Biostatistical Estimation of Tau Threshold Hallmarks (BETTH) Algorithm for Human Tau PET Imaging Studies

Tau Imaging: Use and Implementation in New Diagnostic and Therapeutic Paradigms for Alzheimer's Disease

Alzheimer's disease (AD) affects an estimated 6.9 million older adults in the United States and is projected to impact as many as 13.8 million people by 2060. As studies continue to search for ways to combat the development and progression of AD, it is imperative to ensure that confident diagnoses can be made before the onset of severe clinical symptoms and new therapies can be evaluated effectively. Tau positron emission tomography (PET) has emerged as one method that may be capable of both, given its ability to recognize the presence of tau, a primary pathologic hallmark of AD; its usefulness in determining the spatial distribution of tau, which is necessary for differentiating AD from other tauopathies; and its association with measures of cognition. This review aims to evaluate the scope of tau PET's utility in clinical trials and practice. Firstly, the potential of using tau PET for differential diagnoses, distinguishing AD from other dementias, is considered. Next, the value of tau PET as a tool for staging disease progression is investigated. Finally, tau PET as a prognostic method for identifying the individuals most at risk of cognitive decline and, therefore, most in need of, and likely to benefit from, intervention, is discussed.

The Taiwan-ADNI workflow toward integrating plasma p-tau217 into prediction models for the risk of Alzheimer's disease and tau burden

INTRODUCTION

We integrated plasma biomarkers from the Taiwan Alzheimer's Disease Neuroimaging Initiative and propose a workflow to identify individuals showing amyloid-positive positron emission tomography (PET) with low/intermediate tau burden based on [18F]Florzolotau PET-based quantification.

METHODS

We assessed 361 participants across the Alzheimer's disease (AD) and non-AD continuum and measured plasma phosphorylated tau (p-tau)217, p-tau181, amyloid beta (Aβ)42/40 ratio, neurofilament light chain, and glial fibrillary acidic protein levels at two medical centers. We evaluated the diagnostic potential of these biomarkers.

RESULTS

Among all plasma biomarkers, p-tau217 had the highest consistency with amyloid PET results (area under the curve = 0.94), and a cutoff value could have reduced the number of confirmatory amyloid PET scans by 57.5%. In amyloid PET-positive cases intending to use anti-amyloid therapy, p-tau217 level, along with clinical parameters, had the highest predictive ability for low/intermediate tau burden.

DISCUSSION

A two-step workflow based on p-tau217 and confirmatory amyloid PET could accurately classify AD patients showing low/intermediate tau burden.

HIGHLIGHTS

The emergence of anti-amyloid therapy increases the need to accurately diagnose Alzheimer's disease (AD). The use of plasma biomarkers, especially phosphorylated tau 217 (p-tau217), can help in the diagnosis of AD. P-tau217 is a better predictor of amyloid positron emission tomography (PET) positivity than other core biomarkers. In amyloid PET-positive individuals, p-tau217 can predict tau burden. We propose a two-step workflow to identify AD cases suitable for treatment.

Kinetic modeling of the monoamine oxidase-B radioligand [18F]SMBT-1 in human brain with positron emission tomography

This paper describes pharmacokinetic analyses of the monoamine-oxidase-B (MAO-B) radiotracer [18F](S)-(2-methylpyrid-5-yl)-6-[(3-fluoro-2-hydroxy)propoxy]quinoline ([18F]SMBT-1) for positron emission tomography (PET) brain imaging. Brain MAO-B expression is widespread, predominantly within astrocytes. Reactive astrogliosis in response to neurodegenerative disease pathology is associated with MAO-B overexpression. Fourteen elderly subjects (8 control, 5 mild cognitive impairment, 1 Alzheimer's disease) with amyloid ([11C]PiB) and tau ([18F]flortaucipir) imaging assessments underwent dynamic [18F]SMBT-1 PET imaging with arterial input function determination. [18F]SMBT-1 showed high brain uptake and a retention pattern consistent with the known MAO-B distribution. A two-tissue compartment (2TC) model where the K1/k2 ratio was fixed to a whole brain value best described [18F]SMBT-1 kinetics. The 2TC total volume of distribution (VT) was well identified and highly correlated (r2∼0.8) with post-mortem MAO-B indices. Cerebellar grey matter (CGM) showed the lowest mean VT of any region and is considered the optimal pseudo-reference region. Simplified analysis methods including reference tissue models, non-compartmental models, and standard uptake value ratios (SUVR) agreed with 2TC outcomes (r2 > 0.9) but with varying bias. We found the CGM-normalized 70-90 min SUVR to be highly correlated (r2 = 0.93) with the 2TC distribution volume ratio (DVR) with acceptable bias (∼10%), representing a practical alternative for [18F]SMBT-1 analyses.

Multi-analyte proteomic analysis identifies blood-based neuroinflammation, cerebrovascular and synaptic biomarkers in preclinical Alzheimer's disease

BACKGROUND

Blood-based biomarkers are gaining grounds for the detection of Alzheimer's disease (AD) and related disorders (ADRDs). However, two key obstacles remain: the lack of methods for multi-analyte assessments and the need for biomarkers for related pathophysiological processes like neuroinflammation, vascular, and synaptic dysfunction. A novel proteomic method for pre-selected analytes, based on proximity extension technology, was recently introduced. Referred to as the NULISAseq CNS disease panel, the assay simultaneously measures ~ 120 analytes related to neurodegenerative diseases, including those linked to both core (i.e., tau and amyloid-beta (Aβ)) and non-core AD processes. This study aimed to evaluate the technical and clinical performance of this novel targeted proteomic panel.

METHODS

The NULISAseq CNS disease panel was applied to 176 plasma samples from 113 individuals in the MYHAT-NI cohort of predominantly cognitively normal participants from an economically underserved region in southwestern Pennsylvania, USA. Classical AD biomarkers, including p-tau181, p-tau217, p-tau231, GFAP, NEFL, Aβ40, and Aβ42, were independently measured using Single Molecule Array (Simoa) and correlations and diagnostic performances compared. Aβ pathology, tau pathology, and neurodegeneration (AT(N) statuses) were evaluated with [11C] PiB PET, [18F]AV-1451 PET, and an MRI-based AD-signature composite cortical thickness index, respectively. Linear mixed models were used to examine cross-sectional and Wilcoxon rank sum tests for longitudinal associations between NULISA and neuroimaging-determined AT(N) biomarkers.

RESULTS

NULISA concurrently measured 116 plasma biomarkers with good technical performance (97.2 ± 13.9% targets gave signals above assay limits of detection), and significant correlation with Simoa assays for the classical biomarkers. Cross-sectionally, p-tau217 was the top hit to identify Aβ pathology, with age, sex, and APOE genotype-adjusted AUC of 0.930 (95%CI: 0.878-0.983). Fourteen markers were significantly decreased in Aβ-PET + participants, including TIMP3, BDNF, MDH1, and several cytokines. Longitudinally, FGF2, IL4, and IL9 exhibited Aβ PET-dependent yearly increases in Aβ-PET + participants. Novel plasma biomarkers with tau PET-dependent longitudinal changes included proteins associated with neuroinflammation, synaptic function, and cerebrovascular integrity, such as CHIT1, CHI3L1, NPTX1, PGF, PDGFRB, and VEGFA; all previously linked to AD but only reliable when measured in cerebrospinal fluid. The autophagosome cargo protein SQSTM1 exhibited significant association with neurodegeneration after adjusting age, sex, and APOE ε4 genotype.

CONCLUSIONS

Together, our results demonstrate the feasibility and potential of immunoassay-based multiplexing to provide a comprehensive view of AD-associated proteomic changes, consistent with the recently revised biological and diagnostic framework. Further validation of the identified inflammation, synaptic, and vascular markers will be important for establishing disease state markers in asymptomatic AD.

Apolipoprotein E and Alzheimer's disease pathology in African American older adults

The apolipoprotein-E4 (APOE*4) and apolipoprotein-E2 (APOE*2) alleles are more common in African American versus non-Hispanic white populations, but relationships of both alleles with Alzheimer's disease (AD) pathology among African American individuals are unclear. We measured APOE allele and β-amyloid (Aβ) and tau using blood samples and positron emission tomography (PET) images, respectively. Individual regression models tested associations of each APOE allele with Aβ or tau PET overall, stratified by racialized group, and with a racialized group interaction. We included 358 older adults (42% African American) with Aβ PET, 134 (29% African American) of whom had tau PET. APOE*4 was associated with higher Aβ in non-Hispanic white (P < 0.0001), but not African American (P = 0.64) participants; racialized group modified the association between APOE*4 and Aβ (P < 0.0001). There were no other racialized group differences. These results suggest that the association of APOE*4 and Aβ differs between African American and non-Hispanic white populations. Other drivers of AD pathology in African American populations should be identified as potential therapeutic targets.

Multi-analyte proteomic analysis identifies blood-based neuroinflammation, cerebrovascular and synaptic biomarkers in preclinical Alzheimer's disease

Background

Blood-based biomarkers are gaining grounds for Alzheimer's disease (AD) detection. However, two key obstacles need to be addressed: the lack of methods for multi-analyte assessments and the need for markers of neuroinflammation, vascular, and synaptic dysfunction. Here, we evaluated a novel multi-analyte biomarker platform, NULISAseq CNS disease panel, a multiplex NUcleic acid-linked Immuno-Sandwich Assay (NULISA) targeting ~120 analytes, including classical AD biomarkers and key proteins defining various disease hallmarks.

Methods

The NULISAseq panel was applied to 176 plasma samples from the MYHAT-NI cohort of cognitively normal participants from an economically underserved region in Western Pennsylvania. Classical AD biomarkers, including p-tau181 p-tau217, p-tau231, GFAP, NEFL, Aβ40, and Aβ42, were also measured using Single Molecule Array (Simoa). Amyloid pathology, tau pathology, and neurodegeneration were evaluated with [11C] PiB PET, [18F]AV-1451 PET, and MRI, respectively. Linear mixed models were used to examine cross-sectional and Wilcoxon rank sum tests for longitudinal associations between NULISA biomarkers and AD pathologies. Spearman correlations were used to compare NULISA and Simoa.

Results

NULISA concurrently measured 116 plasma biomarkers with good technical performance, and good correlation with Simoa measures. Cross-sectionally, p-tau217 was the top hit to identify Aβ pathology, with age, sex, and APOE genotype-adjusted AUC of 0.930 (95%CI: 0.878-0.983). Fourteen markers were significantly decreased in Aβ-PET+ participants, including TIMP3, which regulates brain Aβ production, the neurotrophic factor BDNF, the energy metabolism marker MDH1, and several cytokines. Longitudinally, FGF2, IL4, and IL9 exhibited Aβ PET-dependent yearly increases in Aβ-PET+ participants. Markers with tau PET-dependent longitudinal changes included the microglial activation marker CHIT1, the reactive astrogliosis marker CHI3L1, the synaptic protein NPTX1, and the cerebrovascular markers PGF, PDGFRB, and VEFGA; all previously linked to AD but only reliably measured in cerebrospinal fluid. SQSTM1, the autophagosome cargo protein, exhibited a significant association with neurodegeneration status after adjusting age, sex, and APOE ε4 genotype.

Conclusions

Together, our results demonstrate the feasibility and potential of immunoassay-based multiplexing to provide a comprehensive view of AD-associated proteomic changes. Further validation of the identified inflammation, synaptic, and vascular markers will be important for establishing disease state markers in asymptomatic AD.

Implementation and Assessment of Tau Thresholds in Non-Demented Individuals as Predictors of Cognitive Decline in Tau Imaging Studies

Background

Tau accumulation in Alzheimer's disease is associated with short term clinical progression and faster rates of cognitive decline in individuals with high amyloid-β deposition. Defining an optimal threshold of tau accumulation predictive of cognitive decline remains a challenge.

Objective

We tested the ability of regional tau PET sensitivity and specificity thresholds to predict longitudinal cognitive decline. We also tested the predictive performance of thresholds in the proposed new NIA-AA biological staging for Alzheimer's disease where multiple levels of tau positivity are used to stage participants.

Methods

18F-flortaucipir scans from 301 non-demented participants were processed and sampled. Four cognitive measures were assessed longitudinally. Regional standardized uptake value ratios were split into infra- and suprathreshold groups at baseline using previously derived thresholds. Survival analysis, log rank testing, and Generalized Estimation Equations assessed the relationship between the application of regional sensitivity/specificity thresholds and change in cognitive measures as well as tau threshold performance in predicting cognitive decline within the new NIA-AA biological staging.

Results

The meta temporal region was best for predicting risk of short-term cognitive decline in suprathreshold, as compared to infrathreshold participants. When applying multiple levels of tau positivity, each subsequent level of tau identified cognitive decline at earlier timepoints.

Conclusions

When using 18F-flortaucipir, meta temporal suprathreshold classification was associated with increased risk of cognitive decline, suggesting that abnormal tau deposition in the cortex predicts decline. Likewise, the application of multiple levels of tau clearly predicts the distinctive cognitive trajectories in the new NIA-AA biological staging framework.