Current trends in blood biomarker detection and imaging for Alzheimer’s disease

Automatic offline-capable smartphone paper-based microfluidic device for efficient biomarker detection of Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) is a prevalent neurodegenerative disease with no effective treatment. Efficient and rapid detection plays a crucial role in mitigating and managing AD progression. Deep learning-assisted smartphone-based microfluidic paper analysis devices (μPADs) offer the advantages of low cost, good sensitivity, and rapid detection, providing a strategic pathway to address large-scale disease screening in resource-limited areas. However, existing smartphone-based detection platforms usually rely on large devices or cloud servers for data transfer and processing. Additionally, the implementation of automated colorimetric enzyme-linked immunoassay (c-ELISA) on μPADs can further facilitate the realization of smartphone μPADs platforms for efficient disease detection.

RESULTS

This paper introduces a new deep learning-assisted offline smartphone platform for early AD screening, offering rapid disease detection in low-resource areas. The proposed platform features a simple mechanical rotating structure controlled by a smartphone, enabling fully automated c-ELISA on μPADs. Our platform successfully applied sandwich c-ELISA for detecting the β-amyloid peptide 1-42 (Aβ 1-42, a crucial AD biomarker) and demonstrated its efficacy in 38 artificial plasma samples (healthy: 19, unhealthy: 19, N = 6). Moreover, we employed the YOLOv5 deep learning model and achieved an impressive 97 % accuracy on a dataset of 1824 images, which is 10.16 % higher than the traditional method of curve-fitting results. The trained YOLOv5 model was seamlessly integrated into the smartphone using the NCNN (Tencent's Neural Network Inference Framework), enabling deep learning-assisted offline detection. A user-friendly smartphone application was developed to control the entire process, realizing a streamlined "samples in, answers out" approach.

SIGNIFICANCE

This deep learning-assisted, low-cost, user-friendly, highly stable, and rapid-response automated offline smartphone-based detection platform represents a good advancement in point-of-care testing (POCT). Moreover, our platform provides a feasible approach for efficient AD detection by examining the level of Aβ 1-42, particularly in areas with low resources and limited communication infrastructure.

Progress on early diagnosing Alzheimer's disease

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that affects both cognition and non-cognition functions. The disease follows a continuum, starting with preclinical stages, progressing to mild cognitive and behavioral impairment, ultimately leading to dementia. Early detection of AD is crucial for better diagnosis and more effective treatment. However, the current AD diagnostic tests of biomarkers using cerebrospinal fluid and/or brain imaging are invasive or expensive, and mostly are still not able to detect early disease state. Consequently, there is an urgent need to develop new diagnostic techniques with higher sensitivity and specificity during the preclinical stages of AD. Various non-cognitive manifestations, including behavioral abnormalities, sleep disturbances, sensory dysfunctions, and physical changes, have been observed in the preclinical AD stage before occurrence of notable cognitive decline. Recent research advances have identified several biofluid biomarkers as early indicators of AD. This review focuses on these non-cognitive changes and newly discovered biomarkers in AD, specifically addressing the preclinical stages of the disease. Furthermore, it is of importance to explore the potential for developing a predictive system or network to forecast disease onset and progression at the early stage of AD.

Electrochemical peptide-based biosensor for the detection of the inflammatory disease biomarker, interleukin-1beta

This paper reports the development of a highly sensitive and selective electrochemical peptide-based biosensor for the detection of the inflammatory disease biomarker, interleukin-1beta (IL-1β). To this end, flower-like Au-Ag@MoS2-rGO nanocomposites were used as the signal amplification platform to achieve a label-free biosensor with a high sensitivity and selectivity. First, a high-affinity peptide for IL-1β was identified through biopanning with M13 random peptide libraries, and was newly designed by incorporating cysteine at the C-terminus. An IL-1β specific binding peptide was used as the bio-receptor, and the interaction between the IL-1β binding peptide and IL-1β was confirmed via enzyme-linked immunosorbent assay and various physicochemical and electrochemical analyses. Under optimal conditions, the biosensor achieved an ultrasensitive and specific IL-1β detection in a wide linear concentration range of 0-250 ng/mL with a picomolar-level detection limit (∼2.4 pM), low binding constant (∼0.62 pM), and a low coefficient of variation (<1.65 %). The biosensor was successfully utilized for IL-1β determination in the serum of Crohn's disease patients with a good correlation coefficient. In addition, the detection performance was comparable to that of commercially available IL-1β ELISA kit. This indicates that the electrochemical peptide-based biosensor may offer a potentially valuable platform for the clinical diagnosis of various inflammatory disease biomarkers.

Light on Alzheimer's disease: from basic insights to preclinical studies

Alzheimer's disease (AD), referring to a gradual deterioration in cognitive function, including memory loss and impaired thinking skills, has emerged as a substantial worldwide challenge with profound social and economic implications. As the prevalence of AD continues to rise and the population ages, there is an imperative demand for innovative imaging techniques to help improve our understanding of these complex conditions. Photoacoustic (PA) imaging forms a hybrid imaging modality by integrating the high-contrast of optical imaging and deep-penetration of ultrasound imaging. PA imaging enables the visualization and characterization of tissue structures and multifunctional information at high resolution and, has demonstrated promising preliminary results in the study and diagnosis of AD. This review endeavors to offer a thorough overview of the current applications and potential of PA imaging on AD diagnosis and treatment. Firstly, the structural, functional, molecular parameter changes associated with AD-related brain imaging captured by PA imaging will be summarized, shaping the diagnostic standpoint of this review. Then, the therapeutic methods aimed at AD is discussed further. Lastly, the potential solutions and clinical applications to expand the extent of PA imaging into deeper AD scenarios is proposed. While certain aspects might not be fully covered, this mini-review provides valuable insights into AD diagnosis and treatment through the utilization of innovative tissue photothermal effects. We hope that it will spark further exploration in this field, fostering improved and earlier theranostics for AD.

Advances in targeted tracking and detection of soluble amyloid-β aggregates as a biomarker of Alzheimer's disease

Misfolding and aggregation of amyloid-β (Aβ) peptides are key hallmarks of Alzheimer's disease (AD). With accumulating evidence suggesting that different Aβ species have varied neurotoxicity and implications in AD development, the discovery of affinity ligands and analytical approaches to selective distinguish, detect, and monitor Aβ becomes an active research area. Remarkable advances have been achieved, which not only promote our understanding of the biophysical chemistry of the protein aggregation during neurodegeneration, but also provide promising tools for early detection of the disease. In view of this, we summarize the recent progress in selective and sensitive approaches for tracking and detection of Aβ species. Specific attentions are given to soluble Aβ oligomers, due to their crucial roles in AD development and occurrence at early stages. The design principle, performance of targeting units, and their cooperative effects with signal reporters for Aβ analysis are discussed. The applications of the novel targeting probes and sensing systems for dynamic monitoring oligomerization, measuring Aβ in biosamples and in vivo imaging in brain are summarized. Finally, the perspective and challenges are discussed regarding the future development of Aβ-targeting analytical tools to explore the unknown field to contribute to the early diagnosis and treatment of AD.

Biomarkers as Endpoints in Clinical Trials for Alzheimer's Disease

Background

Alzheimer's disease (AD) is a neurodegenerative disease that imposes economic and societal burden. Biomarkers have played a crucial role in the recent approval of aducanumab and lecanemab as disease-modifying therapies which marked a significant milestone for the treatment of AD. The inclusion of biomarkers in AD trials facilitates precise diagnosis, monitors safety, demonstrates target engagement, and supports disease modification.

Objective

This study analyzed the utilization state and trends of biomarkers as endpoints in AD trials.

Methods

In this retrospective study, trials were collected by searching clinicaltrials.gov using the term "Alzheimer". Primary and secondary outcomes were analyzed separately for each phase.

Results

Among the 1,048 analyzed trials, 313 (29.87%) adopted biomarkers as primary endpoints and 364 (34.73%) as secondary endpoints, mainly in phases 1 and 2. The top three biomarkers adopted as primary endpoints in phases 1, 2, and 3 were amyloid-PET, tau-PET, and MRI. The top three biomarkers adopted as secondary endpoints, in phase 1, were cerebrospinal fluid (CSF) amyloid-β (Aβ), blood Aβ and amyloid-PET; in phase 2, they were MRI, CSF Aβ, and CSF phospho-tau; and in phase 3, they were amyloid PET, MRI, and blood Aβ. There was a statistically significant increase in the adoption of biomarkers as primary endpoints in phase 2 trials (p = 0.001) and secondary endpoints in phase 3 trials (p = 0.001).

Conclusions

The growing recognition of the importance of biomarkers in AD trial' design and drug development is evident by the significant steady increase in biomarkers' utilization in phases 2 and 3.

Systematic identification of key basement membrane related genes as potential new biomarkers in Alzheimer's disease

OBJECTIVE

The study aimed to identify biomarkers associated with basement membranes (BMs)-related genes (BMGs) in Alzheimer's disease (AD) and investigate their potential role in the progression of AD pathology.

METHODS

Gene expression profiles were retrieved from Gene Expression Omnibus database. 222 human BMGs were collected from the relevant literature. Subsequently, the differentially expressed BMGs (DE-BMGs) were filtered, and the key DE-BMGs were identified using weighted gene correlation network analysis (WGCNA) and two machine learning algorithms. The expression levels, diagnostic values, clinical significances, enrichment analyses and regulatory networks of these candidate biomarkers were further examined.

RESULTS

A total of 44 DE-BMGs were acquired by comparing AD temporal cortex with nondemented controls. Using WGCNA and machine learning, versiscan (VCAN), tissue inhibitor of metalloproteinase 1 (TIMP1), structural maintenance of chromosome 3 (SMC3), and laminin β2 (LAMB2) were ultimately identified as candidate biomarkers, and they were verified in a murine model. These biomarkers had high diagnostic value (area under the curve (AUC)＞0.8). The diagnostic value of the four gene combination was then evaluated in multiple databases, yielding AUCs ranging from 0.688 to 1. Furthermore, a meaningful correlation between these biomarkers and AD pathology progression was observed. Finally, comprehensive analyses involving Hallmark pathway enrichment, immune cell infiltration analysis, transcriptional regulatory, and competitive endogenous RNA networks indicated that key DE-BMGs closely correlated with oxidative stress and immune dysfunction.

CONCLUSION

Our study comprehensively identified four candidate BMGs and their combination model that play a crucial part in the diagnosis and pathogenesis of AD.

Attitudes toward pre-symptomatic screening for Alzheimer's dementia in five European countries: a comparison of family members of people with Alzheimer's dementia versus non-family members

Introduction: Pre-symptomatic screening is getting more attention in healthcare as it detects the risk for developing neurodegenerative diseases like Alzheimer's disease (AD), which is very useful for treatment or prevention. AD screening could play an important role in individuals with at least one affected first-degree relative, but also without family history. As the demand for screening is rising worldwide, it is important to consider possible cross-cultural differences in attitudes toward pre-symptomatic screening in order to tailor healthcare services to the needs of each country. Objective: This study aims to investigate the attitudes of family members and non-family members of people with dementia toward pre-symptomatic screening and explore possible differences in attitudes across five European countries (Belgium, Germany, Greece, Spain, Turkey) using translated versions of the "Perceptions regarding pRE-symptomatic Alzheimer's Disease Screening" questionnaire (PRE-ADS). Methods: The multicultural sample (N = 650) was recruited from samples that were previously used in validation studies of the translated PRE-ADS versions. The subscale "Acceptability of Screening", consisting of five PRE-ADS items to specifically explore willingness to undergo screening, was created. Ιnternal consistency was measured, and structural validity was determined using Confirmatory Factor Analysis (CFA). Group comparisons were performed to investigate differences in attitudes toward pre-symptomatic AD screening regarding family history and country of origin using the PRE-ADS and the "Acceptability of Screening" mean scores. Results: Construct validity was acceptable for the PRE-ADS. Both the PRE-ADS (α = 0.76) and its subscale "Acceptability of Screening" (α = 0.90) had good internal consistency. Overall, 56.9% of the total sample expressed a positive intention toward pre-symptomatic AD screening. T-tests showed significantly higher mean scores of participants with an affected family member. An international comparison revealed differences in the "Acceptability of Screening" mean score across the five European countries. No cross-cultural differences were found for the PRE-ADS mean score after adjusting for confounding variables. Conclusion: The PRE-ADS and its subscale are reliable tools for assessing pre-symptomatic AD screening attitudes. Variations in the acceptability of screening seem to be linked to family history and cultural influences. Further research with larger samples is needed to explore underlying relationships.

Design of an electrochemical aptasensor in the presence of an array of gold nanostructure and a GO-MWCNTs nanocomposite: application in diagnosis of Alzheimer's disease

Alzheimer's disease (AD) is considered one of the main progressive chronic diseases in elderly individuals. Early diagnosis using related biomarkers, specifically beta-amyloid peptide (Aβ), allows finding expected treatment routes. Here, we developed an electrochemical aptasensing platform for AD by employing a glassy carbon electrode (GCE) modified with a layer of jagged gold (JG) nanostructure (diameter: 60-185 nm) and graphene oxide-carboxylic acid functionalized multiwalled carbon nanotubes (GO-c-MWCNTs) nanocomposite. These surface modifications acted as the signal amplifier and provided an optimum nano-interface substrate for immobilizing aptamer strands. The measurements of Aβ were performed via differential pulse voltammetry (DPV), and the aptasensor detected the analyte in a linear range from 0.1 pg mL-1 to 1 ng mL-1, with an estimated limit of detection (LOD) of about 0.088 pg mL-1 (S/N = 3). The aptasensor showed sufficient stability (11 days), reversibility (three times), and reproducibility (five times re-fabrication with relative standard deviation (RSD): 1.27). The potential interfering agents showed negligible impact on the sensing performance. Finally, the application of the aptasensor was evaluated in the presence of 10 serum samples, and the recovery values were from 93 to 110.1%.

Emerging nanotechnology for Alzheimer's disease: From detection to treatment

Alzheimer's disease (AD), one of the most common chronic neurodegenerative diseases, is characterized by memory impairment, synaptic dysfunction, and character mutations. The pathological features of AD are Aβ accumulation, tau protein enrichment, oxidative stress, and immune inflammation. Since the pathogenesis of AD is complicated and ambiguous, it is still challenging to achieve early detection and timely treatment of AD. Due to the unique physical, electrical, magnetic, and optical properties of nanoparticles (NPs), nanotechnology has shown great potential for detecting and treating AD. This review provides an overview of the latest developments in AD detection via nanotechnology based on NPs with electrochemical sensing, optical sensing, and imaging techniques. Meanwhile, we highlight the important advances in nanotechnology-based AD treatment through targeting disease biomarkers, stem-cell therapy and immunotherapy. Furthermore, we summarize the current challenges and present a promising prospect for nanotechnology-based AD diagnosis and intervention.

Cerebrospinal Fluid Biomarkers for Diagnosis and the Prognostication of Acute Ischemic Stroke: A Systematic Review

Despite the high incidence and burden of stroke, biological biomarkers are not used routinely in clinical practice to diagnose, determine progression, or prognosticate outcomes of acute ischemic stroke (AIS). Because of its direct interface with neural tissue, cerebrospinal fluid (CSF) is a potentially valuable source for biomarker development. This systematic review was conducted using three databases. All trials investigating clinical and preclinical models for CSF biomarkers for AIS diagnosis, prognostication, and severity grading were included, yielding 22 human trials and five animal studies for analysis. In total, 21 biomarkers and other multiomic proteomic markers were identified. S100B, inflammatory markers (including tumor necrosis factor-alpha and interleukin 6), and free fatty acids were the most frequently studied biomarkers. The review showed that CSF is an effective medium for biomarker acquisition for AIS. Although CSF is not routinely clinically obtained, a potential benefit of CSF studies is identifying valuable biomarkers from the pathophysiologic microenvironment that ultimately inform optimization of targeted low-abundance assays from peripheral biofluid samples (e.g., plasma). Several important catabolic and anabolic markers can serve as effective measures of diagnosis, etiology identification, prognostication, and severity grading. Trials with large cohorts studying the efficacy of biomarkers in altering clinical management are still needed.

Fluorescent Sensing Platforms for Detecting and Imaging the Biomarkers of Alzheimer's Disease

Alzheimer's disease (AD) is an irreversible neurodegenerative disease with clinical symptoms of memory loss and cognitive impairment. Currently, no effective drug or therapeutic method is available for curing this disease. The major strategy used is to identify and block AD at its initial stage. Thus, early diagnosis is very important for intervention of the disease and assessment of drug efficacy. The gold standards of clinical diagnosis include the measurement of AD biomarkers in cerebrospinal fluid and positron emission tomography imaging of the brain for amyloid-β (Aβ) deposits. However, these methods are difficult to apply to the general screening of a large aging population because of their high cost, radioactivity and inaccessibility. Comparatively, blood sample detection is less invasive and more accessible for the diagnosis of AD. Hence, a variety of assays based on fluorescence analysis, surface-enhanced Raman scattering, electrochemistry, etc., were developed for the detection of AD biomarkers in blood. These methods play significant roles in recognizing asymptomatic AD and predicting the course of the disease. In a clinical setting, the combination of blood biomarker detection with brain imaging may enhance the accuracy of early diagnosis. Fluorescence-sensing techniques can be used not only to detect the levels of biomarkers in blood but also to image biomarkers in the brain in real time due to their low toxicity, high sensitivity and good biocompatibility. In this review, we summarize the newly developed fluorescent sensing platforms and their application in detecting and imaging biomarkers of AD, such as Aβ and tau in the last five years, and discuss their prospects for clinical applications.

Evolution of Detecting Early Onset of Alzheimer's Disease: From Neuroimaging to Optical Immunoassays

Alzheimer's disease (AD) is a pathological disorder defined by the symptoms of memory loss and deterioration of cognitive abilities over time. Although the etiology is complex, it is mainly associated with the accumulation of toxic amyloid-β peptide (Aβ) aggregates and tau protein-induced neurofibrillary tangles (NFTs). Even now, creating non-invasive, sensitive, specific, and cost-effective diagnostic methods for AD remains challenging. Over the past few decades, polymers, and nanomaterials (e.g., nanodiamonds, nanogold, quantum dots) have become attractive and practical tools in nanomedicine for diagnosis and treatment. This review focuses on current developments in sensing methods such as enzyme-linked immunosorbent assay (ELISA) and surface-enhanced Raman scattering (SERS) to boost the sensitivity in detecting related biomarkers for AD. In addition, optical analysis platforms such as ELISA and SERS have found increasing popularity among researchers due to their excellent sensitivity and specificity, which may go as low as the femtomolar range. While ELISA offers easy technological usage and high throughput, SERS has the advantages of improved mobility, simple electrical equipment integration, and lower cost. Both portable optical sensing techniques are highly superior in terms of sensitivity, specificity, human application, and practicality, enabling the early identification of AD biomarkers.

Revolutionizing the Early Detection of Alzheimer's Disease through Non-Invasive Biomarkers: The Role of Artificial Intelligence and Deep Learning

Alzheimer's disease (AD) is now classified as a silent pandemic due to concerning current statistics and future predictions. Despite this, no effective treatment or accurate diagnosis currently exists. The negative impacts of invasive techniques and the failure of clinical trials have prompted a shift in research towards non-invasive treatments. In light of this, there is a growing need for early detection of AD through non-invasive approaches. The abundance of data generated by non-invasive techniques such as blood component monitoring, imaging, wearable sensors, and bio-sensors not only offers a platform for more accurate and reliable bio-marker developments but also significantly reduces patient pain, psychological impact, risk of complications, and cost. Nevertheless, there are challenges concerning the computational analysis of the large quantities of data generated, which can provide crucial information for the early diagnosis of AD. Hence, the integration of artificial intelligence and deep learning is critical to addressing these challenges. This work attempts to examine some of the facts and the current situation of these approaches to AD diagnosis by leveraging the potential of these tools and utilizing the vast amount of non-invasive data in order to revolutionize the early detection of AD according to the principles of a new non-invasive medicine era.

Modern Approaches to the Diagnosis of Cognitive Impairment and Alzheimer's Disease: A Narrative Literature Review

BACKGROUND

The aging of the worlds population leads to an increase in the prevalence of age-related diseases, including cognitive impairment. At the stage of dementia, therapeutic interventions become usually ineffective. Therefore, researchers and clinical practitioners today are looking for methods that allow for early diagnosis of cognitive impairment, including techniques that are based on the use of biological markers.

AIM

The aim of this literature review is to delve into scientific papers that are centered on modern laboratory tests for Alzheimers disease, including tests for biological markers at the early stages of cognitive impairment.

METHODS

The authors have carried out a descriptive review of scientific papers published from 2015 to 2023. Studies that are included in the PubMed and Web of Science electronic databases were analyzed. A descriptive analysis was used to summarized the gleaned information.

RESULTS

Blood and cerebrospinal fluid (CSF) biomarkers, as well as the advantages and disadvantages of their use, are reviewed. The most promising neurotrophic, neuroinflammatory, and genetic markers, including polygenic risk models, are also discussed.

CONCLUSION

The use of biomarkers in clinical practice will contribute to the early diagnosis of cognitive impairment associated with Alzheimers disease. Genetic screening tests can improve the detection threshold of preclinical abnormalities in the absence of obvious symptoms of cognitive decline. The active use of biomarkers in clinical practice, in combination with genetic screening for the early diagnosis of cognitive impairment in Alzheimers disease, can improve the timeliness and effectiveness of medical interventions.

The dynamics of plasma biomarkers across the Alzheimer's continuum

BACKGROUND

Failures in drug trials strengthen the necessity to further determine the neuropathological events during the development of Alzheimer's disease (AD). We sought to investigate the dynamic changes and performance of plasma biomarkers across the entire Alzheimer's continuum in the Chinese population.

METHODS

Plasma amyloid-β (Αβ)42, Aβ40, Aβ42/Aβ40, phosphorylated tau (p-tau)181, neurofilament light (NfL), and glial fibrillary acidic protein (GFAP) were measured utilizing the ultrasensitive single-molecule array technology across the AD continuum (n=206), wherein Aβ status was defined by the values of cerebrospinal fluid (CSF) Aβ42 or Aβ positron emission tomography (PET). Their trajectories were compared with those of putative CSF biomarkers.

RESULTS

Plasma GFAP and p-tau181 increased only in Aβ-positive individuals throughout aging, whereas NfL increased with aging regardless of Aβ status. Among the plasma biomarkers studied, GFAP was the one that changed first. It had a prominent elevation early in the cognitively unimpaired (CU) A+T- phase (CU A+T- phase: 97.10±41.29 pg/ml; CU A-T- phase: 49.18±14.39 pg/ml; p<0.001). From preclinical to symptomatic stages of AD, plasma GFAP started to rise sharply as soon as CSF Aβ became abnormal and continued to increase until reaching its highest level during the AD dementia phase. The greatest slope of change was seen in plasma GFAP. This is followed by CSF p-tau181 and total-tau, and, to a lesser extent, then plasma p-tau181. In contrast, the changes in plasma NfL, Aβ42/Aβ40, Aβ42, and Aβ40 were less pronounced. Of note, these plasma biomarkers exhibited smaller dynamic ranges than their CSF counterparts, except for GFAP which was the opposite. Plasma GFAP and p-tau181 were tightly associated with AD pathologies and amyloid tracer uptake in widespread brain areas. Plasma GFAP could accurately identify CSF Aβ42 (area under the curve (AUC)=0.911) and Aβ PET (AUC=0.971) positivity. Plasma p-tau181 also performed well in discriminating Aβ PET status (AUC=0.916), whereas the discriminative accuracy was relatively low for other plasma biomarkers.

CONCLUSIONS

This study is the first to delineate the trajectories of plasma biomarkers throughout the Alzheimer's continuum in the Chinese population, providing important implications for future trials targeting plasma GFAP to facilitate AD prevention and treatment.

HERV-W ENV Induces Innate Immune Activation and Neuronal Apoptosis via linc01930/cGAS Axis in Recent-Onset Schizophrenia

Schizophrenia is a severe neuropsychiatric disorder affecting about 1% of individuals worldwide. Increased innate immune activation and neuronal apoptosis are common findings in schizophrenia. Interferon beta (IFN-β), an essential cytokine in promoting and regulating innate immune responses, causes neuronal apoptosis in vitro. However, the precise pathogenesis of schizophrenia is unknown. Recent studies indicate that a domesticated endogenous retroviral envelope glycoprotein of the W family (HERV-W ENV, also called ERVWE1 or syncytin 1), derived from the endogenous retrovirus group W member 1 (ERVWE1) locus on chromosome 7q21.2, has a high level in schizophrenia. Here, we found an increased serum IFN-β level in schizophrenia and showed a positive correlation with HERV-W ENV. In addition, serum long intergenic non-protein coding RNA 1930 (linc01930), decreased in schizophrenia, was negatively correlated with HERV-W ENV and IFN-β. In vitro experiments showed that linc01930, mainly in the nucleus and with noncoding functions, was repressed by HERV-W ENV through promoter activity suppression. Further studies indicated that HERV-W ENV increased IFN-β expression and neuronal apoptosis by restraining the expression of linc01930. Furthermore, HERV-W ENV enhanced cyclic GMP-AMP synthase (cGAS) and stimulator of interferon genes protein (STING) expression and interferon regulatory factor 3 (IRF3) phosphorylation in neuronal cells. Notably, cGAS interacted with HERV-W ENV and triggered IFN-β expression and neuronal apoptosis caused by HERV-W ENV. Moreover, Linc01930 participated in the increased neuronal apoptosis and expression level of cGAS and IFN-β induced by HERV-W ENV. To summarize, our results suggested that linc01930 and IFN-β might be novel potential blood-based biomarkers in schizophrenia. The totality of these results also showed that HERV-W ENV facilitated antiviral innate immune response, resulting in neuronal apoptosis through the linc01930/cGAS/STING pathway in schizophrenia. Due to its monoclonal antibody GNbAC1 application in clinical trials, we considered HERV-W ENV might be a reliable therapeutic choice for schizophrenia.

Toward Reagent-Free Discrimination of Alzheimer's Disease Using Blood Plasma Spectral Digital Biomarkers and Machine Learning

BACKGROUND

Alzheimer's disease (AD) is the most prevalent neurodegenerative disease. The detection of early-stage AD is particularly desirable because it would allow early intervention. However, a minimally invasive, low-cost, and accurate discrimination or diagnostic method for AD is especially difficult in the earliest stage of AD.

OBJECTIVE

The aim of this research is to discover blood plasma spectral digital biomarkers of AD, develop a novel intelligent method for the discrimination of AD and accelerate the translation of Fourier transform infrared (FTIR) spectral-based disease discrimination methods from the laboratory to clinical practice.

METHODS

Since vibration spectroscopy can provide the structure and chemical composition information of biological samples at the molecular level, we investigated the potential of FTIR spectral biomarkers of blood plasma to differentiate between AD patients and healthy controls. Combined with machine learning technology, we designed a hierarchical discrimination system that provides reagent-free and accurate AD discrimination based on blood plasma spectral digital biomarkers of AD.

RESULTS

Accurate segregation between AD patients and healthy controls was achieved with 89.3% sensitivity and 85.7% specificity for early-stage AD patients, 92.8% sensitivity and 87.5% specificity for middle-stage AD patients, and 100% sensitivity and 100% specificity for late-stage AD patients.

CONCLUSIONS

Our results show that blood plasma spectral digital biomarkers hold great promise as discrimination markers of AD, indicating the potential for the development of an inexpensive, reagent-free, and less laborious clinical test. As a result, our research outcome will accelerate the clinical application of spectral digital biomarkers and machine learning.

An adjustable amyloid-β oligomers aptasensor based on the synergistic effect of self-enhanced metal-organic gel luminophore and triple-helix DNA system

Amyloid-β oligomers (AβOs) was the core-biomarker of Alzheimer's disease (AD), and the detection of AβOs is very important for the early diagnosis of AD. However, existing tests for AβOs are majorly suffering from complex process and poor sensitivity. Thus, an adjustable AβOs electrochemiluminescence (ECL) aptasensor based on the synergistic effect of self-enhanced metal-organic gel (AgCNS) and triple-helix DNA system (THS) was successfully constructed. AgCNS was prepared by an extremely simple one-pot method and was an innovative luminophore with excellent ECL performance. The AgCNS-labeled complementary sequence (AgCNS@CP) was interlaced with the unlabeled aptamer (Apt) carrying two short-arms fixed on the gold electrode (GE) to form the THS. Along with the specific-binding of AβOs and Apt, the THS was disrupted and adjusted flexibly between "on" and "off", resulting in significant changes in the ECL signals. Thus, ECL detection of AβOs was sensitively achieved with a detection limit as low as 0.23 fM and the different forms of Aβ can be specifically distinguished. The aptasensor also exhibited satisfactory selectivity, stability and reproducibility. Moreover, when proposed method and ELISA-kit were simultaneously applied to artificial cerebrospinal fluid (A-CSF) samples, the obtained results were completely consistent, reflecting the potential clinical application value of this work.

Neurospecific Molecules Measured in Periphery in Humans: How Do They Correlate with the Brain Levels? A Systematic Review

Human brain state is usually estimated by brain-specific substances in peripheral tissues, but, for most analytes, a concordance between their content in the brain and periphery is unclear. In this systematic review, we summarized the investigated correlations in humans. PubMed was searched up to June 2022. We included studies measuring the same endogenous neurospecific analytes in the central nervous system and periphery in the same subjects. Not eligible were studies of cerebrospinal fluid, with significant blood–brain barrier disruption, of molecules with well-established blood-periphery concordance or measured in brain tumors. Seventeen studies were eligible. Four studies did not report on correlation and four revealed no significant correlation. Four molecules were examined twice. For BDNF, there was no correlation in both studies. For phenylalanine, glutamine, and glutamate, results were contradictory. Strong correlations were found for free tryptophan (r = 0.97) and translocator protein (r = 0.90). Thus, only for three molecules was there some certainty. BDNF in plasma or serum does not reflect brain content, whereas free tryptophan (in plasma) and translocator protein (in blood cells) can serve as peripheral biomarkers. We expect a breakthrough in the field with advanced in vivo metabolomic analyses, neuroimaging techniques, and blood assays for exosomes of brain origin.

Portable Vertical Graphene@Au-Based Electrochemical Aptasensing Platform for Point-of-Care Testing of Tau Protein in the Blood

Alzheimer’s disease (AD) is a long-term neurodegenerative disease that poses a serious threat to human life and health. It is very important to develop a portable quantitative device for AD diagnosis and personal healthcare. Herein, we develop a portable electrochemical sensing platform for the point-of-care detection of AD biomarkers in the blood. Such a portable platform integrates nanoAu-modified vertical graphene (VG@Au) into a working electrode, which can significantly improve sensitivity and reduce detection limit due to the large specific surface, excellent electrical conductivity, high stability, and good biocompatibility. The tau protein, as an important factor in the course of AD, is selected as a key AD biomarker. The results show that the linear range of this sensing platform is 0.1 pg/mL to 1 ng/mL, with a detection limit of 0.034 pg/mL (S/N = 3), indicating that this portable sensing platform meets the demand for the detection of the tau protein in the blood. This work offers great potential for AD diagnosis and personal healthcare.