Alzheimer's disease and CSF biomarkers: key challenges for broad clinical applications

Changes in CSF sPDGFRβ level and their association with blood-brain barrier breakdown in Alzheimer's disease with or without small cerebrovascular lesions

BACKGROUND

CSF-soluble platelet-derived growth factor receptor beta (sPDGFRβ) is closely associated with pericyte damage. However, the changes in CSF sPDGFRβ levels and their role in blood-brain barrier (BBB) leakage at different stages of Alzheimer's disease (AD), with or without cerebral small vessel disease (CSVD) burden, remain unclear.

METHODS

A total of 158 individuals from the China Aging and Neurodegenerative Disorder Initiative cohort were selected, including 27, 48, and 83 individuals with a clinical dementia rating (CDR) score of 0, 0.5, and 1-2, respectively. CSF total tau, phosphorylated tau181 (p-tau181), Aβ40, and Aβ42 were measured using the Simoa assay. Albumin and CSF sPDGFRβ were measured by commercial assay kits. CSVD burden was assessed by magnetic resonance imaging.

RESULTS

CSF sPDGFRβ was the highest level in the CDR 0.5 group. CSF sPDGFRβ was significantly correlated with the CSF/serum albumin ratio (Q-alb) in the CDR 0-0.5 group (β = 0.314, p = 0.008) but not in the CDR 1-2 group (β = - 0.117, p = 0.317). In the CDR 0-0.5 group, CSF sPDGFRβ exhibited a significant mediating effect between Aβ42/Aβ40 levels and Q-alb (p = 0.038). Q-alb, rather than CSF sPDGFRβ, showed a significant difference between individuals with or without CSVD burden. Furthermore, in the CDR 0.5 group, CSF sPDGFRβ was higher in subjects with progressive mild cognitive impairment than in those with stable mild cognitive impairment subjects (p < 0.001). Meanwhile, CSF sPDGFRβ was significantly associated with yearly changes in MMSE scores in the CDR 0.5 group (β = - 0.400, p = 0.020) and CDR 0.5 (A+) subgroup (β = - 0.542, p = 0.019).

CONCLUSIONS

We provide evidence that increased CSF sPDGFRβ is associated with BBB leakage in the early cognitive impairment stage of AD, which may contribute to cognitive impairment in AD progression.

Correlation of blood-brain barrier leakage with cerebral small vessel disease including cerebral microbleeds in Alzheimer's disease

Background

Blood-brain barrier (BBB) damage is considered an important part of Alzheimer's disease (AD) progression, and cerebral small-vessel disease (CSVD) is commonly associated with AD. However, the relationship between BBB damage, small cerebrovascular lesions, especially cerebral microbleeds (CMBs), and amyloid and tau biomarkers remains controversial. Therefore, our study aimed to further investigate their association in our cohort of patients with AD.

Methods

A total of 139 individuals were divided into probable AD (¹⁸F-florbetapir PET positive, n = 101) and control group (cognitively normal, n = 38). The levels of cerebrospinal fluid (CSF) and plasma t-tau, p-tau181, Aβ40, Aβ42, and albumin were measured using corresponding commercial assay kits, and the CSF/plasma albumin ratio (Qalb), an indicator of BBB dysfunction, was calculated. CSVD burden and the number of CMBs were defined using magnetic resonance imaging.

Results

Patients with AD had higher Qalb (p = 0.0024), higher numbers of CMBs (p = 0.03), and greater CSVD burden (p < 0.0001). In the AD group, CMBs and CSVD correlated with a higher Qalb (p = 0.03), and the numbers of CMBs negatively correlated with CSF Aβ42 (p = 0.02).

Conclusion

Blood-brain barrier damage was accompanied by a more severe burden of CSVD, including CMB, in patients with AD.

The unique effect of TDP-43 on hippocampal subfield morphometry and cognition

•We explored postmortem TDP-43 burden and antemortem hippocampal surface deformation. •TDP-43 was uniquely associated with inward deformation in the hippocampus. •Deformation patterns account for co-existing disease showing TDP-43′s unique effect. •Deformation was significantly correlated with cognition scores.

β-Amyloid in Cerebrospinal Fluid: How to Keep It Floating (Not Sticking) by Standardization of Preanalytic Processes and Collection Tubes

BACKGROUND

Phosphorylated tau (pTau), total tau (tTau), and β-amyloid (Aβ) are established cerebrospinal fluid (CSF) biomarkers used to help diagnose Alzheimer disease. Preanalytic workups of CSF samples lack harmonization, making interlaboratory comparison of these biomarkers challenging. The Aβ adsorbs to sample tubes, yielding underestimated concentrations, and may result in false Alzheimer disease diagnosis. Our primary aim was to compare Aβ recovery across multiple polypropylene tubes and to test the stability of tTau, pTau, and Aβ in the best performing tube.

METHODS

Eight polypropylene tubes were tested using 3 CSF pools with Aβ concentrations <500, 500-1000, and >1000 ng/L. All samples were analyzed in duplicate. Tubes were cut open to assess their different infrared adsorption spectra. Freshly drawn CSF from 14 patients was distributed into 4 Sarstedt 5-mL (no. 63.504.027; Sar5CSF) tubes, left at room temperature for up to 7 days, and analyzed for pTau, tTau, and Aβ by ELISA.

RESULTS

Two Sarstedt 5-mL tubes and a Sarstedt 10-mL (Sar10CSF) tube showed significantly higher Aβ recovery at all 3 concentrations compared with the 5 other tubes. The infrared adsorption spectra of Sar10CSF and Sar5CSF tubes were practically identical, unlike the other tubes. No significant loss of pTau, tTau, and Aβ was observed in CSF left at room temperature for up to 7 days (P > 0.05).

CONCLUSIONS

Recovery of Aβ from Sar5CSF tubes is equivalent to Aβ recovery from Sar10CSF tubes. Levels of pTau, tTau, and Aβ were stable for at least 7 days at room temperature but not at 37 °C.

Exploring a Cost-Efficient Model for Predicting Cerebral Aβ Burden Using MRI and Neuropsychological Markers in the ADNI-2 Cohort

Many studies have focused on the early detection of Alzheimer’s disease (AD). Cerebral amyloid beta (Aβ) is a hallmark of AD and can be observed in vivo via positron emission tomography imaging using an amyloid tracer or cerebrospinal fluid assessment. However, these methods are expensive. The current study aimed to identify and compare the ability of magnetic resonance imaging (MRI) markers and neuropsychological markers to predict cerebral Aβ status in an AD cohort using machine learning (ML) approaches. The prediction ability of candidate markers for cerebral Aβ status was examined by analyzing 724 participants from the ADNI-2 cohort. Demographic variables, structural MRI markers, and neuropsychological test scores were used as input in several ML algorithms to predict cerebral Aβ positivity. Out of five combinations of candidate markers, neuropsychological markers with demographics showed the most cost-efficient result. The selected model could distinguish abnormal levels of Aβ with a prediction ability of 0.85, which is the same as that for MRI-based models. In this study, we identified the prediction ability of MRI markers using ML approaches and showed that the neuropsychological model with demographics can predict Aβ positivity, suggesting a more cost-efficient method for detecting cerebral Aβ status compared to MRI markers.

Cognitive Profiling Related to Cerebral Amyloid Beta Burden Using Machine Learning Approaches

Background: Cerebral amyloid beta (Aβ) is a hallmark of Alzheimer’s disease (AD). Aβ can be detected in vivo with amyloid imaging or cerebrospinal fluid assessments. However, these technologies can be both expensive and invasive, and their accessibility is limited in many clinical settings. Hence the current study aims to identify multivariate cost-efficient markers for Aβ positivity among non-demented individuals using machine learning (ML) approaches.

Methods: The relationship between cost-efficient candidate markers and Aβ status was examined by analyzing 762 participants from the Alzheimer’s Disease Neuroimaging Initiative-2 cohort at baseline visit (286 cognitively normal, 332 with mild cognitive impairment, and 144 with AD; mean age 73.2 years, range 55–90). Demographic variables (age, gender, education, and APOE status) and neuropsychological test scores were used as predictors in an ML algorithm. Cerebral Aβ burden and Aβ positivity were measured using ¹⁸F-florbetapir positron emission tomography images. The adaptive least absolute shrinkage and selection operator (LASSO) ML algorithm was implemented to identify cognitive performance and demographic variables and distinguish individuals from the population at high risk for cerebral Aβ burden. For generalizability, results were further checked by randomly dividing the data into training sets and test sets and checking predictive performances by 10-fold cross-validation.

Results: Out of neuropsychological predictors, visuospatial ability and episodic memory test results were consistently significant predictors for Aβ positivity across subgroups with demographic variables and other cognitive measures considered. The adaptive LASSO model using out-of-sample classification could distinguish abnormal levels of Aβ. The area under the curve of the receiver operating characteristic curve was 0.754 in the mild change group, 0.803 in the moderate change group, and 0.864 in the severe change group, respectively.

Conclusion: Our results showed that the cost-efficient neuropsychological model with demographics could predict Aβ positivity, suggesting a potential surrogate method for detecting Aβ deposition non-invasively with clinical utility. More specifically, it could be a very brief screening tool in various settings to recruit participants with potential biomarker evidence of AD brain pathology. These identified individuals would be valuable participants in secondary prevention trials aimed at detecting an anti-amyloid drug effect in the non-demented population.

A review of biomarkers of Alzheimer's disease in noninvasive samples

The discovery of biomarkers that confer high confidence of presymptomatic Alzheimer's disease (AD) diagnosis would be a valuable tool to study the etiology of the disease, to find risk factors, to discover more treatments and medicines. The present work reviews the potential biomarkers of AD based on the concentration changes of small molecules and chemical elements in noninvasive samples (urine, saliva, hair and others). An updated table with 74 target compounds is produced and ranked. Until the present date, there are a few biomarkers, present in urine, with the most promising potential: isoprostane 8,12-iso-iPF2a-VI, total free amino acids, 8-hydroxy-2'-deoxyguanosine, glycine and enzymatic activity of NaCl-stimulated PON1. All show increased levels in AD carriers, with the exception of NaCl-stimulated PON1.

Biomedical informatics applications for precision management of neurodegenerative diseases

Modern medicine is in the midst of a revolution driven by "big data," rapidly advancing computing power, and broader integration of technology into healthcare. Highly detailed and individualized profiles of both health and disease states are now possible, including biomarkers, genomic profiles, cognitive and behavioral phenotypes, high-frequency assessments, and medical imaging. Although these data are incredibly complex, they can potentially be used to understand multi-determinant causal relationships, elucidate modifiable factors, and ultimately customize treatments based on individual parameters. Especially for neurodegenerative diseases, where an effective therapeutic agent has yet to be discovered, there remains a critical need for an interdisciplinary perspective on data and information management due to the number of unanswered questions. Biomedical informatics is a multidisciplinary field that falls at the intersection of information technology, computer and data science, engineering, and healthcare that will be instrumental for uncovering novel insights into neurodegenerative disease research, including both causal relationships and therapeutic targets and maximizing the utility of both clinical and research data. The present study aims to provide a brief overview of biomedical informatics and how clinical data applications such as clinical decision support tools can be developed to derive new knowledge from the wealth of available data to advance clinical care and scientific research of neurodegenerative diseases in the era of precision medicine.

Is cerebral glucose metabolism related to blood-brain barrier dysfunction and intrathecal IgG synthesis in Alzheimer disease?: A 18F-FDG PET/CT study

The aim of this study was to investigate the relationships between blood-brain barrier (BBB) dysfunction, intrathecal IgG synthesis, and brain glucose consumption as detectable by means of serum/cerebrospinal fluid (CSF) albumin index (Qalb) and IgG index [(CSF IgG/serum IgG) × Serum albumin/CSF albumin)] and 2-deoxy-2-(F) fluoro-D-glucose (F-FDG) positron emission tomography/computed tomography (PET/CT) in a selected population affected by Alzheimer disease (AD). The study included 134 newly diagnosed AD patients according to the NINCDS-ADRDA criteria. The mean (±SD) age of the patients was 70 (±6) years; 60 were male and 64 were female. Mini mental State Examination was equal to 18.9 (±7.2). All patients underwent a CSF assay and magnetic resonance before F-FDG PET scanning. The relationships were evaluated by means of statistical parametric mapping (SPM8). We found a significant negative correlation between the increase of Qalb and F-FDG uptake in the Brodmann Area 42 and 22 that corresponds to the left superior temporal gyrus, with higher Qalb values being related to a reduced glucose consumption in these areas. No significant relationships have been found between brain glucose consumption and IgG index. The results of our study suggest that BBB dysfunction is related to reduction of cortical activity in the left temporal cortex in AD subjects.

Role of cerebrospinal fluid biomarkers to predict conversion to dementia in patients with mild cognitive impairment: a clinical cohort study

BACKGROUND

Cerebrospinal fluid (CSF) levels assessment of Aβ1-42 and Tau proteins may be accurate diagnostic biomarkers for the differentiation of preclinical Alzheimer's disease (AD) from age-associated memory impairment, depression and other forms of dementia in patients with mild cognitive impairment (MCI). The aim of our study was to explore the utility of CSF biomarkers in combination with common cognitive markers as predictors for the risk of AD development, and other forms of dementia, and the time to conversion in community patients with MCI.

METHODS

A group of 71 MCI patients underwent neurological assessment, extended neuropsychological evaluation, routine blood tests, ApoE determination, and lumbar puncture to dose t-tau, p-tau181, Aβ1-42. We investigated baseline CSF and neuropsychological biomarker patterns according to groups stratified with later diagnoses of AD conversion (MCI-AD), other dementia (MCI-NAD) conversion, or clinical stability (sMCI).

RESULTS

Baseline Aβ1-42 CSF levels were significantly lower in MCI-AD patients compared to both sMCI and MCI-NAD. Additionally, p-tau181 was higher in the MCI-AD group compared to sMCI. The MCI-AD subgroup analysis confirmed the role of Aβ1-42 in its predictive role of time to conversion: rapid converters had lower Aβ1-42 levels compared to slow converters. Logistic regression and survival analysis further supported the key predictive role of baseline Aβ1-42 for incipient AD and dementia-free survival.

CONCLUSIONS

Our results confirm the key role of CSF biomarkers in predicting patient conversion from MCI to dementia. The study suggests that CSF biomarkers may also be reliable in a real world clinical setting.

Functional correlates of t-Tau, p-Tau and Aβ₁₋₄₂ amyloid cerebrospinal fluid levels in Alzheimer's disease: a ¹⁸F-FDG PET/CT study

AIM

The aim of the study was to investigate the relationships between cerebrospinal fluid (CSF) levels of t-Tau, p-Tau and amyloid-β (Aβ₁₋₄₂) amyloid peptide and fluorine-18 fluorodeoxyglucose (¹⁸F-FDG) brain distribution in a group of patients with Alzheimer's disease.

MATERIALS AND METHODS

The study included 81 newly diagnosed Alzheimer's disease patients according to the NINCDS-ADRDA criteria. The mean (±SD) age of the patients was 70 (±6) years; 44 were male and 37 were female. All patients underwent a CSF assay and MRI before ¹⁸F-FDG PET scanning. The relationships were evaluated by means of statistical parametric mapping (SPM8).

RESULTS

Increased t-Tau CSF levels were related to reduced glucose consumption in a wide portion of the right frontal lobe [Brodmann area (BA 47)] and limbic lobe bilaterally (BA 31,32), whereas no areas of increased ¹⁸F-FDG uptake related to t-Tau levels were detected. Elevated p-Tau concentrations in CSF were related to increased glucose consumption in both the right and the left limbic lobe and in the left frontal lobe (BA 32 and 8). We did not find any specific cortical area of reduced glucose consumption being related to low levels of Aβ₁₋₄₂ in CSF, whereas a spawn of ¹⁸F-FDG uptake was detectable in BA 18,19 and in the right cerebellum.

CONCLUSION

The results of our study suggest that reduced Aβ₁₋₄₂ concentrations in CSF are related to a wide cortical dysfunction, whereas t-Tau and p-Tau are related to more selective cortical metabolic patterns that mainly involve the cingulate cortex.

CSF Aβ1-42 combined with neuroimaging biomarkers in the early detection, diagnosis and prediction of Alzheimer's disease

The development of validated, qualified, and standardized biomarkers for Alzheimer's disease (AD) that allow for an early presymptomatic diagnosis and discrimination (classification) from other types of dementia and neurodegenerative diseases is warranted to accelerate the successful development of novel disease-modifying therapies. Here, we focus on the value of the 42-residue-long amyloid β isoform (Aβ1-42) peptide in the cerebrospinal fluid as the core, feasible neurobiochemical marker for the amyloidogenic mechanisms in early-onset familial and late-onset sporadic AD. We discuss the role and use of Aβ1-42 in combination with evolving neuroimaging biomarkers in AD detection and diagnosis. Multimodal neuroimaging techniques, directly providing structural-functional-metabolic aspects of brain pathophysiology, are supportive to predict and monitor the progression of the disease. Advances in multimodal neuroimaging provide new insights into brain organization and enable the detection of specific proteins and/or protein aggregates associated with AD. The combination of biomarkers from different methodologies is believed to be of incrementally added risk-value to accurately identify asymptomatic and prodromal individuals who will likely progress to dementia and represent rational biomarker candidates for preventive and symptomatic pharmacological intervention trials.

Biomarkers in Alzheimer's disease: a review

Alzheimer's disease is the most common form of dementia affecting millions of individuals worldwide. It is currently diagnosed only via clinical assessments and confirmed by postmortem brain pathology. The development of validated biomarkers for Alzheimer's disease is essential to improve diagnosis and accelerate the development of new therapies. Biochemical and neuroimaging markers could facilitate diagnosis, predict AD progression from a pre-AD state of mild cognitive impairment (MCI), and be used to monitor efficacies of disease-modifying therapies. Cerebrospinal fluid (CSF) levels of Aβ40, Aβ42, total tau, and phosphorylated tau have diagnostic values in AD. Measurements of the above CSF markers in combination are useful in predicting the risk of progression from MCI to AD. New potential biomarkers are emerging, and CSF or plasma marker profiles may eventually become part of the clinician's toolkit for accurate AD diagnosis and management. These biomarkers along with clinical assessment, neuropsychological testing, and neuroimaging could achieve a much higher diagnostic accuracy for AD and related disorders in the future.

The "Alzheimer's disease signature": potential perspectives for novel biomarkers

Alzheimer's disease is a progressive and neurodegenerative disorder which involves multiple molecular mechanisms. Intense research during the last years has accumulated a large body of data and the search for sensitive and specific biomarkers has undergone a rapid evolution. However, the diagnosis remains problematic and the current tests do not accurately detect the process leading to neurodegeneration. Biomarkers discovery and validation are considered the key aspects to support clinical diagnosis and provide discriminatory power between different stages of the disorder. A considerable challenge is to integrate different types of data from new potent approach to reach a common interpretation and replicate the findings across studies and populations. Furthermore, long-term clinical follow-up and combined analysis of several biomarkers are among the most promising perspectives to diagnose and manage the disease. The present review will focus on the recent published data providing an updated overview of the main achievements in the genetic and biochemical research of the Alzheimer's disease. We also discuss the latest and most significant results that will help to define a specific disease signature whose validity might be clinically relevant for future AD diagnosis.

Role of CSF biomarkers in the diagnosis of prodromal Alzheimer’s disease

Alzheimer’s disease (AD) core biomarkers (Aβ1-42, total tau and phosphorylated tau) have proven to be useful in the clinical practice to evaluate patients with mild cognitive impairment in order to predict progression to Alzheimer’s disease. Multicenter studies have shown an good overall performance of Aβ1-42, total tau and phosphorylated tau in the diagnosis of early AD; however, they also evidenced some possible weakness in terms of variability among centers, which generates some concern about their use in routine clinical practice. Therefore, the need for a joint effort of academia, companies and government agencies is evident. In this article we will provide the state of art of AD biomarkers application for the diagnosis of early AD, also describing some of the most promising new putative biomarkers currently studied. The final aim is to introduce a panel of AD biomarkers that is able to describe the preclinical phases of AD, as fully as possible paving the way to a routine early diagnosis in view of treatment by means of disease-modifying drugs.

Neurodegenerative processes in Alzheimer’s disease: an overview of pathogenesis with strategic biomarker potential

Since Alzheimer’s disease (AD) is the leading cause of senile dementia in the USA, affecting 15% of people over the age of 65 years and almost 50% of those aged over 85 years, the need for an adequate and early diagnosis as well as preventative measure against disease onset and progression is increasing. Epidemiological and molecular studies suggest that AD has multiple etiologies, including genetic mutations, genetic variations affecting susceptibility and environmental factors. All these aspects can promote the formation and the accumulation of insoluble amyloid-β and hyperphosphorylated tau. Since the disease is multifactorial and clinical diagnosis is highly exclusive, the need for a sensitive, specific and reliable biomarker for the disease is crucial. While amyloid and amyloid-related compounds may be useful biomarkers in the early diagnosis of AD, the multitude of other characteristic features of AD presented in this article may be similarly appropriate. For example, genetic mutations play a role in a subset of AD patients (often with early disease onset and more severe disease progression), and genetic analysis could thus play a role in disease diagnosis. Similarly, oxidative damage to various proteins, nucleic acids and other cellular compounds, probably arising from mitochondrial abnormalities, is found early in the disease and may provide certain biochemical signatures of disease. Ultimately, specific assays for genetic, protein and oxidative profiles and mitochondrial abnormalities, as well as those for amyloid-β and its immunological response, may serve as a relevant group of biomarkers that could be informative to individuals regarding risk of disease, as well as for indicators of the progression of disease. Correspondingly, new developments in treatment options will probably be available.

Problems associated with fluid biomarkers for Parkinson's disease

This article focuses on biochemical markers that may be used in the diagnostics of Parkinson's disease and associated disorders, and to identify early cases and stratify patients into subgroups. We present an updated account of some currently available candidate fluid biomarkers, and discuss their diagnostic performance and limitations. We also discuss some of the general problems with Parkinson's disease biomarkers and possible ways of moving forward. It may be concluded that a diagnostically useful fluid biomarker for Parkinson's disease is yet to be identified. However, some interesting candidates exist and may prove useful in the future, alone or when analyzed together in patterns.