Plasma p-tau217: from 'new kid' to most promising candidate for Alzheimer's disease blood test

Performance of plasma p-tau217 for the detection of amyloid-β positivity in a memory clinic cohort using an electrochemiluminescence immunoassay

BACKGROUND

Plasma p-tau217 has emerged as the most promising blood-based marker (BBM) for the detection of Alzheimer Disease (AD) pathology, yet few studies have evaluated plasma p-tau217 performance in memory clinic settings. We examined the performance of plasma p-tau217 for the detection of AD using a high-sensitivity immunoassay in individuals undergoing diagnostic lumbar puncture (LP).

METHODS

Paired plasma and cerebrospinal fluid (CSF) samples were analysed from the TIMC-BRAiN cohort. Amyloid (Aβ) and Tau (T) pathology were classified based on established cut-offs for CSF Aβ42 and CSF p-tau181 respectively. High-sensitivity electrochemiluminescence (ECL) immunoassays were performed on paired plasma/CSF samples for p-tau217, p-tau181, Glial Fibrillary Acidic Protein (GFAP), Neurofilament Light (NfL) and total tau (t-tau). Biomarker performance was evaluated using Receiver-Operating Curve (ROC) and Area-Under-the-Curve (AUC) analysis.

RESULTS

Of 108 participants (age: 69 ± 6.5 years; 54.6% female) with paired samples obtained at time of LP, 64.8% (n = 70/108) had Aβ pathology detected (35 with Mild Cognitive Impairment and 35 with mild dementia). Plasma p-tau217 was over three-fold higher in Aβ + (12.4 pg/mL; 7.3-19.2 pg/mL) vs. Aβ- participants (3.7 pg/mL; 2.8-4.1 pg/mL; Mann-Whitney U = 230, p < 0.001). Plasma p-tau217 exhibited excellent performance for the detection of Aβ pathology (AUC: 0.91; 95% Confidence Interval [95% CI]: 0.86-0.97)-greater than for T pathology (AUC: 0.83; 95% CI: 0.75-0.90; z = 1.75, p = 0.04). Plasma p-tau217 outperformed plasma p-tau181 for the detection of Aβ pathology (z = 3.24, p < 0.001). Of the other BBMs, only plasma GFAP significantly differed by Aβ status which significantly correlated with plasma p-tau217 in Aβ + (but not in Aβ-) individuals. Application of a two-point threshold at 95% and 97.5% sensitivities & specificities may have enabled avoidance of LP in 58-68% of cases.

CONCLUSIONS

Plasma p-tau217 measured using a high-sensitivity ECL immunoassay demonstrated excellent performance for detection of Aβ pathology in a real-world memory clinic cohort. Moving forward, clinical use of plasma p-tau217 to detect AD pathology may substantially reduce need for confirmatory diagnostic testing for AD pathology with diagnostic LP in specialist memory services.

Diagnostic performance of plasma pTau217, pTau181, Aβ1-42 and Aβ1-40 in the LUMIPULSE automated platform for the detection of Alzheimer disease

BACKGROUND

Recently developed blood markers for Alzheimer's disease (AD) detection have high accuracy but usually require ultra-sensitive analytic tools not commonly available in clinical laboratories, and their performance in clinical practice is unknown.

METHODS

We analyzed plasma samples from 290 consecutive participants that underwent lumbar puncture in routine clinical practice in a specialized memory clinic (66 cognitively unimpaired, 130 participants with mild cognitive impairment, and 94 with dementia). Participants were classified as amyloid positive (A +) or negative (A-) according to CSF Aβ1-42/Aβ1-40 ratio. Plasma pTau217, pTau181, Aβ1-42 and Aβ1-40 were measured in the fully-automated LUMIPULSE platform. We used linear regression to compare plasma biomarkers concentrations between A + and A- groups, evaluated Spearman's correlation between plasma and CSF and performed ROC analyses to assess their diagnostic accuracy to detect brain amyloidosis as determined by CSF Aβ1-42/Aβ1-40 ratio. We analyzed the concordance of pTau217 with CSF amyloidosis.

RESULTS

Plasma pTau217 and pTau181 concentration were higher in A + than A- while the plasma Aβ1-42/Aβ1-40 ratio was lower in A + compared to A-. pTau181 and the Aβ1-42/Aβ1-40 ratio showed moderate correlation between plasma and CSF (Rho = 0.66 and 0.69, respectively). The areas under the ROC curve to discriminate A + from A- participants were 0.94 (95% CI 0.92-0.97) for pTau217, and 0.88 (95% CI 0.84-0.92) for both pTau181 and Aβ1-42/Aβ1-40. Chronic kidney disease (CKD) was related to increased plasma biomarker concentrations, but ratios were less affected. Plasma pTau217 had the highest fold change (× 3.2) and showed high predictive capability in discriminating A + from A-, having 4-7% misclassification rate. The global accuracy of plasma pTau217 using a two-threshold approach was robust in symptomatic groups, exceeding 90%.

CONCLUSION

The evaluation of blood biomarkers on an automated platform exhibited high diagnostic accuracy for AD pathophysiology, and pTau217 showed excellent diagnostic accuracy to identify participants with AD in a consecutive sample representing the routine clinical practice in a specialized memory unit.

Evaluating p-tau217 and p-tau231 as Biomarkers for Early Diagnosis and Differentiation of Alzheimer's Disease: A Narrative Review

The escalating prevalence of Alzheimer's disease (AD) highlights the urgent need to develop reliable biomarkers for early diagnosis and intervention. AD is characterized by the pathological accumulation of amyloid-beta plaques and tau neurofibrillary tangles. Phosphorylated tau (p-tau) proteins, particularly p-tau217 and p-tau231, have been identified as promising biomarker candidates to differentiate the disease progression from preclinical stages. This narrative review is devoted to a critical evaluation of the diagnostic accuracy, sensitivity, and specificity of p-tau217 and p-tau231 levels in the detection of AD, measured in plasma, serum, and cerebrospinal fluid, compared to established biomarkers. Additionally, the efficacy of these markers in distinguishing AD from other neurodegenerative disorders is examined. The significant advances offered by p-tau217 and p-tau231 in AD diagnostics are highlighted, demonstrating their unique utility in early detection and differential diagnosis. This comprehensive analysis not only confirms the excellent diagnostic capabilities of these markers, but also deepens the understanding of the molecular dynamics of AD, contributing to the broader scientific discourse on neurodegenerative diseases. This review is aimed to provide key information for researchers and clinicians across disciplines, filling interdisciplinary gaps and highlighting the role of p-tau proteins in revolutionizing AD research and clinical practice.

Plasma Aβ42/Aβ40 and phospho-tau217 concentration ratios increase the accuracy of amyloid PET classification in preclinical Alzheimer's disease

INTRODUCTION

Incorporating blood-based Alzheimer's disease biomarkers such as tau and amyloid beta (Aβ) into screening algorithms may improve screening efficiency.

METHODS

Plasma Aβ, phosphorylated tau (p-tau)181, and p-tau217 concentration levels from AHEAD 3-45 study participants were measured using mass spectrometry. Tau concentration ratios for each proteoform were calculated to normalize for inter-individual differences. Receiver operating characteristic (ROC) curve analysis was performed for each biomarker against amyloid positivity, defined by > 20 Centiloids. Mixture of experts analysis assessed the value of including tau concentration ratios into the existing predictive algorithm for amyloid positron emission tomography status.

RESULTS

The area under the receiver operating curve (AUC) was 0.87 for Aβ42/Aβ40, 0.74 for phosphorylated variant p-tau181 ratio (p-tau181/np-tau181), and 0.92 for phosphorylated variant p-tau217 ratio (p-tau217/np-tau217). The Plasma Predicted Centiloid (PPC), a predictive model including p-tau217/np-tau217, Aβ42/Aβ40, age, and apolipoprotein E improved AUC to 0.95.

DISCUSSION

Including plasma p-tau217/np-tau217 along with Aβ42/Aβ40 in predictive algorithms may streamline screening preclinical individuals into anti-amyloid clinical trials.

CLINICALTRIALS

gov Identifier: NCT04468659 HIGHLIGHTS: The addition of plasma phosphorylated variant p-tau217 ratio (p-tau217/np-tau217) significantly improved plasma biomarker algorithms for identifying preclinical amyloid positron emission tomography positivity. Prediction performance at higher NAV Centiloid levels was improved with p-tau217/np-tau217. All models generated for this study are incorporated into the Plasma Predicted Centiloid (PPC) app for public use.

A novel ultrasensitive assay for plasma p-tau217: Performance in individuals with subjective cognitive decline and early Alzheimer's disease

INTRODUCTION

Detection of Alzheimer's disease (AD) pathophysiology among individuals with mild cognitive changes and those experiencing subjective cognitive decline (SCD) remains challenging. Plasma phosphorylated tau 217 (p-tau217) is one of the most promising of the emerging biomarkers for AD. However, accessible methods are limited.

METHODS

We employed a novel p-tau217 immunoassay (University of Gothenburg [UGOT] p-tau217) in four independent cohorts (n = 308) including a cerebrospinal fluid (CSF) biomarker-classified cohort (Discovery), two cohorts consisting mostly of cognitively unimpaired (CU) and mild cognitively impaired (MCI) participants (MYHAT and Pittsburgh), and a population-based cohort of individuals with SCD (Barcelonaβeta Brain Research Center's Alzheimer's At-Risk Cohort [β-AARC]).

RESULTS

UGOT p-tau217 showed high accuracy (area under the curve [AUC] = 0.80-0.91) identifying amyloid beta (Aβ) pathology, determined either by Aβ positron emission tomography or CSF Aβ42/40 ratio. In individuals experiencing SCD, UGOT p-tau217 showed high accuracy identifying those with a positive CSF Aβ42/40 ratio (AUC = 0.91).

DISCUSSION

UGOT p-tau217 can be an easily accessible and efficient way to screen and monitor patients with suspected AD pathophysiology, even in the early stages of the continuum.

Amyloid and Tau Prediction of Cognitive and Functional Decline in Unimpaired Older Individuals: Longitudinal Data from the A4 and LEARN Studies

BACKGROUND

Converging evidence suggests that markers of Alzheimer's disease (AD) pathology in cognitively unimpaired older individuals are associated with high risk of cognitive decline and progression to functional impairment. The Anti-Amyloid Treatment in Asymptomatic Alzheimer's disease (A4) and Longitudinal Evaluation of Amyloid and Neurodegeneration Risk (LEARN) Studies enrolled a large cohort of cognitively normal older individuals across a range of baseline amyloid PET levels. Recent advances in AD blood-based biomarkers further enable the comparison of baseline markers in the prediction of longitudinal clinical outcomes.

OBJECTIVES

We sought to evaluate whether biomarker indicators of higher levels of AD pathology at baseline predicted greater cognitive and functional decline, and to compare the relative predictive power of amyloid PET imaging, tau PET imaging, and a plasma P-tau217 assay.

DESIGN

All participants underwent baseline amyloid PET scan, plasma P-tau217; longitudinal cognitive testing with the Primary Alzheimer Cognitive Composite (PACC) every 6 months; and annual functional assessments with the clinical dementia rating (CDR), cognitive functional index (CFI), and activities of daily living (ADL) scales. Baseline tau PET scans were obtained in a subset of participants. Participants with elevated amyloid (Aβ+) on screening PET who met inclusion/exclusion criteria were randomized to receive placebo or solanezumab in a double-blind phase of the A4 Study over 240+ weeks. Participants who did not have elevated amyloid (Aβ-) but were otherwise eligible for the A4 Study were referred to the companion observational LEARN Study with the same outcome assessments over 240+ weeks.

SETTING

The A4 and LEARN Studies were conducted at 67 clinical trial sites in the United States, Canada, Japan and Australia.

PARTICIPANTS

Older participants (ages 65-85) who were cognitively unimpaired at baseline (CDR-GS=0, MMSE 25-30 with educational adjustment, and Logical Memory scores within the normal range LMIIa 6-18) were eligible to continue in screening. Aβ+ participants were randomized to either placebo (n=583) or solanezumab (n=564) in the A4 Study. A subset of Aβ+ underwent tau PET imaging in A4 (n=350). Aβ- were enrolled into the LEARN Study (n=553).

MEASUREMENTS

Baseline 18-F Florbetapir amyloid PET, 18-F Flortaucipir tau PET in a subset and plasma P-tau217 with an electrochemiluminescence (ECL) immunoassay were evaluated as predictors of cognitive (PACC), and functional (CDR, CFI and ADL) change. Models were evaluated to explore the impact of baseline tertiles of amyloid PET and tertiles of plasma P-tau217 on cognitive and functional outcomes in the A4 Study compared to LEARN. Multivariable models were used to evaluate the unique and common variance explained in longitudinal outcomes based on baseline predictors, including effects for age, gender, education, race/ethnic group, APOEε4 carrier status, baseline PACC performance and treatment assignment in A4 participants (solanezumab vs placebo).

RESULTS

Higher baseline amyloid PET CL and P-tau217 levels were associated with faster rates of PACC decline, and increased likelihood of progression to functional impairment (CDR 0.5 or higher on two consecutive measurements), both across LEARN Aβ- and A4 Aβ+ (solanezumab and placebo arms). In analyses considering all baseline predictor variables, P-tau217 was the strongest predictor of PACC decline. Among participants in the highest tertiles of amyloid PET or P-tau217, >50% progressed to CDR 0.5 or greater. In the tau PET substudy, neocortical tau was the strongest predictor of PACC decline, but plasma P-tau217 contributed additional independent predictive variance in commonality variance models.

CONCLUSIONS

In a large cohort of cognitively unimpaired individuals enrolled in a Phase 3 clinical trial and companion observational study, these findings confirm that higher baseline levels of amyloid and tau markers are associated with increased rates of cognitive decline and progression to functional impairment. Interestingly, plasma P-tau217 was the best predictor of decline in the overall sample, superior to baseline amyloid PET. Neocortical tau was the strongest predictor of cognitive decline in the subgroup with tau PET, suggesting that tau deposition is most closely linked to clinical decline. These findings indicate that biomarkers of AD pathology are useful to predict decline in an older asymptomatic population and may prove valuable in the selection of individuals for disease-modifying treatments.

Longitudinal Phospho-tau217 Predicts Amyloid Positron Emission Tomography in Asymptomatic Alzheimer's Disease

BACKGROUND

Blood-based AD biomarkers such as plasma P-tau217 are increasingly used in clinical trials as a screening tool.

OBJECTIVES

To assess the utility of an electrochemiluminescence (ECL) immunoassay in predicting brain amyloid PET status in cognitively unimpaired individuals.

SETTING

Plasma samples collected at baseline, week 12, and week 240 or endpoint originated from the Anti-Amyloid Treatment in Asymptomatic Alzheimer's Disease (A4) trial and the companion Longitudinal Evaluation of Amyloid Risk and Neurodegeneration (LEARN) study.

PARTICIPANTS

Both A4 and LEARN enrolled eligible cognitively unimpaired persons 65 to 85 years. Individuals with elevated brain amyloid PET levels were eligible for the A4 Study, while those without elevated brain amyloid PET levels were eligible for the LEARN Study.

INTERVENTION

Participants in the A4 Study received intravenous solanezumab (up to 1600 mg) or placebo every 4 weeks. The LEARN Study is an observational study without intervention.

MEASUREMENTS

Plasma P-tau217 concentration levels from A4 Study participants were measured using an ECL immunoassay. Receiver Operating Characteristic (ROC) curve analysis was performed for each biomarker against amyloid positivity, defined by ≥22 CL and ≥ 33 CL.

RESULTS

Receiver operating characteristic curve (ROC) analysis indicates high diagnostic value of P-tau217 in individuals with amyloid PET ≥ 20 (Area under the ROC (AUROC): 0.87) and ≥ 33 CL (AUROC: 0.89). Repeated testing with the placebo group taken 12 weeks apart (range: 68 to 143 days) and the LEARN participants taken between 1.4 and 1.75 years resulted in a strong positive correlation (Corr. 0.91 (0.90 to 0.92)).

CONCLUSION

An ECL immunoassay testing plasma P-tau217 accurately predicts amyloid PET positivity in cognitively unimpaired individuals. Our future analyses aim to determine if use of this assay may reduce the screening burden of preclinical individuals into anti-amyloid clinical trials.

A novel ultrasensitive assay for plasma p-tau217: performance in individuals with subjective cognitive decline and early Alzheimer's disease

INTRODUCTION

Detection of Alzheimer's disease (AD) pathophysiology among cognitively unimpaired individuals and those experiencing subjective cognitive decline (SCD) remains challenging. Plasma p-tau217 is one of the most promising of the emerging biomarkers for AD. However, accessible methods are limited.

METHODS

We employed a novel p-tau217 immunoassay (UGOT p-tau217) in four independent cohorts (n=308) including a cerebrospinal fluid (CSF) biomarker-classified cohort (Discovery), two cohorts consisting mostly of cognitively unimpaired participants (MYHAT and Pittsburgh), and a population-based cohort of individuals with SCD (β-AARC).

RESULTS

UGOT p-tau217 showed high accuracy (AUC= 0.80-0.91) identifying Aβ pathology, determined either by Aβ positron emission tomography or CSF Aβ42/40 ratio. In individuals experiencing SCD, UGOT p-tau217 showed high accuracy identifying those with a positive CSF Aβ42/40 ratio (AUC= 0.91).

DISCUSSION

UGOT p-tau217 can be an easily accessible and efficient way to screen and monitor patients with suspected AD pathophysiology, even in the early stages of the continuum.

Modern Methods of Diagnostics and Treatment of Neurodegenerative Diseases and Depression

This paper discusses the promising areas of research into machine learning applications for the prevention and correction of neurodegenerative and depressive disorders. These two groups of disorders are among the leading causes of decline in the quality of life in the world when estimated using disability-adjusted years. Despite decades of research, the development of new approaches for the assessment (especially pre-clinical) and correction of neurodegenerative diseases and depressive disorders remains among the priority areas of research in neurophysiology, psychology, genetics, and interdisciplinary medicine. Contemporary machine learning technologies and medical data infrastructure create new research opportunities. However, reaching a consensus on the application of new machine learning methods and their integration with the existing standards of care and assessment is still a challenge to overcome before the innovations could be widely introduced to clinics. The research on the development of clinical predictions and classification algorithms contributes towards creating a unified approach to the use of growing clinical data. This unified approach should integrate the requirements of medical professionals, researchers, and governmental regulators. In the current paper, the current state of research into neurodegenerative and depressive disorders is presented.

Using the Alzheimer's Disease Neuroimaging Initiative to improve early detection, diagnosis, and treatment of Alzheimer's disease

INTRODUCTION

The Alzheimer's Disease Neuroimaging Initiative (ADNI) has accumulated 15 years of clinical, neuroimaging, cognitive, biofluid biomarker and genetic data, and biofluid samples available to researchers, resulting in more than 3500 publications. This review covers studies from 2018 to 2020.

METHODS

We identified 1442 publications using ADNI data by conventional search methods and selected impactful studies for inclusion.

RESULTS

Disease progression studies supported pivotal roles for regional amyloid beta (Aβ) and tau deposition, and identified underlying genetic contributions to Alzheimer's disease (AD). Vascular disease, immune response, inflammation, resilience, and sex modulated disease course. Biologically coherent subgroups were identified at all clinical stages. Practical algorithms and methodological changes improved determination of Aβ status. Plasma Aβ, phosphorylated tau181, and neurofilament light were promising noninvasive biomarkers. Prognostic and diagnostic models were externally validated in ADNI but studies are limited by lack of ethnocultural cohort diversity.

DISCUSSION

ADNI has had a profound impact in improving clinical trials for AD.

Mass spectrometry-based methods for robust measurement of Alzheimer's disease biomarkers in biological fluids

Alzheimer's disease (AD) is the most common form of dementia affecting 60%-70% of people afflicted with this disease. Accurate antemortem diagnosis is urgently needed for early detection of AD to enable reliable estimation of prognosis, intervention, and monitoring of the disease. The National Institute on Aging/Alzheimer's Association sponsored the 'Research Framework: towards a biological definition of AD', which recommends using different biomarkers in living persons for a biomarker-based definition of AD regardless of clinical status. Fluid biomarkers represent one of key groups of them. Since cerebrospinal fluid (CSF) is in direct contact with brain and many proteins present in the brain can be detected in CSF, this fluid has been regarded as the best biofluid in which to measure AD biomarkers. Recently, technological advancements in protein detection made possible the effective study of plasma AD biomarkers despite their significantly lower concentrations versus to that in CSF. This and other challenges that face plasma-based biomarker measurements can be overcome by using mass spectrometry. In this review, we discuss AD biomarkers which can be reliably measured in CSF and plasma using targeted mass spectrometry coupled to liquid chromatography (LC/MS/MS). We describe progress in LC/MS/MS methods' development, emphasize the challenges, and summarize major findings. We also highlight the role of mass spectrometry and progress made in the process of global standardization of the measurement of Aβ42/Aβ40. Finally, we briefly describe exploratory proteomics which seek to identify new biomarkers that can contribute to detection of co-pathological processes that are common in sporadic AD.

The blood biomarkers puzzle - A review of protein biomarkers in neurodegenerative diseases

Neurodegenerative diseases are heterogeneous in their cause and clinical presentation making clinical assessment and disease monitoring challenging. Because of this, there is an urgent need for objective tools such as fluid biomarkers able to quantitate different aspects of the disease. In the last decade, technological improvements and awareness of the importance of biorepositories led to the discovery of an evolving number of fluid biomarkers covering the main characteristics of neurodegenerative diseases such as neurodegeneration, protein aggregates and inflammation. The ability to quantitate each aspect of the disease at a high definition enables a more precise stratification of the patients at inclusion in clinical trials, hence reducing the noise that may hamper the detection of therapeutical efficacy and allowing for smaller but likewise powered studies, which particularly improves the ability to start clinical trials for rare neurological diseases. Moreover, the use of fluid biomarkers has the potential to support a targeted therapeutical intervention, as it is now emerging for the treatment of amyloid-beta deposition in patients suffering from Alzheimer's disease. Here we review the knowledge that evolved from the measurement of fluid biomarker proteins in neurodegenerative conditions.