Biofluid Biomarkers of Alzheimer’s Disease: Progress, Problems, and Perspectives

Navigating the Landscape of Plasma Biomarkers in Alzheimer's Disease: Focus on Past, Present, and Future Clinical Applications

As the prevalence of Alzheimer's disease (AD) and its impact on healthcare systems increase, developing tools for accurate diagnosis and monitoring of disease progression is a priority. Recent technological advancements have allowed for the development of blood-based biomarkers (BBMs) to aid in the diagnosis of AD, but many questions remain regarding the clinical implementation of these BBMs. This review outlines the historical timeline of AD BBM development. It highlights key breakthroughs that have transformed the perspective of AD BBMs from theoretically ideal but unattainable markers, to clinically valid and reliable BBMs with potential for implementation in healthcare settings. Technological advancements like single-molecule detection and mass spectrometry methods have significantly improved assay sensitivity and accuracy. High-throughput, fully automated platforms have potential for clinical use. Despite these advancements, however, significant work is needed before AD BBMs can be implemented in widespread clinical practice. Cutpoints must be established, the influence of chronic conditions and medications on BBM levels must be better understood, and guidelines must be created for healthcare providers related to interpreting and communicating information obtained from AD BBMs. Additionally, the development of BBMs for synaptic dysfunction, inflammation, and cerebrovascular disease may provide better precision medicine approaches to treating AD and related dementia. Future research and collaboration between scientists and physicians are essential to addressing these challenges and further advancing AD BBMs, with the goal of integration in clinical practice.

Plasma proteomics for risk prediction of Alzheimer's disease in the general population

We aimed to develop and validate a protein risk score for predicting Alzheimer's disease (AD) and compare its performance with a validated clinical risk model (Cognitive Health and Dementia Risk Index for AD [CogDrisk-AD]) and apolipoprotein E (APOE) genotypes. The development cohort, consisting of 35,547 participants from England in the UK Biobank, was randomly divided into a 7:3 training-testing ratio. The validation cohort included 4667 participants from Scotland and Wales in the UK Biobank. In the training set, an AD protein risk score was constructed using 31 proteins out of 2911 proteins. In the testing set, the AD protein risk score had a C-index of 0.867 (95% CI, 0.828, 0.906) for AD prediction, followed by CogDrisk-AD risk factors (C-index, 0.856; 95% CI, 0.823, 0.889), and APOE genotypes (C-index, 0.705; 95% CI, 0.660, 0.750). Adding the AD protein risk score to CogDrisk-AD risk factors (C-index increase, 0.050; 95% CI, 0.008, 0.093) significantly improved the predictive performance for AD. However, adding CogDrisk-AD risk factors (C-index increase, 0.040; 95% CI, -0.007, 0.086) or APOE genotypes (C-index increase, 0.000; 95% CI, -0.054, 0.055) to the AD protein risk score did not significantly improve the predictive performance for AD. The top 10 proteins with the highest coefficients in the AD protein risk score contributed most of the predictive power for AD risk. These results were verified in the external validation cohort. EGFR, GFAP, and CHGA were identified as key proteins within the protein network. Our result suggests that the AD protein risk score demonstrated a good predictive performance for AD risk.

Biofluid biomarkers for Alzheimer's disease: past, present, and future

Alzheimer's disease (AD) is a gradually progressive neurodegenerative disease with tremendous social and economic burden. Therefore, early and accurate diagnosis is imperative for effective treatment or prevention of the disease. Cerebrospinal fluid and blood biomarkers emerge as favorable diagnostic tools due to their relative accessibility and potential for widespread clinical use. This review focuses on the AT(N) biomarker system, which includes biomarkers reflecting AD core pathologies, amyloid deposition, and pathological tau, as well as neurodegeneration. Novel biomarkers associated with inflammation/immunity, synaptic dysfunction, vascular pathology, and α-synucleinopathy, which might contribute to either the pathogenesis or the clinical progression of AD, have also been discussed. Other emerging candidates including non-coding RNAs, metabolites, and extracellular vesicle-based markers have also enriched the biofluid biomarker landscape for AD. Moreover, the review discusses the current challenges of biofluid biomarkers in AD diagnosis and offers insights into the prospective future development.

Association between blood-based protein biomarkers and brain MRI in the Alzheimer's disease continuum: a systematic review

Blood-based biomarkers (BBM) are becoming easily detectable tools to reveal pathological changes in Alzheimer's disease (AD). A comprehensive and up-to-date overview of the association between BBM and brain MRI parameters is not available. This systematic review aimed to summarize the literature on the associations between the main BBM and MRI markers across the clinical AD continuum. A systematic literature search was carried out on PubMed and Web of Science and a total of 33 articles were included. Hippocampal volume was positively correlated with Aβ42 and Aβ42/Aβ40 and negatively with Aβ40 plasma levels. P-tau181 and p-tau217 concentrations were negatively correlated with temporal grey matter volume and cortical thickness. NfL levels were negatively correlated with white matter microstructural integrity, whereas GFAP levels were positively correlated with myo-inositol values in the posterior cingulate cortex/precuneus. These findings highlight consistent associations between various BBM and brain MRI markers even in the pre-clinical and prodromal stages of AD. This suggests a possible advantage in combining multiple AD-related markers to improve accuracy of early diagnosis, prognosis, progression monitoring and treatment response.

Value proposition of retinal imaging in Alzheimer's disease screening: A review of eight evolving trends

Alzheimer's disease (AD) is the leading cause of dementia worldwide. Current diagnostic modalities of AD generally focus on detecting the presence of amyloid β and tau protein in the brain (for example, positron emission tomography [PET] and cerebrospinal fluid testing), but these are limited by their high cost, invasiveness, and lack of expertise. Retinal imaging exhibits potential in AD screening and risk stratification, as the retina provides a platform for the optical visualization of the central nervous system in vivo, with vascular and neuronal changes that mirror brain pathology. Given the paradigm shift brought by advances in artificial intelligence and the emergence of disease-modifying therapies, this article aims to summarize and review the current literature to highlight 8 trends in an evolving landscape regarding the role and potential value of retinal imaging in AD screening.

EBF1 is a potential biomarker for predicting progression from mild cognitive impairment to Alzheimer's disease: an in silico study

Introduction

The prediction of progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD) is an important clinical challenge. This study aimed to identify the independent risk factors and develop a nomogram model that can predict progression from MCI to AD.

Methods

Data of 141 patients with MCI were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. We set a follow-up time of 72 months and defined patients as stable MCI (sMCI) or progressive MCI (pMCI) according to whether or not the progression of MCI to AD occurred. We identified and screened independent risk factors by utilizing weighted gene co-expression network analysis (WGCNA), where we obtained 14,893 genes after data preprocessing and selected the soft threshold β = 7 at an R 2 of 0.85 to achieve a scale-free network. A total of 14 modules were discovered, with the midnightblue module having a strong association with the prognosis of MCI. Using machine learning strategies, which included the least absolute selection and shrinkage operator and support vector machine-recursive feature elimination; and the Cox proportional-hazards model, which included univariate and multivariable analyses, we identified and screened independent risk factors. Subsequently, we developed a nomogram model for predicting the progression from MCI to AD. The performance of our nomogram was evaluated by the C-index, calibration curve, and decision curve analysis (DCA). Bioinformatics analysis and immune infiltration analysis were conducted to clarify the function of early B cell factor 1 (EBF1).

Results

First, the results showed that 40 differentially expressed genes (DEGs) related to the prognosis of MCI were generated by weighted gene co-expression network analysis. Second, five hub variables were obtained through the abovementioned machine learning strategies. Third, a low Montreal Cognitive Assessment (MoCA) score [hazard ratio (HR): 4.258, 95% confidence interval (CI): 1.994-9.091] and low EBF1 expression (hazard ratio: 3.454, 95% confidence interval: 1.813-6.579) were identified as the independent risk factors through the Cox proportional-hazards regression analysis. Finally, we developed a nomogram model including the MoCA score, EBF1, and potential confounders (age and gender). By evaluating our nomogram model and validating it in both internal and external validation sets, we demonstrated that our nomogram model exhibits excellent predictive performance. Through the Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes Genomes (KEGG) functional enrichment analysis, and immune infiltration analysis, we found that the role of EBF1 in MCI was closely related to B cells.

Conclusion

EBF1, as a B cell-specific transcription factor, may be a key target for predicting progression from MCI to AD. Our nomogram model was able to provide personalized risk factors for the progression from MCI to AD after evaluation and validation.

Updates in Alzheimer's disease: from basic research to diagnosis and therapies

Alzheimer's disease (AD) is the most common neurodegenerative disorder, characterized pathologically by extracellular deposition of β-amyloid (Aβ) into senile plaques and intracellular accumulation of hyperphosphorylated tau (pTau) as neurofibrillary tangles. Clinically, AD patients show memory deterioration with varying cognitive dysfunctions. The exact molecular mechanisms underlying AD are still not fully understood, and there are no efficient drugs to stop or reverse the disease progression. In this review, we first provide an update on how the risk factors, including APOE variants, infections and inflammation, contribute to AD; how Aβ and tau become abnormally accumulated and how this accumulation plays a role in AD neurodegeneration. Then we summarize the commonly used experimental models, diagnostic and prediction strategies, and advances in periphery biomarkers from high-risk populations for AD. Finally, we introduce current status of development of disease-modifying drugs, including the newly officially approved Aβ vaccines, as well as novel and promising strategies to target the abnormal pTau. Together, this paper was aimed to update AD research progress from fundamental mechanisms to the clinical diagnosis and therapies.

Proteomics profiling of extracellular vesicle for identification of potential biomarkers in Alzheimer's disease: A comprehensive review

The intricate origins and diverse symptoms of Alzheimer's disease (AD) pose significant challenges for both diagnosis and treatment. Exosomes and microvesicles, which carry disease-specific cargo from a variety of central nervous system cell types, have emerged as promising reservoirs of biomarkers for AD. Research on the screening of possible biomarkers in Alzheimer's disease using proteomic profiling of EVs is systematically reviewed in this comprehensive review. We highlight key methodologies employed in EV isolation, characterization, and proteomic analysis, elucidating their advantages and limitations. Furthermore, we summarize the evolving landscape of EV-associated biomarkers implicated in AD pathogenesis, including proteins involved in amyloid-beta metabolism, tau phosphorylation, neuroinflammation, synaptic dysfunction, and neuronal injury. The literature review highlights the necessity for robust validation strategies and standardized protocols to effectively transition EV-based biomarkers into clinical use. In the concluding section, this review delves into potential future avenues and technological advancements pivotal in crafting EV-derived biomarkers applicable to AD diagnostics and prognostics. This review contributes to our comprehension of AD pathology and the advancement of precision medicine in neurodegenerative diseases, hinting at a promising era in AD precision medicine.

Novel diagnostic and prognostic approach for rapidly progressive dementias: Indicators based on amyloid/tau/neurodegeneration (ATN) framework

AIMS

Apply established cerebrospinal fluid (CSF) and serum biomarkers and novel combined indicators based on the amyloid/tau/neurodegeneration (ATN) framework to improve diagnostic and prognostic power in patients with rapidly progressive dementias (RPDs).

METHODS

CSF and serum biomarkers of Alzheimer's disease (AD) common neuropathology including Aβ42, Aβ40, p-Tau, and t-Tau were measured in cognitively normal (CN) controls (n = 33) and three RPD groups with rapidly progressive AD (rpAD, n = 23), autoimmune encephalitis (AE, n = 25), and Creutzfeldt-Jakob disease (CJD, n = 28). Logistic regression and multiple linear regression were used for producing combined indicators and prognostic assessment, respectively, including A&T, A&N, T&N, A&T&N, etc. RESULTS: Combined diagnostic indicator with A&T&N had the potential for differentiating AE from other types of RPDs, identifying 62.51% and 75% of AE subjects based on CSF and serum samples, respectively, compared to 39.13% and 37.5% when using autoantibodies. CSF t-Tau was associated with survival in the CJD group (adjusted R-Square = 0.16, p = 0.02), and its prognosis value improved when using combined predictors based on the ATN framework (adjusted R-Square = 0.273, p = 0.014).

CONCLUSION

Combined indicators based on the ATN framework provide a novel perspective for establishing biomarkers for early recognition of RPDs due to treatment-responsive causes.

Salivary biomarkers: The early diagnosis of Alzheimer's disease

The precise identification of Alzheimer's disease and other prevalent neurodegenerative diseases remains a difficult issue that requires the development of early detection of the disease and inexpensive biomarkers that can replace the present cerebrospinal fluid and imaging biomarkers. Blood biomarkers, such as amyloid and neurofilament light, have been emphasized as an important and practical tool in a testing or examination procedure thanks to advancements in ultra-sensitive detection techniques. Although saliva is not currently being researched for neurodegenerative diseases, it is an important source of biomarkers that can be used for the identification of diseases and has some advantages over other biofluids. While this may be true for most people, getting saliva from elderly people presents some significant challenges. In this overview, we will first discuss how saliva is created and how aging-related illnesses may affect the amount and kind of saliva produced. The findings support the use of salivary amyloid protein, tau species, and novel biomarkers in the diagnosis of Alzheimer's disease.

A critical appraisal of blood-based biomarkers for Alzheimer's disease

Biomarkers that predict the clinical onset of Alzheimer's disease (AD) enable the identification of individuals in the early, preclinical stages of the disease. Detecting AD at this point may allow for more effective therapeutic interventions and optimized enrollment for clinical trials of novel drugs. The current biological diagnosis of AD is based on the AT(N) classification system with the measurement of brain deposition of amyloid-β (Aβ) ("A"), tau pathology ("T"), and neurodegeneration ("N"). Diagnostic cut-offs for Aβ1-42, the Aβ1-42/Aβ1-40 ratio, tau and hyperphosphorylated-tau concentrations in cerebrospinal fluid have been defined and may support AD clinical diagnosis. Blood-based biomarkers of the AT(N) categories have been described in the AD continuum. Cross-sectional and longitudinal studies have shown that the combination of blood biomarkers tracking neuroaxonal injury (neurofilament light chain) and neuroinflammatory pathways (glial fibrillary acidic protein) enhance sensitivity and specificity of AD clinical diagnosis and improve the prediction of AD onset. However, no international accepted cut-offs have been identified for these blood biomarkers. A kit for blood Aβ1-42/Aβ1-40 is commercially available in the U.S.; however, it does not provide a diagnosis, but simply estimates the risk of developing AD. Although blood-based AD biomarkers have a great potential in the diagnostic work-up of AD, they are not ready for the routine clinical use.

The potential roles of salivary biomarkers in neurodegenerative diseases

Current research efforts on neurodegenerative diseases are focused on identifying novel and reliable biomarkers for early diagnosis and insight into disease progression. Salivary analysis is gaining increasing interest as a promising source of biomarkers and matrices for measuring neurodegenerative diseases. Saliva collection offers multiple advantages over the currently detected biofluids as it is easily accessible, non-invasive, and repeatable, allowing early diagnosis and timely treatment of the diseases. Here, we review the existing findings on salivary biomarkers and address the potential value in diagnosing neurodegenerative diseases, such as Alzheimer's disease, Parkinson's disease, Huntington's disease and Amyotrophic lateral sclerosis. Based on the available research, β-amyloid, tau protein, α-synuclein, DJ-1, Huntington protein in saliva profiles display reliability and validity as the biomarkers of neurodegenerative diseases.

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.

Sleep Biomarkers for Predicting Cognitive Decline and Alzheimer's Disease: A Systematic Review of Longitudinal Studies

BACKGROUND

Sleep disturbances are considered a hallmark of dementia, and strong evidence supports the association between alterations in sleep parameters and cognitive decline in patients with mild cognitive impairment and Alzheimer's disease (AD).

OBJECTIVE

This systematic review aims to summarize the existing evidence on the longitudinal association between sleep parameters and cognitive decline, with the goal of identifying potential sleep biomarkers of AD-related neurodegeneration.

METHODS

Literature search was conducted in PubMed, Web of Science, and Scopus databases from inception to 28 March 2023. Longitudinal studies investigating the association between baseline objectively-measured sleep parameters and cognitive decline were assessed for eligibility.

RESULTS

Seventeen studies were included in the qualitative synthesis. Sleep fragmentation, reduced sleep efficiency, reduced REM sleep, increased light sleep, and sleep-disordered breathing were identified as predictors of cognitive decline. Sleep duration exhibited a U-shaped relation with subsequent neurodegeneration. Additionally, several sleep microstructural parameters were associated with cognitive decline, although inconsistencies were observed across studies.

CONCLUSIONS

These findings suggest that sleep alterations hold promise as early biomarker of cognitive decline, but the current evidence is limited due to substantial methodological heterogeneity among studies. Further research is necessary to identify the most reliable sleep parameters for predicting cognitive impairment and AD, and to investigate interventions targeting sleep that can assist clinicians in the early recognition and treatment of cognitive decline. Standardized procedures for longitudinal studies evaluating sleep and cognition should be developed and the use of continuous sleep monitoring techniques, such as actigraphy or EEG headband, might be encouraged.

Effects of Hepatorenal Function on Urinary Alzheimer-Associated Neuronal Thread Protein: A Laboratory-Based Cross-Sectional Study Among the Older Chinese Population

Background

Urinary Alzheimer-associated neuronal thread protein (AD7c-NTP) is a biomarker for the early diagnosis of Alzheimer's disease (AD). It remains unclear whether hepatorenal function affects the urinary AD7c-NTP level.

Objective

To evaluate the effects of hepatorenal function on urinary AD7c-NTP level.

Methods

We enrolled 453 participants aged 60-100 years. An automated chemistry analyzer was used to determine the indicators of serum hepatorenal function. Enzyme-linked immunosorbent assay was used to measure the urinary AD7c-NTP level.

Results

Spearman's correlation analysis showed a negative correlation between urinary AD7c-NTP levels and indicators of hepatorenal function, including albumin (r = -0.181, p < 0.001), albumin/globulin ratio (r = -0.224, p < 0.001), cholinesterase (r = -0.094, p = 0.046), total carbon dioxide (r = -0.102, p = 0.030), and glomerular filtration rate (r = -0.260, p < 0.001), as well as a positive correlation with globulin (r = 0.141, p = 0.003), aspartate transaminase (r = 0.186, p < 0.001), blood urine nitrogen (r = 0.210, p < 0.001), creatinine (r = 0.202, p < 0.001), uric acid (r = 0.229, p < 0.001), and cystatin C (r = 0.265, p < 0.001). The least absolute shrinkage and selection operator (LASSO) regression analysis and multiple linear regression model analyses showed that the statistically significant hepatorenal indicators for predicting AD7c-NTP were A/G (p = 0.007), AST (p = 0.002), BUN (p = 0.019), and UA (p = 0.003).

Conclusions

The effects of hepatorenal indicators should be considered when using urinary AD7c-NTP levels in clinical settings.

Quantification of Neuroinflammatory Markers in Blood, Cerebrospinal Fluid, and Resected Brain Samples Obtained from Patients

Cytokines have the potential to be the ideal biomarkers to track the onset and progression of immune-mediated diseases, study the development of novel therapeutic strategies, and they can serve as outcome parameters due to their crucial role in the regulation of immune and inflammatory responses. It is vital to keep track of the entire cytokine spectrum due to the complex interactions, pleiotropic effects, and redundancy in the cytokine network. The multiplex immunoassay (MIA) is, therefore, the best method for achieving that goal. This chapter addresses the key methodological processes of this technique, such as sample preparation, antibody coupling to beads, and assay procedure.

Biomarkers associated with the pathogenesis of Alzheimer's disease

Alzheimer's disease (AD) is a progressive degenerative neurological illness with insidious onset. Due to the complexity of the pathogenesis of AD and different pathological changes, the clinical phenotypes of dementia are diverse, and these pathological changes also interact with each other. Therefore, it is of great significance to search for biomarkers that can diagnose these pathological changes to improve the ability to monitor the course of disease and treat the disease. The pathological mechanism hypothesis with high recognition of AD mainly includes the accumulation of β-amyloid (Aβ) around neurons and hyperphosphorylation of tau protein, which results in the development of neuronal fiber tangles (NFTs) and mitochondrial dysfunction. AD is an irreversible disease; currently, there is no clinical cure or delay in the disease process of drugs, and there is a lack of effective early clinical diagnosis methods. AD patients, often in the dementia stages and moderate cognitive impairment, will seek medical treatment. Biomarkers can help diagnose the presence or absence of specific diseases and their pathological processes, so early screening and diagnosis are crucial for the prevention and therapy of AD in clinical practice. β-amyloid deposition (A), tau pathology (T), and neurodegeneration/neuronal damage (N), also known as the AT (N) biomarkers system, are widely validated core humoral markers for the diagnosis of AD. In this paper, the pathogenesis of AD related to AT (N) and the current research status of cerebrospinal fluid (CSF) and blood related biomarkers were reviewed. At the same time, the limitations of humoral markers in the diagnosis of AD were also discussed, and the future development of humoral markers for AD was prospected. In addition, the contents related to mitochondrial dysfunction, prion virology and intestinal microbiome related to AD are also described, so as to understand the pathogenesis of AD in many aspects and dimensions, so as to evaluate the pathological changes related to AD more comprehensively and accurately.

Plasma ATN(I) classification and precision pharmacology in Alzheimer's disease

Evaluating potential therapies for Alzheimer's disease (AD) depends on use of biomarkers for appropriate subject selection and monitoring disease progression. Biomarkers that predict onset of clinical symptoms are particularly important for AD because they enable intervention before irreversible neurodegeneration occurs. The amyloid-β-tau-neurodegeneration (ATN) classification system is currently used as a biological staging model for AD and is based on three classes of biomarkers evaluating amyloid-β (Aβ), tau pathology and neurodegeneration or neuronal injury. Promising blood-based biomarkers for each of these categories have been identified (Aβ42/Aβ40 ratio, phosphorylated tau, neurofilament light chain), and this matrix is now being expanded toward an ATN(I) system, where "I" represents a neuroinflammatory biomarker. The plasma ATN(I) system, together with APOE genotyping, offers a basis for individualized evaluation and a move away from the classic "one size fits all" approach toward a biomarker-driven individualisation of therapy for patients with AD.

Associations of Blood and Cerebrospinal Fluid Aβ and tau Levels with Renal Function

Amyloid β (Aβ) and tau play pivotal roles in the pathogenesis of Alzheimer's disease (AD). Previous studies have shown that brain-derived Aβ and tau can be cleared through transport into the periphery, and the kidneys may be vital organs involved in the clearance of Aβ and tau. However, the effects of deficiency in the clearance of Aβ and tau by the kidneys on brain AD-type pathologies in humans remain largely unknown. In this study, we first recruited 41 patients with chronic kidney disease (CKD) and 40 age- and sex-matched controls with normal renal function to analyze the associations of the estimated glomerular filtration rate (eGFR) with plasma Aβ and tau levels. To analyze the associations of eGFR with cerebrospinal fluid (CSF) AD biomarkers, we recruited 42 cognitively normal CKD patients and 150 cognitively normal controls with CSF samples. Compared with controls with normal renal function, CKD patients had higher plasma levels of Aβ40, Aβ42 and total tau (T-tau), lower CSF levels of Aβ40 and Aβ42 and higher levels of CSF T-tau/Aβ42 and phosphorylated tau (P-tau)/Aβ42. Plasma Aβ40, Aβ42, and T-tau levels were negatively correlated with eGFR. In addition, eGFR was negatively correlated with CSF levels of T-tau, T-tau/Aβ42, and P-tau/Aβ42 but positively correlated with Mini-Mental State Examination (MMSE) scores. Thus, this study showed that the decline in renal function was correlated with abnormal AD biomarkers and cognitive decline, which provides human evidence that renal function may be involved in the pathogenesis of AD.

Translating blood biomarkers into clinical practice for Alzheimer's disease: Challenges and perspectives

Early and accurate diagnosis of Alzheimer's disease (AD) in clinical practice is urgent with advances in AD treatment. Blood biomarker assays are preferential diagnostic tools for widespread clinical use with the advantages of being less invasive, cost effective, and easily accessible, and they have shown good performance in research cohorts. However, in community-based populations with maximum heterogeneity, great challenges are still faced in diagnosing AD based on blood biomarkers in terms of accuracy and robustness. Here, we analyze these challenges, including the confounding impact of systemic and biological factors, small changes in blood biomarkers, and difficulty in detecting early changes. Furthermore, we provide perspectives on several potential strategies to overcome these challenges for blood biomarkers to bridge the gap from research to clinical practice.

Soluble TREM2 Concentrations in the Cerebrospinal Fluid Correlate with the Severity of Neurofibrillary Degeneration, Cognitive Impairment, and Inflammasome Activation in Alzheimer's Disease

BACKGROUND

Individuals with specific TREM2 gene variants that encode for a Triggering Receptor Expressed on Myeloid cells 2 have a higher prevalence of Alzheimer's disease (AD). By interacting with amyloid and apolipoproteins, the TREM2 receptor regulates the number of myeloid cells, phagocytosis, and the inflammatory response. Higher TREM2 expression has been suggested to protect against AD. However, it is extremely difficult to comprehend TREM2 signaling in the context of AD. Previous results are variable and show distinct effects on diverse pathological changes in AD, differences between soluble and membrane isoform signaling, and inconsistency between animal models and humans. In addition, the relationship between TREM2 and inflammasome activation pathways is not yet entirely understood.

OBJECTIVE

This study aimed to determine the relationship between soluble TREM2 (sTREM2) levels in cerebrospinal fluid (CSF) and plasma samples and other indicators of AD pathology.

METHODS

Using the Enzyme-Linked Immunosorbent Assay (ELISA), we analyzed 98 samples of AD plasma, 35 samples of plasma from individuals with mild cognitive impairment (MCI), and 11 samples of plasma from healthy controls (HC), as well as 155 samples of AD CSF, 90 samples of MCI CSF, and 50 samples of HC CSF.

RESULTS

CSF sTREM2 levels were significantly correlated with neurofibrillary degeneration, cognitive decline, and inflammasome activity in AD patients. In contrast to plasma sTREM2, CSF sTREM2 levels in the AD group were higher than those in the MCI and HC groups. Moreover, concentrations of sTREM2 in CSF were substantially higher in the MCI group than in the HC group, indicating that CSF sTREM2 levels could be used not only to distinguish between HC and AD patients but also as a biomarker to detect earlier changes in the MCI stage.

CONCLUSIONS

The results indicate CSF sTREM2 levels reliably predict neurofibrillary degeneration, cognitive decline, and inflammasome activation, and also have a high diagnostic potential for distinguishing diseased from healthy individuals. To add sTREM2 to the list of required AD biomarkers, future studies will need to include a larger number of patients and utilize a standardized methodology.

The role of PQBP1 in neural development and function

Mutations in the polyglutamine tract-binding protein 1 (PQBP1) gene are associated with Renpenning syndrome, which is characterized by microcephaly, intellectual deficiency, short stature, small testes, and distinct facial dysmorphism. Studies using different models have revealed that PQBP1 plays essential roles in neural development and function. In this mini-review, we summarize recent findings relating to the roles of PQBP1 in these processes, including in the regulation of neural progenitor proliferation, neural projection, synaptic growth, neuronal survival, and cognitive function via mRNA transcription and splicing-dependent or -independent processes. The novel findings provide insights into the mechanisms underlying the pathogenesis of Renpenning syndrome and may advance drug discovery and treatment for this condition.

Colorimetric and surface-enhanced Raman scattering dual-mode magnetic immunosensor for ultrasensitive detection of blood phosphorylated tau in Alzheimer's disease

Phosphorylation of tau at Ser 396, 404 (p-tau^396,404) is the earliest phosphorylation event and a promising biomarker for the early diagnosis of Alzheimer's disease (AD). However, the detection of blood p-tau is challenging because of its low abundance, easy degradation, and complex formation with various blood proteins or cells, often leading to the underestimation of p-tau levels in conventional plasma-based assays. Herein, we developed a colorimetric and surface-enhanced Raman scattering (SERS) dual-mode magnetic immunosensor for highly sensitive, specific, and robust detection of p-tau^396,404 in whole blood samples. The detection assay was based on an immunoreaction between p-tau^396,404 proteins, wherein antibody-modified superparamagnetic iron oxide nanoparticles act as recognition elements to capture p-tau^396,404 in blood, and then horseradish peroxidase- and Raman tags label the corresponding paired antibody as a reporter to provide high signal-to-noise ratios for the immunosensor. This dual-mode immunosensor achieved identified as low as 1.5 pg/mL of p-tau^396,404 in the blood in SERS mode and 24 pg/mL in colorimetric mode by the naked eye. More importantly, this immunosensor rapidly and accurately distinguished AD patients from healthy individuals based on blood p-tau^396,404 levels, and also had the potential to distinguish AD patients of different severities. Therefore, the dual-mode immunosensor is promising for rapid clinical diagnosis of AD, especially in large-scale AD screening.

Dry Chemistry-Based Bipolar Electrochemiluminescence Immunoassay Device for Point-of-Care Testing of Alzheimer-Associated Neuronal Thread Protein

In this study, we developed, for the first time, a novel dry chemistry-based bipolar electrochemiluminescence (ECL) immunoassay device for point-of-care testing (POCT) of Alzheimer-associated neuronal thread protein (AD7c-NTP), where the ECL signals were automatically collected and analyzed after the sample and buffer solutions were manually added onto the immunosensor. The proposed immunoassay device contains an automatic ECL analyzer and a dry chemistry-based ECL immunosensor fabricated with a screen-printed fiber material-based chip and a three-dimensional (3D)-printed shell. Each pad of the fiber material-based chip was premodified with certain reagents for immunoreaction and then assembled to form the ECL immunosensor. The self-enhanced ECL of the Ru(II)-poly-l-lysine complex and the lateral flow fiber material-based chip make the addition of coreactants and repeated flushing unnecessary. Only the sample and buffer solutions are added to the ECL immunosensor, and the process of ECL detection can be completed in about 6 min using the proposed automatic ECL analyzer. Under optimized conditions, the linear detection range for AD7c-NTP was 1 to 10⁴ pg/mL, and the detection limit was 0.15 pg/mL. The proposed ECL immunoassay device had acceptable selectivity, stability, and reproducibility and had been successfully applied to detect AD7c-NTP levels in human urine. In addition, the accurate detection of AD7c-NTP and duplex detection of AD7c-NTP and apolipoprotein E ε4 gene were also validated. It is believed that the proposed ECL immunoassay device may be a candidate for future POCT applications.

Certification of visinin-like protein-1 (VILIP-1) certified reference material by amino acid-based and sulfur-based liquid chromatography isotope dilution mass spectrometry

As an emerging neurodegenerative disease, Alzheimer's disease (AD) has become a leading cause of dementia in older adults. Visinin-like protein-1 (VILIP-1) is an increasingly used biomarker for AD besides the widely accepted Aβ_1-40, Aβ_1-42, and tau. However, significant variations exist in the commercial immuno-based assays for VILIP-1 quantification, underlining the necessity to establish a traceability chain. Certified reference materials (CRMs) located at the top of the traceability chain are traceability sources for relevant matrix standard materials. In this work, VILIP-1 solution CRM with a certified value and uncertainty of 39.82±1.52 μg·g^-1 was developed and certified using amino acid-based isotope dilution mass spectrometry (AA-ID-MS) and sulfur-based isotope dilution inductively coupled plasma mass spectrometry (ID-ICP-MS). Certified values from both strategies showed great consistency, with traceability to SI units. Moreover, the candidate VILIP-1 CRM shows excellent homogeneity and can be stable for at least 7 days at -20°C and 12 months at -70°C. The VILIP-1 CRM developed can be used in value assignment to secondary calibrators and clinical matrix CRMs, showing prospects in early diagnosis and disease monitoring for AD.

TWAS Atlas: a curated knowledgebase of transcriptome-wide association studies

Transcriptome-wide association studies (TWASs), as a practical and prevalent approach for detecting the associations between genetically regulated genes and traits, are now leading to a better understanding of the complex mechanisms of genetic variants in regulating various diseases and traits. Despite the ever-increasing TWAS outputs, there is still a lack of databases curating massive public TWAS information and knowledge. To fill this gap, here we present TWAS Atlas (https://ngdc.cncb.ac.cn/twas/), an integrated knowledgebase of TWAS findings manually curated from extensive literature. In the current implementation, TWAS Atlas collects 401,266 high-quality human gene-trait associations from 200 publications, covering 22,247 genes and 257 traits across 135 tissue types. In particular, an interactive knowledge graph of the collected gene-trait associations is constructed together with single nucleotide polymorphism (SNP)-gene associations to build up comprehensive regulatory networks at multi-omics levels. In addition, TWAS Atlas, as a user-friendly web interface, efficiently enables users to browse, search and download all association information, relevant research metadata and annotation information of interest. Taken together, TWAS Atlas is of great value for promoting the utility and availability of TWAS results in explaining the complex genetic basis as well as providing new insights for human health and disease research.

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

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

Biomarkers for the Diagnosis of Alzheimer’s Disease in Clinical Practice: The Role of CSF Biomarkers during the Evolution of Diagnostic Criteria

Alzheimer’s disease (AD) is a progressive condition and the most common cause of dementia worldwide. The neuropathological changes characteristic of the disorder can be successfully detected before the development of full-blown AD. Early diagnosis of the disease constitutes a formidable challenge for clinicians. CSF biomarkers are the in vivo evidence of neuropathological changes developing in the brain of dementia patients. Therefore, measurement of their concentrations allows for improved accuracy of clinical diagnosis. Moreover, AD biomarkers may provide an indication of disease stage. Importantly, the CSF biomarkers of AD play a pivotal role in the new diagnostic criteria for the disease, and in the recent biological definition of AD by the National Institute on Aging, NIH and Alzheimer’s Association. Due to the necessity of collecting CSF by lumbar puncture, the procedure seems to be an important issue not only from a medical, but also a legal, viewpoint. Furthermore, recent technological advances may contribute to the automation of AD biomarkers measurement and may result in the establishment of unified cut-off values and reference limits. Moreover, a group of international experts in the field of AD biomarkers have developed a consensus and guidelines on the interpretation of CSF biomarkers in the context of AD diagnosis. Thus, technological advancement and expert recommendations may contribute to a more widespread use of these diagnostic tests in clinical practice to support a diagnosis of mild cognitive impairment (MCI) or dementia due to AD. This review article presents up-to-date data regarding the usefulness of CSF biomarkers in routine clinical practice and in biomarkers research.

Establishment of combined diagnostic models of Alzheimer's disease in a Chinese cohort: the Chongqing Ageing & Dementia Study (CADS)

Cerebrospinal fluid (CSF) biomarkers are essential for the accurate diagnosis of Alzheimer's disease (AD), yet their measurement levels vary widely across centers and regions, leaving no uniform cutoff values to date. Diagnostic cutoff values of CSF biomarkers for AD are lacking for the Chinese population. As a member of the Alzheimer's Association Quality Control program for CSF biomarkers, we aimed to establish diagnostic models based on CSF biomarkers and risk factors for AD in a Chinese cohort. A total of 64 AD dementia patients and 105 age- and sex-matched cognitively normal (CN) controls from the Chongqing Ageing & Dementia Study cohort were included. CSF Aβ42, P-tau181, and T-tau levels were measured by ELISA. Combined biomarker models and integrative models with demographic characteristics were established by logistic regression. The cutoff values to distinguish AD from CN were 933 pg/mL for Aβ42, 48.7 pg/mL for P-tau181 and 313 pg/mL for T-tau. The AN model, including Aβ42 and T-tau, had a higher diagnostic accuracy of 89.9%. Integrating age and APOE ε4 status to AN model (the ANA'E model) increased the diagnostic accuracy to 90.5% and improved the model performance. This study established cutoff values of CSF biomarkers and optimal combined models for AD diagnosis in a Chinese cohort.