Amyloid and tau signatures of brain metabolic decline in preclinical Alzheimer's disease

Advancing Alzheimer's Research With Zebrafish Models: Current Insights, Addressing Challenges, and Charting Future Courses

Alzheimer's disease (AD) is a neurological condition that progressively impairs cognitive function and results in memory loss. Despite substantial research efforts, little is known about the specific processes driving AD, and there are few proven therapies. Because of their physiological and genetic resemblance to humans, zebrafish (Danio rerio) have become an important model organism for furthering research on AD. This abstract discusses the difficulties faced, looks at the insights currently garnered from zebrafish models, and suggests future research options. AD knowledge has greatly benefited from the use of zebrafish models. Transgenic zebrafish that express human AD-associated genes, such as tau and amyloid precursor protein (APP), display tau neurofibrillary tangles (NFTs) and amyloid-beta (Aβ) plaques, two of the disease's main clinical characteristics. These models have clarified the roles of oxidative stress, inflammation, and calcium homeostasis in the course of AD and allowed for the purpose of high-throughput screening of potential therapeutic agents. Understanding the growth and deterioration of neurons has been greatly aided by real-time zebrafish imaging. Fully using zebrafish models in AD research requires addressing a number of issues. The dissimilarities in zebrafish anatomy and physiology from humans, the difficulty of developing models that replicate progressive and late-onset AD (LOAD), and the requirement for standardized procedures to evaluate alterations in zebrafish cognition and behavior are a few issues. Furthermore, variations in the genetic makeup of zebrafish strains might affect the results of experiments. Future directions include developing standardized behavioral assays and cognitive tests, working together to create extensive databases of zebrafish genetic and phenotypic data, and using genetic engineering techniques like CRISPR/Cas9 to create more complex zebrafish models. Combining zebrafish models with other model species helps expedite the conversion of research results into therapeutic applications and offers a more thorough knowledge of AD. To sum up, zebrafish models have made a substantial contribution to Alzheimer's research by offering insightful information on the causes of the illness and possible therapies. By tackling present issues and formulating a planned future path, we can improve the use of zebrafish to decipher the mysteries of Alzheimer's and help create successful treatments.

The use of individual-based FDG-PET volume of interest in predicting conversion from mild cognitive impairment to dementia

BACKGROUND

Based on a longitudinal cohort design, the aim of this study was to investigate whether individual-based 18F fluorodeoxyglucose positron emission tomography (18F-FDG-PET) regional signals can predict dementia conversion in patients with mild cognitive impairment (MCI).

METHODS

We included 44 MCI converters (MCI-C), 38 non-converters (MCI-NC), 42 patients with Alzheimer's disease with dementia, and 40 cognitively normal controls. Data from annual cognitive measurements, 3D T1 magnetic resonance imaging (MRI) scans, and 18F-FDG-PET scans were used for outcome analysis. An individual-based FDG-PET approach was applied using seven volumes of interest (VOIs), Z transformed using a normal FDG-PET template. Hypometabolism was defined as a Z score < -2 of regional standard uptake value ratio. For the longitudinal cognitive test scores, generalized estimating equations were used. A linear mixed-effects model was used to compare the temporal impact of cortical hypometabolism and cortical thickness degeneration.

RESULTS

The clinical follow-up period was 6.6 ± 3.8 years (range 3.1 to 16.0 years). The trend of cognitive decline could differentiate MCI-C from MCI-NC after 3 years of follow-up. In the baseline 18F-FDG-PET scan of the patients with MCI, medial temporal lobe (MTL; 94.7% sensitivity, 80.5% specificity) and posterior cingulate cortex (PCC; 89.5% sensitivity, 73.1% specificity) hypometabolism predicted conversion with high accuracy. 18F-FDG-PET hypometabolism preceded dementia conversion at an interval of 3.70 ± 1.68 years and was earlier than volumetric changes, with the exception of the MTL.

CONCLUSIONS

Our finding supports the use of individual-based 18F-FDG-PET analysis to predict MCI conversion to dementia. Reduced FDG-PET metabolism in the MTL and PCC were strongly associated with future cognitive decline in the MCI-C group. Changes in 18F-FDG-PET occurred 1 to 8 years prior to conversion to dementia. Progressive hypometabolism in the PCC, precuneus and lateral temporal lobe, but not MTL, preceded MRI findings at the MCI stage.

Spatial association between distributed β-amyloid and tau varies with cognition

Several PET studies have explored the relationship between β-amyloid load and tau uptake at the early stages of Alzheimer's disease (AD) progression. Most of these studies have focused on the linear relationship between β-amyloid and tau at the local level and their synergistic effect on different AD biomarkers. We hypothesize that patterns of spatial association between β-amyloid and tau might be uncovered using alternative association metrics that account for linear as well as more complex, possible nonlinear dependencies. In the present study, we propose a new Canonical Distance Correlation Analysis (CDCA) to generate distinctive spatial patterns of the cross-correlation structure between tau, as measured by [18F]flortaucipir PET, and β-amyloid, as measured by [18F]florbetapir PET, from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. We found that the CDCA-based β-amyloid scores were not only maximally distance-correlated to tau in cognitively normal (CN) controls and mild cognitive impairment (MCI), but also differentiated between low and high levels of β-amyloid uptake. The most distinctive spatial association pattern was characterized by a spread of β-amyloid covering large areas of the cortex and localized tau in the entorhinal cortex. More importantly, this spatial dependency varies according to cognition, which cannot be explained by the uptake differences in β-amyloid or tau between CN and MCI subjects. Hence, the CDCA-based scores might be more accurate than the amyloid or tau SUVR for the enrollment in clinical trials of those individuals on the path of cognitive deterioration.

A cross-scanner and cross-tracer deep learning method for the recovery of standard-dose imaging quality from low-dose PET

PURPOSE

A critical bottleneck for the credibility of artificial intelligence (AI) is replicating the results in the diversity of clinical practice. We aimed to develop an AI that can be independently applied to recover high-quality imaging from low-dose scans on different scanners and tracers.

METHODS

Brain [18F]FDG PET imaging of 237 patients scanned with one scanner was used for the development of AI technology. The developed algorithm was then tested on [18F]FDG PET images of 45 patients scanned with three different scanners, [18F]FET PET images of 18 patients scanned with two different scanners, as well as [18F]Florbetapir images of 10 patients. A conditional generative adversarial network (GAN) was customized for cross-scanner and cross-tracer optimization. Three nuclear medicine physicians independently assessed the utility of the results in a clinical setting.

RESULTS

The improvement achieved by AI recovery significantly correlated with the baseline image quality indicated by structural similarity index measurement (SSIM) (r = -0.71, p < 0.05) and normalized dose acquisition (r = -0.60, p < 0.05). Our cross-scanner and cross-tracer AI methodology showed utility based on both physical and clinical image assessment (p < 0.05).

CONCLUSION

The deep learning development for extensible application on unknown scanners and tracers may improve the trustworthiness and clinical acceptability of AI-based dose reduction.

Cerebrospinal fluid p-tau231 as an early indicator of emerging pathology in Alzheimer's disease

BACKGROUND

Phosphorylated tau (p-tau) epitopes in cerebrospinal fluid (CSF) are accurate biomarkers for a pathological and clinical diagnosis of Alzheimer's disease (AD) and are seen to be increased in preclinical stage of the disease. However, it is unknown if these increases transpire earlier, prior to amyloid-beta (Aβ) positivity as determined by position emission tomography (PET), and if an ordinal sequence of p-tau epitopes occurs at this incipient phase METHODS: We measured CSF concentrations of p-tau181, p-tau217 and p-tau231 in 171 participants across the AD continuum who had undergone Aβ ([¹⁸F]AZD4694) and tau ([¹⁸F]MK6240) position emission tomography (PET) and clinical assessment FINDINGS: All CSF p-tau biomarkers were accurate predictors of cognitive impairment but CSF p-tau217 demonstrated the largest fold-changes in AD patients in comparison to non-AD dementias and cognitively unimpaired individuals. CSF p-tau231 and p-tau217 predicted Aβ and tau to a similar degree but p-tau231 attained abnormal levels first. P-tau231 was sensitive to the earliest changes of Aβ in the medial orbitofrontal, precuneus and posterior cingulate before global Aβ PET positivity was reached INTERPRETATION: We demonstrate that CSF p-tau231 increases early in development of AD pathology and is a principal candidate for detecting incipient Aβ pathology for therapeutic trial application FUNDING: Canadian Institutes of Health Research (CIHR), Canadian Consortium of Neurodegeneration and Aging, Weston Brain Institute, Brain Canada Foundation, the Fonds de Recherche du Québec.

Longitudinal 18F-MK-6240 tau tangles accumulation follows Braak stages

Tracking longitudinal tau tangles accumulation across the Alzheimer's disease continuum is crucial to better understand the natural history of tau pathology and for clinical trials. Although the available first-generation tau PET tracers detect tau accumulation in symptomatic individuals, their nanomolar affinity offers limited sensitivity to detect early tau accumulation in asymptomatic subjects. Here, we hypothesized the novel sub-nanomolar affinity tau tangles tracer [18F]MK-6240 can detect longitudinal tau accumulation in asymptomatic and symptomatic subjects. We studied 125 living individuals (65 cognitively unimpaired elderly amyloid-β negative, 22 cognitively unimpaired elderly amyloid-β positive, 21 mild cognitive impairment amyloid-β positive, 17 Alzheimer's disease dementia amyloid-β positive) with baseline amyloid-β [18F]AZD4694 PET and baseline and follow-up tau [18F]MK-6240 PET. [18F]MK-6240 standardized uptake value ratio (SUVR) was calculated at 90-110 min after tracer injection and used the cerebellar crus I as the reference region. In addition, we assessed in vivo [18F]MK-6240 SUVR and postmortem phosphorylated tau pathology in two Alzheimer's disease dementia participants who deceased after the PET scans. We found that cognitively unimpaired amyloid-β negative individuals had significant longitudinal tau accumulation confined to PET Braak-like stage I (3.9%) and II (2.8%) areas. Cognitively unimpaired amyloid-β positive showed greater tau accumulation in Braak-like stage I (8.9%), compared to later Braak stages. Mild cognitive impairment and Alzheimer's dementia amyloid-β positive patients showed tau accumulation in Braak III-VI, but not in Braak I-II regions. Cognitively impaired amyloid-β positive individuals that were Braak II-IV at baseline showed 4.6-7.5% annual increase in tau accumulation in Braak III-IV regions, whereas cognitively impaired amyloid-β positive Braak V-VI at baseline had 8.3-10.7% annual increase in Braak V-VI regions. Neuropathological assessments confirmed the PET-based Braak stages V-VI observed in the two brain donors. Our results suggest that [18F]MK-6240 SUVR is able to detect longitudinal tau accumulation in asymptomatic and symptomatic Alzheimer's disease. The highest magnitude of [18F]MK-6240 SUVR accumulation moved from medial temporal to sensorimotor cortex across the disease clinical spectrum. Trials using [18F]MK-6240 SUVR in cognitively unimpaired would be required to use regions-of-interest corresponding to early Braak stages, whereas trials in cognitively impaired would benefit from using regions-of-interest in late Braak stages. Anti-tau trials should take into consideration individuals' baseline PET Braak-like stage to minimize the variability introduced by the hierarchical accumulation of tau tangles in the human brain. Finally, our postmortem findings supported [18F]MK-6240 SUVR as a biomarker to stage tau pathology in Alzheimer's disease patients.

Microglial activation and tau propagate jointly across Braak stages

Compelling experimental evidence suggests that microglial activation is involved in the spread of tau tangles over the neocortex in Alzheimer's disease (AD). We tested the hypothesis that the spatial propagation of microglial activation and tau accumulation colocalize in a Braak-like pattern in the living human brain. We studied 130 individuals across the aging and AD clinical spectrum with positron emission tomography brain imaging for microglial activation ([¹¹C]PBR28), amyloid-β (Aβ) ([¹⁸F]AZD4694) and tau ([¹⁸F]MK-6240) pathologies. We further assessed microglial triggering receptor expressed on myeloid cells 2 (TREM2) cerebrospinal fluid (CSF) concentrations and brain gene expression patterns. We found that [¹¹C]PBR28 correlated with CSF soluble TREM2 and showed regional distribution resembling TREM2 gene expression. Network analysis revealed that microglial activation and tau correlated hierarchically with each other following Braak-like stages. Regression analysis revealed that the longitudinal tau propagation pathways depended on the baseline microglia network rather than the tau network circuits. The co-occurrence of Aβ, tau and microglia abnormalities was the strongest predictor of cognitive impairment in our study population. Our findings support a model where an interaction between Aβ and activated microglia sets the pace for tau spread across Braak stages.

Single and Combined Neuroimaging Techniques for Alzheimer's Disease Detection

Alzheimer's disease (AD) consists of the gradual process of decreasing volume and quality of neuron connection in the brain, which consists of gradual synaptic integrity and loss of cognitive functions. In recent years, there has been significant attention in AD classification and early detection with machine learning algorithms. There are different neuroimaging techniques for capturing data and using it for the classification task. Input data as images will help machine learning models to detect different biomarkers for AD classification. This marker has a more critical role for AD detection than other diseases because beta-amyloid can extract complex structures with some metal ions. Most researchers have focused on using 3D and 4D convolutional neural networks for AD classification due to reasonable amounts of data. Also, combination neuroimaging techniques like functional magnetic resonance imaging and positron emission tomography for AD detection have recently gathered much attention. However, gathering a combination of data can be expensive, complex, and tedious. For time consumption reasons, most patients prefer to throw one of the neuroimaging techniques. So, in this review article, we have surveyed different research studies with various neuroimaging techniques and ML methods to see the effect of using combined data as input. The result has shown that the use of the combination method would increase the accuracy of AD detection. Also, according to the sensitivity metrics from different machine learning methods, MRI and fMRI showed promising results.

CSF TNF-α Levels Were Associated with Longitudinal Change in Brain Glucose Metabolism Among Non-Demented Older People

PURPOSE

Emerging studies have suggested that tumor necrosis factor-alpha (TNF-α) is implicated in the pathogenesis of Alzheimer's disease (AD), and that cerebral glucose hypometabolism is a key feature of AD. However, the association of CSF TNF-α levels with changes in cerebral glucose metabolism has not been studied among non-demented older people.

PATIENTS AND METHODS

At baseline, there were a total of 214 non-demented older people from Alzheimer's Disease Neuroimaging Initiative (ADNI) study. We examined the cross-sectional and longitudinal associations of CSF TNF-α with global cognition (as assessed by mini-mental state examination), verbal memory (as assessed by Rey Auditory Verbal Learning Test-total learning score), and cerebral glucose metabolism (as measured by FDF-PET). Linear mixed-effects models were used to examine the longitudinal association of CSF TNF- α with change in each outcome over time with adjustment of age, educational level, gender, and APOE4 status.

RESULTS

In the cross-sectional study, CSF TNF-α was negatively associated with MMSE scores, but not verbal memory or FDG-PET. In the longitudinal study, higher CSF TNF- α at baseline was associated with a faster decline in cerebral glucose metabolism, but not MMSE scores or RAVLT total learning scores.

CONCLUSION

Higher CSF TNF-α levels were associated with a steeper decline in cerebral glucose metabolism among non-demented older people.

Periodontal dysbiosis associates with reduced CSF Aβ42 in cognitively normal elderly

INTRODUCTION

Periodontal disease is a chronic, inflammatory bacterial dysbiosis that is associated with both Alzheimer's disease (AD) and Down syndrome.

METHODS

A total of 48 elderly cognitively normal subjects were evaluated for differences in subgingival periodontal bacteria (assayed by 16S rRNA sequencing) between cerebrospinal fluid (CSF) biomarker groups of amyloid and neurofibrillary pathology. A dysbiotic index (DI) was defined at the genus level as the abundance ratio of known periodontal bacteria to healthy bacteria. Analysis of variance/analysis of covariance (ANOVA/ANCOVA), linear discriminant effect-size analyses (LEfSe) were used to determine the bacterial genera and species differences between the CSF biomarker groups.

RESULTS

At genera and species levels, higher subgingival periodontal dysbiosis was associated with reduced CSF amyloid beta (Aβ)42 (P = 0.02 and 0.01) but not with P-tau.

DISCUSSION

We show a selective relationship between periodontal disease bacterial dysbiosis and CSF biomarkers of amyloidosis, but not for tau. Further modeling is needed to establish the direct link between oral bacteria and Aβ.

Biphasic cortical macro- and microstructural changes in autosomal dominant Alzheimer's disease

INTRODUCTION

A biphasic model for brain structural changes in preclinical Alzheimer's disease (AD) could reconcile some conflicting and paradoxical findings in observational studies and anti-amyloid clinical trials.

METHODS

In this study we tested this model fitting linear versus quadratic trajectories and computed the timing of the inflection points vertexwise of cortical thickness and cortical diffusivity-a novel marker of cortical microstructure-changes in 389 participants from the Dominantly Inherited Alzheimer Network.

RESULTS

In early preclinical AD, between 20 and 15 years before estimated symptom onset, we found increases in cortical thickness and decreases in cortical diffusivity followed by cortical thinning and cortical diffusivity increases in later preclinical and symptomatic stages. The inflection points 16 to 19 years before estimated symptom onset are in agreement with the start of tau biomarker alterations.

DISCUSSION

These findings confirm a biphasic trajectory for brain structural changes and have direct implications when interpreting magnetic resonance imaging measures in preventive AD clinical trials.

18F-MK-6240 PET for early and late detection of neurofibrillary tangles

Braak stages of tau neurofibrillary tangle accumulation have been incorporated in the criteria for the neuropathological diagnosis of Alzheimer's disease. It is expected that Braak staging using brain imaging can stratify living individuals according to their individual patterns of tau deposition, which may prove crucial for clinical trials and practice. However, previous studies using the first-generation tau PET agents have shown a low sensitivity to detect tau pathology in areas corresponding to early Braak histopathological stages (∼20% of cognitively unimpaired elderly with tau deposition in regions corresponding to Braak I-II), in contrast to ∼80-90% reported in post-mortem cohorts. Here, we tested whether the novel high affinity tau tangles tracer 18F-MK-6240 can better identify individuals in the early stages of tau accumulation. To this end, we studied 301 individuals (30 cognitively unimpaired young, 138 cognitively unimpaired elderly, 67 with mild cognitive impairment, 54 with Alzheimer's disease dementia, and 12 with frontotemporal dementia) with amyloid-β 18F-NAV4694, tau 18F-MK-6240, MRI, and clinical assessments. 18F-MK-6240 standardized uptake value ratio images were acquired at 90-110 min after the tracer injection. 18F-MK-6240 discriminated Alzheimer's disease dementia from mild cognitive impairment and frontotemporal dementia with high accuracy (∼85-100%). 18F-MK-6240 recapitulated topographical patterns consistent with the six hierarchical stages proposed by Braak in 98% of our population. Cognition and amyloid-β status explained most of the Braak stages variance (P < 0.0001, R2 = 0.75). No single region of interest standardized uptake value ratio accurately segregated individuals into the six topographic Braak stages. Sixty-eight per cent of the cognitively unimpaired elderly amyloid-β-positive and 37% of the cognitively unimpaired elderly amyloid-β-negative subjects displayed tau deposition, at least in the transentorhinal cortex (Braak I). Tau deposition solely in the transentorhinal cortex was associated with an elevated prevalence of amyloid-β, neurodegeneration, and cognitive impairment (P < 0.0001). 18F-MK-6240 deposition in regions corresponding to Braak IV-VI was associated with the highest prevalence of neurodegeneration, whereas in Braak V-VI regions with the highest prevalence of cognitive impairment. Our results suggest that the hierarchical six-stage Braak model using 18F-MK-6240 imaging provides an index of early and late tau accumulation as well as disease stage in preclinical and symptomatic individuals. Tau PET Braak staging using high affinity tracers has the potential to be incorporated in the diagnosis of living patients with Alzheimer's disease in the near future.

3D-Deep Learning Based Automatic Diagnosis of Alzheimer's Disease with Joint MMSE Prediction Using Resting-State fMRI

We performed this research to 1) evaluate a novel deep learning method for the diagnosis of Alzheimer's disease (AD) and 2) jointly predict the Mini Mental State Examination (MMSE) scores of South Korean patients with AD. Using resting-state functional Magnetic Resonance Imaging (rs-fMRI) scans of 331 participants, we obtained functional 3-dimensional (3-D) independent component spatial maps for use as features in classification and regression tasks. A 3-D convolutional neural network (CNN) architecture was developed for the classification task. MMSE scores were predicted using: linear least square regression (LLSR), support vector regression, bagging-based ensemble regression, and tree regression with group independent component analysis (gICA) features. To improve MMSE regression performance, we applied feature optimization methods including least absolute shrinkage and selection operator and support vector machine-based recursive feature elimination (SVM-RFE). The mean balanced test accuracy was 85.27% for the classification of AD versus healthy controls. The medial visual, default mode, dorsal attention, executive, and auditory related networks were mainly associated with AD. The maximum clinical MMSE score prediction accuracy with the LLSR method applied on gICA combined with SVM-RFE features had the lowest root mean square error (3.27 ± 0.58) and the highest R² value (0.63 ± 0.02). Classification of AD and healthy controls can be successfully achieved using only rs-fMRI and MMSE scores can be accurately predicted using functional independent component features. In the absence of trained clinicians, AD disease status and clinical MMSE scores can be jointly predicted using 3-D deep learning and regression learning approaches with rs-fMRI data.

Topographical distribution of Aβ predicts progression to dementia in Aβ positive mild cognitive impairment

INTRODUCTION

Abnormal brain amyloid beta (Aβ) is typically assessed in vivo using global concentrations from cerebrospinal fluid and positron emission tomography (PET). However, it is unknown whether the assessment of the topographical distribution of Aβ pathology can provide additional information to identify, among global Aβ positive individuals, those destined for dementia.

METHODS

We studied 260 amnestic mild cognitive impairment (MCI) subjects who were Aβ-PET positive with [18F]florbetapir. Using [18F]florbetapir, we assessed the percentage of voxels sowing Aβ abnormality as well as the standardized uptake value ratio (SUVR) values across brain regions. Regressions tested the predictive effect of Aβ on progression to dementia over 2 years.

RESULTS

Neither global nor regional [18F]florbetapir SUVR concentrations predicted progression to dementia. In contrast, the spatial extent of Aβ pathology in regions comprising the default mode network was highly associated with the development of dementia over 2 years.

DISCUSSION

These results highlight that the regional distribution of Aβ abnormality may provide important complementary information at an individual level regarding the likelihood of Aβ positive MCI to progress to dementia.

Late-stage Anle138b treatment ameliorates tau pathology and metabolic decline in a mouse model of human Alzheimer's disease tau

BACKGROUND

Augmenting the brain clearance of toxic oligomers with small molecule modulators constitutes a promising therapeutic concept against tau deposition. However, there has been no test of this concept in animal models of Alzheimer's disease (AD) with initiation at a late disease stage. Thus, we aimed to investigate the effects of interventional late-stage Anle138b treatment, which previously indicated great potential to inhibit oligomer accumulation by binding of pathological aggregates, on the metabolic decline in transgenic mice with established tauopathy in a longitudinal 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) study.

METHODS

Twelve transgenic mice expressing all six human tau isoforms (hTau) and ten controls were imaged by FDG-PET at baseline (14.5 months), followed by randomization into Anle138b treatment and vehicle groups for 3 months. FDG-PET was repeated after treatment for 3 months, and brains were analyzed by tau immunohistochemistry. Longitudinal changes of glucose metabolism were compared between study groups, and the end point tau load was correlated with individual FDG-PET findings.

RESULTS

Tau pathology was significantly ameliorated by late-stage Anle138b treatment when compared to vehicle (frontal cortex - 53%, p < 0.001; hippocampus - 59%, p < 0.005). FDG-PET revealed a reversal of metabolic decline during Anle138b treatment, whereas the vehicle group showed ongoing deterioration. End point glucose metabolism in the brain of hTau mice had a strong correlation with tau deposition measured by immunohistochemistry (R = 0.92, p < 0.001).

CONCLUSION

Late-stage oligomer modulation effectively ameliorated tau pathology in hTau mice and rescued metabolic function. Molecular imaging by FDG-PET can serve for monitoring effects of Anle138b treatment.

Aβ-induced vulnerability propagates via the brain's default mode network

The link between brain amyloid-β (Aβ), metabolism, and dementia symptoms remains a pressing question in Alzheimer's disease. Here, using positron emission tomography ([18F]florbetapir tracer for Aβ and [18F]FDG tracer for glucose metabolism) with a novel analytical framework, we found that Aβ aggregation within the brain's default mode network leads to regional hypometabolism in distant but functionally connected brain regions. Moreover, we found that an interaction between this hypometabolism with overlapping Aβ aggregation is associated with subsequent cognitive decline. These results were also observed in transgenic Aβ rats that do not form neurofibrillary tangles, which support these findings as an independent mechanism of cognitive deterioration. These results suggest a model in which distant Aβ induces regional metabolic vulnerability, whereas the interaction between local Aβ with a vulnerable environment drives the clinical progression of dementia.

Elecsys® Total-Tau and Phospho-Tau (181P) CSF assays: Analytical performance of the novel, fully automated immunoassays for quantification of tau proteins in human cerebrospinal fluid

BACKGROUND

Total tau (tTau) and phosphorylated 181P tau (pTau) are supportive diagnostic cerebrospinal fluid (CSF) biomarkers for Alzheimer's disease. Manual CSF tau assays are limited by lot-to-lot and between-laboratory variability and long incubation/turnaround times. Elecsys^® Total-Tau CSF and Phospho-Tau (181P) CSF immunoassays were developed for fully automated cobas e analyzers, allowing broader access in clinical practice and trials.

METHODS

Analytical performance, reproducibility, method comparisons with commercially available assays, and lot-to-lot and platform comparability (cobas e 601/411) of the Elecsys^® CSF assays were assessed. Tau distributions and concentration ranges were evaluated in CSF samples from two clinical cohorts.

RESULTS

Both assays showed high sensitivity (limit of quantitation [LoQ]: 63 pg/mL [tTau]; 4 pg/mL [pTau]) and linearity over the measuring range (80-1300 pg/mL; 8-120 pg/mL), which covered the entire concentration range measured in clinical samples. Lot-to-lot and platform comparability demonstrated good consistency (Pearson's r: 0.998; 1.000). Multicenter evaluation coefficients of variation (CVs): repeatability, < 1.8%; intermediate precision, < 2.8%; between-laboratory variability, < 2.7% (both assays); and total reproducibility, < 6.7% (tTau) and < 4.7% (pTau). Elecsys^® CSF assays demonstrated good correlation with commercially available tau assays.

CONCLUSIONS

Elecsys^® Total-Tau CSF and Phospho-Tau (181P) CSF assays demonstrate good analytical performance with clinically relevant measuring ranges; data support their use in clinical trials and practice.