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

Genetically Engineered Mouse Models for Alzheimer Disease and Frontotemporal Dementia: New Insights from Single-Cell and Spatial Transcriptomics

Neurodegenerative diseases, including Alzheimer disease, frontotemporal dementia, Parkinson disease, Huntington disease, and amyotrophic lateral sclerosis, are often casually linked to protein aggregation and inclusion. As the origins of those proteinopathies have been biochemically traced and genetically mapped, genetically engineered animal models carrying the specific mutations or variants are widely used for investigating the etiology of these diseases, as well as for testing potential therapeutics. This article focuses on the mouse models of Alzheimer disease and closely related frontotemporal dementia, particularly the ones that have provided most valuable knowledge, or are in a trajectory of doing so. More importantly, some of the major findings from these models are summarized, based on the recent single-cell transcriptomics, multiomics, and spatial transcriptomics studies. While no model is perfect, it is hoped that the new insights from these models and the practical use of these models will continue to help to establish a path forward.

Predicting Alzheimer's disease CSF core biomarkers: a multimodal Machine Learning approach

Introduction

Alzheimer's disease (AD) is a progressive neurodegenerative disorder. Current core cerebrospinal fluid (CSF) AD biomarkers, widely employed for diagnosis, require a lumbar puncture to be performed, making them impractical as screening tools. Considering the role of sleep disturbances in AD, recent research suggests quantitative sleep electroencephalography features as potential non-invasive biomarkers of AD pathology. However, quantitative analysis of comprehensive polysomnography (PSG) signals remains relatively understudied. PSG is a non-invasive test enabling qualitative and quantitative analysis of a wide range of parameters, offering additional insights alongside other biomarkers. Machine Learning (ML) gained interest for its ability to discern intricate patterns within complex datasets, offering promise in AD neuropathology detection. Therefore, this study aims to evaluate the effectiveness of a multimodal ML approach in predicting core AD CSF biomarkers.

Methods

Mild-moderate AD patients were prospectively recruited for PSG, followed by testing of CSF and blood samples for biomarkers. PSG signals underwent preprocessing to extract non-linear, time domain and frequency domain statistics quantitative features. Multiple ML algorithms were trained using four subsets of input features: clinical variables (CLINVAR), conventional PSG parameters (SLEEPVAR), quantitative PSG signal features (PSGVAR) and a combination of all subsets (ALL). Cross-validation techniques were employed to evaluate model performance and ensure generalizability. Regression models were developed to determine the most effective variable combinations for explaining variance in the biomarkers.

Results

On 49 subjects, Gradient Boosting Regressors achieved the best results in estimating biomarkers levels, using different loss functions for each biomarker: least absolute deviation (LAD) for the Aβ42, least squares (LS) for p-tau and Huber for t-tau. The ALL subset demonstrated the lowest training errors for all three biomarkers, albeit with varying test performance. Specifically, the SLEEPVAR subset yielded the best test performance in predicting Aβ42, while the ALL subset most accurately predicted p-tau and t-tau due to the lowest test errors.

Conclusions

Multimodal ML can help predict the outcome of CSF biomarkers in early AD by utilizing non-invasive and economically feasible variables. The integration of computational models into medical practice offers a promising tool for the screening of patients at risk of AD, potentially guiding clinical decisions.

Risk of conversion to mild cognitive impairment or dementia among subjects with amyloid and tau pathology: a systematic review and meta-analysis

BACKGROUND

Measurement of beta-amyloid (Aβ) and phosphorylated tau (p-tau) levels offers the potential for early detection of neurocognitive impairment. Still, the probability of developing a clinical syndrome in the presence of these protein changes (A+ and T+) remains unclear. By performing a systematic review and meta-analysis, we investigated the risk of mild cognitive impairment (MCI) or dementia in the non-demented population with A+ and A- alone and in combination with T+ and T- as confirmed by PET or cerebrospinal fluid examination.

METHODS

A systematic search of prospective and retrospective studies investigating the association of Aβ and p-tau with cognitive decline was performed in three databases (MEDLINE via PubMed, EMBASE, and CENTRAL) on January 9, 2024. The risk of bias was assessed using the Cochrane QUIPS tool. Odds ratios (OR) and Hazard Ratios (HR) were pooled using a random-effects model. The effect of neurodegeneration was not studied due to its non-specific nature.

RESULTS

A total of 18,162 records were found, and at the end of the selection process, data from 36 cohorts were pooled (n= 7,793). Compared to the unexposed group, the odds ratio (OR) for conversion to dementia in A+ MCI patients was 5.18 [95% CI 3.93; 6.81]. In A+ CU subjects, the OR for conversion to MCI or dementia was 5.79 [95% CI 2.88; 11.64]. Cerebrospinal fluid Aβ42 or Aβ42/40 analysis and amyloid PET imaging showed consistent results. The OR for conversion in A+T+ MCI subjects (11.60 [95% CI 7.96; 16.91]) was significantly higher than in A+T- subjects (2.73 [95% CI 1.65; 4.52]). The OR for A-T+ MCI subjects was non-significant (1.47 [95% CI 0.55; 3.92]). CU subjects with A+T+ status had a significantly higher OR for conversion (13.46 [95% CI 3.69; 49.11]) than A+T- subjects (2.04 [95% CI 0.70; 5.97]). Meta-regression showed that the ORs for Aβ exposure decreased with age in MCI. (beta = -0.04 [95% CI -0.03 to -0.083]).

CONCLUSIONS

Identifying Aβ-positive individuals, irrespective of the measurement technique employed (CSF or PET), enables the detection of the most at-risk population before disease onset, or at least at a mild stage. The inclusion of tau status in addition to Aβ, especially in A+T+ cases, further refines the risk assessment. Notably, the higher odds ratio associated with Aβ decreases with age.

TRIAL REGISTRATION

The study was registered in PROSPERO (ID: CRD42021288100).

The free plasma amyloid Aβ1-42/Aβ1-40 ratio predicts conversion to dementia for subjects with mild cognitive impairment with performance equivalent to that of the total plasma Aβ1-42/Aβ1-40 ratio. The BALTAZAR study

BACKGROUND AND PURPOSE

Blood-based biomarkers are a non-invasive solution to predict the risk of conversion of mild cognitive impairment (MCI) to dementia. The utility of free plasma amyloid peptides (not bound to plasma proteins and/or cells) as an early indicator of conversion to dementia is still debated, as the results of studies have been contradictory. In this context, we investigated whether plasma levels of the free amyloid peptides Aβ1-42 and Aβ1-40 and the free plasma Aβ1-42/Aβ1-40 ratio are associated with the conversion of MCI to dementia, in particular AD, over three years of follow-up in a subgroup of the BALTAZAR cohort. We also compared their predictive value to that of total plasma Aβ1-42 and Aβ1-40 levels and the total plasma Aβ1-42/Aβ1-40 ratio.

METHODS

The plasma Aβ1-42 and Aβ1-40 peptide assay was performed using the INNO-BIA kit (Fujirebio Europe). Free amyloid levels (defined by the amyloid fraction directly accessible to antibodies of the assay) were obtained with the undiluted plasma, whereas total amyloid levels were obtained after the dilution of plasma (1/3) with a denaturing buffer. Free and total Aβ1-42 and Aβ1-40 levels were measured at inclusion for a subgroup of participants (N = 106) with mild cognitive impairment (MCI) from the BALTAZAR study (a large-scale longitudinal multicenter cohort with a three-year follow-up). Associations between conversion and the free/total plasma Aβ1-42 and Aβ1-40 levels and Aβ1-42/Aβ1-40 ratio were analyzed using logistic and Cox Proportional Hazards models. Demographic, clinical, cognitive (MMSE, ADL and IADL), APOE, and MRI characteristics (relative hippocampal volume) were compared using non-parametric (Mann-Whitney) or parametric (Student) tests for quantitative variables and Chi-square or Fisher exact tests for qualitative variables.

RESULTS

The risk of conversion to dementia was lower for patients in the highest quartile of free plasma Aβ1-42/Aβ1-40 (≥ 25.8%) than those in the three lower quartiles: hazard ratio = 0.36 (95% confidence interval [0.15-0.87]), after adjustment for age, sex, education, and APOE ε4 (p-value = 0.022). This was comparable to the risk of conversion in the highest quartile of total plasma Aβ1-42/Aβ1-40: hazard ratio = 0.37 (95% confidence interval [0.16-0.89], p-value = 0.027). However, while patients in the highest quartile of total plasma Aβ1-42/Aβ1-40 showed higher MMSE scores and a higher hippocampal volume than patients in the three lowest quartiles of total plasma Aβ1-42/Aβ1-40, as well as normal CSF biomarker levels, the patients in the highest quartile of free plasma Aβ1-42/Aβ1-40 did not show any significant differences in MMSE scores, hippocampal volume, or CSF biomarker levels relative to the three lowest quartiles of free plasma Aβ1-42/Aβ1-40.

CONCLUSION

The free plasma Aβ1-42/Aβ1-40 ratio is associated with a risk of conversion from MCI to dementia within three years, with performance comparable to that of the total plasma Aβ1-42/Aβ1-40 ratio. Threshold levels of the free and total plasma Aβ1-42/Aβ1-40 ratio could be determined, with a 60% lower risk of conversion for patients above the threshold than those below.

Role of sleep in neurodegeneration: the consensus report of the 5th Think Tank World Sleep Forum

Sleep abnormalities may represent an independent risk factor for neurodegeneration. An international expert group convened in 2021 to discuss the state-of-the-science in this domain. The present article summarizes the presentations and discussions concerning the importance of a strategy for studying sleep- and circadian-related interventions for early detection and prevention of neurodegenerative diseases. An international expert group considered the current state of knowledge based on the most relevant publications in the previous 5 years; discussed the current challenges in the field of relationships among sleep, sleep disorders, and neurodegeneration; and identified future priorities. Sleep efficiency and slow wave activity during non-rapid eye movement (NREM) sleep are decreased in cognitively normal middle-aged and older adults with Alzheimer's disease (AD) pathology. Sleep deprivation increases amyloid-β (Aβ) concentrations in the interstitial fluid of experimental animal models and in cerebrospinal fluid in humans, while increased sleep decreases Aβ. Obstructive sleep apnea (OSA) is a risk factor for dementia. Studies indicate that positive airway pressure (PAP) treatment should be started in patients with mild cognitive impairment or AD and comorbid OSA. Identification of other measures of nocturnal hypoxia and sleep fragmentation could better clarify the role of OSA as a risk factor for neurodegeneration. Concerning REM sleep behavior disorder (RBD), it will be crucial to identify the subset of RBD patients who will convert to a specific neurodegenerative disorder. Circadian sleep-wake rhythm disorders (CSWRD) are strong predictors of caregiver stress and institutionalization, but the absence of recommendations or consensus statements must be considered. Future priorities include to develop and validate existing and novel comprehensive assessments of CSWRD in patients with/at risk for dementia. Strategies for studying sleep-circadian-related interventions for early detection/prevention of neurodegenerative diseases are required. CSWRD evaluation may help to identify additional biomarkers for phenotyping and personalizing treatment of neurodegeneration.

Biomarkers as Endpoints in Clinical Trials for Alzheimer's Disease

Background

Alzheimer's disease (AD) is a neurodegenerative disease that imposes economic and societal burden. Biomarkers have played a crucial role in the recent approval of aducanumab and lecanemab as disease-modifying therapies which marked a significant milestone for the treatment of AD. The inclusion of biomarkers in AD trials facilitates precise diagnosis, monitors safety, demonstrates target engagement, and supports disease modification.

Objective

This study analyzed the utilization state and trends of biomarkers as endpoints in AD trials.

Methods

In this retrospective study, trials were collected by searching clinicaltrials.gov using the term "Alzheimer". Primary and secondary outcomes were analyzed separately for each phase.

Results

Among the 1,048 analyzed trials, 313 (29.87%) adopted biomarkers as primary endpoints and 364 (34.73%) as secondary endpoints, mainly in phases 1 and 2. The top three biomarkers adopted as primary endpoints in phases 1, 2, and 3 were amyloid-PET, tau-PET, and MRI. The top three biomarkers adopted as secondary endpoints, in phase 1, were cerebrospinal fluid (CSF) amyloid-β (Aβ), blood Aβ and amyloid-PET; in phase 2, they were MRI, CSF Aβ, and CSF phospho-tau; and in phase 3, they were amyloid PET, MRI, and blood Aβ. There was a statistically significant increase in the adoption of biomarkers as primary endpoints in phase 2 trials (p = 0.001) and secondary endpoints in phase 3 trials (p = 0.001).

Conclusions

The growing recognition of the importance of biomarkers in AD trial' design and drug development is evident by the significant steady increase in biomarkers' utilization in phases 2 and 3.

Targeted examination of amyloid beta and tau protein accumulation via positron emission tomography for the differential diagnosis of Alzheimer's disease based on the A/T(N) research framework

Alzheimer's disease (AD) is one of the most common neurodegenerative diseases among the older population. Its main pathological features include the abnormal deposition of extracellular amyloid-β plaques and the intracellular neurofibrillary tangles of tau proteins. Its clinical presentation is complex. This review introduces the pathological processes in AD and other common neurodegenerative diseases. It then discusses the positron emission tomography (PET) probes that target amyloid-β plaques and tau proteins for diagnosing AD. According to the A/T(N) research framework, combined targeted amyloid-β and tau protein detection via PET to further improve the diagnostic accuracy of AD. In particular, the properties of the 18F-flortaucipir and 18F-MK6240 tracers-may be more beneficial in helping to differentiate AD from other common neurodegenerative diseases, such as dementia with Lewy bodies, Parkinson's disease dementia, and frontotemporal dementia. Furthermore, the A/T(N) research framework should be used as the clinical diagnosis model of AD in the future.

Identifying underlying patterns in Alzheimer's disease trajectory: a deep learning approach and Mendelian randomization analysis

Background

Alzheimer's disease (AD) is a heterogeneously progressive neurodegeneration disorder with varied rates of deterioration, either between subjects or within different stages of a certain subject. Estimating the course of AD at early stages has treatment implications. We aimed to analyze disease progression to identify distinct patterns in AD trajectory.

Methods

We proposed a deep learning model to identify underlying patterns in the trajectory from cognitively normal (CN) to a state of mild cognitive impairment (MCI) to AD dementia, by jointly predicting time-to-conversion and clustering out distinct subgroups characterized by comprehensive features as well as varied progression rates. We designed and validated our model on the ADNI dataset (1370 participants). Prediction of time-to-conversion in AD trajectory was used to validate the expression of the identified patterns. Causality between patterns and time-to-conversion was further inferred using Mendelian randomization (MR) analysis. External validation was performed on the AIBL dataset (233 participants).

Findings

The proposed model clustered out patterns characterized by significantly different biomarkers and varied progression rates. The discovered patterns also showed a strong prediction ability, as indicated by hazard ratio (CN→MCI, HR = 3.51, p < 0.001; MCI→AD, HR = 8.11, p < 0.001), C-Index (CN→MCI, 0.618; MCI→AD, 0.718), and AUC (CN→MCI, 3 years 0.802, 5 years 0.876; MCI→AD, 3 years 0.914, 5 years 0.957). In the external validation cohort, our model demonstrated competitive performance on conversion time prediction (CN→MCI, C-Index = 0.693; MCI→AD, C-Index = 0.752). Moreover, suggestive associations between CN→MCI/MCI→AD patterns with four/three SNPs were mediated and MR analysis indicated a causal link between MCI→AD patterns and time-to-conversion in the first three years.

Interpretation

Our proposed model identifies biologically and clinically meaningful patterns from real-world data and provides promising performance on time-to-conversion prediction in AD trajectory, which could promote the understanding of disease progression, facilitate clinical trial design, and provide potential for decision-making.

Funding

The National Key Research and Development Program of China, the Key R&D Program of Zhejiang, and the National Nature Science Foundation of China.

Global biomarker trends in Alzheimer's research: a bibliometric analysis

Alzheimer's disease (AD) has no effective treatment, although antibody drugs targeting beta-amyloid, mainly aducanumab, have produced useful clinical results. Biomarkers can be used to determine drug regimens effectively and to monitor the effects of drugs. A concept in which biomarkers reflect disease states is emerging. Although several AD biomarker studies have been reported, measurement methods and target molecules are still being validated, and various biomarkers are being explored. This study analyzed trends in research on AD biomarkers using bibliometric methods, revealing an exponential increase in research reports in this field, with the US most active in research. Analysis of the 'Burst' biomarkers using CiteSpace revealed that networks centered on authors, rather than networks among countries, drive new research trends in this area.

Personalising Alzheimer's Disease progression using brain atrophy markers

INTRODUCTION

Neuroanatomical normative modelling can capture individual variability in Alzheimer's Disease (AD). We used neuroanatomical normative modelling to track individuals' disease progression in people with mild cognitive impairment (MCI) and patients with AD.

METHODS

Cortical thickness and subcortical volume neuroanatomical normative models were generated using healthy controls (n~58k). These models were used to calculate regional Z-scores in 4361 T1-weighted MRI time-series scans. Regions with Z-scores <-1.96 were classified as outliers and mapped on the brain, and also summarised by total outlier count (tOC).

RESULTS

Rate of change in tOC increased in AD and in people with MCI who converted to AD and correlated with multiple non-imaging markers. Moreover, a higher annual rate of change in tOC increased the risk of MCI progression to AD. Brain Z-score maps showed that the hippocampus had the highest rate of atrophy change.

CONCLUSIONS

Individual-level atrophy rates can be tracked by using regional outlier maps and tOC.

Exploring the ATN classification system using brain morphology

BACKGROUND

The NIA-AA proposed amyloid-tau-neurodegeneration (ATN) as a classification system for AD biomarkers. The amyloid cascade hypothesis (ACH) implies a sequence across ATN groups that patients might undergo during transition from healthy towards AD: A-T-N-➔A+T-N-➔A+T+N-➔A+T+N+. Here we assess the evidence for monotonic brain volume decline for this particular (amyloid-conversion first, tau-conversion second, N-conversion last) and alternative progressions using voxel-based morphometry (VBM) in a large cross-sectional MRI cohort.

METHODS

We used baseline data of the DELCODE cohort of 437 subjects (127 controls, 168 SCD, 87 MCI, 55 AD patients) which underwent lumbar puncture, MRI scanning, and neuropsychological assessment. ATN classification was performed using CSF-Aβ42/Aβ40 (A+/-), CSF phospho-tau (T+/-), and adjusted hippocampal volume or CSF total-tau (N+/-). We compared voxel-wise model evidence for monotonic decline of gray matter volume across various sequences over ATN groups using the Bayesian Information Criterion (including also ROIs of Braak stages). First, face validity of the ACH transition sequence A-T-N-➔A+T-N-➔A+T+N-➔A+T+N+ was compared against biologically less plausible (permuted) sequences among AD continuum ATN groups. Second, we evaluated evidence for 6 monotonic brain volume progressions from A-T-N- towards A+T+N+ including also non-AD continuum ATN groups.

RESULTS

The ACH-based progression A-T-N-➔A+T-N-➔A+T+N-➔A+T+N+ was consistent with cognitive decline and clinical diagnosis. Using hippocampal volume for operationalization of neurodegeneration (N), ACH was most evident in 9% of gray matter predominantly in the medial temporal lobe. Many cortical regions suggested alternative non-monotonic volume progressions over ACH progression groups, which is compatible with an early amyloid-related tissue expansion or sampling effects, e.g., due to brain reserve. Volume decline in 65% of gray matter was consistent with a progression where A status converts before T or N status (i.e., ACH/ANT) when compared to alternative sequences (TAN/TNA/NAT/NTA). Brain regions earlier affected by tau tangle deposition (Braak stage I-IV, MTL, limbic system) present stronger evidence for volume decline than late Braak stage ROIs (V/VI, cortical regions). Similar findings were observed when using CSF total-tau for N instead.

CONCLUSION

Using the ATN classification system, early amyloid status conversion (before tau and neurodegeneration) is associated with brain volume loss observed during AD progression. The ATN system and the ACH are compatible with monotonic progression of MTL atrophy.

TRIAL REGISTRATION

DRKS00007966, 04/05/2015, retrospectively registered.

The Clinical Application of Optimized AT(N) Classification in Alzheimer’s Clinical Syndrome (ACS) and non-ACS Conditions

We aimed to assess the utility of AT(N) classification in clinical practice. We measured the cerebrospinal fluid levels of amyloid-β (Aβ) 42, Aβ40, phosphorylated tau, total tau, and neurofilament light chain (NfL) in samples from 230 patients with Alzheimer's clinical syndrome (ACS) and 328 patients with non-ACS. The concordance of two A-markers (i.e., Aβ42 alone and the Aβ42/Aβ40 ratio) was not significantly different between the ACS (87.4%) and non-ACS (74.1%) groups. However, the frequency of discordant cases with A_Aβ42-alone+/A_Aβ-ratio- was significantly higher in the non-ACS (23.8%) than in the ACS group (7.4%). The concordance of two N-markers (i.e., total tau and NfL) was 40.4% in the ACS group and 24.4% in the non-ACS group. In the ACS samples, the frequency of biological Alzheimer's disease (i.e., A+T+) in N_tau+ cases was 95% while that in N_NfL+ cases was 65%. Reflecting Aβ deposition and neurodegeneration more accurately, we recommend the use of AT(N) classification defined by cerebrospinal fluid A_Aβ-ratioTN_NfL in clinical practice.

Pathology vs pathogenesis: Rationale and pitfalls in the clinicopathology model of neurodegeneration

In neurodegenerative disorders, the term pathology is often implicitly referred to as pathogenesis. Pathology has been conceived as a window into the pathogenesis of neurodegenerative disorders. This clinicopathologic framework posits that what can be identified and quantified in postmortem brain tissue can explain both premortem clinical manifestations and the cause of death, a forensic approach to understanding neurodegeneration. As the century-old clinicopathology framework has yielded little correlation between pathology and clinical features or neuronal loss, the relationship between proteins and degeneration is ripe for revisitation. There are indeed two synchronous consequences of protein aggregation in neurodegeneration: the loss of the soluble/normal proteins on one; the accrual of the insoluble/abnormal fraction of these proteins on the other. The omission of the first part in the protein aggregation process is an artifact of the early autopsy studies: soluble, normal proteins have disappeared, with only the remaining insoluble fraction amenable to quantification. We here review the collective evidence from human data suggesting that protein aggregates, known collectively as pathology, are the consequence of many biological, toxic, and infectious exposures, but may not explain alone the cause or pathogenesis of neurodegenerative disorders.

The Case for a Novel Therapeutic Approach to Dementia: Small Molecule Hepatocyte Growth Factor (HGF/MET) Positive Modulators

An estimated 6.5 million Americans aged 65 years or older have Alzheimer's disease (AD), which will grow to 13.8 million Americans by 2060. Despite the growing burden of dementia, no fundamental change in drug development for AD has been seen in > 20 years. Currently approved drugs for AD produce only modest symptomatic improvements in cognition with small effect sizes. A growing mismatch exists between the urgent need to develop effective drugs for symptomatic AD and the largely failed search for disease modification. The failure rate of clinical trials in AD is high overall, and in particular for disease-modifying therapies. Research efforts in AD have focused predominantly on amyloid-β and tau pathologies, but limiting clinical research to these "classical hallmarks" of the disease does not address the most urgent patient, caregiver, or societal needs. Rather, clinical research should consider the complex pathophysiology of AD. Innovative approaches are needed that provide outside-the-box thinking, and re-imagine trial design, interventions, and outcomes as well as progress in proteomics and fluid biomarker analytics for both diagnostics and disease monitoring. A new approach offering a highly specific, yet multi-pronged intervention that exerts positive modulation on the HGF/MET neurotrophic system is currently being tested in mid-to-late-stage clinical trials in mild to moderate AD. Findings from such trials may provide data to support novel approaches for development of innovative drugs for treating AD at various disease stages, including among patients already symptomatic, and may offer benefits for other neurodegenerative diseases.

A call for better understanding of target engagement in Tau antibody development

Significant efforts have been channeled into developing antibodies for the treatment of CNS indications. Disappointment with the first generation of clinical Tau antibodies in Alzheimer's disease has highlighted the challenges in understanding whether an antibody can reach or affect the target in the compartment where it is involved in pathological processes. Here, we highlight different aspects essential for improving translatability of Tau-based immunotherapy.

Association of Klotho Protein Levels and KL-VS Heterozygosity With Alzheimer Disease and Amyloid and Tau Burden

IMPORTANCE

Identification of proteins and genetic factors that reduce Alzheimer disease (AD) pathology is of importance when searching for novel AD treatments. Heterozygosity of the KL-VS haplotype has been associated with reduced amyloid and tau burden. Whether this association is mediated by the Klotho protein remains unclear.

OBJECTIVES

To assess concentrations of Klotho in cerebrospinal fluid (CSF) and plasma among cognitively healthy controls and patients with AD and to correlate these findings with KL-VS heterozygosity status and amyloid and tau burden.

DESIGN, SETTING, AND PARTICIPANTS

This case-control study combined 2 independent case-control AD cohorts consisting of 243 referred patients with AD and volunteer controls recruited from January 1, 2009, to December 31, 2018. Klotho levels were measured in CSF and plasma and correlated with KL-VS heterozygosity status and levels of CSF amyloid-β 42 (Aβ42), total tau, and phosphorylated tau. Statistical analysis was performed from January 1, 2021, to March 1, 2022.

MAIN OUTCOMES AND MEASURES

Associations of Klotho levels in CSF and plasma with levels of CSF biomarkers were analyzed using linear regression. Association analyses were stratified separately by clinical groups, APOE4 status, and KL-VS heterozygosity. Pearson correlation was used to assess the correlation between CSF and plasma Klotho levels.

RESULTS

A total of 243 participants were included: 117 controls (45 men [38.5%]; median age, 65 years [range, 41-84 years]), 102 patients with mild cognitive impairment due to AD (AD-MCI; 59 men [57.8%]; median age, 66 years [range, 46-80 years]), and 24 patients with dementia due to AD (AD-dementia; 12 men [50.0%]; median age, 64.5 years [range, 54-75 years]). Median CSF Klotho levels were higher in controls (1236.4 pg/mL [range, 20.4-1726.3 pg/mL]; β = 0.103; 95% CI, 0.023-0.183; P = .01) and patients with AD-MCI (1188.1 pg/mL [range, 756.3-1810.3 pg/mL]; β = 0.095; 95% CI, 0.018-0.172; P = .02) compared with patients with AD-dementia (1073.3 pg/mL [range, 698.2-1661.4 pg/mL]). Higher levels of CSF Klotho were associated with lower CSF Aβ42 burden (β = 0.519; 95% CI, 0.201-0.836; P < .001) and tau burden (CSF total tau levels: β = -0.884; 95% CI, 0.223 to -0.395; P < .001; CSF phosphorylated tau levels: β = -0.672; 95% CI, -1.022 to -0.321; P < .001) independent of clinical, KL-VS heterozygosity, or APOE4 status. There was a weak correlation between Klotho CSF and plasma levels among the entire cohort (Pearson correlation r = 0.377; P < .001).

CONCLUSIONS AND RELEVANCE

The findings of this case-control study suggest that Klotho protein levels were associated with clinical stages of AD, cognitive decline, and amyloid and tau burden and that these outcomes were more clearly mediated by the protein directly rather than the KL-VS heterozygosity variant. When selecting individuals at risk for clinical trials, the Klotho protein level and not only the genetic profile should be considered.

Alzheimer’s Disease Diagnosis Based on the Amyloid, Tau, and Neurodegeneration Scheme (ATN) in a Real-Life Multicenter Cohort of General Neurological Centers

Background: The ATN scheme was proposed as an unbiased biological characterization of the Alzheimer’s disease (AD) spectrum, grouping biomarkers into three categories: brain Amyloidosis-A, Tauopathy-T, Neurodegeneration-N. Although this scheme was mainly recommended for research, it is relevant for diagnosis. Objective: To evaluate the ATN scheme performance in real-life cohorts reflecting the inflow of patients with cognitive complaints and different underlying disorders in general neurological centers. Methods: We included patients (n = 1,128) from six centers with their core cerebrospinal fluid-AD biomarkers analyzed centrally. A was assessed through Aβ 42/Aβ 40, T through pTau-181, and N through tTau. Association between demographic features, clinical diagnosis at baseline/follow-up and ATN profiles was assessed. Results: The prevalence of ATN categories was: A-T-N-: 28.3% ; AD continuum (A + T-/+N-/+): 47.8% ; non-AD (A- plus T or/and N+): 23.9% . ATN profiles prevalence was strongly influenced by age, showing differences according to gender, APOE genotype, and cognitive status. At baseline, 74.6% of patients classified as AD fell in the AD continuum, decreasing to 47.4% in mild cognitive impairment and 42.3% in other neurodegenerative conditions. At follow-up, 41% of patients changed diagnosis, and 92% of patients that changed to AD were classified within the AD continuum. A + was the best individual marker for predicting a final AD diagnosis, and the combinations A + T+(irrespective of N) and A + T+N+had the highest overall accuracy (83%). Conclusion: The ATN scheme is useful to guide AD diagnosis real-life neurological centers settings. However, it shows a lack of accuracy for patients with other types of dementia. In such cases, the inclusion of other markers specific for non-AD proteinopathies could be an important aid to the differential diagnosis.

Different AT(N) profiles and clinical progression classified by two different N markers using total tau and neurofilament light chain in cerebrospinal fluid

Background

The AT(N) classification was proposed for categorising individuals according to biomarkers. However, AT(N) profiles may vary depending on the markers chosen and the target population.

Methods

We stratified 177 individuals who participated in the Japanese Alzheimer's Disease Neuroimaging Initiative by AT(N) classification according to cerebrospinal fluid (CSF) biomarkers. We compared the frequency of AT(N) profiles between the classification using total tau and neurofilament light chain (NfL) as N markers (AT(N)_tau and AT(N)_NfL). Baseline characteristics, and longitudinal biological and clinical changes were examined between AT(N) profiles.

Results

We found that 9% of cognitively unimpaired subjects, 49% of subjects with mild cognitive impairment, and 61% of patients with Alzheimer's disease (AD) dementia had the biological AD profile (ie, A+T+) in the cohort. The frequency of AT(N) profiles substantially differed between the AT(N)_tau and AT(N)_NfL classifications. When we used t-tau as the N marker (AT(N)_tau), those who had T- were more frequently assigned to (N)-, whereas those who had T+were more frequently assigned to (N)+ than when we used NfL as the N marker (AT(N)_NfL). During a follow-up, the AD continuum group progressed clinically and biologically compared with the normal biomarker group in both the AT(N)_tau and AT(N)_NfL classifications. More frequent conversion to dementia was observed in the non-AD pathological change group in the AT(N)_tau classification, but not in the AT(N)_NfL classification.

Conclusions

AT(N)_tau and AT(N)_NfL in CSF may capture different aspects of neurodegeneration and provide a different prognostic value. The AT(N) classification aids in understanding the AD continuum biology in various populations.

Plasma apolipoprotein E levels in longitudinally followed patients with mild cognitive impairment and Alzheimer’s disease

Background

Low levels of plasma apolipoprotein E (apoE) and presence of the APOE ε4 allele are associated with an increased risk of Alzheimer’s disease (AD). Although the increased risk of AD in APOE ε4-carriers is well-established, the protein levels have received limited attention.

Methods

We here report the total plasma apoE and apoE isoform levels at baseline from a longitudinally (24 months) followed cohort including controls (n = 39), patients with stable amnestic mild cognitive impairment during 24 months follow up (MCI-MCI, n = 30), patients with amnestic MCI (aMCI) that during follow-up were clinically diagnosed with AD with dementia (ADD) (MCI-ADD, n = 28), and patients with AD with dementia (ADD) at baseline (ADD, n = 28). We furthermore assessed associations between plasma apoE levels with cerebrospinal fluid (CSF) AD biomarkers and α-synuclein, as well as both CSF and plasma neurofilament light chain (NfL), YKL-40 and kallikrein 6.

Results

Irrespective of clinical diagnosis, the highest versus the lowest apoE levels were found in APOE ε2/ε3 versus APOE ε4/ε4 subjects, with the most prominent differences exhibited in females. Total plasma apoE levels were 32% and 21% higher in the controls versus MCI-ADD and ADD patients, respectively. Interestingly, MCI-ADD patients exhibited a 30% reduction in plasma apoE compared to MCI-MCI patients. This decrease appeared to be associated with brain amyloid-β (Aβ42) pathology regardless of disease status as assessed using the Amyloid, Tau, and Neurodegeneration (A/T/N) classification. In addition to the association between low plasma apoE and low levels of CSF Aβ42, lower apoE levels were also related to higher levels of CSF total tau (t-tau) and tau phosphorylated at Threonine 181 residue (p-tau) and NfL as well as a worse performance on the mini-mental-state-examination. In MCI-ADD patients, low levels of plasma apoE were associated with higher levels of CSF α-synuclein and kallikrein 6. No significant correlations between plasma apoE and the astrocytic inflammatory marker YKL40 were observed.

Conclusions

Our results demonstrate important associations between low plasma apoE levels, Aβ pathology, and progression from aMCI to a clinical ADD diagnosis.

Association between obstructive sleep apnea and Alzheimer's disease-related blood and cerebrospinal fluid biomarkers: A meta-analysis

INTRODUCTION

Recent studies indicate that Alzheimer's disease- (AD) related biomarkers, including amyloid β (Aβ40 and Aβ42) and tau proteins (P-tau and T-tau), in blood and cerebrospinal fluid (CSF) are associated with obstructive sleep apnea (OSA). However, the results have been inconsistent. Therefore, the primary purpose of this meta-analysis was to determine the relationship between blood and CSF AD-related biomarkers and OSA.

METHODS

We searched the Embase, PubMed, Scopus, and Cochrane Library databases for relevant articles till February 2022.

RESULTS

Eight articles were finally included after the literature screening, including 446 patients with OSA and 286 controls. Pooled analysis showed that CSF Aβ42 (SMD = -0.220, P = 0.136), T-tau (SMD = 0.012, P = 0.89), and P-tau (SMD = 0.099, P = 0.274) levels were not different between patients with OSA and controls. In patients with moderate to severe OSA, CSF Aβ42 (SMD = -0.482, P = 0.031) were significantly lower than in controls. Blood T-tau (SMD = 0.560, P = 0.026), P-tau (SMD = 0.621, P < 0.001), and Aβ40 (SMD = 0.656, P < 0.001) levels were significantly higher in patients with OSA than in controls. Blood Aβ42 (SMD = 0.241, P = 0.232) were not different between patients with OSA and controls.

CONCLUSION

OSA is associated with changes in AD-related markers. Higher OSA severity may be associated with the development of AD. AD-related biomarkers, especially in the blood, are clinically efficient, less invasively assessed and monitored, and may be useful for detecting OSA and related cognitive impairments. Further studies are needed to confirm these results.

Peripheral sTREM2-Related Inflammatory Activity Alterations in Early-Stage Alzheimer's Disease

Alzheimer's disease (AD) has been linked to multiple immune system-related genetic variants. Triggering receptor expressed on myeloid cells 2 (TREM2) genetic variants are risk factors for AD and other neurodegenerative diseases. In addition, soluble TREM2 (sTREM2) isoform is elevated in cerebrospinal fluid in the early stages of AD and is associated with slower cognitive decline in a disease stage-dependent manner. Multiple studies have reported an altered peripheral immune response in AD. However, less is known about the relationship between peripheral sTREM2 and an altered peripheral immune response in AD. The objective of this study was to explore the relationship between human plasma sTREM2 and inflammatory activity in AD. The hypothesis of this exploratory study was that sTREM2-related inflammatory activity differs by AD stage. We observed different patterns of inflammatory activity across AD stages that implicate early-stage alterations in peripheral sTREM2-related inflammatory activity in AD. Notably, fractalkine showed a significant relationship with sTREM2 across different analyses in the control groups that was lost in later AD-related stages with high levels in mild cognitive impairment. Although multiple other inflammatory factors either differed significantly between groups or were significantly correlated with sTREM2 within specific groups, three inflammatory factors (fibroblast growth factor-2, GM-CSF, and IL-1β) are notable because they exhibited both lower levels in AD, compared with mild cognitive impairment, and a change in the relationship with sTREM2. This evidence provides important support to the hypothesis that sTREM2-related inflammatory activity alterations are AD stage specific and provides critical information for therapeutic strategies focused on the immune response.

Association of CSF, Plasma, and Imaging Markers of Neurodegeneration With Clinical Progression in People With Subjective Cognitive Decline

BACKGROUND AND OBJECTIVES

Multiple biomarkers have been suggested to measure neurodegeneration (N) in the AT(N) framework, leading to inconsistencies between studies. We investigated the association of 5 N biomarkers with clinical progression and cognitive decline in individuals with subjective cognitive decline (SCD).

METHODS

We included individuals with SCD from the Amsterdam Dementia Cohort and SCIENCe project, a longitudinal cohort study (follow-up 4±3 years). We used the following N biomarkers: CSF total tau (t-tau), medial temporal atrophy visual rating on MRI, hippocampal volume (HV), serum neurofilament light (NfL), and serum glial fibrillary acidic protein (GFAP). We determined correlations between biomarkers. We assessed associations between N biomarkers and clinical progression to mild cognitive impairment or dementia (Cox regression) and Mini-Mental State Examination (MMSE) over time (linear mixed models). Models included age, sex, CSF β-amyloid (Aβ) (A), and CSF p-tau (T) as covariates, in addition to the N biomarker.

RESULT

We included 401 individuals (61±9 years, 42% female, MMSE 28 ± 2, vascular comorbidities 8%-19%). N biomarkers were modestly to moderately correlated (range r -0.28 - 0.58). Serum NfL and GFAP correlated most strongly (r 0.58, p < 0.01). T-tau was strongly correlated with p-tau (r 0.89, p < 0.01), although these biomarkers supposedly represent separate biomarker groups. All N biomarkers individually predicted clinical progression, but only HV, NfL, and GFAP added predictive value beyond Aβ and p-tau (hazard ratio 1.52 [95% CI 1.11-2.09]; 1.51 [1.05-2.17]; 1.50 [1.04-2.15]). T-tau, HV, and GFAP individually predicted MMSE slope (range β -0.17 to -0.11, p < 0.05), but only HV remained associated beyond Aβ and p-tau (β -0.13 [SE 0.04]; p < 0.05).

DISCUSSION

In cognitively unimpaired older adults, correlations between different N biomarkers were only moderate, indicating they reflect different aspects of neurodegeneration and should not be used interchangeably. T-tau was strongly associated with p-tau (T), which makes it less desirable to use as a measure for N. HV, NfL, and GFAP predicted clinical progression beyond A and T. Our results do not allow to choose one most suitable biomarker for N, but illustrate the added prognostic value of N beyond A and T.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that HV, NfL, and GFAP predicted clinical progression beyond A and T in individuals with SCD.

Intermittent hypoxia and sleep disruption in obstructive sleep apnea increase serum tau and amyloid-beta levels

Obstructive sleep apnea is characterized by intermittent hypoxia and sleep disruption, leading to accelerated neurodegenerative changes and cognitive decline. Serum amyloid-beta and tau proteins, which are markers for Alzheimer's disease, have been reported to increase in patients with obstructive sleep apnea. This study compared the serum levels of amyloid-beta proteins and tau proteins in 46 cognitively normal obstructive sleep apnea patients and 30 healthy controls. Sleep parameters and severity of obstructive sleep apnea were determined using overnight polysomnography. Serum levels of Aβ40, Aβ42, total tau and phosphorylated-tau were determined by enzyme-linked immunosorbent assay. Patients with obstructive sleep apnea had significantly higher median serum levels of Aβ40 (121.0 versus 78.3 pg ml^-1 ), Aβ42 (105.6 versus 18.6 pg ml^-1 ) and total tau (168.5 versus 10.9 pg ml^-1 ) than controls. Serum levels of phosphorylated-tau did not differ significantly between the two groups. Serum levels of amyloid and tau proteins correlated with parameters of nocturnal oxygen saturation. Rapid eye movement sleep was negatively correlated with total amyloid-beta proteins. We conclude that serum levels of amyloid-beta and total tau are higher in patients with obstructive sleep apnea and hypoxia as well as changes in sleep architecture associated with their increased levels. Patients with obstructive sleep apnea should be closely monitored for the signs of cognitive impairment. Obstructive sleep apnea is a modifiable risk factor, and its treatment may reverse neurodegenerative changes and prevent cognitive impairment.

Developing the ATX(N) classification for use across the Alzheimer disease continuum

Breakthroughs in the development of highly accurate fluid and neuroimaging biomarkers have catalysed the conceptual transformation of Alzheimer disease (AD) from the traditional clinical symptom-based definition to a clinical-biological construct along a temporal continuum. The AT(N) system is a symptom-agnostic classification scheme that categorizes individuals using biomarkers that chart core AD pathophysiological features, namely the amyloid-β (Aβ) pathway (A), tau-mediated pathophysiology (T) and neurodegeneration (N). This biomarker matrix is now expanding towards an ATX(N) system, where X represents novel candidate biomarkers for additional pathophysiological mechanisms such as neuroimmune dysregulation, synaptic dysfunction and blood-brain barrier alterations. In this Perspective, we describe the conceptual framework and clinical importance of the existing AT(N) system and the evolving ATX(N) system. We provide a state-of-the-art summary of the potential contexts of use of these systems in AD clinical trials and future clinical practice. We also discuss current challenges related to the validation, standardization and qualification process and provide an outlook on the real-world application of the AT(N) system.

CSF neurofilament light may predict progression from amnestic mild cognitive impairment to Alzheimer's disease dementia

Neurofilament light (NfL) is a promising biomarker of neurodegeneration in Alzheimer's disease (AD). In this study, cerebrospinal fluid (CSF) NfL was measured in a 24-month longitudinal cohort consisting of control (n = 52), amnestic mild cognitive impairment (aMCI) (n = 55), and probable AD dementia (n = 28) individuals. The cohort was reevaluated after 6-10 years. Baseline CSF NfL was significantly elevated in aMCI and probable AD dementia groups compared to controls (p < 0.0001). CSF NfL was significantly lower in stable aMCI patients compared to aMCI patients who converted to probable AD dementia within the 24-month period (p = 0.004). Substituting T-tau for NfL in the core AD biomarkers model (Aβ42/P-tau/T-tau) did not improve ability to separate control and AD, or stable and converter aMCI patients. Our results support that elevated CSF NfL could predict progression in aMCI patients, but its utility cannot improve the core AD biomarkers.

Soluble Amyloid-β Consumption in Alzheimer's Disease

Brain proteins function in their soluble, native conformation and cease to function when transformed into insoluble aggregates, also known as amyloids. Biophysically, the soluble-to-insoluble phase transformation represents a process of polymerization, similar to crystallization, dependent on such extrinsic factors as concentration, pH, and a nucleation surface. The resulting cross-β conformation of the insoluble amyloid is markedly stable, making it an unlikely source of toxicity. The spread of brain amyloidosis can be fully explained by mechanisms of spontaneous or catalyzed polymerization and phase transformation instead of active replication, which is an enzyme- and energy-requiring process dependent on a specific nucleic acid code for the transfer of biological information with high fidelity. Early neuronal toxicity in Alzheimer's disease may therefore be mediated to a greater extent by a reduction in the pool of soluble, normal-functioning protein than its accumulation in the polymerized state. This alternative loss-of-function hypothesis of pathogenicity can be examined by assessing the clinical and neuroimaging effects of administering non-aggregating peptide analogs to replace soluble amyloid-β levels above the threshold below which neuronal toxicity may occur. Correcting the depletion of soluble amyloid-β, however, would only exemplify 'rescue medicine.' Precision medicine will necessitate identifying the pathogenic factors catalyzing the protein aggregation in each affected individual. Only then can we stratify patients for etiology-specific treatments and launch precision medicine for Alzheimer's disease and other neurodegenerative disorders.

Serum Levels of Clusterin, PKR, and RAGE Correlate with Amyloid Burden in Alzheimer's Disease

BACKGROUND

Alzheimer's disease (AD) is the most common form of dementia and biomarkers are essential to help in the diagnosis of this disease. Image techniques and cerebrospinal fluid (CSF) biomarkers are limited in their use because they are expensive or invasive. Thus, the search for blood-borne biomarkers is becoming central to the medical community.

OBJECTIVE

The main objective of this study is the evaluation of three serum proteins as potential biomarkers in AD patients.

METHODS

We recruited 27 healthy controls, 19 mild cognitive impairment patients, and 17 AD patients. Using the recent A/T/N classification we split our population into two groups (AD and control). We used ELISA kits to determine Aβ42, tau, and p-tau in CSF and clusterin, PKR, and RAGE in serum.

RESULTS

The levels of serum clusterin, PKR, and RAGE were statistically different in the AD group compared to controls. These proteins showed a statistically significant correlation with CSF Aβ42. So, they were selected to generate an AD detection model showing an AUC-ROC of 0.971 (CI 95%, 0.931-0.998).

CONCLUSION

The developed model based on serum biomarkers and other co-variates could reflect the AD core pathology. So far, not one single blood-biomarker has been described, with effectiveness offering high sensitivity and specificity. We propose that the complexity of AD pathology could be reflected in a set of biomarkers also including clinical features of the patients.

2020 update on the clinical validity of cerebrospinal fluid amyloid, tau, and phospho-tau as biomarkers for Alzheimer's disease in the context of a structured 5-phase development framework

Purpose

In the last decade, the research community has focused on defining reliable biomarkers for the early detection of Alzheimer’s disease (AD) pathology. In 2017, the Geneva AD Biomarker Roadmap Initiative adapted a framework for the systematic validation of oncological biomarkers to cerebrospinal fluid (CSF) AD biomarkers—encompassing the 42 amino-acid isoform of amyloid-β (Aβ42), phosphorylated-tau (P-tau), and Total-tau (T-tau)—with the aim to accelerate their development and clinical implementation. The aim of this work is to update the current validation status of CSF AD biomarkers based on the Biomarker Roadmap methodology.

Methods

A panel of experts in AD biomarkers convened in November 2019 at a 2-day workshop in Geneva. The level of maturity (fully achieved, partly achieved, preliminary evidence, not achieved, unsuccessful) of CSF AD biomarkers was assessed based on the Biomarker Roadmap methodology before the meeting and presented and discussed during the workshop.

Results

By comparison to the previous 2017 Geneva Roadmap meeting, the primary advances in CSF AD biomarkers have been in the area of a unified protocol for CSF sampling, handling and storage, the introduction of certified reference methods and materials for Aβ42, and the introduction of fully automated assays. Additional advances have occurred in the form of defining thresholds for biomarker positivity and assessing the impact of covariates on their discriminatory ability.

Conclusions

Though much has been achieved for phases one through three, much work remains in phases four (real world performance) and five (assessment of impact/cost). To a large degree, this will depend on the availability of disease-modifying treatments for AD, given these will make accurate and generally available diagnostic tools key to initiate therapy.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-021-05258-7.

Dementia in Latin America: Paving the way toward a regional action plan

Across Latin American and Caribbean countries (LACs), the fight against dementia faces pressing challenges, such as heterogeneity, diversity, political instability, and socioeconomic disparities. These can be addressed more effectively in a collaborative setting that fosters open exchange of knowledge. In this work, the Latin American and Caribbean Consortium on Dementia (LAC-CD) proposes an agenda for integration to deliver a Knowledge to Action Framework (KtAF). First, we summarize evidence-based strategies (epidemiology, genetics, biomarkers, clinical trials, nonpharmacological interventions, networking, and translational research) and align them to current global strategies to translate regional knowledge into transformative actions. Then we characterize key sources of complexity (genetic isolates, admixture in populations, environmental factors, and barriers to effective interventions), map them to the above challenges, and provide the basic mosaics of knowledge toward a KtAF. Finally, we describe strategies supporting the knowledge creation stage that underpins the translational impact of KtAF.

Millipore xMap® Luminex (HATMAG-68K): An Accurate and Cost-Effective Method for Evaluating Alzheimer's Biomarkers in Cerebrospinal Fluid

Background: Alzheimer's disease (AD) biomarkers are of great relevance in clinical research, especially after the AT(N) framework. They enable early diagnosis, disease staging and research with new promising drugs, monitoring therapeutic response. However, the high cost and low availability of the most well-known methods limits their use in low and medium-income countries. In this context, Millipore xMap^® Luminex may be a cost-effective alternative. In our study, using INNOTEST^® as reference, we assess the diagnostic accuracy of Millipore xMap^® and propose a cutoff point for AD. Methods: We performed lumbar puncture of seven older individuals with clinically defined AD, 17 with amnestic mild cognitive impairment (aMCI) and 11 without objective cognitive impairment-control group (CG). Cerebrospinal fluid (CSF) biomarkers concentrations for aB42, p-Tau, and t-Tau were measured by INNOTEST^® and Millipore xMap^®, and then the techniques were compared to assess the diagnostic accuracy of the new test and to define a cutoff. Results: INNOTEST^® and Millipore xMap^® measurements showed all correlations >0.8 for the same biomarker, except for t-Tau that was 0.66. Millipore xMap^® measurements showed a robust accuracy for all biomarkers, with AUC higher than 0.808 (t-Tau), and the best for Aβ42 (AUC = 0.952). The most accurate cutoffs were found at 1012.98 pg/ml (Aβ42), 64.54 pg/ml (p-tau), 3251.81 pg/ml (t-tau), 3.370 (t-Tau/Aβ42), and 0.059 (p-Tau/Aβ42). Conclusion: Given its good accuracy and cost-effectiveness, Milliplex xMap^® tests seems a reliable and promising tool, especially for low and middle-income countries.