 90%.

CONCLUSION

The evaluation of blood biomarkers on an automated platform exhibited high diagnostic accuracy for AD pathophysiology, and pTau217 showed excellent diagnostic accuracy to identify participants with AD in a consecutive sample representing the routine clinical practice in a specialized memory unit.

Detection of APP gene recombinant in human blood plasma

The pathogenesis of Alzheimer's disease (AD) is believed to involve the accumulation of amyloid-β in the brain, which is produced by the sequential cleavage of amyloid precursor protein (APP) by β-secretase and γ-secretase. Recently, analysis of genomic DNA and mRNA from postmortem brain neurons has revealed intra-exonic recombinants of APP (gencDNA), which have been implicated in the accumulation of amyloid-β. In this study, we computationally analyzed publicly available sequence data (SRA) using probe sequences we constructed to screen APP gencDNAs. APP gencDNAs were detected in SRAs constructed from both genomic DNA and RNA obtained from the postmortem brain and in the SRA constructed from plasma cell-free mRNA (cf-mRNA). The SRA constructed from plasma cf-mRNA showed a significant difference in the number of APP gencDNA reads between SAD and NCI: the p-value from the Mann-Whitney U test was 5.14 × 10-6. The transcripts were also found in circulating nucleic acids (CNA) from our plasma samples with NGS analysis. These data indicate that transcripts of APP gencDNA can be detected in blood plasma and suggest the possibility of using them as blood biomarkers for Alzheimer's disease.

Novel harmine derivatives as potent acetylcholinesterase and amyloid beta aggregation dual inhibitors for management of Alzheimer's disease

In this study, a series of potential ligands for the treatment of AD were synthesised and characterised as novel harmine derivatives modified at position 9 with benzyl piperazinyl. In vitro studies revealed that the majority of the derivatives exhibited moderate to potent inhibition against hAChE and Aβ1 - 42 aggregation. Notably, compounds 13 and 17d displayed potent drug - likeness and ADMET properties, demonstrating remarkable inhibitory activities towards AChE (IC50 = 58.76 nM and 89.38 nM, respectively) as well as Aβ aggregation (IC50 = 9.31 μM and 13.82 μM, respectively). More importantly, compounds 13 and 17d showed exceptional neuroprotective effects against Aβ1 - 42-induced SH - SY5Y damage, while maintaining low toxicity in SH - SY5Y cells. Further exploration of the mechanism through kinetic studies and molecular modelling confirmed that compound 13 could interact with both the CAS and the PAS of AChE. These findings suggested that harmine derivatives hold great potential as dual - targeted candidates for treating AD.

Levels of Alzheimer's disease blood biomarkers are altered after food intake-A pilot intervention study in healthy adults

INTRODUCTION

Blood biomarkers accurately identify Alzheimer's disease (AD) pathophysiology and axonal injury. We investigated the influence of food intake on AD-related biomarkers in cognitively healthy, obese adults at high metabolic risk.

METHODS

One-hundred eleven participants underwent repeated blood sampling during 3 h after a standardized meal (postprandial group, PG). For comparison, blood was sampled from a fasting subgroup over 3 h (fasting group, FG). Plasma neurofilament light (NfL), glial fibrillary acidic protein (GFAP), amyloid-beta (Aβ) 42/40, phosphorylated tau (p-tau) 181 and 231, and total-tau were measured via single molecule array assays.

RESULTS

Significant differences were found for NfL, GFAP, Aβ42/40, p-tau181, and p-tau231 between FG and PG. The greatest change to baseline occurred for GFAP and p-tau181 (120 min postprandially, p < 0.0001).

CONCLUSION

Our data suggest that AD-related biomarkers are altered by food intake. Further studies are needed to verify whether blood biomarker sampling should be performed in the fasting state.

HIGHLIGHTS

Acute food intake alters plasma biomarkers of Alzheimer's disease in obese, otherwise healthy adults. We also found dynamic fluctuations in plasma biomarkers concentration in the fasting state suggesting physiological diurnal variations. Further investigations are highly needed to verify if biomarker measurements should be performed in the fasting state and at a standardized time of day to improve the diagnostic accuracy.