The global Alzheimer's Association round robin study on plasma amyloid β methods

Gene-variant specific effects of plasma amyloid-β levels in Swedish autosomal dominant Alzheimer disease

BACKGROUND

Several blood-based biomarkers offer the opportunity of in vivo detection of brain pathology and neurodegeneration in Alzheimer disease with high specificity and sensitivity, but the performance of amyloid-β (Aβ) measurements remains under evaluation. Autosomal dominant Alzheimer disease (ADAD) with mutations in PSEN1, PSEN2 and APP can be studied as a model for sporadic Alzheimer disease. However, clarifying the genetic effects on the Aβ-levels in different matrices such as cerebrospinal fluid or plasma is crucial for generalizability and utility of data. We aimed to explore plasma Aβ concentrations over the Alzheimer disease continuum in a longitudinal cohort of genetic Alzheimer disease.

METHODS

92 plasma samples were collected from at-risk individuals (n = 47) in a Swedish cohort of ADAD, including 18 mutation carriers (13 APPswe (p.KM670/671NL) MC), 5 PSEN1 (p.H163Y) MC) and 29 non-carriers (NC) as the reference group. Concentrations of Aβ1-38, Aβ1-40 and Aβ1-42 were analyzed in plasma using immunoprecipitation coupled to tandem liquid chromatography mass spectrometry (IP-LC-MS/MS). Cross-sectional and repeated-measures data analyses were investigated family-wise, applying non-parametric tests as well as mixed-effects models.

RESULTS

Cross-sectional analysis at baseline showed more than a 3-fold increase in all plasma Aβ peptides in APPswe MC, regardless of clinical status, compared to controls (p < 0.01). PSEN1 (p.H163Y) presymptomatic MC had a decrease of plasma Aβ1-38 compared to controls (p < 0.05). There was no difference in Aβ1-42/1-40 ratio between APPswe MC (PMC and SMC), PSEN1 MC (PMC) and controls at baseline. Notably, both cross-sectional data and repeated-measures analysis suggested that APPswe MC have a stable Aβ1-42/1-40 ratio with increasing age, in contrast to the decrease seen with aging in both controls and PSEN1 (p.H163Y) MC.

CONCLUSION

These data show very strong mutation-specific effects on Aβ profiles in blood, most likely due to a ubiquitous production outside of the CNS. Hence, analyses in an unselected clinical setting might unintentionally disclose genetic status. Furthermore, our findings suggest that the Aβ ratio might be a poor indicator of brain Aβ pathology in selected genetic cases. The very small sample size is a limitation that needs to be considered but reflects the scarcity of longitudinal in vivo data from genetic cohorts.

Development of thresholds and a visualization tool for use of a blood test in routine clinical dementia practice

INTRODUCTION

We developed a multimarker blood test result interpretation tool for the clinical dementia practice, including phosphorylated (P-)tau181, amyloid-beta (Abeta)42/40, glial fibrillary acidic protein (GFAP), and neurofilament light (NfL).

METHODS

We measured the plasma biomarkers with Simoa (n = 1199), applied LASSO regression for biomarker selection and receiver operating characteristics (ROC) analyses to determine diagnostic accuracy. We validated our findings in two independent cohorts and constructed a visualization approach.

RESULTS

P-tau181, GFAP, and NfL were selected. This combination had area under the curve (AUC) = 83% to identify amyloid positivity in pre-dementia stages, AUC = 87%-89% to differentiate Alzheimer's or controls from frontotemporal dementia, AUC = 74%-76% to differentiate Alzheimer's or controls from dementia with Lewy bodies. Highly reproducible AUCs were obtained in independent cohorts. The resulting visualization tool includes UpSet plots to visualize the stand-alone biomarker results and density plots to visualize the biomarker results combined.

DISCUSSION

Our multimarker blood test interpretation tool is ready for testing in real-world clinical dementia settings.

HIGHLIGHTS

We developed a multimarker blood test interpretation tool for clinical dementia practice. Our interpretation tool includes plasma biomarkers P-tau, GFAP, and NfL. Our tool is particularly useful for Alzheimer's and frontotemporal dementia diagnosis.

15 Years of Longitudinal Genetic, Clinical, Cognitive, Imaging, and Biochemical Measures in DIAN

This manuscript describes and summarizes the Dominantly Inherited Alzheimer Network Observational Study (DIAN Obs), highlighting the wealth of longitudinal data, samples, and results from this human cohort study of brain aging and a rare monogenic form of Alzheimer's disease (AD). DIAN Obs is an international collaborative longitudinal study initiated in 2008 with support from the National Institute on Aging (NIA), designed to obtain comprehensive and uniform data on brain biology and function in individuals at risk for autosomal dominant AD (ADAD). ADAD gene mutations in the amyloid protein precursor (APP), presenilin 1 (PSEN1), or presenilin 2 (PSEN2) genes are deterministic causes of ADAD, with virtually full penetrance, and a predictable age at symptomatic onset. Data and specimens collected are derived from full clinical assessments, including neurologic and physical examinations, extensive cognitive batteries, structural and functional neuro-imaging, amyloid and tau pathological measures using positron emission tomography (PET), flurordeoxyglucose (FDG) PET, cerebrospinal fluid and blood collection (plasma, serum, and whole blood), extensive genetic and multi-omic analyses, and brain donation upon death. This comprehensive evaluation of the human nervous system is performed longitudinally in both mutation carriers and family non-carriers, providing one of the deepest and broadest evaluations of the human brain across decades and through AD progression. These extensive data sets and samples are available for researchers to address scientific questions on the human brain, aging, and AD.

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.

CSF and plasma Aβ42/40 across Alzheimer's disease continuum: comparison of two ultrasensitive Simoa® assays targeting distinct amyloid regions

OBJECTIVES

Decreased cerebrospinal fluid (CSF) amyloid beta 42/40 ratio (Aβ42/40) is one of the core Alzheimer's disease (AD) biomarkers. Measurement of Aβ42/40 in plasma has also been proposed as a surrogate marker for amyloidosis, however the validity and the diagnostic performance of this biomarker is still uncertain. Here we evaluated two immunoassays targeting distinct regions of the amyloid peptides by (a) performing a method comparison in both CSF and plasma, and (b) assessing the diagnostic performance across the AD continuum.

METHODS

We used N4PE and N3PA Simoa® assays to measure Aβ42/40 in CSF and plasma of 134 patients: preclinical AD (pre-AD, n=19), mild cognitive impairment due to AD (MCI-AD, n=41), AD at the dementia stage (AD-dem, n=35), and a control group (CTRL, n=39). The N4PE includes a detector antibody targeting the amyloid N-terminus, while the N3PA uses a detector targeting amyloid mid-region.

RESULTS

Method comparison of N4PE and N3PA assays revealed discrepancies in assessment of plasma Aβ42/Aβ40. While the diagnostic performance of the two assays did not significantly differ in CSF, in plasma, N4PE assay provided better accuracy for AD discrimination than N3PA assay (AUC AD-dem vs. CTRL 0.77 N4PE, 0.68 N3PA).

CONCLUSIONS

While both Aβ42/40 assays allowed for an effective discrimination between CTRL and different AD stages, the assay targeting amyloid N-terminal region provided the best diagnostic performance in plasma. Differences observed in technical and diagnostic performance of the two assays may depend on matrix-specific amyloid processing, suggesting that further studies should be carried to standardize amyloid ratio measurement in plasma.

Blood-Based Biomarkers for Early Alzheimer's Disease Diagnosis in Real-World Settings

As our knowledge about the biology of Alzheimer's disease (AD) expands and we recognize the significance of early intervention for effective treatment, there is a shift in focus toward detecting the disease at an early stage. AD is characterized by the accumulation of misfolded amyloid-β (Aβ) and phosphorylated tau proteins in the brain, leading to the formation of senile plaques and neurofibrillary tangles. While a definitive diagnosis of AD can only be confirmed through autopsy by examining these pathological features, there are now reliable methods available for diagnosing the disease in living individuals. These methods involve analyzing cerebrospinal fluid and using positron emission tomography to accurately assess the presence of Aβ and tau proteins. While these diagnostic markers have shown high accuracy in memory-clinic populations, they do have limitations such as the requirement for invasive lumbar puncture or exposure to ionizing radiation. Additionally, they are not easily accessible outside of specialized healthcare settings. Blood-based biomarkers of the core pathological features of AD are being developed, showing promise for less invasive, scalable identification of AD cases in the community. The advantages for the healthcare systems of this development are obvious, but the diagnostic performance of blood-based biomarkers in broader, non-selected populations outside of retrospective analyses and research cohorts still requires further investigation, including the combination with more effective neuropsychological assessments such as digital cognitive test solutions.

ATN cerebrospinal fluid biomarkers in dementia with Lewy bodies: Initial results from the United States Dementia with Lewy Bodies Consortium

INTRODUCTION

The National Institute on Aging - Alzheimer's Association (NIA-AA) ATN research framework proposes to use biomarkers for amyloid (A), tau (T), and neurodegeneration (N) to stage individuals with AD pathological features and track changes longitudinally. The overall aim was to utilize this framework to characterize pre-mortem ATN status longitudinally in a clinically diagnosed cohort of dementia with Lewy bodies (DLB) and to correlate it with the post mortem diagnosis.

METHODS

The cohort was subtyped by cerebrospinal fluid (CSF) ATN category. A subcohort had longitudinal data, and a subgroup was neuropathologically evaluated.

RESULTS

We observed a significant difference in Aβ42/40 after 12 months in the A+T- group. Post mortem neuropathologic analyses indicated that most of the p-Tau 181 positive (T+) cases also had a high Braak stage.

DISCUSSION

This suggests that DLB patients who are A+ but T- may need to be monitored to determine whether they remain A+ or ever progress to T positivity.

HIGHLIGHTS

Some A+T- DLB subjects transition from A+ to negative after 12-months. Clinically diagnosed DLB with LBP-AD (A+T+) maintain their positivity. Clinically diagnosed DLB with LBP-AD (A+T+) maintain their positivity. Monitoring of the A+T- sub-type of DLB may be necessary.

Blood-brain barrier integrity impacts the use of plasma amyloid-β as a proxy of brain amyloid-β pathology

INTRODUCTION

Amyloid-β (Aβ) and tau can be quantified in blood. However, biological factors can influence the levels of brain-derived proteins in the blood. The blood-brain barrier (BBB) regulates protein transport between cerebrospinal fluid (CSF) and blood. BBB altered permeability might affect the relationship between brain and blood biomarkers.

METHODS

We assessed 224 participants in research (TRIAD, n = 96) and clinical (BIODEGMAR, n = 128) cohorts with plasma and CSF/positron emission tomography Aβ, p-tau, and albumin measures.

RESULTS

Plasma Aβ42/40 better identified CSF Aβ42/40 and Aβ-PET positivity in individuals with high BBB permeability. An interaction between plasma Aβ42/40 and BBB permeability on CSF Aβ42/40 was observed. Voxel-wise models estimated that the association of positron emission tomography (PET), with plasma Aβ was most affected by BBB permeability in AD-related brain regions. BBB permeability did not significantly impact the relationship between brain and plasma p-tau levels.

DISCUSSION

These findings suggest that BBB integrity may influence the performance of plasma Aβ, but not p-tau, biomarkers in research and clinical settings.

HIGHLIGHTS

BBB permeability affects the association between brain and plasma Aβ levels. BBB integrity does not affect the association between brain and plasma p-tau levels. Plasma Aβ was most affected by BBB permeability in AD-related brain regions. BBB permeability increases with age but not according to cognitive status.

Effects of storage conditions on the stability of blood-based markers for the diagnosis of Alzheimer's disease

OBJECTIVES

Alzheimer's disease (AD) is considered the most common cause of dementia in older people. Recently, blood-based markers (BBM) Aβ1-42, Aβ1-40, and phospho Tau181 (p-Tau181) have demonstrated the potential to transform the diagnosis and prognostic assessment of AD. Our aim was to investigate the effect of different storage conditions on the quantification of these BBM and to evaluate the interchangeability of plasma and serum samples.

METHODS

Forty-two individuals with some degree of cognitive impairment were studied. Thirty further patients were retrospectively selected. Aβ1-42, Aβ1-40, and p-Tau181 were quantified using the LUMIPULSE-G600II automated platform. To assess interchangeability between conditions, correction factors for magnitudes that showed strong correlations were calculated, followed by classification consistency studies.

RESULTS

Storing samples at 4 °C for 8-9 days was associated with a decrease in Aβ fractions but not when stored for 1-2 days. Using the ratio partially attenuated the pre-analytical effects. For p-Tau181, samples stored at 4 °C presented lower concentrations, whereas frozen samples presented higher ones. Concerning classification consistency in comparisons that revealed strong correlations (p-Tau181), the percentage of total agreement was greater than 90 % in a large number of the tested cut-offs values.

CONCLUSIONS

Our findings provide relevant information for the standardization of sample collection and storage in the analysis of AD BBM in an automated platform. This knowledge is crucial to ensure their introduction into clinical settings.

Harmonization and standardization of biofluid-based biomarker measurements for AT(N) classification in Alzheimer's disease

Fluid biomarkers are currently measured in cerebrospinal fluid and blood for Alzheimer's disease diagnosis and are promising targets for drug development and for patients' follow-up in clinical trials. These biomarkers have been grouped in an unbiased research framework, the amyloid (Aβ), tau, and neurodegeneration (AT[N]) biomarker system to aid patients' early diagnosis and stratification. Metrological approaches relying on mass spectrometry have been used for the development of reference materials and reference measurement procedures. Despite their excellent performances as clinical tools, fluid biomarkers often present an important between-laboratory variation. Standardization efforts were carried out on the biomarkers currently included in the AT(N) classification system, involving the collaboration of national metrology institutes, clinicians, researchers, and in vitro diagnostic providers. This article provides an overview of current activities towards standardization. These reference methods and reference materials may be used for recalibration of immunoassays and the establishment of standardized cutoff values allowing a better stratification of Alzheimer's disease patients.

Highlights

The AT(N) biomarker system allows stratifying AD patients on the basis of biomarker profiles.Fluid biomarker measurements often present an important between-laboratory variation preventing the establishment of standardized cutoff values.Overview on the standardization initiatives involving the fluid biomarkers currently included in the AT(N) framework.

Annual stability of the plasma Aß40/42 ratio and associated factors

OBJECTIVE

The plasma Aß40/42 ratio is a biomarker of brain amyloidosis. However, the threshold difference between amyloid positivity and negativity is only 10-20% and fluctuates with circadian rhythms, aging, and APOE-ε4 during the decades of evolution of Alzheimer's disease.

METHODS

Plasma Aß40 and Aß42 levels in 1472 participants aged between 19 and 93 years in the Iwaki Health Promotion Project for 4 years were statistically analyzed.

RESULTS

The means and standard deviations of annual inter-individual coefficients of variation were 5.3 ± 3.2% for Aß40, 7.8 ± 4.6% for Aß42, and 6.4 ± 4.1% for the Aß40/42 ratio. No significant age-dependent changes were observed in inter-individual coefficients of variation. Age-dependent increases in Aβ42 levels were suppressed, whereas those in the Aβ40/42 ratio were enhanced in APOE-ε4 carriers. The change points of Aß42, Aß40, and the Aß40/42 ratio were 36.4, 38.2, and 43.5 years, respectively. In the presence of APOE-ε4, the Aß40/42 ratio increased in middle-aged and elderly subjects while Aβ42 levels decreased in elderly subjects.

INTERPRETATION

Individual values for Aß40, Aß42, and the Aß40/42 ratio did not fluctuate annually or in an age-dependent manner. If the plasma Aβ40/42 ratio changes by more than 14.7% (+2 standard deviations) relative to age- and APOE-ε4-adjusted normal annual fluctuations, other biomarkers also need to be examined.

Comparative analytical performance of multiple plasma Aβ42 and Aβ40 assays and their ability to predict positron emission tomography amyloid positivity

INTRODUCTION

This report details the approach taken to providing a dataset allowing for analyses on the performance of recently developed assays of amyloid beta (Aβ) peptides in plasma and the extent to which they improve the prediction of amyloid positivity.

METHODS

Alzheimer's Disease Neuroimaging Initiative plasma samples with corresponding amyloid positron emission tomography (PET) data were run on six plasma Aβ assays. Statistical tests were performed to determine whether the plasma Aβ measures significantly improved the area under the receiver operating characteristic curve for predicting amyloid PET status compared to age and apolipoprotein E (APOE) genotype.

RESULTS

The age and APOE genotype model predicted amyloid status with an area under the curve (AUC) of 0.75. Three assays improved AUCs to 0.81, 0.81, and 0.84 (P < .05, uncorrected for multiple comparisons).

DISCUSSION

Measurement of Aβ in plasma contributes to addressing the amyloid component of the ATN (amyloid/tau/neurodegeneration) framework and could be a first step before or in place of a PET or cerebrospinal fluid screening study.

HIGHLIGHTS

The Foundation of the National Institutes of Health Biomarkers Consortium evaluated six plasma amyloid beta (Aβ) assays using Alzheimer's Disease Neuroimaging Initiative samples. Three assays improved prediction of amyloid status over age and apolipoprotein E (APOE) genotype. Plasma Aβ42/40 predicted amyloid positron emission tomography status better than Aβ42 or Aβ40 alone.

Association of plasma biomarkers of amyloid and neurodegeneration with cerebrovascular disease and Alzheimer's disease

The objective of this study was to determine the differential mapping of plasma biomarkers to postmortem neuropathology measures. We identified 64 participants in a population-based study with antemortem plasma markers (amyloid-β [Aβ] x-42, Aβx-40, neurofilament light [NfL], and total tau [T-tau]) who also had neuropathologic assessments of Alzheimer's and cerebrovascular pathology. We conducted weighted linear-regression models to evaluate relationships between plasma measures and neuropathology. Higher plasma NfL and Aβ42/40 ratio were associated with cerebrovascular neuropathologic scales (p < 0.05) but not with Braak stage, neuritic plaque score, or Thal phase. Plasma Aβ42/40 and NfL explained up to 18% of the variability in cerebrovascular neuropathologic scales. In participants predominantly with modest levels of Alzheimer's pathologic change, biomarkers of amyloid and neurodegeneration were associated with cerebrovascular neuropathology. NfL is a non-specific marker of brain injury, therefore its association with cerebrovascular neuropathology was expected. The association between elevated Aβ42/40 and cerebrovascular disease pathology needs further investigation but could be due to the use of less specific amyloid-β assays (x-40, x-42).

Classification accuracy of blood-based and neurophysiological markers in the differential diagnosis of Alzheimer's disease and frontotemporal lobar degeneration

BACKGROUND

In the last decade, non-invasive blood-based and neurophysiological biomarkers have shown great potential for the discrimination of several neurodegenerative disorders. However, in the clinical workup of patients with cognitive impairment, it will be highly unlikely that any biomarker will achieve the highest potential predictive accuracy on its own, owing to the multifactorial nature of Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD).

METHODS

In this retrospective study, performed on 202 participants, we analysed plasma neurofilament light (NfL), glial fibrillary acidic protein (GFAP), and tau phosphorylated at amino acid 181 (p-Tau181) concentrations, as well as amyloid β42 to 40 ratio (Aβ1-42/1-40) ratio, using the ultrasensitive single-molecule array (Simoa) technique, and neurophysiological measures obtained by transcranial magnetic stimulation (TMS), including short-interval intracortical inhibition (SICI), intracortical facilitation (ICF), long-interval intracortical inhibition (LICI), and short-latency afferent inhibition (SAI). We assessed the diagnostic accuracy of combinations of both plasma and neurophysiological biomarkers in the differential diagnosis between healthy ageing, AD, and FTLD.

RESULTS

We observed significant differences in plasma NfL, GFAP, and p-Tau181 levels between the groups, but not for the Aβ1-42/Aβ1-40 ratio. For the evaluation of diagnostic accuracy, we adopted a two-step process which reflects the clinical judgement on clinical grounds. In the first step, the best single biomarker to classify "cases" vs "controls" was NfL (AUC 0.94, p < 0.001), whilst in the second step, the best single biomarker to classify AD vs FTLD was SAI (AUC 0.96, p < 0.001). The combination of multiple biomarkers significantly increased diagnostic accuracy. The best model for classifying "cases" vs "controls" included the predictors p-Tau181, GFAP, NfL, SICI, ICF, and SAI, resulting in an AUC of 0.99 (p < 0.001). For the second step, classifying AD from FTD, the best model included the combination of Aβ1-42/Aβ1-40 ratio, p-Tau181, SICI, ICF, and SAI, resulting in an AUC of 0.98 (p < 0.001).

CONCLUSIONS

The combined assessment of plasma and neurophysiological measures may greatly improve the differential diagnosis of AD and FTLD.

Development of Alzheimer’s Disease Biomarkers: From CSF- to Blood-Based Biomarkers

In the 115 years since the discovery of Alzheimer’s disease (AD), our knowledge, diagnosis, and therapeutics have significantly improved. Biomarkers are the primary tools for clinical research, diagnostics, and therapeutic monitoring in clinical trials. They provide much insightful information, and while they are not clinically used routinely, they help us to understand the mechanisms of this disease. This review charts the journey of AD biomarker discovery and development from cerebrospinal fluid (CSF) amyloid-beta 1-42 (Aβ42), total tau (T-tau), and phosphorylated tau (p-tau) biomarkers and imaging technologies to the next generation of biomarkers. We also discuss advanced high-sensitivity assay platforms for CSF Aβ42, T-tau, p-tau, and blood analysis. The recently proposed Aβ deposition/tau biomarker/neurodegeneration or neuronal injury (ATN) scheme might facilitate the definition of the biological status underpinning AD and offer a common language among researchers across biochemical biomarkers and imaging. Moreover, we highlight blood-based biomarkers for AD that offer a scalable alternative to CSF biomarkers through cost-saving and reduced invasiveness, and may provide an understanding of disease initiation and development. We discuss different groups of blood-based biomarker candidates, their advantages and limitations, and paths forward, from identification and analysis to clinical validation. The development of valid blood-based biomarkers may facilitate the implementation of future AD therapeutics and diagnostics.