Confounding factors influencing amyloid Beta concentration in cerebrospinal fluid

Alzheimer blood biomarkers: practical guidelines for study design, sample collection, processing, biobanking, measurement and result reporting

Alzheimer's disease (AD), the most common form of dementia, remains challenging to understand and treat despite decades of research and clinical investigation. This might be partly due to a lack of widely available and cost-effective modalities for diagnosis and prognosis. Recently, the blood-based AD biomarker field has seen significant progress driven by technological advances, mainly improved analytical sensitivity and precision of the assays and measurement platforms. Several blood-based biomarkers have shown high potential for accurately detecting AD pathophysiology. As a result, there has been considerable interest in applying these biomarkers for diagnosis and prognosis, as surrogate metrics to investigate the impact of various covariates on AD pathophysiology and to accelerate AD therapeutic trials and monitor treatment effects. However, the lack of standardization of how blood samples and collected, processed, stored analyzed and reported can affect the reproducibility of these biomarker measurements, potentially hindering progress toward their widespread use in clinical and research settings. To help address these issues, we provide fundamental guidelines developed according to recent research findings on the impact of sample handling on blood biomarker measurements. These guidelines cover important considerations including study design, blood collection, blood processing, biobanking, biomarker measurement, and result reporting. Furthermore, the proposed guidelines include best practices for appropriate blood handling procedures for genetic and ribonucleic acid analyses. While we focus on the key blood-based AD biomarkers for the AT(N) criteria (e.g., amyloid-beta [Aβ]40, Aβ42, Aβ42/40 ratio, total-tau, phosphorylated-tau, neurofilament light chain, brain-derived tau and glial fibrillary acidic protein), we anticipate that these guidelines will generally be applicable to other types of blood biomarkers. We also anticipate that these guidelines will assist investigators in planning and executing biomarker research, enabling harmonization of sample handling to improve comparability across studies.

Alzheimer's disease biomarker utilization at first referral enhances differential diagnostic precision with simultaneous exclusion of Creutzfeldt-Jakob disease

Most suspected Creutzfeldt-Jakob disease (CJD) cases are eventually diagnosed with other disorders. We assessed the utility of investigating Alzheimer's disease (AD) biomarkers and neurofilament light (NfL) in patients when CJD is suspected. The study cohort consisted of cerebrospinal fluid (CSF) samples referred for CJD biomarker screening wherein amyloid beta 1-42 (Aβ1-42), phosphorylated tau 181 (p-tau181), and total tau (t-tau) could be assessed via Elecsys immunoassays (n = 419) and NfL via enzyme-linked immunosorbent assay (ELISA; n = 161). In the non-CJD sub cohort (n = 371), 59% (219/371) had A+T- (abnormal Aβ1-42 only) and 21% (79/371) returned A+T+ (abnormal Aβ1-42 and p-tau181). In the 48 CJD subjects, a similar AD biomarker profile distribution was observed. To partially address the prevalence of likely pre-symptomatic AD, NfL was utilized to assess for neuronal damage. NfL was abnormal in 76% (25/33) of A+T- subjects 40 to 69 years of age, 80% (20/25) of whom had normal t-tau. This study reinforces AD as an important differential diagnosis of suspected CJD, highlighting that incorporating AD biomarkers and NfL at initial testing is worthwhile.

Tutorial review for peptide assays: An ounce of pre-analytics is worth a pound of cure

The recent increase in peptidomimetic-based medications and the growing interest in peptide hormones has brought new attention to the quantification of peptides for diagnostic purposes. Indeed, the circulating concentrations of peptide hormones in the blood provide a snapshot of the state of the body and could eventually lead to detecting a particular health condition. Although extremely useful, the quantification of such molecules, preferably by liquid chromatography coupled to mass spectrometry, might be quite tricky. First, peptides are subjected to hydrolysis, oxidation, and other post-translational modifications, and, most importantly, they are substrates of specific and nonspecific proteases in biological matrixes. All these events might continue after sampling, changing the peptide hormone concentrations. Second, because they include positively and negatively charged groups and hydrophilic and hydrophobic residues, they interact with their environment; these interactions might lead to a local change in the measured concentrations. A phenomenon such as nonspecific adsorption to lab glassware or materials has often a tremendous effect on the concentration and needs to be controlled with particular care. Finally, the circulating levels of peptides might be low (pico- or femtomolar range), increasing the impact of the aforementioned effects and inducing the need for highly sensitive instruments and well-optimized methods. Thus, despite the extreme diversity of these peptides and their matrixes, there is a common challenge for all the assays: the need to keep concentrations unchanged from sampling to analysis. While significant efforts are often placed on optimizing the analysis, few studies consider in depth the impact of pre-analytical steps on the results. By working through practical examples, this solution-oriented tutorial review addresses typical pre-analytical challenges encountered during the development of a peptide assay from the standpoint of a clinical laboratory. We provide tips and tricks to avoid pitfalls as well as strategies to guide all new developments. Our ultimate goal is to increase pre-analytical awareness to ensure that newly developed peptide assays produce robust and accurate results.

Genetic propensity for cerebral amyloidosis and risk of mild cognitive impairment and Alzheimer's disease within a cognitive reserve framework

INTRODUCTION

We constructed a polygenic risk score (PRS) for β-amyloid (PRSAβ42) to proxy AD pathology and investigated its association with incident Alzheimer's disease (AD)/amnestic mild cognitive impairment (aMCI) and the influence of cognitive reserve (CR), proxied by educational years, on the relationship between PRSAβ42 and AD/aMCI risk.

METHODS

A total of 618 cognitive-normal participants were followed-up for 2.92 years. The association of PRSAβ42 and CR with AD/aMCI incidence was examined with COX models. Then we examined the additive interaction between PRSAβ42 and CR and the CR effect across participants with different PRSAβ42 levels.

RESULTS

Higher PRSAβ42 and CR were associated with a 33.9% higher risk and 8.3% less risk for AD/aMCI, respectively. An additive interaction between PRSAβ42 and CR was observed. High CR was associated with 62.6% less risk of AD/aMCI incidence only in the high-PRSAβ42 group.

DISCUSSION

A super-additive effect of PRSAβ42 and CR on AD/aMCI risk was observed. CR influence was evident in participants with high PRSAβ42.

Different associations between amyloid-βeta 42, amyloid-βeta 40, and amyloid-βeta 42/40 with soluble phosphorylated-tau and disease burden in Alzheimer's disease: a cerebrospinal fluid and fluorodeoxyglucose-positron emission tomography study

BACKGROUND

Despite the high sensitivity of cerebrospinal fluid (CSF) amyloid beta (Aβ)42 to detect amyloid pathology, the Aβ42/Aβ40 ratio (amyR) better estimates amyloid load, with higher specificity for Alzheimer's disease (AD). However, whether Aβ42 and amyR have different meanings and whether Aβ40 represents more than an Aβ42-corrective factor remain to be clarified. Our study aimed to compare the ability of Aβ42 and amyR to detect AD pathology in terms of p-tau/Aβ42 ratio and brain glucose metabolic patterns using fluorodeoxyglucose-positron emission tomography (FDG-PET).

METHODS

CSF biomarkers were analyzed with EUROIMMUN ELISA. We included 163 patients showing pathological CSF Aβ42 and normal p-tau (A + T -  = 98) or pathological p-tau levels (A + T +  = 65) and 36 control subjects (A - T -). A + T - patients were further stratified into those with normal (CSFAβ42 + /amyR -  = 46) and pathological amyR (CSFAβ42 + /amyR +  = 52). We used two distinct cut-offs to determine pathological values of p-tau/Aβ42: (1) ≥ 0.086 and (2) ≥ 0.122. FDG-PET patterns were evaluated in a subsample of patients (n = 46) and compared to 24 controls.

RESULTS

CSF Aβ40 levels were the lowest in A - T - and in CSFAβ42 + /amyR - , higher in CSFAβ42 + /amyR + and highest in A + T + (F = 50.75; p < 0.001), resembling CSF levels of p-tau (F = 192; p < 0.001). We found a positive association between Aβ40 and p-tau in A - T - (β = 0.58; p < 0.001), CSFAβ42 + /amyR - (β = 0.47; p < 0.001), and CSFAβ42 + /amyR + patients (β = 0.48; p < 0.001) but not in A + T + . Investigating biomarker changes as a function of amyR, we observed a weak variation in CSF p-tau (+ 2 z-scores) and Aβ40 (+ 0.8 z-scores) in the normal amyR range, becoming steeper over the pathological threshold of amyR (p-tau: + 5 z-scores, Aβ40: + 4.5 z-score). CSFAβ42 + /amyR + patients showed a significantly higher probability of having pathological p-tau/Aβ42 than CSFAβ42 + /amyR - (cut-off ≥ 0.086: OR 23.3; cut-off ≥ 0.122: OR 8.8), which however still showed pathological values of p-tau/Aβ42 in some cases (cut-off ≥ 0.086: 35.7%; cut-off ≥ 0.122: 17.3%) unlike A - T - . Accordingly, we found reduced FDG metabolism in the temporoparietal regions of CSFAβ42 + /amyR - compared to controls, and further reduction in frontal areas in CSFAβ42 + /amyR + , like in A + T + .

CONCLUSIONS

Pathological p-tau/Aβ42 and FDG hypometabolism typical of AD can be found in patients with decreased CSF Aβ42 levels alone. AmyR positivity, associated with higher Aβ40 levels, is accompanied by higher CSF p-tau and widespread FDG hypometabolism.

Plasma amyloid beta 42 is a biomarker for patients with hereditary, but not sporadic, cerebral amyloid angiopathy

BACKGROUND

The diagnosis of probable cerebral amyloid angiopathy (CAA) is currently mostly based on characteristics of brain MRI. Blood biomarkers would be a cost-effective, easily accessible diagnostic method that may complement diagnosis by MRI and aid in monitoring disease progression. We studied the diagnostic potential of plasma Aβ38, Aβ40, and Aβ42 in patients with hereditary Dutch-type CAA (D-CAA) and sporadic CAA (sCAA).

METHODS

All Aβ peptides were quantified in the plasma by immunoassays in a discovery cohort (11 patients with presymptomatic D-CAA and 24 patients with symptomatic D-CAA, and 16 and 24 matched controls, respectively) and an independent validation cohort (54 patients with D-CAA, 26 presymptomatic and 28 symptomatic, and 39 and 46 matched controls, respectively). In addition, peptides were quantified in the plasma in a group of 61 patients with sCAA and 42 matched controls. We compared Aβ peptide levels between patients and controls using linear regression adjusting for age and sex.

RESULTS

In the discovery cohort, we found significantly decreased levels of all Aβ peptides in patients with presymptomatic D-CAA (Aβ38: p < 0.001; Aβ40: p = 0.009; Aβ42: p < 0.001) and patients with symptomatic D-CAA (Aβ38: p < 0.001; Aβ40: p = 0.01; Aβ42: p < 0.001) compared with controls. In contrast, in the validation cohort, plasma Aβ38, Aβ40, and Aβ42 were similar in patients with presymptomatic D-CAA and controls (Aβ38: p = 0.18; Aβ40: p = 0.28; Aβ42: p = 0.63). In patients with symptomatic D-CAA and controls, plasma Aβ38 and Aβ40 were similar (Aβ38: p = 0.14; Aβ40: p = 0.38), whereas plasma Aβ42 was significantly decreased in patients with symptomatic D-CAA (p = 0.033). Plasma Aβ38, Aβ40, and Aβ42 levels were similar in patients with sCAA and controls (Aβ38: p = 0.092; Aβ40: p = 0.64. Aβ42: p = 0.68).

CONCLUSIONS

Plasma Aβ42 levels, but not plasma Aβ38 and Aβ40, may be used as a biomarker for patients with symptomatic D-CAA. In contrast, plasma Aβ38, Aβ40, and Aβ42 levels do not appear to be applicable as a biomarker in patients with sCAA.

Proteomic Discovery and Validation of Novel Fluid Biomarkers for Improved Patient Selection and Prediction of Clinical Outcomes in Alzheimer’s Disease Patient Cohorts

Alzheimer’s disease (AD) is an irreversible neurodegenerative disease characterized by progressive cognitive decline. The two cardinal neuropathological hallmarks of AD include the buildup of cerebral β amyloid (Aβ) plaques and neurofibrillary tangles of hyperphosphorylated tau. The current disease-modifying treatments are still not effective enough to lower the rate of cognitive decline. There is an urgent need to identify early detection and disease progression biomarkers that can facilitate AD drug development. The current established readouts based on the expression levels of amyloid beta, tau, and phospho-tau have shown many discrepancies in patient samples when linked to disease progression. There is an urgent need to identify diagnostic and disease progression biomarkers from blood, cerebrospinal fluid (CSF), or other biofluids that can facilitate the early detection of the disease and provide pharmacodynamic readouts for new drugs being tested in clinical trials. Advances in proteomic approaches using state-of-the-art mass spectrometry are now being increasingly applied to study AD disease mechanisms and identify drug targets and novel disease biomarkers. In this report, we describe the application of quantitative proteomic approaches for understanding AD pathophysiology, summarize the current knowledge gained from proteomic investigations of AD, and discuss the development and validation of new predictive and diagnostic disease biomarkers.

Importance of cerebrospinal fluid storage conditions for the Alzheimer's disease diagnostics on an automated platform

OBJECTIVES

Alzheimer's disease (AD) is considered the most common cause of dementia in older people. Cerebrospinal fluid (CSF) Aβ1-42, Aβ1-40, total Tau (t-Tau), and phospho Tau (p-Tau) are important biomarkers for the diagnosis, however, they are highly dependent on the pre-analytical conditions. Our aim was to investigate the potential influence of different storage conditions on the simultaneous quantification of these biomarkers in a fully-automated platform to accommodate easier pre-analytical conditions for laboratories.

METHODS

CSF samples were obtained from 11 consecutive patients. Aβ1-42, Aβ1-40, p-Tau, and t-Tau were quantified using the LUMIPULSE G600II automated platform.

RESULTS

Temperature and storage days significantly influenced Aβ1-42 and Aβ1-40 with concentrations decreasing with days spent at 4 °C. The use of the Aβ1-42/Aβ1-40 ratio could partly compensate it. P-Tau and t-Tau were not affected by any of the tested storage conditions. For conditions involving storage at 4 °C, a correction factor of 1.081 can be applied. Diagnostic agreement was almost perfect in all conditions.

CONCLUSIONS

Cutoffs calculated in samples stored at -80 °C can be safely used in samples stored at -20 °C for 15-16 days or up to two days at RT and subsequent freezing at -80 °C. For samples stored at 4 °C, cutoffs would require applying a correction factor, allowing to work with the certainty of reaching the same clinical diagnosis.

Exploring discordant low amyloid beta and high neocortical tau positron emission tomography cases

Introduction

Methods

Results

Discussion

Establishing pre-analytical requirements and maximizing peptide recovery in the analytical phase for mass spectrometric quantification of amyloid-β peptides 1-42 and 1-40 in CSF

OBJECTIVES

Amyloid-β (Aβ) peptides in cerebrospinal fluid (CSF), including Aβ42 (residues 1-42) and Aβ40 (residues 1-40), are utilized as biomarkers in the diagnostic workup of Alzheimer's disease. Careful consideration has been given to the pre-analytical and analytical factors associated with measurement of these peptides via immunoassays; however, far less information is available for mass spectrometric methods. As such, we performed a comprehensive evaluation of pre-analytical and analytical factors specific to Aβ quantification using mass spectrometry.

METHODS

Using our quantitative mass spectrometry assay for Aβ42 and Aβ40 in CSF, we investigated the potential for interference from hemolysate, bilirubin, lipids, and anti-Aβ-antibodies. We also optimized the composition of the calibrator surrogate matrix and Aβ recovery during and after solid phase extraction (SPE).

RESULTS

There was no interreference observed with total protein up to 12 g/L, hemolysate up to 10% (v/v), bilirubin up to 0.5% (v/v), intralipid up to 1% (v/v), or anti-Aβ-antibodies at expected therapeutic concentrations. For hemolysate, bilirubin and lipids, visual CSF contamination thresholds were established. In the analytical phase, Aβ recovery was increased by ∼50% via SPE solvent modifications and by over 150% via modification of the SPE collection plate, which also extended analyte stability in the autosampler.

CONCLUSIONS

Attention to mass spectrometric-specific pre-analytical and analytical considerations improved analytical sensitivity and reproducibility, as well as, established CSF specimen acceptance and rejection criteria for use by the clinical laboratory.

Bias-generating factors in biofluid amyloid-β measurements for Alzheimer's disease diagnosis

Alzheimer's disease (AD) is the most prevalent cause of dementia worldwide, yet the dearth of readily accessible diagnostic biomarkers is a substantial hindrance towards progressing to effective preventive and therapeutic approaches. Due to a long delay between cerebral amyloid-β (Aβ) accumulation and the onset of cognitive impairments, biomarkers that reflect Aβ pathology and enable routine screening for disease progression are of urgent need for application in the clinical diagnosis of AD. According to accumulating evidences, cerebrospinal fluid (CSF) and plasma offer windows to the brain as they allow monitoring of biochemical changes in the brain. Considering the high availability and accuracy in depicting Aβ deposition in the brain, Aβ levels in CSF and plasma are regarded as promising fluid biomarkers for the diagnosis of AD patients at an early stage. However, clinical data with intra- and interindividual variations in the concentrations of CSF and plasma Aβ implicate the need to reevaluate current Aβ detection methods and establish a standardized operating procedure. Therefore, this review introduces three bias-generating factors in biofluid Aβ measurement that may hamper the accurate Aβ quantification and how such complications can be overcome for the widespread implementation of fluid Aβ detection in clinical practice.

White Matter Hyperintensities Are No Major Confounder for Alzheimer's Disease Cerebrospinal Fluid Biomarkers

Background:

The cerebrospinal fluid (CSF) biomarkers amyloid-β 1–42 (Aβ₄₂), total and phosphorylated tau (t-tau, p-tau) are increasingly used to assist in the clinical diagnosis of Alzheimer’s disease (AD). However, CSF biomarker levels can be affected by confounding factors.

Objective:

To investigate the association of white matter hyperintensities (WMHs) present in the brain with AD CSF biomarker levels.

Methods:

We included CSF biomarker and magnetic resonance imaging (MRI) data of 172 subjects (52 controls, 72 mild cognitive impairment (MCI), and 48 AD patients) from 9 European Memory Clinics. A computer aided detection system for standardized automated segmentation of WMHs was used on MRI scans to determine WMH volumes. Association of WMH volume with AD CSF biomarkers was determined using linear regression analysis.

Results:

A small, negative association of CSF Aβ₄₂, but not p-tau and t-tau, levels with WMH volume was observed in the AD (r² = 0.084, p = 0.046), but not the MCI and control groups, which was slightly increased when including the distance of WMHs to the ventricles in the analysis (r² = 0.105, p = 0.025). Three global patterns of WMH distribution, either with 1) a low, 2) a peak close to the ventricles, or 3) a high, broadly-distributed WMH volume could be observed in brains of subjects in each diagnostic group.

Conclusion:

Despite an association of WMH volume with CSF Aβ₄₂ levels in AD patients, the occurrence of WMHs is not accompanied by excess release of cellular proteins in the CSF, suggesting that WMHs are no major confounder for AD CSF biomarker assessment.

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.

Accurate characterization of β-amyloid (Aβ40, Aβ42) standards using species-specific isotope dilution by means of HPLC-ICP-MS/MS

The amyloid β peptide, as one of the main components in senile plaque, represents a defining pathological feature for Alzheimer’s disease, and is therefore commonly used as a biomarker for this disease in clinical analysis. However, the selection of suitable standards is limited here, since only a few are commercially available, and these suffer from varying purity. Hence, the accurate characterization of these standards is of great importance. In this study, we developed a method for the traceable quantification of the peptide content using species-specific isotope dilution and ICP-MS/MS detection. It is based on the separation of the sulfur-containing amino acids methionine and cysteine after oxidation and hydrolysis of the peptide. Using a strong anion exchange column, both amino acids could be separated from each other, as well as from their oxidized forms and sulfate. The sulfur content was determined via ICP-MS/MS using oxygen as reaction gas. Species-specific isotope dilution was enabled by using a ³⁴S-labeled yeast hydrolysate, containing methionine sulfone and cysteic acid with different isotopic composition. The peptide contents of Aβ standards (Aβ40,42), as well as myoglobin and lysozyme with different degrees of purity, were determined. For validation purposes, the standard reference material NIST 2389a, which contains the amino acids in a similar concentration, was subjected to the developed sample preparation and analysis method. In addition to accounting for errors during sample preparation, high levels of accuracy and precision could be obtained using this method, making it fit-for-purpose for the characterization of peptide standards.

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.

Biomarkers of Alzheimer Disease

BACKGROUND

Alzheimer disease (AD) was once a clinical diagnosis confirmed by postmortem autopsy. Today, with the development of AD biomarkers, laboratory assays to detect AD pathology are able to complement clinical diagnosis in symptomatic individuals with uncertain diagnosis. A variety of commercially available assays are performed as laboratory-developed tests, and many more are in development for both clinical and research purposes.

CONTENT

The role of laboratory medicine in diagnosing and managing AD is expanding; thus, it is important for laboratory professionals and ordering physicians to understand the strengths and limitations of both existing and emerging AD biomarker assays. In this review, we will provide an overview of the diagnosis of AD, discuss existing laboratory assays for AD and their recommended use, and examine the clinical performance of emerging AD biomarkers.

SUMMARY

The field of AD biomarker discovery and assay development is rapidly evolving, with recent studies promising to improve both the diagnosis of symptomatic individuals and enrollment and monitoring of asymptomatic individuals in research studies. However, care must be taken to ensure proper use and interpretation of these assays. For clinical purposes, these assays are meant to aid in diagnosis but are not themselves diagnostic. For individuals without symptoms, AD biomarker tests are still only appropriate for research purposes. Additionally, there are analytical challenges that require careful attention, especially for longitudinal use of AD tests.

The Amyloid, Tau, and Neurodegeneration (A/T/N) Classification Applied to a Clinical Research Cohort with Long-Term Follow-Up

Background:

The unbiased amyloid, tau, and neurodegeneration (A/T/N) classification is designed to characterize individuals in the Alzheimer continuum and is currently little explored in clinical cohorts.

Objective:

A retrospective comparison of the A/T/N classification system with the results of a two-year clinical study, with extended follow-up up to 10 years after inclusion.

Methods:

Patients (n = 102) clinically diagnosed as Alzheimer’s disease (AD) with dementia or amnestic mild cognitive impairment (MCI), and 61 cognitively healthy control individuals were included. Baseline cerebrospinal fluid core biomarkers for AD (Aβ₄₂, phosphorylated tau, and total tau) were applied to the A/T/N classification using the final clinical diagnosis at extended follow-up as the gold standard.

Results:

A + T + N+ was a strong predictor for AD dementia, even among cognitively healthy individuals. Amnestic MCI was heterogenous, considering both clinical outcome and distribution within A/T/N. Some individuals with amnestic MCI progressed to clinical AD dementia within all four major A/T/N groups. The highest proportion of progression was among triple positive cases, but progression was also common in individuals with suspected non-Alzheimer pathophysiology (A-T + N+), and those with triple negative status. A-T-N- individuals who were cognitively healthy overwhelmingly remained cognitively intact over time, but in amnestic MCI the clinical outcome was heterogenous, including AD dementia, other dementias, and recovery.

Conclusion:

The A/T/N framework accentuates biomarkers over clinical status. However, when selecting individuals for research, a combination of the two may be necessary since the prognostic value of the A/T/N framework depends on clinical status.

Effect of Patient-Specific Preanalytic Variables on CSF Aβ1-42 Concentrations Measured on an Automated Chemiluminescent Platform

BACKGROUND

Cerebrospinal fluid (CSF) biomarkers are increasingly used to confirm the accuracy of a clinical diagnosis of mild cognitive impairment or dementia due to Alzheimer disease (AD). Recent evidence suggests that fully automated assays reduce the impact of some preanalytical factors on the variability of these measures. This study evaluated the effect of several preanalytical variables common in clinical settings on the variability of CSF β-amyloid 1-42 (Aβ1-42) concentrations.

METHODS

Aβ1-42 concentrations were measured using the LUMIPULSE G1200 from both freshly collected and frozen CSF samples. Preanalytic variables examined were: (1) patient fasting prior to CSF collection, (2) blood contamination of specimens, and (3) aliquoting specimens sequentially over the course of collection (i.e., CSF gradients).

RESULTS

Patient fasting did not significantly affect CSF Aβ1-42 levels. While assessing gradient effects, Aβ1-42 concentrations remained stable within the first 5 1-mL aliquots. However, there is evidence of a gradient effect toward higher concentrations over successive aliquots. Aβ1-42 levels were stable when fresh CSF samples were spiked with up to 2.5% of blood. However, in frozen CSF samples, even 0.25% blood contamination significantly decreased Aβ1-42 concentrations.

CONCLUSIONS

The preanalytical variables examined here do not have significant effects on Aβ1-42 concentrations if fresh samples are processed within 2 h. However, a gradient effect can be observed on Aβ1-42 concentrations after the first 5 mL of collection and blood contamination has a significant impact on Aβ1-42 concentrations once specimens have been frozen.

Plasma metabolomics of presymptomatic PSEN1-H163Y mutation carriers: a pilot study

BACKGROUND AND OBJECTIVE

PSEN1-H163Y carriers, at the presymptomatic stage, have reduced ¹⁸ FDG-PET binding in the cerebrum of the brain (Scholl et al., Neurobiol Aging 32:1388-1399, 2011). This could imply dysfunctional energy metabolism in the brain. In this study, plasma of presymptomatic PSEN1 mutation carriers was analyzed to understand associated metabolic changes.

METHODS

We analyzed plasma from noncarriers (NC, n = 8) and presymptomatic PSEN1-H163Y mutation carriers (MC, n = 6) via untargeted metabolomics using gas and liquid chromatography coupled with mass spectrometry, which identified 1199 metabolites. All the metabolites were compared between MC and NC using univariate analysis, as well as correlated with the ratio of Aβ_{1-42/A β 1-40} , using Spearman's correlation. Altered metabolites were subjected to Ingenuity Pathway Analysis (IPA).

RESULTS

Based on principal component analysis the plasma metabolite profiles were divided into dataset A and dataset B. In dataset A, when comparing between presymptomatic MC and NC, the levels of 79 different metabolites were altered. Out of 79, only 14 were annotated metabolites. In dataset B, 37 metabolites were significantly altered between presymptomatic MC and NC and nine metabolites were annotated. In both datasets, annotated metabolites represent amino acids, fatty acyls, bile acids, hexoses, purine nucleosides, carboxylic acids, and glycerophosphatidylcholine species. 1-docosapentaenoyl-GPC was positively correlated, uric acid and glucose were negatively correlated with the ratio of plasma Aβ_1-42 /Aβ_1-40 (P < 0.05).

INTERPRETATION

This study finds dysregulated metabolite classes, which are changed before the disease symptom onset. Also, it provides an opportunity to compare with sporadic Alzheimer's Disease. Observed findings in this study need to be validated in a larger and independent Familial Alzheimer's Disease (FAD) cohort.

Amyloid B-Protein Aggregation at Physiologically Relevant Concentrations. A Critical Role of Membranes

BACKGROUND

The aggregation of amyloid beta (Aβ) is a self-assembly process that results in the production of fibrillar structures along with neurotoxic aggregates. However, in the vast majority studies in vitro the required Ab concentrations is several orders higher of the physiological relevant concentrations of Aβ; no aggregation is observed at physiological low nanomolar range of Aβ. This suggests that the assembly of Aβ in aggregates in vivo utilizes pathways different from those used in experiments in vitro.

RESULTS

The spontaneous assembly of Aβ oligomers within the physiologically relevant concentration range can occur, but it is the on-surface aggregation mechanism, in which the surface pays a role of the catalyst of the aggregation process. The model for the on-surface aggregation process suggests that the self-assembly of Aβ oligomers is initiated by the interaction of amyloid proteins with the cellular membrane. The membrane catalyzes amyloid aggregation by stabilizing an aggregation-prone conformation of amyloids. The lipid composition contributes to the membrane-mediated misfolding and aggregation of Aβ monomers.

CONCLUSION

Membrane-mediated aggregation catalysis explains a number of observations associated with the development of AD. The affinity of Aβ monomers to the membrane surface is the major factor defining the aggregation process rather than Aβ concentration. According to the model, the development of potential preventions for the interaction of monomeric amyloids with membrane can help control the aggregation process. This is a paradigm change for the development of efficient treatments, early diagnostics, and preventions for Alzheimer's disease.

Impact of Pre-Analytical Differences on Biomarkers in the ADNI and PPMI Studies: Implications in the Era of Classifying Disease Based on Biomarkers

BACKGROUND

Neurodegenerative diseases require characterization based on underlying biology using biochemical biomarkers. Mixed pathology complicates discovery of biomarkers and characterization of cohorts, but inclusion of greater numbers of patients with different, related diseases with frequently co-occurring pathology could allow better accuracy. Combining cohorts collected from different studies would be a more efficient use of resources than recruiting subjects from each population of interest for each study.

OBJECTIVE

To explore the possibility of combining existing datasets by controlling pre-analytic variables in the Alzheimer's Disease Neuroimaging Initiative (ADNI) and Parkinson's Progression Markers Initiative (PPMI) studies.

METHODS

Cerebrospinal fluid (CSF) was collected and processed from 30 subjects according to both the ADNI and PPMI protocols. Relationships between reported levels of Alzheimer's disease (AD) and Parkinson's disease (PD) biomarkers in the same subject under each protocol were examined.

RESULTS

Protocol-related differences were observed for Aβ, but not t-tau or α-syn, and trended different for p-tau and pS129. Values of α-syn differed by platform. Conversion of α-syn values between ADNI and PPMI platforms did not completely eliminate differences in distribution.

DISCUSSION

Factors not captured in the pre-analytical sample handling influence reported biomarker values. Assay standardization and better harmonized characterization of cohorts should be included in future studies of CSF biomarkers.

Validation of the Erlangen Score Algorithm for Differential Dementia Diagnosis in Autopsy-Confirmed Subjects

Background:

Despite decades of research on the optimization of the diagnosis of Alzheimer’s disease (AD), its biomarker-based diagnosis is being hampered by the lack of comparability of raw biomarker data. In order to overcome this limitation, the Erlangen Score (ES), among other approaches, was set up as a diagnostic-relevant interpretation algorithm.

Objective:

To validate the ES algorithm in a cohort of neuropathologically confirmed cases with AD (n = 106) and non-AD dementia (n = 57).

Methods:

Cerebrospinal fluid (CSF) biomarker concentrations of Aβ_1-42, T-tau, and P-tau₁₈₁ were measured with commercially available single analyte ELISA kits. Based on these biomarkers, ES was calculated as previously reported.

Results:

This algorithm proved to categorize AD in different degrees of likelihood, ranging from neurochemically “normal”, “improbably having AD”, “possibly having AD”, to “probably having AD”, with a diagnostic accuracy of 74% using the neuropathology as a reference.

Conclusion:

The ability of the ES to overcome the high variability of raw CSF biomarker data may provide a useful diagnostic tool for comparing neurochemical diagnoses between different labs or methods used.

First amyloid β1-42 certified reference material for re-calibrating commercial immunoassays

INTRODUCTION

Reference materials based on human cerebrospinal fluid were certified for the mass concentration of amyloid beta (Aβ)1-42 (Aβ₄₂ ). They are intended to be used to calibrate diagnostic assays for Aβ₄₂ .

METHODS

The three certified reference materials (CRMs), ERM-DA480/IFCC, ERM-DA481/IFCC and ERM-DA482/IFCC, were prepared at three concentration levels and characterized using isotope dilution mass spectrometry methods. Roche, EUROIMMUN, and Fujirebio used the three CRMs to re-calibrate their immunoassays.

RESULTS

The certified Aβ₄₂ mass concentrations in ERM-DA480/IFCC, ERM-DA481/IFCC, and ERM-DA482/IFCC are 0.45, 0.72, and 1.22 μg/L, respectively, with expanded uncertainties (k = 2) of 0.07, 0.11, and 0.18 μg/L, respectively. Before re-calibration, a good correlation (Pearson's r > 0.97), yet large biases, were observed between results from different commercial assays. After re-calibration the between-assay bias was reduced to < 5%.

DISCUSSION

The Aβ₄₂ CRMs can ensure the equivalence of results between methods and across platforms for the measurement of Aβ₄₂ .

Proteomic profiles for Alzheimer's disease and mild cognitive impairment among adults with Down syndrome spanning serum and plasma: An Alzheimer's Biomarker Consortium-Down Syndrome (ABC-DS) study

INTRODUCTION

Previously generated serum and plasma proteomic profiles were examined among adults with Down syndrome (DS) to determine whether these profiles could discriminate those with mild cognitive impairment (MCI-DS) and Alzheimer's disease (DS-AD) from those cognitively stable (CS).

METHODS

Data were analyzed on n = 305 (n = 225 CS; n = 44 MCI-DS; n = 36 DS-AD) enrolled in the Alzheimer's Biomarker Consortium-Down Syndrome (ABC-DS).

RESULTS

Distinguishing MCI-DS from CS, the serum profile produced an area under the curve (AUC) = 0.95 (sensitivity [SN] = 0.91; specificity [SP] = 0.99) and an AUC = 0.98 (SN = 0.96; SP = 0.97) for plasma when using an optimized cut-off score. Distinguishing DS-AD from CS, the serum profile produced an AUC = 0.93 (SN = 0.81; SP = 0.99) and an AUC = 0.95 (SN = 0.86; SP = 1.0) for plasma when using an optimized cut-off score. AUC remained unchanged to slightly improved when age and sex were included. Eotaxin3, interleukin (IL)-10, C-reactive protein, IL-18, serum amyloid A , and FABP3 correlated fractions at r2 > = 0.90.

DISCUSSION

Proteomic profiles showed excellent detection accuracy for MCI-DS and DS-AD.

Human plasma biomarker responses to inhalational general anaesthesia without surgery

BACKGROUND

Postoperative neurocognitive disorders may arise in part from adverse effects of general anaesthetics on the CNS, especially in older patients or individuals otherwise vulnerable to neurotoxicity because of systemic disease or the presence of pre-existing neuropathology. Previous studies have documented cytokine and injury biomarker responses to surgical procedures that included general anaesthesia, but it is not clear to what degree anaesthetics contribute to these responses.

METHODS

We performed a prospective cohort study of 59 healthy volunteers aged 40-80 yr who did not undergo surgery. Plasma markers of neurological injury and inflammation were measured immediately before and 5 h after induction of general anaesthesia with 1 minimum alveolar concentration of sevoflurane. Biomarkers included interleukin-6 (IL-6), tumour necrosis factor alpha (TNF-α), C-reactive protein (CRP), and neural injury (tau, neurofilament light [NF-L], and glial fibrillary acidic protein [GFAP]).

RESULTS

Baseline biomarkers were in the normal range, although NF-L and GFAP were elevated as a function of age. At 5 h after induction of anaesthesia, plasma tau, NF-L, and GFAP were significantly decreased relative to baseline. Plasma IL-6 was significantly increased after anaesthesia, but by a biologically insignificant degree (<1 pg ml^-1); plasma TNF-α and CRP were unchanged.

CONCLUSIONS

Sevoflurane general anaesthesia without surgery, even in older adults, did not provoke an inflammatory state or neuronal injury at a concentration that is detectable by an acute elevation of measured plasma biomarkers in the early hours after exposure.

CLINICAL TRIAL REGISTRATION

NCT02275026.

Proteomic profiles of incident mild cognitive impairment and Alzheimer's disease among adults with Down syndrome

INTRODUCTION

We sought to determine if proteomic profiles could predict risk for incident mild cognitive impairment (MCI) and Alzheimer's disease (AD) among adults with Down syndrome (DS).

METHODS

In a cohort of 398 adults with DS, a total of n = 186 participants were determined to be non-demented and without MCI or AD at baseline and throughout follow-up; n = 103 had incident MCI and n = 81 had incident AD. Proteomics were conducted on banked plasma samples from a previously generated algorithm.

RESULTS

The proteomic profile was highly accurate in predicting incident MCI (area under the curve [AUC] = 0.92) and incident AD (AUC = 0.88). For MCI risk, the support vector machine (SVM)-based high/low cut-point yielded an adjusted hazard ratio (HR) = 6.46 (P < .001). For AD risk, the SVM-based high/low cut-point score yielded an adjusted HR = 8.4 (P < .001).

DISCUSSION

The current results provide support for our blood-based proteomic profile for predicting risk for MCI and AD among adults with DS.

Proteomic profiles of prevalent mild cognitive impairment and Alzheimer's disease among adults with Down syndrome

INTRODUCTION

We sought to determine if a proteomic profile approach developed to detect Alzheimer's disease (AD) in the general population would apply to adults with Down syndrome (DS).

METHODS

Plasma samples were obtained from 398 members of a community-based cohort of adults with DS. A total of n = 186 participants were determined to be non-demented and without mild cognitive impairment (MCI) at baseline and throughout follow-up; n = 50 had prevalent MCI; n = 42 had prevalent AD.

RESULTS

The proteomic profile yielded an area under the curve (AUC) of 0.92, sensitivity (SN) = 0.80, and specificity (SP) = 0.98 detecting prevalent MCI. For detecting prevalent AD, the proteomic profile yielded an AUC of 0.89, SN = 0.81, and SP = 0.97. The overall profile closely resembled our previously published profile of AD in the general population.

DISCUSSION

These data provide evidence of the applicability of our blood-based algorithm for detecting MCI/AD among adults with DS.

Interaction of Aβ42 with Membranes Triggers the Self-Assembly into Oligomers

The self-assembly of amyloid β (Aβ) proteins into oligomers is the major pathogenic event leading to Alzheimer’s disease (AD). Typical in vitro experiments require high protein concentrations, whereas the physiological concentration of Aβ is in the picomolar to low nanomolar range. This complicates the translation of results obtained in vitro to understanding the aggregation process in vivo. Here, we demonstrate that Aβ42 self-assembles into aggregates on membrane bilayers at low nanomolar concentrations - a pathway in which the membrane plays the role of a catalyst. Additionally, physiological ionic conditions (150 mM NaCl) significantly enhance on-membrane aggregation, leading to the rapid formation of oligomers. The self-assembly process is reversible, so assembled aggregates can dissociate from the membrane surface into the bulk solution to further participate in the aggregation process. Molecular dynamics simulations demonstrate that the transient membrane-Aβ interaction dramatically changes the protein conformation, facilitating the assembly of dimers. The results indicate peptide–membrane interaction is the critical step towards oligomer formation at physiologically low protein concentrations.

CSF biomarkers and amyloid PET: concordance and diagnostic accuracy in a MCI cohort

Brain amyloid deposition is one of the main hallmarks of Alzheimer's disease (AD) and two approaches are available for assessing amyloid pathology in vivo: cerebrospinal fluid (CSF) biomarkers levels and amyloid load visualized by amyloid beta positron emission tomography imaging (Amy-PET) probes. We aimed to investigate the concordance between CSF biomarkers and Amy-PET in a memory clinic cohort. Moreover, using a proper clinical follow-up, we wanted to assess the diagnostic accuracy of CSF and PET biomarkers in predicting the progression of patients with mild cognitive impairment (MCI) to AD dementia. We included 31 MCI patients who underwent [18F]florbetaben PET and CSF sampling (Aβ1-42, t-Tau, p-Tau). A semiquantitative visual scan assessment was used to quantify amyloid deposition in 5 brain regions, rating from 1 (negative), to 2 and 3 (positive). CSF biomarkers were considered abnormal if: Aβ1-42 < 600 pg/ml, p-Tau/Aβ1-42 > 0.08 and t-Tau/Aβ1-42 > 0.52. We also applied less lenient cutoffs of 550 pg/ml and 450 pg/ml for Aβ1-42. The concordance rate was 77% between Amy-PET and CSF Aβ1-42 levels, and 89% between Amy-PET and p-Tau/Aβ1-42 and t-Tau/Aβ1-42. According to the clinical follow-up, Amy-PET (sensitivity [SE] 93.7%, specificity [SP] 80%) exhibited the best diagnostic accuracy in discriminating AD from non-AD, followed by p-Tau/Aβ1-42 ratio and t-Tau/Aβ1-42 ratio (SE 93.7%, SP 66.6%), and Aβ1-42 levels (SE 81%, SP 60%). The regional uptake of [18F]florbetaben PET in the precuneus and the striatum showed the best SP (86.6%). In discordant cases, the clinical diagnosis was most often in agreement with PET results. In general, concordance between CSF biomarkers and Amy-PET was good, especially when the ratios between CSF amyloid and Tau biomarkers were used. However, Amy-PET proved to be superior to CSF Aβ1-42 in terms of diagnostic accuracy for AD, with the possibility to further increase its specificity by focusing the analysis in specific areas such as the precuneus/posterior cingulate cortex and the striatum.

Agreement of amyloid PET and CSF biomarkers for Alzheimer's disease on Lumipulse

OBJECTIVE

To determine the cutoffs that optimized the agreement between ¹⁸ F-Florbetapir positron emission tomography (PET) and Aβ1-42, Aβ1-40, tTau, pTau and their ratios measured in cerebrospinal fluid (CSF) on the LUMIPULSE G600II instrument, we quantified the levels of these four biomarkers in 94 CSF samples from participants of the Sant Pau Initiative on Neurodegeneration (SPIN cohort) using the Lumipulse G System with available ¹⁸ F-Florbetapir imaging.

METHODS

Participants had mild cognitive impairment (n = 35), AD dementia (n = 12), other dementias or neurodegenerative diseases (n = 41), or were cognitively normal controls (n = 6). Levels of Aβ1-42 were standardized to certified reference material. Amyloid scans were assessed visually and through automated quantification. We determined the cutoffs of CSF biomarkers that optimized their agreement with ¹⁸ F-Florbetapir PET and evaluated concordance between markers of the amyloid category.

RESULTS

Aβ1-42, tTau and pTau (but not Aβ1-40) and the ratios with Aβ1-42 had good diagnostic agreement with ¹⁸ F-Florbetapir PET. As a marker of amyloid pathology, the Aβ1-42/Aβ1-40 ratio had higher agreement and better correlation with amyloid PET than Aβ1-42 alone.

INTERPRETATION

CSF biomarkers measured with the Lumipulse G System show good agreement with amyloid imaging in a clinical setting with heterogeneous presentations of neurological disorders. Combination of Aβ1-42 with Aβ1-40 increases the agreement between markers of amyloid pathology.

Pre-analytical stability of novel cerebrospinal fluid biomarkers

Stability of the cerebrospinal fluid (CSF) composition under different pre-analytical conditions is relevant for the diagnostic potential of biomarkers. Our aim was to examine the pre-analytical stability of promising CSF biomarkers that are currently evaluated for their discriminative use in various neurological diseases. Pooled CSF was aliquoted and experimentally exposed to delayed storage: 0, 1, 2, 4, 24, 72, or 168 h at 4 °C or room temperature (RT), or 1-4 months at -20 °C; or up to 7 freeze/thaw (f/t) cycles, before final storage at -80 °C. Eleven CSF biomarkers were screened using immunoassays, liquid chromatography, or enzymatic methods. Levels of neurogranin (truncP75), chitinase-3-like protein (YKL-40), beta-site amyloid precursor protein cleaving enzyme 1 (BACE1), acetylcholinesterase (AChE) enzymatic activity, theobromine, secreted protein acidic and rich in cysteine-like 1 (SPARCL-1) and homovanillic acid (HVA) levels were not affected by the applied storage conditions. 3-Methoxy-4-hydroxyphenylglycol (MHPG) levels linearly and strongly decreased after 4 h at RT (-10%) or 24 h at 4 °C (-27%), and with 6% after every f/t cycle. 5-Methyltetrahydrofolate (5-MTHF) (-29% after 1 week at RT) and 5-hydroxyindoleacetic acid levels (5-HIAA) (-16% after 1 week at RT) were reduced and 3,4-dihydroxyphenylacetic acid (DOPAC) levels (+22% after 1 week at RT) increased, but only after >24 h at RT. Ten out of eleven potential CSF novel biomarkers showed very limited change under common storage and f/t conditions, suggesting that these CSF biomarkers can be trustfully tested under the pre-analytical conditions present across different cohorts.

Towards a unified protocol for handling of CSF before β-amyloid measurements

Background

Widespread implementation of Alzheimer’s disease biomarkers in routine clinical practice requires the establishment of standard operating procedures for pre-analytical handling of cerebrospinal fluid (CSF).

Methods

Here, CSF collection and storage protocols were optimized for measurements of β-amyloid (Aβ). We investigated the effects of (1) storage temperature, (2) storage time, (3) centrifugation, (4) sample mixing, (5) blood contamination, and (6) collection gradient on CSF levels of Aβ. For each study participant, we used fresh CSF directly collected into a protein low binding (LoB) tube that was analyzed within hours after lumbar puncture (LP) as standard of truth. Aβ42 and Aβ40 were measured in de-identified CSF samples using EUROIMMUN and Mesoscale discovery assays.

Results

CSF Aβ42 and Aβ40 were stable for at least 72 h at room temperature (RT), 1 week at 4 °C, and 2 weeks at − 20 °C and − 80 °C. Centrifugation of non-blood-contaminated CSF or mixing of samples before the analysis did not affect Aβ levels. Addition of 0.1–10% blood to CSF that was stored at RT without centrifugation led to a dose- and time-dependent decrease in Aβ42 and Aβ40, while Aβ42/Aβ40 did not change. The effects of blood contamination were mitigated by centrifugation and/or storage at 4 °C or − 20 °C. Aβ levels did not differ between the first to fourth 5-ml portions of CSF.

Conclusions

CSF can be stored for up to 72 h at RT, 1 week at 4 °C, or at least 2 weeks at either − 20 °C or − 80 °C before Aβ measurements. Centrifugation of fresh non-blood-contaminated CSF after LP, or mixing before analysis, is not required. In case of visible blood contamination, centrifugation and storage at 4 °C or − 20 °C is recommended. After discarding the first 2 ml, any portion of up to 20 ml of CSF is suitable for Aβ analysis. These findings will be important for the development of a clinical routine protocol for pre-analytical handling of CSF.

Electronic supplementary material

The online version of this article (10.1186/s13195-019-0517-9) contains supplementary material, which is available to authorized users.

Interaction of Amyloidogenic Proteins with Membranes and Molecular Mechanism for the Development of Alzheimer's disease

Molecular mechanism of diseases like Alzheimer's disease (AD) and Parkinson's diseases (PD) is associated with misfolding of specific proteins, such as amyloid beta (Aβ) proteins in the case of AD, followed by their self-assembly into toxic oligomers along with the formation of amyloid fibrils assembled as plaques in the brain. Interaction of Aβ with membrane can lead to membrane damage; this process is considered as the major factor associated with the AD development. Additionally, membrane can facilitate the aggregation process of Aβ proteins. This important property of membranes is discussed in this review. A specific emphasis is given to the recently discovered property of cellular membranes to catalyze the initial step of Aβ aggregation process by which self-assembly of Aβ can be observed at physiologically low concentrations of Aβ proteins. At such low concentrations, no spontaneous aggregation occurs in the bulk solution. This fact was a major weakness of the protein aggregation model for AD. The catalytic property of membrane surfaces towards Aβ aggregation depends on the membrane composition. This finding suggests a number of novel ideas on the development of treatments and preventions for AD, which is briefly discussed in the review.

The Past and the Future of Alzheimer's Disease Fluid Biomarkers

Following the development of the first methods to measure the core Alzheimer’s disease (AD) cerebrospinal fluid (CSF) biomarkers total-tau (T-tau), phosphorylated tau (P-tau) and the 42 amino acid form of amyloid-β (Aβ₄₂), there has been an enormous expansion of this scientific research area. Today, it is generally acknowledged that these biochemical tests reflect several central pathophysiological features of AD and contribute diagnostically relevant information, also for prodromal AD. In this article in the 20th anniversary issue of the Journal of Alzheimer’s Disease, we review the AD biomarkers, from early assay development to their entrance into diagnostic criteria. We also summarize the long journey of standardization and the development of assays on fully automated instruments, where we now have high precision and stable assays that will serve as the basis for common cut-off levels and a more general introduction of these diagnostic tests in clinical routine practice. We also discuss the latest expansion of the AD CSF biomarker toolbox that now also contains synaptic proteins such as neurogranin, which seemingly is specific for AD and predicts rate of future cognitive deterioration. Last, we are at the brink of having blood biomarkers that may be implemented as screening tools in the early clinical management of patients with cognitive problems and suspected AD. Whether this will become true, and whether it will be plasma Aβ₄₂, the Aβ_42/40 ratio, or neurofilament light, or a combination of these, remains to be established in future clinical neurochemical studies.

Cerebrospinal Fluid Biomarkers for Early and Differential Alzheimer's Disease Diagnosis

An accurate and early diagnosis of Alzheimer’s disease (AD) is important to select optimal patient care and is critical in current clinical trials targeting core AD neuropathological features. The past decades, much progress has been made in the development and validation of cerebrospinal fluid (CSF) biomarkers for the biochemical diagnosis of AD, including standardization and harmonization of (pre-) analytical procedures. This has resulted in three core CSF biomarkers for AD diagnostics, namely the 42 amino acid long amyloid-beta peptide (Aβ_1-42), total tau protein (T-tau), and tau phosphorylated at threonine 181 (P-tau₁₈₁). These biomarkers have been incorporated into research diagnostic criteria for AD and have an added value in the (differential) diagnosis of AD and related disorders, including mixed pathologies, atypical presentations, and in case of ambiguous clinical dementia diagnoses. The implementation of the CSF Aβ_1-42/Aβ_1-40 ratio in the core biomarker panel will improve the biomarker analytical variability, and will also improve early and differential AD diagnosis through a more accurate reflection of pathology. Numerous biomarkers are being investigated for their added value to the core AD biomarkers, aiming at the AD core pathological features like the amyloid mismetabolism, tau pathology, or synaptic or neuronal degeneration. Others aim at non-AD neurodegenerative, vascular or inflammatory hallmarks. Biomarkers are essential for an accurate identification of preclinical AD in the context of clinical trials with potentially disease-modifying drugs. Therefore, a biomarker-based early diagnosis of AD offers great opportunities for preventive treatment development in the near future.

Advantages and disadvantages of the use of the CSF Amyloid β (Aβ) 42/40 ratio in the diagnosis of Alzheimer's Disease

The cerebrospinal fluid (CSF) biochemical markers (biomarkers) Amyloidβ 42 (Aβ₄₂), total Tau (T-tau) and Tau phosphorylated at threonine 181 (P-tau₁₈₁) have proven diagnostic accuracy for mild cognitive impairment and dementia due to Alzheimer’s Disease (AD). In an effort to improve the accuracy of an AD diagnosis, it is important to be able to distinguish between AD and other types of dementia (non-AD). The concentration ratio of Aβ₄₂ to Aβ₄₀ (Aβ_42/40 Ratio) has been suggested to be superior to the concentration of Aβ₄₂ alone when identifying patients with AD. This article reviews the available evidence on the use of the CSF Aβ_42/40 ratio in the diagnosis of AD. Based on the body of evidence presented herein, it is the conclusion of the current working group that the CSF Aβ_42/40 ratio, rather than the absolute value of CSF Aβ₄₂, should be used when analysing CSF AD biomarkers to improve the percentage of appropriately diagnosed patients.

Preanalytical sample handling recommendations for Alzheimer's disease plasma biomarkers

Introduction

We examined the influence of common preanalytical factors on the measurement of Alzheimer's disease-specific biomarkers in human plasma.

Methods

Amyloid β peptides (Aβ[1-40], Aβ[1-42]) and total Tau plasma concentrations were quantified using fully automated Roche Elecsys assays.

Results

Aβ(1-40), Aβ(1-42), and total Tau plasma concentrations were not affected by up to three freeze/thaw cycles, up to five tube transfers, the collection tube material, or the size; circadian rhythm had a minor effect. All three biomarkers were influenced by the anticoagulant used, particularly total Tau. Aβ concentrations began decreasing 1 hour after blood draw/before centrifugation and decreased by up to 5% and 10% at 2 and 6 hours, respectively. For separated plasma, time to measurement influenced Aβ levels by up to 7% after 6 hours and 10% after 24 hours.

Discussion

Our findings provide guidance for standardizing blood sample collection, handling, and storage to ensure reliable analysis of Alzheimer's disease plasma biomarkers in routine practice and clinical trials.

A proteomic signature for dementia with Lewy bodies

Introduction

We sought to determine if a proteomic profile approach developed to detect Alzheimer's disease would distinguish patients with Lewy body disease from normal controls, and if it would distinguish dementia with Lewy bodies (DLB) from Parkinson's disease (PD).

Methods

Stored plasma samples were obtained from 145 patients (DLB n = 57, PD without dementia n = 32, normal controls n = 56) enrolled from patients seen in the Behavioral Neurology or Movement Disorders clinics at the Mayo Clinic, Florida. Proteomic assays were conducted and analyzed as per our previously published protocols.

Results

In the first step, the proteomic profile distinguished the DLB-PD group from controls with a diagnostic accuracy of 0.97, sensitivity of 0.91, and specificity of 0.86. In the second step, the proteomic profile distinguished the DLB from PD groups with a diagnostic accuracy of 0.92, sensitivity of 0.94, and specificity of 0.88.

Discussion

These data provide evidence of the potential utility of a multitiered blood-based proteomic screening method for detecting DLB and distinguishing DLB from PD.

Association of longitudinal white matter degeneration and cerebrospinal fluid biomarkers of neurodegeneration, inflammation and Alzheimer's disease in late-middle-aged adults

Alzheimer's disease (AD) is characterized by substantial neurodegeneration, including both cortical atrophy and loss of underlying white matter fiber tracts. Understanding longitudinal alterations to white matter may provide new insights into trajectories of brain change in both healthy aging and AD, and fluid biomarkers may be particularly useful in this effort. To examine this, 151 late-middle-aged participants enriched with risk for AD with at least one lumbar puncture and two diffusion tensor imaging (DTI) scans were selected for analysis from two large observational and longitudinally followed cohorts. Cerebrospinal fluid (CSF) was assayed for biomarkers of AD-specific pathology (phosphorylated-tau/Aβ42 ratio), axonal degeneration (neurofilament light chain protein, NFL), dendritic degeneration (neurogranin), and inflammation (chitinase-3-like protein 1, YKL-40). Linear mixed effects models were performed to test the hypothesis that biomarkers for AD, neurodegeneration, and inflammation, or two-year change in those biomarkers, would be associated with worse white matter health overall and/or progressively worsening white matter health over time. At baseline in the cingulum, phosphorylated-tau/Aβ42 was associated with higher mean diffusivity (MD) overall (intercept) and YKL-40 was associated with increases in MD over time. Two-year change in neurogranin was associated with higher mean diffusivity and lower fractional anisotropy overall (intercepts) across white matter in the entire brain and in the cingulum. These findings suggest that biomarkers for AD, neurodegeneration, and inflammation are potentially important indicators of declining white matter health in a cognitively healthy, late-middle-aged cohort.

MicroRNAs as diagnostic and therapeutic tools for Alzheimer's disease: advances and limitations

Alzheimer’s disease (AD) is the most common age-related, progressive neurodegenerative disease. It is characterized by memory loss and cognitive decline and responsible for most cases of dementia in the elderly. Late-onset or sporadic AD accounts for > 95% of cases, with age at onset > 65 years. Currently there are no drugs or other therapeutic agents available to prevent or delay the progression of AD. The cellular and molecular changes occurring in the brains of individuals with AD include accumulation of β-amyloid peptide and hyperphosphorylated tau protein, decrease of acetylcholine neurotransmitter, inflammation, and oxidative stress. Aggregation of β-amyloid peptide in extracellular plaques and the hyperphosphorylated tau protein in intracellular neurofibrillary tangles are characteristic of AD. A major challenge is identifying molecular biomarkers of the early-stage AD in patients as most studies have been performed with blood or brain tissue samples (postmortem) at late-stage AD. Subjects with mild cognitive impairment almost always have the neuropathologic features of AD with about 50% of mild cognitive impairment patients progressing to AD. They could provide important information about AD pathomechanism and potentially also highlight minimally or noninvasive, easy-to-access biomarkers. MicroRNAs are dysregulated in AD, and may facilitate the early detection of the disease and potentially the continual monitoring of disease progression and allow therapeutic interventions to be evaluated. Four recent reviews have been published of microRNAs in AD, each of which identified areas of weakness or limitations in the reported studies. Importantly, studies in the last three years have shown considerable progress in overcoming some of these limitations and identifying specific microRNAs as biomarkers for AD and mild cognitive impairment. Further large-scale human studies are warranted with less disparity in the study populations, and using an appropriate method to validate the findings.

Guidelines for CSF Processing and Biobanking: Impact on the Identification and Development of Optimal CSF Protein Biomarkers

The field of neurological diseases strongly needs biomarkers for early diagnosis and optimal stratification of patients in clinical trials or to monitor disease progression. Cerebrospinal fluid (CSF) is one of the main sources for the identification of novel protein biomarkers for neurological diseases. Despite the enormous efforts employed to identify novel CSF biomarkers, the high variability observed across different studies has hampered their validation and implementation in clinical practice. Such variability is partly caused by the effect of different pre-analytical confounding factors on protein stability, highlighting the importance to develop and comply with standardized operating procedures. In this chapter, we describe the international consensus pre-analytical guidelines for CSF processing and biobanking that have been established during the last decade, with a special focus on the influence of pre-analytical confounders on the global CSF proteome. In addition, we provide novel results on the influence of different delayed storage and freeze/thaw conditions on the CSF proteome using two novel large multiplex protein arrays (SOMAscan and Olink). Compliance to consensus guidelines will likely facilitate the successful development and implementation of CSF protein biomarkers in both research and clinical settings, ultimately facilitating the successful development of disease-modifying therapies.

Impact of CSF storage volume on the analysis of Alzheimer's disease biomarkers on an automated platform

OBJECTIVES

To assess the potential influence of the ratio between the storage tube surface area and the volume of cerebrospinal fluid (CSF) (surface/volume) on the quantifications of four Alzheimer's disease (AD) biomarkers on the Lumipulse G600II automated platform.

METHODS

CSF samples of 10 consecutive patients were stored in 2 ml polypropylene tubes containing four different CSF volumes: 1.5 ml, 1 ml, 0.5 ml and 0.25 ml. Concentration of CSF Aβ1-42, Aβ1-40, t-Tau and p-Tau were measured in all aliquots using the LUMIPULSE G600II automated platform from Fujirebio.

RESULTS

Levels of CSF Aβ1-42 and Aβ1-40 were lower in samples stored with lower volumes (higher surface/volume ratios). This decrease was partly compensated by using the ratio Aβ1-42/Aβ1-40. Quantification of t-Tau and p-Tau were not influenced by this pre-analytical condition.

CONCLUSION

The surface/volume ratio can potentially influence the results of amyloid AD biomarkers. It appears essential to take into account the surface/volume ratio of the storage tubes when quantifying CSF biomarkers in clinical routine.

Preanalytical approaches to improve recovery of amyloid-β peptides from CSF as measured by immunological or mass spectrometry-based assays

Background

Amyloid-β 1–42 (Aβ_1–42) peptide is a well-established cerebrospinal fluid (CSF) biomarker for Alzheimer’s disease (AD). Reduced levels of Aβ_1–42 are indicative of AD, but significant variation in the absolute concentrations of this analyte has been described for both healthy and diseased populations. Preanalytical factors such as storage tube type are reported to impact Aβ recovery and quantification accuracy. Using complementary immunological and mass spectrometry-based approaches, we identified and characterized preanalytical factors that influence measured concentrations of CSF Aβ peptides in stored samples.

Methods

CSF from healthy control subjects and patients with AD was aliquoted into polypropylene tubes at volumes of 0.1 ml and 0.5 ml. CSF Aβ_1–42 concentrations were initially measured by immunoassay; subsequent determinations of CSF Aβ_1–42, Aβ_1–40, Aβ_1–38, Aβ_1–37, and Aβ_1–34 concentrations were made with an absolute quantitative mass spectrometry assay. In a second study, CSF from healthy control subjects and patients with dementia was denatured with guanidine hydrochloride (GuHCl) at different stages of the CSF collection and aliquoting process and then measured with the mass spectrometry assay.

Results

Two distinct immunoassays demonstrated that CSF Aβ_1–42 concentrations measured from 0.5-ml aliquots were higher than those from 0.1-ml aliquots. Tween-20 surfactant supplementation increased Aβ_1–42 recovery but did not effectively resolve measured concentration differences associated with aliquot size. A CSF Aβ peptide mass spectrometry assay confirmed that Aβ peptide recovery was linked to sample volume. Unlike the immunoassay experiments, measured differences were consistently eliminated when aliquots were denatured in the original sample tube. Recovery from a panel of low-retention polypropylene tubes was assessed, and 1.5-ml Eppendorf LoBind® tubes were determined to be the least absorptive for Aβ_1–42. A comparison of CSF collection and processing methods suggested that Aβ peptide recovery was improved by denaturing CSF earlier in the collection/aliquoting process and that the Aβ_1–42/Aβ_1–40 ratio was a useful method to reduce variability.

Conclusions

Analyte loss due to nonspecific sample tube adsorption is a significant preanalytical factor that can compromise the accuracy of CSF Aβ_1–42 measurements. Sample denaturation during aliquoting increases recovery of Aβ peptides and improves measurement accuracy. The Aβ_1–42/Aβ_1–40 ratio can overcome some of the quantitative variability precipitated by preanalytical factors affecting recovery.

Electronic supplementary material

The online version of this article (10.1186/s13195-018-0445-0) contains supplementary material, which is available to authorized users.

Cerebrospinal Fluid BACE1 Activity and sAβPPβ as Biomarker Candidates of Alzheimer's Disease

BACKGROUND/AIMS

The utility of β-site amyloid-β precursor protein (AβPP) cleaving enzyme 1 (BACE1) activity and soluble AβPP β (sAβPPβ) levels in cerebrospinal fluid (CSF) in detecting Alzheimer's disease (AD) is still elusive.

METHODS

BACE1 activity and sAβPPβ concentration were measured in patients with AD dementia (n = 56) and mild cognitive impairment (MCI) due to AD (n = 76) with abnormal routine AD CSF markers, in patients with MCI with normal CSF markers (n = 39), and in controls without preclinical AD (n = 48). In a subsample with available 18F-fluorodeoxyglucose positron emission tomography (FDG PET) data, ordinal regression models were employed to compare the contribution of BACE1 and sAβPPβ to correct diagnostic classification to that of FDG PET.

RESULTS

BACE1 activity was significantly higher in patients with MCI due to AD compared to both controls and patients with MCI with normal CSF markers. sAβPPβ did not differ between any of the studied groups. Interestingly, BACE1 activity was not found to be inferior to FDG PET as predictive covariate in differentiating between the diagnostic groups.

CONCLUSIONS

Further studies using biomarker-underpinned diagnoses are warranted to shed more light on the potential diagnostic utility of BACE1 activity as AD biomarker candidate in MCI.

Diagnostic performance of Elecsys immunoassays for cerebrospinal fluid Alzheimer's disease biomarkers in a nonacademic, multicenter memory clinic cohort: The ABIDE project

Introduction

We compared the automated Elecsys and manual Innotest immunoassays for cerebrospinal fluid (CSF) Alzheimer's disease biomarkers in a multicenter diagnostic setting.

Methods

We collected CSF samples from 137 participants in eight local memory clinics. Amyloid β(1–42) (Aβ42), total tau (t-tau), and phosphorylated tau (p-tau) were centrally analyzed with Innotest and Elecsys assays. Concordances between methods were assessed.

Results

Biomarker results strongly correlated between assays with Spearman's ρ 0.94 for Aβ42, 0.98 for t-tau, and 0.98 for p-tau. Using Gaussian mixture modeling, cohort-specific cut-points were estimated at 1092 pg/mL for Aβ42, 235 pg/mL for t-tau, and 24 pg/mL for p-tau. We found an excellent concordance of biomarker abnormality between assays of 97% for Aβ42 and 96% for both t-tau and p-tau.

Discussion

The high concordances between Elecsys and Innotest in this nonacademic, multicenter cohort support the use of Elecsys for CSF Alzheimer's disease diagnostics and allow conversion of results between methods.

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Method comparison of 137 CSF samples collected in eight nonacademic memory clinics.

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Innotest and Elecsys strongly correlated: ρ = 0.94 Aβ42; 0.98 t-tau; 0.98 p-tau.

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Concordances of biomarker abnormalities: 97% Aβ42; 96% t-tau and p-tau.

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Concordance of NIA-AA–based Alzheimer's disease profile (Aβ42 decreased and p-tau increased): 89%.

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Preanalytical protocol deviations did not show effects on biomarker correlations.

Diagnosis of neurodegenerative dementia: where do we stand, now?

After many years of large efforts made for understanding the pathogenesis of dementias, the early diagnosis of these degenerative diseases remains an open challenge. Alzheimer's disease (AD) represents the most common form of dementia, followed by Lewy body disease and frontotemporal degeneration. Actually, different pathological processes can determine similar and overlapping clinical syndrome. To detect in vivo the pathological process underlying progressive cognitive and behavior impairment, the Internationals guidelines recommend the use of biological and topographical markers, which can reflect neuropathological modifications in brain. In cerebrospinal fluid (CSF), decrease of amyloid beta 1-42 (Aβ42) and a low ratio of Aβ42 with amyloid beta 1-40 (Aβ42/Aβ40), together with the increase of both total tau protein (t-tau) and phosphorylated tau (p-tau), contribute to define the "Alzheimer's signature". This review points out on the evolution of the concept for early diagnosis of AD, and on the current use of CSF proteins for research purposes and in clinical setting. Then, we discuss the limitations and drawbacks in wide application of CSF biomarkers for diagnosing degenerative dementias, and on the role of laboratory medicine to convey these biomarkers from "research" toward "clinical practice".

Interlaboratory proficiency processing scheme in CSF aliquoting: implementation and assessment based on biomarkers of Alzheimer's disease

BACKGROUND

In this study, we tested to which extent possible between-center differences in standardized operating procedures (SOPs) for biobanking of cerebrospinal fluid (CSF) samples influence the homogeneity of the resulting aliquots and, consequently, the concentrations of the centrally analyzed selected Alzheimer's disease biomarkers.

METHODS

Proficiency processing samples (PPSs), prepared by pooling of four individual CSF samples, were sent to 10 participating centers, which were asked to perform aliquoting of the PPSs into two secondary aliquots (SAs) under their local SOPs. The resulting SAs were shipped to the central laboratory, where the concentrations of amyloid beta (Aβ) 1-42, pTau181, and albumin were measured in one run with validated routine analytical methods. Total variability of the concentrations, and its within-center and between-center components, were analyzed with hierarchical regression models.

RESULTS

We observed neglectable variability in the concentrations of pTau181 and albumin across the centers and the aliquots. In contrast, the variability of the Aβ1-42 concentrations was much larger (overall coefficient of variation 31%), with 28% of the between-laboratory component and 10% of the within-laboratory (i.e., between-aliquot) component. We identified duration of the preparation of the aliquots and the centrifugation force as two potential confounders influencing within-center variability and biomarker concentrations, respectively.

CONCLUSIONS

Proficiency processing schemes provide objective evidence for the most critical preanalytical variables. Standardization of these variables may significantly enhance the quality of the collected biospecimens. Studies utilizing retrospective samples collected under different local SOPs need to consider such differences in the statistical evaluations of the data.

Concordance Between Cerebrospinal Fluid Biomarkers with Alzheimer's Disease Pathology Between Three Independent Assay Platforms

BACKGROUND

To enhance the accuracy of clinical diagnosis for Alzheimer's disease (AD), pre-mortem biomarkers have become increasingly important for diagnosis and for participant recruitment in disease-specific treatment trials. Cerebrospinal fluid (CSF) biomarkers provide a low-cost alternative to positron emission tomography (PET) imaging for in vivo quantification of different AD pathological hallmarks in the brains of affected subjects; however, consensus around the best platform, most informative biomarker and correlations across different methodologies are controversial.

OBJECTIVE

Assessing levels of Aβ-amyloid and tau species determined using three different versions of immunoassays, the current study explored the ability of CSF biomarkers to predict PET Aβ-amyloid (32 Aβ-amyloid-and 45 Aβ-amyloid+), as well as concordance between CSF biomarker levels and PET Aβ-amyloid imaging.

METHODS

Prediction and concordance analyses were performed using a sub-cohort of 77 individuals (48 healthy controls, 15 with mild cognitive impairment, and 14 with AD) from the Australian Imaging Biomarker and Lifestyle study of aging.

RESULTS

Across all three platforms, the T-tau/Aβ42 ratio biomarker had modestly higher correlation with SUVR/BeCKeT (ρ= 0.69-0.8) as compared with Aβ42 alone (ρ= 0.66-0.75). Differences in CSF biomarker levels between the PET Aβ-amyloid-and Aβ-amyloid+ groups were strongest for the Aβ42/Aβ40 and T-tau/Aβ42 ratios (p < 0.0001); however, comparison of predictive models for PET Aβ-amyloid showed no difference between Aβ42 alone and the T-tau/Aβ42 ratio.

CONCLUSION

This study confirms strong concordance between CSF biomarkers and PET Aβ-amyloid status is independent of immunoassay platform, supporting their utility as biomarkers in clinical practice for the diagnosis of AD and for participant enrichment in clinical trials.