Ultrasensitive Detection of Plasma Amyloid-β as a Biomarker for Cognitively Normal Elderly Individuals at Risk of Alzheimer’s Disease

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.

Amyloid deposition and its association with depressive symptoms and cognitive functions in late-life depression: a longitudinal study using amyloid-β PET images and neuropsychological measurements

BACKGROUND

Although depression is linked to an increased risk of dementia, the association between late-onset depression (LOD) and amyloid burden remains unclear. This study aimed to determine amyloid deposition in patients with LOD compared to healthy controls (HC) using amyloid-beta (Aβ) positron emission tomography (PET) images and neuropsychological assessments.

METHODS

Forty patients first diagnosed with major depressive disorder after the age of 60 (LOD) and twenty-one healthy volunteers (HC) were enrolled. Depression and anxiety were evaluated using the 17-item Hamilton Depression Scale, Hamilton Anxiety Rating Scale, and Clinical Global Impression Scale. Cognitive function was assessed using the Korean versions of the Mini-Mental Status Examination, Montreal Cognitive Assessment, and Seoul Neuropsychological Screening Battery at baseline and 3-month follow-up. 18F-florbetapir PET images were co-registered with T1-weighted magnetic resonance images.

RESULTS

There was no significant difference in Aβ deposition between LOD and HC groups. No significant correlation between Aβ burden and depressive symptom severity was found in LOD patients. Higher somatic anxiety was correlated with lower Aβ burden in multiple brain regions, including the left inferior frontal lobe (p = 0.009), right anterior cingulate (p = 0.003), and right superior frontal lobe (p = 0.009). Despite cognitive recovery in areas such as attention (Digit Span Forward, p = 0.026), memory (Auditory Verbal Learning Test Recall Total, p = 0.010; Rey Complex Figure Test Delayed Recall, p = 0.039), and frontal executive function (Contrasting Program, p = 0.033) after three months of antidepressant treatment, cognitive improvement showed no association with amyloid deposition.

CONCLUSIONS

These findings suggest distinct mechanisms may underlie amyloid deposition in neurodegenerative changes associated with depression. While amyloid burden in specific brain regions negatively correlated with somatic anxiety, it showed no significant correlation with the severity of depression or overall cognitive function.

Towards Early Diagnosis and Screening of Alzheimer's Disease Using Frequency Locked Whispering Gallery Mode Microtoroid Biosensors

Alzheimer's disease (AD) is a progressive form of dementia affecting almost 55 million people worldwide. It is characterized by the abnormal deposition of amyloid plaques and neurofibrillary tangles within the brain, leading to a pathological cascade of neuron degeneration and death as well as memory loss and cognitive decline. Amyloid beta (Aβ) is an AD biomarker present in cerebrospinal fluid and blood serum and correlates with the presence of amyloid plaques and tau tangles in the brain. Measuring the levels of Aβ can help with early diagnosis of AD, which is key for studying novel AD drugs and delaying the symptoms of dementia. However, this goal is difficult to achieve due to the low levels of AD biomarkers in biofluids. Here we demonstrate for the first time the use of FLOWER (frequency locked optical whispering evanescent resonator) for quantifying the levels of post-mortem cerebrospinal fluid (CSF) Aβ42 in clinicopathologically classified control, mild cognitive impairment (MCI), and AD participants. FLOWER is capable of measuring CSF Aβ42 (area under curve, AUC = 0.92) with higher diagnostic performance than standard ELISA (AUC = 0.82) and was also able to distinguish between control and MCI samples. Our results demonstrate the capability of FLOWER for screening CSF samples for early diagnosis of Alzheimer's pathology.

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.

Morphometric and Nanomechanical Screening of Peripheral Blood Cells with Atomic Force Microscopy for Label-Free Assessment of Alzheimer's Disease, Parkinson's Disease, and Amyotrophic Lateral Sclerosis

Neurodegenerative disorders (NDDs) are complex, multifactorial disorders with significant social and economic impact in today's society. NDDs are predicted to become the second-most common cause of death in the next few decades due to an increase in life expectancy but also to a lack of early diagnosis and mainly symptomatic treatment. Despite recent advances in diagnostic and therapeutic methods, there are yet no reliable biomarkers identifying the complex pathways contributing to these pathologies. The development of new approaches for early diagnosis and new therapies, together with the identification of non-invasive and more cost-effective diagnostic biomarkers, is one of the main trends in NDD biomedical research. Here we summarize data on peripheral biomarkers, biofluids (cerebrospinal fluid and blood plasma), and peripheral blood cells (platelets (PLTs) and red blood cells (RBCs)), reported so far for the three most common NDDs-Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS). PLTs and RBCs, beyond their primary physiological functions, are increasingly recognized as valuable sources of biomarkers for NDDs. Special attention is given to the morphological and nanomechanical signatures of PLTs and RBCs as biophysical markers for the three pathologies. Modifications of the surface nanostructure and morphometric and nanomechanical signatures of PLTs and RBCs from patients with AD, PD, and ALS have been revealed by atomic force microscopy (AFM). AFM is currently experiencing rapid and widespread adoption in biomedicine and clinical medicine, in particular for early diagnostics of various medical conditions. AFM is a unique instrument without an analog, allowing the generation of three-dimensional cell images with extremely high spatial resolution at near-atomic scale, which are complemented by insights into the mechanical properties of cells and subcellular structures. Data demonstrate that AFM can distinguish between the three pathologies and the normal, healthy state. The specific PLT and RBC signatures can serve as biomarkers in combination with the currently used diagnostic tools. We highlight the strong correlation of the morphological and nanomechanical signatures between RBCs and PLTs in PD, ALS, and AD.

Early Alzheimer's Disease Screening Approach Using Plasma Biomarkers

Alzheimer's disease (AD) is the most prevalent dementia, but it shows similar initial symptoms to other neurocognitive diseases (Lewy body disease (LBD) and frontotemporal dementia (FTD)). Thus, the identification of reliable AD plasma biomarkers is required. The aim of this work is to evaluate the use of a few plasma biomarkers to develop an early and specific AD screening method. Plasma p-Tau181, neurofilament light (NfL), and glial fibrillary acid protein (GFAP) were determined by Single Molecule Assay (SIMOA® Quanterix, Billerica, MA, USA) in patients with mild cognitive impairment due to AD (MCI-AD, n = 50), AD dementia (n = 10), FTD (n = 20), LBD (n = 5), and subjective cognitive impairment (SCI (n = 21)). Plasma p-Tau181 and GFAP showed the highest levels in AD dementia, and significant correlations with clinical AD characteristics; meanwhile, NfL showed the highest levels in FTD, but no significant correlations with AD. The partial least squares (PLS) diagnosis model developed between the AD and SCI groups showed good accuracy with a receiver operating characteristic (ROC) area under curve (AUC) of 0.935 (CI 95% 0.87-0.98), sensitivity of 86%, and specificity of 88%. In a first screen, NfL plasma levels could identify FTD patients among subjects with cognitive impairment. Then, the developed PLS model including p-Tau181 and GFAP levels could identify AD patients, constituting a simple, early, and specific diagnosis approach.

Plasma Aβ42/40 ratio, p-tau181, GFAP, and NfL across the Alzheimer's disease continuum: A cross-sectional and longitudinal study in the AIBL cohort

INTRODUCTION

Plasma amyloid beta (Aβ)1-42/Aβ1-40 ratio, phosphorylated-tau181 (p-tau181), glial fibrillary acidic protein (GFAP), and neurofilament light (NfL) are putative blood biomarkers for Alzheimer's disease (AD). However, head-to-head cross-sectional and longitudinal comparisons of the aforementioned biomarkers across the AD continuum are lacking.

METHODS

Plasma Aβ1-42, Aβ1-40, p-tau181, GFAP, and NfL were measured utilizing the Single Molecule Array (Simoa) platform and compared cross-sectionally across the AD continuum, wherein Aβ-PET (positron emission tomography)-negative cognitively unimpaired (CU Aβ-, n = 81) and mild cognitive impairment (MCI Aβ-, n = 26) participants were compared with Aβ-PET-positive participants across the AD continuum (CU Aβ+, n = 39; MCI Aβ+, n = 33; AD Aβ+, n = 46) from the Australian Imaging, Biomarker & Lifestyle Flagship Study of Ageing (AIBL) cohort. Longitudinal plasma biomarker changes were also assessed in MCI (n = 27) and AD (n = 29) participants compared with CU (n = 120) participants. In addition, associations between baseline plasma biomarker levels and prospective cognitive decline and Aβ-PET load were assessed over a 7 to 10-year duration.

RESULTS

Lower plasma Aβ1-42/Aβ1-40 ratio and elevated p-tau181 and GFAP were observed in CU Aβ+, MCI Aβ+, and AD Aβ+, whereas elevated plasma NfL was observed in MCI Aβ+ and AD Aβ+, compared with CU Aβ- and MCI Aβ-. Among the aforementioned plasma biomarkers, for models with and without AD risk factors (age, sex, and apolipoprotein E (APOE) ε4 carrier status), p-tau181 performed equivalent to or better than other biomarkers in predicting a brain Aβ-/+ status across the AD continuum. However, for models with and without the AD risk factors, a biomarker panel of Aβ1-42/Aβ1-40, p-tau181, and GFAP performed equivalent to or better than any of the biomarkers alone in predicting brain Aβ-/+ status across the AD continuum. Longitudinally, plasma Aβ1-42/Aβ1-40, p-tau181, and GFAP were altered in MCI compared with CU, and plasma GFAP and NfL were altered in AD compared with CU. In addition, lower plasma Aβ1-42/Aβ1-40 and higher p-tau181, GFAP, and NfL were associated with prospective cognitive decline and lower plasma Aβ1-42/Aβ1-40, and higher p-tau181 and GFAP were associated with increased Aβ-PET load prospectively.

DISCUSSION

These findings suggest that plasma biomarkers are altered cross-sectionally and longitudinally, along the AD continuum, and are prospectively associated with cognitive decline and brain Aβ-PET load. In addition, although p-tau181 performed equivalent to or better than other biomarkers in predicting an Aβ-/+ status across the AD continuum, a panel of biomarkers may have superior Aβ-/+ status predictive capability across the AD continuum.

HIGHLIGHTS

Area under the curve (AUC) of p-tau181 ≥ AUC of Aβ42/40, GFAP, NfL in predicting PET Aβ-/+ status (Aβ-/+).  AUC of Aβ42/40+p-tau181+GFAP panel ≥ AUC of Aβ42/40/p-tau181/GFAP/NfL for Aβ-/+.  Longitudinally, Aβ42/40, p-tau181, and GFAP were altered in MCI versus CU.  Longitudinally, GFAP and NfL were altered in AD versus CU.  Aβ42/40, p-tau181, GFAP, and NfL are associated with prospective cognitive decline.  Aβ42/40, p-tau181, and GFAP are associated with increased PET Aβ load prospectively.

Assessment of Plasma and Cerebrospinal Fluid Biomarkers in Different Stages of Alzheimer's Disease and Frontotemporal Dementia

Alzheimer's disease (AD) is the primary type of dementia, followed by frontotemporal lobar degeneration (FTLD). They share some clinical characteristics, mainly at the early stages. So, the identification of early, specific, and minimally invasive biomarkers is required. In this study, some plasma biomarkers (Amyloid β42, p-Tau181, t-Tau, neurofilament light (NfL), TAR DNA-binding protein 43 (TDP-43)) were determined by single molecule array technology (SIMOA^®) in control subjects (n = 22), mild cognitive impairment due to AD (MCI-AD, n = 33), mild dementia due to AD (n = 12), and FTLD (n = 11) patients. The correlations between plasma and cerebrospinal fluid (CSF) levels and the accuracy of plasma biomarkers for AD early diagnosis and discriminating from FTLD were analyzed. As result, plasma p-Tau181 and NfL levels correlated with the corresponding CSF levels. Additionally, plasma p-Tau181 showed good accuracy for distinguishing between the controls and AD, as well as discriminating between AD and FTLD. Moreover, plasma NfL could discriminate dementia-AD vs. controls, FTLD vs. controls, and MCI-AD vs. dementia-AD. Therefore, the determination of these biomarkers in plasma is potentially helpful in AD spectrum diagnosis, but also discriminating from FTLD. In addition, the accessibility of these potential early and specific biomarkers may be useful for AD screening protocols in the future.

β-Amyloid in blood neuronal-derived extracellular vesicles is elevated in cognitively normal adults at risk of Alzheimer's disease and predicts cerebral amyloidosis

Background

Blood biomarkers that can be used for preclinical Alzheimer’s disease (AD) diagnosis would enable trial enrollment at a time when the disease is potentially reversible. Here, we investigated plasma neuronal-derived extracellular vesicle (nEV) cargo in patients along the Alzheimer’s continuum, focusing on cognitively normal controls (NCs) with high brain β-amyloid (Aβ) loads (Aβ+).

Methods

The study was based on the Sino Longitudinal Study on Cognitive Decline project. We enrolled 246 participants, including 156 NCs, 45 amnestic mild cognitive impairment (aMCI) patients, and 45 AD dementia (ADD) patients. Brain Aβ loads were determined using positron emission tomography. NCs were classified into 84 Aβ− NCs and 72 Aβ+ NCs. Baseline plasma nEVs were isolated by immunoprecipitation with an anti-CD171 antibody. After verification, their cargos, including Aβ, tau phosphorylated at threonine 181, and neurofilament light, were quantified using a single-molecule array. Concentrations of these cargos were compared among the groups, and their receiver operating characteristic (ROC) curves were constructed. A subset of participants underwent follow-up cognitive assessment and magnetic resonance imaging. The relationships of nEV cargo levels with amyloid deposition, longitudinal changes in cognition, and brain regional volume were explored using correlation analysis. Additionally, 458 subjects in the project had previously undergone plasma Aβ quantification.

Results

Only nEV Aβ was included in the subsequent analysis. We focused on Aβ₄₂ in the current study. After normalization of nEVs, the levels of Aβ₄₂ were found to increase gradually across the cognitive continuum, with the lowest in the Aβ− NC group, an increase in the Aβ+ NC group, a further increase in the aMCI group, and the highest in the ADD group, contributing to their diagnoses (Aβ− NCs vs. Aβ+ NCs, area under the ROC curve values of 0.663; vs. aMCI, 0.857; vs. ADD, 0.957). Furthermore, nEV Aβ₄₂ was significantly correlated with amyloid deposition, as well as longitudinal changes in cognition and entorhinal volume. There were no differences in plasma Aβ levels among NCs, aMCI, and ADD individuals.

Conclusions

Our findings suggest the potential use of plasma nEV Aβ₄₂ levels in diagnosing AD-induced cognitive impairment and Aβ+ NCs. This biomarker reflects cortical amyloid deposition and predicts cognitive decline and entorhinal atrophy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13195-022-01010-x.

Plasma Aβ as a biomarker for predicting Aβ-PET status in Alzheimer's disease：a systematic review with meta-analysis

OBJECTIVE

Amyloid-β positron emission tomography (Aβ-PET) scan has been proposed to detect amyloid-β (Aβ) deposition in the brain. However, this approach is costly and not ideal for the early diagnosis of Alzheimer's disease. Blood-based Aβ measurement offers a scalable alternative to the costly or invasive biomarkers. The aim of this study was to statistically validate whether plasma Aβ could predict Aβ-PET status via meta-analysis.

METHODS

We systematically searched for eligible studies from PubMed, Embase and Cochrane Library, which reported plasma Aβ levels of amyloid-β positron emission tomography-positive (PET (+)) and amyloid-β positron emission tomography-negative (PET (-)) subjects. We generated pooled estimates using random effects meta-analyses. For any study that has significant heterogeneity, metaregression and subgroup analysis were further conducted. Publication bias was appraised by funnel plots and Egger's test.

RESULTS

16 studies with 3047 participants were included in the meta-analysis. Among all the enrolled studies, 10 studies reported plasma Aβ40 values, while 9 studies reported plasma Aβ42 values and 13 studies reported Aβ42/Aβ40 ratio. The pooled standardised mean difference (SMD) was 0.76 (95% CI -0.61 to 2.14, p=0.28) in the plasma Aβ40 values group. Plasma Aβ42 values group has a pooled SMD of -0.60 (95% CI -0.80 to -0.41, p<0.0001). In the plasma Aβ42/Aβ40 ratio group, the pooled SMD was -1.44 (95% CI -2.17 to -0.72, p<0.0001).

CONCLUSION

Plasma Aβ40 values might not distinguish between PET (+) and PET (-) people. However, plasma Aβ42 values and plasma Aβ42/Aβ40 ratio could be served as independent biomarkers for predicting Aβ-PET status.

Correlation Between Brain Structure Atrophy and Plasma Amyloid-β and Phosphorylated Tau in Patients With Alzheimer’s Disease and Amnestic Mild Cognitive Impairment Explored by Surface-Based Morphometry

Objective

To investigate the changes in the cortical thickness of the region of interest (ROI) and plasma Aβ40, Aβ42, and phosphorylated Tau (P-Tau) concentrations in patients with Alzheimer’s disease (AD) and amnestic mild cognitive impairment (aMCI) as the disease progressed with surface-based morphometry (SBM), to analyze the correlation between ROI cortical thickness and measured plasma indexes and neuropsychological scales, and to explore the clinical value of ROI cortical thickness combined with plasma Aβ40, Aβ42, and P-Tau in the early recognition and diagnosis of AD.

Methods

This study enrolled 33 patients with AD, 48 patients with aMCI, and 33 healthy controls (normal control, NC). Concentration changes in plasma Aβ42, Aβ40, and P-Tau collected in each group were analyzed. Meanwhile, the whole brain T1 structure images (T1WI-3D-MPRAGE) of each group of patients were collected, and T1 image in AD-aMCI, AD-NC, and aMCI-NC group were analyzed and processed by SBM technology to obtain brain regions with statistical differences as clusters, and the cortical thickness of each cluster was extracted. Multivariate ordered logistic regression analysis was used to screen out the measured plasma indexes and the indexes with independent risk factors in the cortical thickness of each cluster. Three comparative receiver operating characteristic (ROC) curves of AD-aMCI, AD-NC, and aMCI-NC groups were plotted, respectively, to explore the diagnostic value of multi-factor combined prediction for cognitive impairment. The relationship between cortical thickness and plasma indexes, and between cortical thickness and Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores were clarified by Pearson correlation analysis.

Results

Plasma Aβ40, Aβ42, and P-Tau proteins in the NC, aMCI, and AD groups increased with the progression of AD (P &lt; 0.01); cortical thickness reductions in the AD-aMCI groups and AD-NC groups mainly involved the bilateral superior temporal gyrus, transverse temporal gyrus, superior marginal gyrus, insula, right entorhinal cortex, right fusiform gyrus, and cingulate gyrus. However, there were no statistical significances in cortical thickness reductions in the aMCI and NC groups. The cortical thickness of the ROI was negatively correlated with plasma Aβ40, Aβ42, and P-Tau concentrations (P &lt; 0.05), and the cortical thickness of the ROI was positively correlated with MMSE and MoCA scores. Independent risk factors such as Aβ40, Aβ42, P-Tau, and AD-NC cluster 1R (right superior temporal gyrus, temporal pole, entorhinal cortex, transverse temporal gyrus, fusiform gyrus, superior marginal gyrus, middle temporal gyrus, and inferior temporal gyrus) were combined to plot ROC curves. The diagnostic efficiency of plasma indexes was higher than that of cortical thickness indexes, the diagnostic efficiency of ROC curves after the combination of cortical thickness and plasma indexes was higher than that of cortical thickness or plasma indexes alone.

Conclusion

Plasma Aβ40, Aβ42, and P-Tau may be potential biomarkers for early prediction of AD. As the disease progressed, AD patients developed cortical atrophy characterized by atrophy of the medial temporal lobe. The combined prediction of these region and plasma Aβ40, Aβ42, and P-Tau had a higher diagnostic value than single-factor prediction for cognitive decline.

Blood-Based Biomarkers for Alzheimer's Disease Diagnosis and Progression: An Overview

Alzheimer's Disease (AD) is a progressive neurodegenerative disease characterized by amyloid-β (Aβ) plaque deposition and neurofibrillary tangle accumulation in the brain. Although several studies have been conducted to unravel the complex and interconnected pathophysiology of AD, clinical trial failure rates have been high, and no disease-modifying therapies are presently available. Fluid biomarker discovery for AD is a rapidly expanding field of research aimed at anticipating disease diagnosis and following disease progression over time. Currently, Aβ1-42, phosphorylated tau, and total tau levels in the cerebrospinal fluid are the best-studied fluid biomarkers for AD, but the need for novel, cheap, less-invasive, easily detectable, and more-accessible markers has recently led to the search for new blood-based molecules. However, despite considerable research activity, a comprehensive and up-to-date overview of the main blood-based biomarker candidates is still lacking. In this narrative review, we discuss the role of proteins, lipids, metabolites, oxidative-stress-related molecules, and cytokines as possible disease biomarkers. Furthermore, we highlight the potential of the emerging miRNAs and long non-coding RNAs (lncRNAs) as diagnostic tools, and we briefly present the role of vitamins and gut-microbiome-related molecules as novel candidates for AD detection and monitoring, thus offering new insights into the diagnosis and progression of this devastating disease.

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

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

The Association Between Alzheimer's Disease-Related Markers and Physical Activity in Cognitively Normal Older Adults

Previous studies have indicated that physical activity may be beneficial in reducing the risk for Alzheimer's disease (AD), although the underlying mechanisms are not fully understood. The goal of this study was to evaluate the relationship between habitual physical activity levels and brain amyloid deposition and AD-related blood biomarkers (i.e., measured using a novel high-performance mass spectrometry-based assay), in apolipoprotein E (APOE) ε4 carriers and noncarriers. We evaluated 143 cognitively normal older adults, all of whom had brain amyloid deposition assessed using positron emission tomography and had their physical activity levels measured using the International Physical Activity Questionnaire (IPAQ). We observed an inverse correlation between brain amyloidosis and plasma beta-amyloid (Aβ)₁₋₄₂ but found no association between brain amyloid and plasma Aβ₁₋₄₀ and amyloid precursor protein (APP)_669−711. Additionally, higher levels of physical activity were associated with lower plasma Aβ₁₋₄₀, Aβ₁₋₄₂, and APP_669−711 levels in APOE ε4 noncarriers. The ratios of Aβ₁₋₄₀/Aβ₁₋₄₂ and APP_669−711/Aβ₁₋₄₂, which have been associated with higher brain amyloidosis in previous studies, differed between APOE ε4 carriers and non-carriers. Taken together, these data indicate a complex relationship between physical activity and brain amyloid deposition and potential blood-based AD biomarkers in cognitively normal older adults. In addition, the role of APOE ε4 is still unclear, and more studies are necessary to bring further clarification.

Fluid Biomarkers in Alzheimer’s Disease and Other Neurodegenerative Disorders: Toward Integrative Diagnostic Frameworks and Tailored Treatments

The diagnosis of neurodegenerative diseases (NDDs) represents an increasing social burden, with the unsolved issue of disease-modifying therapies (DMTs). The failure of clinical trials treating Alzheimer′s Disease (AD) so far highlighted the need for a different approach in drug design and patient selection. Identifying subjects in the prodromal or early symptomatic phase is critical to slow down neurodegeneration, but the implementation of screening programs with this aim will have an ethical and social aftermath. Novel minimally invasive candidate biomarkers (derived from blood, saliva, olfactory brush) or classical cerebrospinal fluid (CSF) biomarkers have been developed in research settings to stratify patients with NDDs. Misfolded protein accumulation, neuroinflammation, and synaptic loss are the pathophysiological hallmarks detected by these biomarkers to refine diagnosis, prognosis, and target engagement of drugs in clinical trials. We reviewed fluid biomarkers of NDDs, considering their potential role as screening, diagnostic, or prognostic tool, and their present-day use in clinical trials (phase II and III). A special focus will be dedicated to novel techniques for the detection of misfolded proteins. Eventually, an applicative diagnostic algorithm will be proposed to translate the research data in clinical practice and select prodromal or early patients to be enrolled in the appropriate DMTs trials for NDDs.

Diagnostic Accuracy of Blood-Based Biomarker Panels: A Systematic Review

Background

Because of high prevalence of Alzheimer's disease (AD) in low- and middle-income countries (LMICs), there is an urgent need for inexpensive and minimally invasive diagnostic tests to detect biomarkers in the earliest and asymptomatic stages of the disease. Blood-based biomarkers are predicted to have the most impact for use as a screening tool and predict the onset of AD, especially in LMICs. Furthermore, it has been suggested that panels of markers may perform better than single protein candidates.

Methods

Medline/Pubmed was searched to identify current relevant studies published from January 2016 to December 2020. We included all full-text articles examining blood-based biomarkers as a set of protein markers or panels to aid in AD's early diagnosis, prognosis, and characterization.

Results

Seventy-six articles met the inclusion criteria for systematic review. Majority of the studies reported plasma and serum as the main source for biomarker determination in blood. Protein-based biomarker panels were reported to aid in AD diagnosis and prognosis with better accuracy than individual biomarkers. Conventional (amyloid-beta and tau) and neuroinflammatory biomarkers, such as amyloid beta-42, amyloid beta-40, total tau, phosphorylated tau-181, and other tau isoforms, were the most represented. We found the combination of amyloid beta-42/amyloid beta-40 ratio and APOEε4 status to be most represented with high accuracy for predicting amyloid beta-positron emission tomography status.

Conclusion

Assessment of Alzheimer's disease biomarkers in blood as a non-invasive and cost-effective alternative will potentially contribute to early diagnosis and improvement of therapeutic interventions. Given the heterogeneous nature of AD, combination of markers seems to perform better in the diagnosis and prognosis of the disease than individual biomarkers.

Novel Ultrasensitive Detection Technologies for the Identification of Early and Minimally Invasive Alzheimer's Disease Blood Biomarkers

BACKGROUND

Single molecule array (SIMOA) and other ultrasensitive detection technologies have allowed the determination of blood-based biomarkers of Alzheimer's disease (AD) for diagnosis and monitoring, thereby opening up a promising field of research.

OBJECTIVE

To review the published bibliography on plasma biomarkers in AD using new ultrasensitive techniques.

METHODS

A systematic review of the PubMed database was carried out to identify reports on the use of blood-based ultrasensitive technology to identify biomarkers for AD.

RESULTS

Based on this search, 86 works were included and classified according to the biomarker determined. First, plasma amyloid-β showed satisfactory accuracy as an AD biomarker in patients with a high risk of developing dementia. Second, plasma t-Tau displayed good sensitivity in detecting different neurodegenerative diseases. Third, plasma p-Tau was highly specific for AD. Fourth, plasma NfL was highly sensitive for distinguishing between patients with neurodegenerative diseases and healthy controls. In general, the simultaneous determination of several biomarkers facilitated greater accuracy in diagnosing AD (Aβ42/Aβ40, p-Tau181/217).

CONCLUSION

The recent development of ultrasensitive technology allows the determination of blood-based biomarkers with high sensitivity, thus facilitating the early detection of AD through the analysis of easily obtained biological samples. In short, as a result of this knowledge, pre-symptomatic and early AD diagnosis may be possible, and the recruitment process for future clinical trials could be more precise. However, further studies are necessary to standardize levels of blood-based biomarkers in the general population and thus achieve reproducible results among different laboratories.

The Longitudinal Early-onset Alzheimer's Disease Study (LEADS): Framework and methodology

Patients with early-onset Alzheimer's disease (EOAD) are commonly excluded from large-scale observational and therapeutic studies due to their young age, atypical presentation, or absence of pathogenic mutations. The goals of the Longitudinal EOAD Study (LEADS) are to (1) define the clinical, imaging, and fluid biomarker characteristics of EOAD; (2) develop sensitive cognitive and biomarker measures for future clinical and research use; and (3) establish a trial-ready network. LEADS will follow 400 amyloid beta (Aβ)-positive EOAD, 200 Aβ-negative EOnonAD that meet National Institute on Aging-Alzheimer's Association (NIA-AA) criteria for mild cognitive impairment (MCI) or AD dementia, and 100 age-matched controls. Participants will undergo clinical and cognitive assessments, magnetic resonance imaging (MRI), [18 F]Florbetaben and [18 F]Flortaucipir positron emission tomography (PET), lumbar puncture, and blood draw for DNA, RNA, plasma, serum and peripheral blood mononuclear cells, and post-mortem assessment. To develop more effective AD treatments, scientists need to understand the genetic, biological, and clinical processes involved in EOAD. LEADS will develop a public resource that will enable future planning and implementation of EOAD clinical trials.

Fully automated chemiluminescence enzyme immunoassays showing high correlation with immunoprecipitation mass spectrometry assays for β-amyloid (1-40) and (1-42) in plasma samples

Blood based β-amyloid (Aβ) assays that can predict amyloid positivity in the brain are in high demand. Current studies that utilize immunoprecipitation mass spectrometry assay (IP-MS), which has high specificity for measuring analytes, have revealed that precise plasma Aβ assays have the potential to detect amyloid positivity in the brain. In this study, we developed plasma Aβ40 and Aβ42 immunoassays using a fully automated immunoassay platform that is used in routine clinical practice. Our assays showed high sensitivity (limit of quantification: 2.46 pg/mL [Aβ40] and 0.16 pg/mL [Aβ42]) and high reproducibility within-run (coefficients of variation [CVs]: <3.7% [Aβ40] and <2.0% [Aβ42]) and within-laboratory (CVs: <4.6% [Aβ40] and <5.3% [Aβ42]). The interference from plasma components was less than 10%, and the cross-reactivity with various lengths of Aβ peptides was less than 0.5%. In addition, we found a significant correlation between the IP-MS method and our immunoassay (correlation coefficients of Pearson's r: 0.91 [Aβ40] and 0.82 [Aβ42]). Our new method to quantify plasma Aβ40 and Aβ42 provides clinicians and patients with a way to continuously monitor disease progression.

Transitioning from cerebrospinal fluid to blood tests to facilitate diagnosis and disease monitoring in Alzheimer's disease

Alzheimer's disease (AD) is increasingly prevalent worldwide, and disease-modifying treatments may soon be at hand; hence, now, more than ever, there is a need to develop techniques that allow earlier and more secure diagnosis. Current biomarker-based guidelines for AD diagnosis, which have replaced the historical symptom-based guidelines, rely heavily on neuroimaging and cerebrospinal fluid (CSF) sampling. While these have greatly improved the diagnostic accuracy of AD pathophysiology, they are less practical for application in primary care, population-based and epidemiological settings, or where resources are limited. In contrast, blood is a more accessible and cost-effective source of biomarkers in AD. In this review paper, using the recently proposed amyloid, tau and neurodegeneration [AT(N)] criteria as a framework towards a biological definition of AD, we discuss recent advances in biofluid-based biomarkers, with a particular emphasis on those with potential to be translated into blood-based biomarkers. We provide an overview of the research conducted both in CSF and in blood to draw conclusions on biomarkers that show promise. Given the evidence collated in this review, plasma neurofilament light chain (N) and phosphorylated tau (p-tau; T) show particular potential for translation into clinical practice. However, p-tau requires more comparisons to be conducted between its various epitopes before conclusions can be made as to which one most robustly differentiates AD from non-AD dementias. Plasma amyloid beta (A) would prove invaluable as an early screening modality, but it requires very precise tests and robust pre-analytical protocols.

Ultrasensitive techniques and protein misfolding amplification assays for biomarker-guided reconceptualization of Alzheimer's and other neurodegenerative diseases

INTRODUCTION

The clinical validation and qualification of biomarkers reflecting the complex pathophysiology of neurodegenerative diseases (NDDs) is a fundamental challenge for current drug discovery and development and next-generation clinical practice. Novel ultrasensitive detection techniques and protein misfolding amplification assays hold the potential to optimize and accelerate this process.

AREAS COVERED

Here we perform a PubMed-based state of the art review and perspective report on blood-based ultrasensitive detection techniques and protein misfolding amplification assays for biomarkers discovery and development in NDDs.

EXPERT OPINION

Ultrasensitive assays represent innovative solutions for blood-based assessments during the entire Alzheimer's disease (AD) biological and clinical continuum, for contexts of use (COU) such as prediction, detection, early diagnosis, and prognosis of AD. Moreover, cerebrospinal fluid (CSF)-based misfolding amplification assays show encouraging performance in detecting α-synucleinopathies in prodromal or at-high-risk individuals and may serve as tools for patients' stratification by the presence of α-synuclein pathology. Further clinical research will help overcome current methodological limitations, also through exploring multiple accessible bodily matrices. Eventually, integrative longitudinal studies will support precise definitions for appropriate COU across NDDs.

Lipid Peroxidation Assessment in Preclinical Alzheimer Disease Diagnosis

BACKGROUND

Alzheimer disease (AD) is an increasingly common neurodegenerative disease, especially in countries with aging populations. Its diagnosis is complex and is usually carried out in advanced stages of the disease. In addition, lipids and oxidative stress have been related to AD since the earliest stages. A diagnosis in the initial or preclinical stages of the disease could help in a more effective action of the treatments.

METHODS

Isoprostanoid biomarkers were determined in plasma samples from preclinical AD participants (n = 12) and healthy controls (n = 31) by chromatography and mass spectrometry (UPLC-MS/MS). Participants were accurately classified according to cerebrospinal fluid (CSF) biomarkers and neuropsychological examination.

RESULTS

Isoprostanoid levels did not show differences between groups. However, some of them correlated with CSF biomarkers (t-tau, p-tau) and with cognitive decline. In addition, a panel including 10 biomarkers showed an area under curve (AUC) of 0.96 (0.903-1) and a validation AUC of 0.90 in preclinical AD prediction.

CONCLUSIONS

Plasma isoprostanoids could be useful biomarkers in preclinical diagnosis for AD. However, these results would require a further validation with an external cohort.

A blood-based diagnostic test incorporating plasma Aβ42/40 ratio, ApoE proteotype, and age accurately identifies brain amyloid status: findings from a multi cohort validity analysis

BACKGROUND

The development of blood-based biomarker tests that are accurate and robust for Alzheimer's disease (AD) pathology have the potential to aid clinical diagnosis and facilitate enrollment in AD drug trials. We developed a high-resolution mass spectrometry (MS)-based test that quantifies plasma Aβ42 and Aβ40 concentrations and identifies the ApoE proteotype. We evaluated robustness, clinical performance, and commercial viability of this MS biomarker assay for distinguishing brain amyloid status.

METHODS

We used the novel MS assay to analyze 414 plasma samples that were collected, processed, and stored using site-specific protocols, from six independent US cohorts. We used receiver operating characteristic curve (ROC) analyses to assess assay performance and accuracy for predicting amyloid status (positive, negative, and standard uptake value ratio; SUVR). After plasma analysis, sites shared brain amyloid status, defined using diverse, site-specific methods and cutoff values; amyloid PET imaging using various tracers or CSF Aβ42/40 ratio.

RESULTS

Plasma Aβ42/40 ratio was significantly (p < 0.001) lower in the amyloid positive vs. negative participants in each cohort. The area under the ROC curve (AUC-ROC) was 0.81 (95% CI = 0.77-0.85) and the percent agreement between plasma Aβ42/40 and amyloid positivity was 75% at the optimal (Youden index) cutoff value. The AUC-ROC (0.86; 95% CI = 0.82-0.90) and accuracy (81%) for the plasma Aβ42/40 ratio improved after controlling for cohort heterogeneity. The AUC-ROC (0.90; 95% CI = 0.87-0.93) and accuracy (86%) improved further when Aβ42/40, ApoE4 copy number and participant age were included in the model.

CONCLUSIONS

This mass spectrometry-based plasma biomarker test: has strong diagnostic performance; can accurately distinguish brain amyloid positive from amyloid negative individuals; may aid in the diagnostic evaluation process for Alzheimer's disease; and may enhance the efficiency of enrolling participants into Alzheimer's disease drug trials.

A Machine Learning Approach to Identify a Circulating MicroRNA Signature for Alzheimer Disease

BACKGROUND

Accurate diagnosis of Alzheimer disease (AD) involving less invasive molecular procedures and at reasonable cost is an unmet medical need. We identified a serum miRNA signature for AD that is less invasive than a measure in cerebrospinal fluid.

METHODS

From the Oxford Project to Investigate Memory and Aging (OPTIMA) study, 96 serum samples were profiled by a multiplex (>500 analytes) microRNA (miRNA) reverse transcription quantitative PCR analysis, including 51 controls, 32 samples from patients with AD, and 13 samples from patients with mild cognitive impairment (MCI). Clinical diagnosis of a subset of AD and the controls was confirmed by postmortem (PM) histologic examination of brain tissue. In a machine learning approach, the AD and control samples were split 70:30 as the training and test cohorts. A multivariate random forest statistical analysis was applied to construct and test a miRNA signature for AD identification. In addition, the MCI participants were included in the test cohort to assess whether the signature can identify early AD patients.

RESULTS

A 12-miRNA signature for AD identification was constructed in the training cohort, demonstrating 76.0% accuracy in the independent test cohort with 90.0% sensitivity and 66.7% specificity. The signature, however, was not able to identify MCI participants. With a subset of AD and control participants with PM-confirmed diagnosis status, a separate 12-miRNA signature was constructed. Although sample size was limited, the PM-confirmed signature demonstrated improved accuracy of 85.7%, largely owing to improved specificity of 80.0% with comparable sensitivity of 88.9%.

CONCLUSION

Although additional and more diverse cohorts are needed for further clinical validation of the robustness, the miRNA signature appears to be a promising blood test to diagnose AD.

Fluid Biomarkers in Clinical Trials for Alzheimer's Disease: Current and Future Application

Alzheimer's disease (AD) research is entering a unique moment in which enormous information about the molecular basis of this disease is being translated into therapeutics. However, almost all drug candidates have failed in clinical trials over the past 30 years. These many trial failures have highlighted a need for the incorporation of biomarkers in clinical trials to help improve the trial design. Fluid biomarkers measured in cerebrospinal fluid and circulating blood, which can reflect the pathophysiological process in the brain, are becoming increasingly important in AD clinical trials. In this review, we first succinctly outline a panel of fluid biomarkers for neuropathological changes in AD. Then, we provide a comprehensive overview of current and future application of fluid biomarkers in clinical trials for AD. We also summarize the many challenges that have been encountered in efforts to integrate fluid biomarkers in clinical trials, and the barriers that have begun to be overcome. Ongoing research efforts in the field of fluid biomarkers will be critical to make significant progress in ultimately unveiling disease-modifying therapies in AD.

Astrogliosis and episodic memory in late life: higher GFAP is related to worse memory and white matter microstructure in healthy aging and Alzheimer's disease

Astrocytes play a formative role in memory consolidation during physiological conditions; when dysregulated, astrocytes release glial fibrillary acidic protein (GFAP), which has been linked with negative memory outcomes in animal studies. We examined the association between blood GFAP, memory, and white matter (WM) integrity, accounting for blood markers of AD pathology (i.e., Aβ42) and neurodegeneration (i.e., total tau; neurofilament light chain) in 114 older adults (asymptomatic, n = 69; MCI/AD dementia, n = 45). Higher levels of GFAP were associated with lower memory scores (p < 0.0001), such that for 1 SD increase in mean GFAP values, the memory composite score decreased on average by 0.49 (Standard error = 0.071). These results remained significant after controlling for diagnostic status and AD-related blood biomarkers. Higher GFAP was also related to lower WM integrity in regions vulnerable to AD pathology; however, WM integrity did not account for the association between GFAP and memory. Study findings suggest that higher blood levels of a marker of astrogliosis may reflect impoverished memory functions and white matter health, independent of markers of amyloid or neurodegeneration.

Resilience to Plasma and Cerebrospinal Fluid Amyloid-β in Cognitively Normal Individuals: Findings From Two Cohort Studies

Objective: To define resilience metrics for cognitive decline based on plasma and cerebrospinal fluid (CSF) amyloid-β (Aβ) and examine the demographic, genetic, and neuroimaging factors associated with interindividual differences among metrics of resilience and to demonstrate the ability of such metrics to predict the diagnostic conversion to mild cognitive impairment (MCI). Methods: In this study, cognitively normal (CN) participants with Aβ-positive were included from the Sino Longitudinal Study on Cognitive Decline (SILCODE, n = 100) and Alzheimer's Disease Neuroimaging Initiative (ADNI, n = 144). Using a latent variable model of data, metrics of resilience [brain resilience (BR), cognitive resilience (CR), and global resilience (GR)] were defined based on the plasma Aβ and CSF Aβ. Linear regression analyses were applied to investigate the association between characteristics of individuals (age, sex, educational level, genetic, and neuroimaging factors) and their resilience. The plausibility of these metrics was tested using linear mixed-effects models and Cox regression models in longitudinal analyses. We also compared the effectiveness of these metrics with conventional metrics in predicting the clinical progression. Results: Although individuals in the ADNI cohort were older (74.68 [5.65] vs. 65.38 [4.66], p < 0.001) and had higher educational levels (16.3 [2.6] vs. 12.6 [2.8], p < 0.001) than those in the SILCODE cohort, similar loadings between resilience and its indicators were found within both models. BR and GR were mainly associated with age, women, and brain volume in both cohorts. Prediction models showed that higher CR and GR were related to better cognitive performance, and specifically, all types of resilience to CSF Aβ could predict longitudinal cognitive decline. Conclusion: Different phenotypes of resilience depending on cognition and brain volumes were associated with different factors. Such comprehensive resilience provided insight into the mechanisms of susceptibility for Alzheimer's disease (AD) at the individual level, and interindividual differences in resilience had the potential to predict the disease progression in CN people.

The search for a convenient procedure to detect one of the earliest signs of Alzheimer's disease: A systematic review of the prediction of brain amyloid status

INTRODUCTION

Convenient, cost-effective tests for amyloid beta (Aβ) are needed to identify those at higher risk for developing Alzheimer's disease (AD). This systematic review evaluates recent models that predict dichotomous Aβ. (PROSPERO: CRD42020144734).

METHODS

We searched Embase and identified 73 studies from 29,581 for review. We assessed study quality using established tools, extracted information, and reported results narratively.

RESULTS

We identified few high-quality studies due to concerns about Aβ determination and analytical issues. The most promising convenient, inexpensive classifiers consist of age, apolipoprotein E genotype, cognitive measures, and/or plasma Aβ. Plasma Aβ may be sufficient if pre-analytical variables are standardized and scalable assays developed. Some models lowered costs associated with clinical trial recruitment or clinical screening.

DISCUSSION

Conclusions about models are difficult due to study heterogeneity and quality. Promising prediction models used demographic, cognitive/neuropsychological, imaging, and plasma Aβ measures. Further studies using standardized Aβ determination, and improved model validation are required.

Detection of β-amyloid positivity in Alzheimer's Disease Neuroimaging Initiative participants with demographics, cognition, MRI and plasma biomarkers

In vivo gold standard for the ante-mortem assessment of brain β-amyloid pathology is currently β-amyloid positron emission tomography or cerebrospinal fluid measures of β-amyloid42 or the β-amyloid42/β-amyloid40 ratio. The widespread acceptance of a biomarker classification scheme for the Alzheimer's disease continuum has ignited interest in more affordable and accessible approaches to detect Alzheimer's disease β-amyloid pathology, a process that often slows down the recruitment into, and adds to the cost of, clinical trials. Recently, there has been considerable excitement concerning the value of blood biomarkers. Leveraging multidisciplinary data from cognitively unimpaired participants and participants with mild cognitive impairment recruited by the multisite biomarker study of Alzheimer's Disease Neuroimaging Initiative, here we assessed to what extent plasma β-amyloid42/β-amyloid40, neurofilament light and phosphorylated-tau at threonine-181 biomarkers detect the presence of β-amyloid pathology, and to what extent the addition of clinical information such as demographic data, APOE genotype, cognitive assessments and MRI can assist plasma biomarkers in detecting β-amyloid-positivity. Our results confirm plasma β-amyloid42/β-amyloid40 as a robust biomarker of brain β-amyloid-positivity (area under curve, 0.80-0.87). Plasma phosphorylated-tau at threonine-181 detected β-amyloid-positivity only in the cognitively impaired with a moderate area under curve of 0.67, whereas plasma neurofilament light did not detect β-amyloid-positivity in either group of participants. Clinical information as well as MRI-score independently detected positron emission tomography β-amyloid-positivity in both cognitively unimpaired and impaired (area under curve, 0.69-0.81). Clinical information, particularly APOE ε4 status, enhanced the performance of plasma biomarkers in the detection of positron emission tomography β-amyloid-positivity by 0.06-0.14 units of area under curve for cognitively unimpaired, and by 0.21-0.25 units for cognitively impaired; and further enhancement of these models with an MRI-score of β-amyloid-positivity yielded an additional improvement of 0.04-0.11 units of area under curve for cognitively unimpaired and 0.05-0.09 units for cognitively impaired. Taken together, these multi-disciplinary results suggest that when combined with clinical information, plasma phosphorylated-tau at threonine-181 and neurofilament light biomarkers, and an MRI-score could effectively identify β-amyloid+ cognitively unimpaired and impaired (area under curve, 0.80-0.90). Yet, when the MRI-score is considered in combination with clinical information, plasma phosphorylated-tau at threonine-181 and plasma neurofilament light have minimal added value for detecting β-amyloid-positivity. Our systematic comparison of β-amyloid-positivity detection models identified effective combinations of demographics, APOE, global cognition, MRI and plasma biomarkers. Promising minimally invasive and low-cost predictors such as plasma biomarkers of β-amyloid42/β-amyloid40 may be improved by age and APOE genotype.

Plasma glial fibrillary acidic protein is elevated in cognitively normal older adults at risk of Alzheimer's disease

Glial fibrillary acidic protein (GFAP), an astrocytic cytoskeletal protein, can be measured in blood samples, and has been associated with Alzheimer's disease (AD). However, plasma GFAP has not been investigated in cognitively normal older adults at risk of AD, based on brain amyloid-β (Aβ) load. Cross-sectional analyses were carried out for plasma GFAP and plasma Aβ1-42/Aβ1-40 ratio, a blood-based marker associated with brain Aβ load, in participants (65-90 years) categorised into low (Aβ-, n = 63) and high (Aβ+, n = 33) brain Aβ load groups via Aβ positron emission tomography. Plasma GFAP, Aβ1-42, and Aβ1-40 were measured using the Single molecule array (Simoa) platform. Plasma GFAP levels were significantly higher (p < 0.00001), and plasma Aβ1-42/Aβ1-40 ratios were significantly lower (p < 0.005), in Aβ+ participants compared to Aβ- participants, adjusted for covariates age, sex, and apolipoprotein E-ε4 carriage. A receiver operating characteristic curve based on a logistic regression of the same covariates, the base model, distinguished Aβ+ from Aβ- (area under the curve, AUC = 0.78), but was outperformed when plasma GFAP was added to the base model (AUC = 0.91) and further improved with plasma Aβ1-42/Aβ1-40 ratio (AUC = 0.92). The current findings demonstrate that plasma GFAP levels are elevated in cognitively normal older adults at risk of AD. These observations suggest that astrocytic damage or activation begins from the pre-symptomatic stage of AD and is associated with brain Aβ load. Observations from the present study highlight the potential of plasma GFAP to contribute to a diagnostic blood biomarker panel (along with plasma Aβ1-42/Aβ1-40 ratios) for cognitively normal older adults at risk of AD.

Blood-based Biomarkers of Alzheimer's Disease: The Long and Winding Road

BACKGROUND

Blood-based biomarkers can be very useful in formulating new diagnostic and treatment proposals in the field of dementia, especially in Alzheimer's disease (AD). However, due to the influence of several factors on the reproducibility and reliability of these markers, their clinical use is still very uncertain. Thus, up-to-date knowledge about the main blood biomarkers that are currently being studied is extremely important in order to discover clinically useful and applicable tools, which could also be used as novel pharmacological strategies for the AD treatment.

METHODS

A narrative review was performed based on the current candidates of blood-based biomarkers for AD to show the main results from different studies, focusing on their clinical applicability and association with AD pathogenesis.

OBJECTIVE

The aim of this paper was to carry out a literature review on the major blood-based biomarkers for AD, connecting them with the pathophysiology of the disease.

RESULTS

Recent advances in the search of blood-based AD biomarkers were summarized in this review. The biomarkers were classified according to the topics related to the main hallmarks of the disease such as inflammation, amyloid, and tau deposition, synaptic degeneration and oxidative stress. Moreover, molecules involved in the regulation of proteins related to these hallmarks were described, such as non-coding RNAs, neurotrophins, growth factors and metabolites. Cells or cellular components with the potential to be considered as blood-based AD biomarkers were described in a separate topic.

CONCLUSION

A series of limitations undermine new discoveries on blood-based AD biomarkers. The lack of reproducibility of findings due to the small size and heterogeneity of the study population, different analytical methods and other assay conditions make longitudinal studies necessary in this field to validate these structures, especially when considering a clinical evaluation that includes a broad panel of these potential and promising blood-based biomarkers.

Fluid Candidate Biomarkers for Alzheimer's Disease: A Precision Medicine Approach

A plethora of dynamic pathophysiological mechanisms underpins highly heterogeneous phenotypes in the field of dementia, particularly in Alzheimer's disease (AD). In such a faceted scenario, a biomarker-guided approach, through the implementation of specific fluid biomarkers individually reflecting distinct molecular pathways in the brain, may help establish a proper clinical diagnosis, even in its preclinical stages. Recently, ultrasensitive assays may detect different neurodegenerative mechanisms in blood earlier. ß-amyloid (Aß) peptides, phosphorylated-tau (p-tau), and neurofilament light chain (NFL) measured in blood are gaining momentum as candidate biomarkers for AD. P-tau is currently the more convincing plasma biomarker for the diagnostic workup of AD. The clinical role of plasma Aβ peptides should be better elucidated with further studies that also compare the accuracy of the different ultrasensitive techniques. Blood NFL is promising as a proxy of neurodegeneration process tout court. Protein misfolding amplification assays can accurately detect α-synuclein in cerebrospinal fluid (CSF), thus representing advancement in the pathologic stratification of AD. In CSF, neurogranin and YKL-40 are further candidate biomarkers tracking synaptic disruption and neuroinflammation, which are additional key pathophysiological pathways related to AD genesis. Advanced statistical analysis using clinical scores and biomarker data to bring together individuals with AD from large heterogeneous cohorts into consistent clusters may promote the discovery of pathophysiological causes and detection of tailored treatments.

Combination of plasma amyloid beta(1-42/1-40) and glial fibrillary acidic protein strongly associates with cerebral amyloid pathology

BACKGROUND

Blood-based biomarkers for Alzheimer's disease (AD) might facilitate identification of participants for clinical trials targeting amyloid beta (Abeta) accumulation, and aid in AD diagnostics. We examined the potential of plasma markers Abeta_(1-42/1-40), glial fibrillary acidic protein (GFAP) and neurofilament light (NfL) to identify cerebral amyloidosis and/or disease severity.

METHODS

We included individuals with a positive (n = 176: 63 ± 7 years, 87 (49%) females) or negative (n = 76: 61 ± 9 years, 27 (36%) females) amyloid PET status, with syndrome diagnosis subjective cognitive decline (18 PET+, 25 PET-), mild cognitive impairment (26 PET+, 24 PET-), or AD-dementia (132 PET+). Plasma Abeta_(1-42/1-40), GFAP, and NfL were measured by Simoa. We applied two-way ANOVA adjusted for age and sex to investigate the associations of the plasma markers with amyloid PET status and syndrome diagnosis; logistic regression analysis with Wald's backward selection to identify an optimal panel that identifies amyloid PET positivity; age, sex, and education-adjusted linear regression analysis to investigate associations between the plasma markers and neuropsychological test performance; and Spearman's correlation analysis to investigate associations between the plasma markers and medial temporal lobe atrophy (MTA).

RESULTS

Abeta_(1-42/1-40) and GFAP independently associated with amyloid PET status (p = 0.009 and p < 0.001 respectively), and GFAP and NfL independently associated with syndrome diagnosis (p = 0.001 and p = 0.048 respectively). The optimal panel identifying a positive amyloid status included Abeta_(1-42/1-40) and GFAP, alongside age and APOE (AUC = 88% (95% CI 83-93%), 82% sensitivity, 86% specificity), while excluding NfL and sex. GFAP and NfL robustly associated with cognitive performance on global cognition and all major cognitive domains (GFAP: range standardized β (sβ) = - 0.40 to - 0.26; NfL: range sβ = - 0.35 to - 0.18; all: p < 0.002), whereas Abeta_(1-42/1-40) associated with global cognition, memory, attention, and executive functioning (range sβ = 0.22 - 0.11; all: p < 0.05) but not language. GFAP and NfL showed moderate positive correlations with MTA (both: Spearman's rho> 0.33, p < 0.001). Abeta_(1-42/1-40) showed a moderate negative correlation with MTA (Spearman's rho = - 0.24, p = 0.001).

DISCUSSION AND CONCLUSIONS

Combination of plasma Abeta_(1-42/1-40) and GFAP provides a valuable tool for the identification of amyloid PET status. Furthermore, plasma GFAP and NfL associate with various disease severity measures suggesting potential for disease monitoring.

Serum Hepcidin Levels in Cognitively Normal Older Adults with High Neocortical Amyloid-β Load

BACKGROUND/OBJECTIVE

Hepcidin, an iron-regulating hormone, suppresses the release of iron by binding to the iron exporter protein, ferroportin, resulting in intracellular iron accumulation. Given that iron dyshomeostasis has been observed in Alzheimer's disease (AD) together with elevated serum hepcidin levels, the current study examined whether elevated serum hepcidin levels are an early event in AD pathogenesis by measuring the hormone in cognitively normal older adults at risk of AD, based on high neocortical amyloid-β load (NAL).

METHODS

Serum hepcidin levels in cognitively normal participants (n = 100) aged between 65-90 years were measured using ELISA. To evaluate NAL, all participants underwent 18F-florbetaben positron emission tomography. A standard uptake value ratio (SUVR)<1.35 was classified as low NAL (n = 65) and ≥1.35 (n = 35) was classified as high NAL.

RESULTS

Serum hepcidin was significantly higher in participants with high NAL compared to those with low NAL before and after adjusting for covariates: age, gender, and APOEɛ4 carriage (p < 0.05). A receiver operating characteristic curve based on a logistic regression of the same covariates, the base model, distinguished high from low NAL (area under the curve, AUC = 0.766), but was outperformed when serum hepcidin was added to the base model (AUC = 0.794) and further improved with plasma Aβ42/40 ratio (AUC = 0.829).

CONCLUSION

The present findings indicate that serum hepcidin is increased in individuals at risk for AD and contribute to the body of evidence supporting iron dyshomeostasis as an early event of AD. Further, hepcidin may add value to a panel of markers that contribute toward identifying individuals at risk of AD; however, further validation studies are required.

Urine dicarboxylic acids change in pre-symptomatic Alzheimer's disease and reflect loss of energy capacity and hippocampal volume

Non-invasive biomarkers will enable widespread screening and early diagnosis of Alzheimer’s disease (AD). We hypothesized that the considerable loss of brain tissue in AD will result in detection of brain lipid components in urine, and that these will change in concert with CSF and brain biomarkers of AD. We examined urine dicarboxylic acids (DCA) of carbon length 3–10 to reflect products of oxidative damage and energy generation or balance that may account for changes in brain function in AD. Mean C4-C5 DCAs were lower and mean C7-C10 DCAs were higher in the urine from AD compared to cognitively healthy (CH) individuals. Moreover, mean C4-C5 DCAs were lower and mean C7-C9 were higher in urine from CH individuals with abnormal compared to normal CSF amyloid and Tau levels; i.e., the apparent urine changes in AD also appeared to be present in CH individuals that have CSF risk factors of early AD pathology. In examining the relationship between urine DCAs and AD biomarkers, we found short chain DCAs positively correlated with CSF Aβ₄₂, while C7-C10 DCAs negatively correlated with CSF Aβ₄₂ and positively correlated with CSF Tau levels. Furthermore, we found a negative correlation of C7-C10 DCAs with hippocampal volume (p < 0.01), which was not found in the occipital volume. Urine measures of DCAs have an 82% ability to predict cognitively healthy participants with normal CSF amyloid/Tau. These data suggest that urine measures of increased lipoxidation and dysfunctional energy balance reflect early AD pathology from brain and CSF biomarkers. Measures of urine DCAs may contribute to personalized healthcare by indicating AD pathology and may be utilized to explore population wellness or monitor the efficacy of therapies in clinical trials.

Plasma amyloid is associated with the rate of cognitive decline in cognitively normal elderly: the SCIENCe project

Plasma biomarkers are promising prognostic tools in individuals with subjective cognitive decline (SCD). We aimed to investigate the relationships of baseline plasma amyloid beta (Aβ)42/Aβ40 and total Tau (tTau) with rate of cognitive decline, in comparison to relationships of baseline cerebrospinal fluid (CSF) Aβ42, tTau, and phosphorylated tau181 (pTau181) with rate of cognitive decline. We included 241 subjects with SCD (age = 61 ± 9, 40% female, Mini-Mental State Examination = 28 ± 2) with follow-up (average: 2 ± 2 years, median visits: 3 [range: 1-11]) for re-evaluation of neuropsychological test performance (attention, memory, language, and executive functioning domains). Using age, gender and education-adjusted linear mixed models, we found that lower plasma Aβ42/Aβ40 was associated with steeper rate of decline on tests for attention, memory, and executive functioning, but not language. Lower CSF Aβ42 was associated with steeper decline on tests covering all domains. Associations for plasma amyloid and cognitive decline mirror those of CSF amyloid. Plasma tTau was not associated with rate of cognitive decline, whereas CSF tTau and pTau181 were on multiple tests covering all domains.

A Sensitive and Cost-Effective Chemiluminescence ELISA for Measurement of Amyloid-β 1-42 Peptide in Human Plasma

BACKGROUND

Amyloid-β42 (Aβ42) is associated with plaque formation in the brain of patients with Alzheimer's disease (AD). Studies have suggested the potential utility of plasma Aβ42 levels in the diagnosis, and in longitudinal study of AD pathology. Conventional ELISAs are used to measure Aβ42 levels in plasma but are not sensitive enough to quantitate low levels. Although ultrasensitive assays like single molecule array or immunoprecipitation-mass spectrometry have been developed to quantitate plasma Aβ42 levels, the high cost of instruments and reagents limit their use.

OBJECTIVE

We hypothesized that a sensitive and cost-effective chemiluminescence (CL) immunoassay could be developed to detect low Aβ42 levels in human plasma.

METHODS

We developed a sandwich ELISA using high affinity rabbit monoclonal antibody specific to Aβ42. The sensitivity of the assay was increased using CL substrate to quantitate low levels of Aβ42 in plasma. We examined the levels in plasma from 13 AD, 25 Down syndrome (DS), and 50 elderly controls.

RESULTS

The measurement range of the assay was 0.25 to 500 pg/ml. The limit of detection was 1 pg/ml. All AD, DS, and 45 of 50 control plasma showed measurable Aβ42 levels.

CONCLUSION

This assay detects low levels of Aβ42 in plasma and does not need any expensive equipment or reagents. It offers a preferred alternative to ultrasensitive assays. Since the antibodies, peptide, and substrate are commercially available, the assay is well suited for academic or diagnostic laboratories, and has a potential for the diagnosis of AD or in clinical trials.