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ImportanceTau positron emission tomography (PET) tracers have proven useful for the differential diagnosis of dementia, but their utility for predicting cognitive change is unclear.ObjectiveTo examine the prognostic accuracy of baseline fluorine 18 (18F)-flortaucipir and [18F]RO948 (tau) PET in individuals across the Alzheimer disease (AD) clinical spectrum and to perform a head-to-head comparison against established magnetic resonance imaging (MRI) and amyloid PET markers.Design, setting, and participantsThis prognostic study collected data from 8 cohorts in South Korea, Sweden, and the US from June 1, 2014, to February 28, 2021, with a mean (SD) follow-up of 1.9 (0.8) years. A total of 1431 participants were recruited from memory clinics, clinical trials, or cohort studies; 673 were cognitively unimpaired (CU group; 253 [37.6%] positive for amyloid-β [Aβ]), 443 had mild cognitive impairment (MCI group; 271 [61.2%] positive for Aβ), and 315 had a clinical diagnosis of AD dementia (315 [100%] positive for Aβ).Exposures[18F]Flortaucipir PET in the discovery cohort (n = 1135) or [18F]RO948 PET in the replication cohort (n = 296), T1-weighted MRI (n = 1431), and amyloid PET (n = 1329) at baseline and repeated Mini-Mental State Examination (MMSE) evaluation.Main outcomes and measuresBaseline [18F]flortaucipir/[18F]RO948 PET retention within a temporal region of interest, MRI-based AD-signature cortical thickness, and amyloid PET Centiloids were used to predict changes in MMSE using linear mixed-effects models adjusted for age, sex, education, and cohort. Mediation/interaction analyses tested whether associations between baseline tau PET and cognitive change were mediated by baseline MRI measures and whether age, sex, and APOE genotype modified these associations.ResultsAmong 1431 participants, the mean (SD) age was 71.2 (8.8) years; 751 (52.5%) were male. Findings for [18F]flortaucipir PET predicted longitudinal changes in MMSE, and effect sizes were stronger than for AD-signature cortical thickness and amyloid PET across all participants (R2, 0.35 [tau PET] vs 0.24 [MRI] vs 0.17 [amyloid PET]; P < .001, bootstrapped for difference) in the Aβ-positive MCI group (R2, 0.25 [tau PET] vs 0.15 [MRI] vs 0.07 [amyloid PET]; P

ObjectiveThe clinical phenotype of the rare behavioural variant of Alzheimer's disease (bvAD) is insufficiently understood. Given the strong clinico-anatomical correlations of tau pathology in AD, we investigated the distribution of tau deposits in bvAD, in-vivo and ex-vivo, using positron emission tomography (PET) and postmortem examination.MethodsFor the tau PET study, seven amyloid-β positive bvAD patients underwent [18F]flortaucipir or [18F]RO948 PET. We converted tau PET uptake values into standardised (W-)scores, adjusting for age, sex and mini mental state examination in a 'typical' memory-predominant AD (n=205) group. W-scores were computed within entorhinal, temporoparietal, medial and lateral prefrontal, insular and whole-brain regions-of-interest, frontal-to-entorhinal and frontal-to-parietal ratios and within intrinsic functional connectivity network templates. For the postmortem study, the percentage of AT8 (tau)-positive area in hippocampus CA1, temporal, parietal, frontal and insular cortices were compared between autopsy-confirmed patients with bvAD (n=8) and typical AD (tAD;n=7).ResultsIndividual regional W-scores ≥1.96 (corresponding to p0.05).ConclusionsBoth in-vivo and ex-vivo, patients with bvAD showed heterogeneous distributions of tau pathology. Since key regions involved in behavioural regulation were not consistently disproportionally affected by tau pathology, other factors are more likely driving the clinical phenotype in bvAD.

BackgroundThe 2017 Alzheimer's disease (AD) Strategic Biomarker Roadmap (SBR) structured the validation of AD diagnostic biomarkers into 5 phases, systematically assessing analytical validity (Phases 1-2), clinical validity (Phases 3-4), and clinical utility (Phase 5) through primary and secondary Aims. This framework allows to map knowledge gaps and research priorities, accelerating the route towards clinical implementation. Within an initiative aimed to assess the development of biomarkers of tau pathology, we revised this methodology consistently with progress in AD research.MethodsWe critically appraised the adequacy of the 2017 Biomarker Roadmap within current diagnostic frameworks, discussed updates at a workshop convening the Alzheimer's Association and 8 leading AD biomarker research groups, and detailed the methods to allow consistent assessment of aims achievement for tau and other AD diagnostic biomarkers.ResultsThe 2020 update applies to all AD diagnostic biomarkers. In Phases 2-3, we admitted a greater variety of study designs (e.g., cross-sectional in addition to longitudinal) and reference standards (e.g., biomarker confirmation in addition to clinical progression) based on construct (in addition to criterion) validity. We structured a systematic data extraction to enable transparent and formal evidence assessment procedures. Finally, we have clarified issues that need to be addressed to generate data eligible to evidence-to-decision procedures.DiscussionThis revision allows for more versatile and precise assessment of existing evidence, keeps up with theoretical developments, and helps clinical researchers in producing evidence suitable for evidence-to-decision procedures. Compliance with this methodology is essential to implement AD biomarkers efficiently in clinical research and diagnostics.

PurposeThis study aims to determine whether comparable target regions of interest (ROIs) and cut-offs can be used across [18F]flortaucipir, [18F]RO948, and [18F]MK6240 tau positron emission tomography (PET) tracers for differential diagnosis of Alzheimer's disease (AD) dementia vs either cognitively unimpaired (CU) individuals or non-AD neurodegenerative diseases.MethodsA total of 1755 participants underwent tau PET using either [18F]flortaucipir (n = 975), [18F]RO948 (n = 493), or [18F]MK6240 (n = 287). SUVR values were calculated across four theory-driven ROIs and several tracer-specific data-driven (hierarchical clustering) regions of interest (ROIs). Diagnostic performance and cut-offs for ROIs were determined using receiver operating characteristic analyses and the Youden index, respectively.ResultsComparable diagnostic performance (area under the receiver operating characteristic curve [AUC]) was observed between theory- and data-driven ROIs. The theory-defined temporal meta-ROI generally performed very well for all three tracers (AUCs: 0.926-0.996). An SUVR value of approximately 1.35 was a common threshold when using this ROI.ConclusionThe temporal meta-ROI can be used for differential diagnosis of dementia patients with [18F]flortaucipir, [18F]RO948, and [18F]MK6240 tau PET with high accuracy, and that using very similar cut-offs of around 1.35 SUVR. This ROI/SUVR cut-off can also be applied across tracers to define tau positivity.

PurposeA substantial proportion of amyloid-β (Aβ)+ patients with clinically diagnosed Alzheimer's disease (AD) dementia and mild cognitive impairment (MCI) are tau PET-negative, while some clinically diagnosed non-AD neurodegenerative disorder (non-AD) patients or cognitively unimpaired (CU) subjects are tau PET-positive. We investigated which demographic, clinical, genetic, and imaging variables contributed to tau PET status.MethodsWe included 2338 participants (430 Aβ+ AD dementia, 381 Aβ+ MCI, 370 non-AD, and 1157 CU) who underwent [18F]flortaucipir (n = 1944) or [18F]RO948 (n = 719) PET. Tau PET positivity was determined in the entorhinal cortex, temporal meta-ROI, and Braak V-VI regions using previously established cutoffs. We performed bivariate binary logistic regression models with tau PET status (positive/negative) as dependent variable and age, sex, APOEε4, Aβ status (only in CU and non-AD analyses), MMSE, global white matter hyperintensities (WMH), and AD-signature cortical thickness as predictors. Additionally, we performed multivariable binary logistic regression models to account for all other predictors in the same model.ResultsTau PET positivity in the temporal meta-ROI was 88.6% for AD dementia, 46.5% for MCI, 9.5% for non-AD, and 6.1% for CU. Among Aβ+ participants with AD dementia and MCI, lower age, MMSE score, and AD-signature cortical thickness showed the strongest associations with tau PET positivity. In non-AD and CU participants, presence of Aβ was the strongest predictor of a positive tau PET scan.ConclusionWe identified several demographic, clinical, and neurobiological factors that are important to explain the variance in tau PET retention observed across the AD pathological continuum, non-AD neurodegenerative disorders, and cognitively unimpaired persons.

Increased cerebrospinal fluid neurofilament light (NfL) is a recognized biomarker for neurodegeneration that can also be assessed in blood. Here, we investigate plasma NfL as a marker of neurodegeneration in 13 neurodegenerative disorders, Down syndrome, depression and cognitively unimpaired controls from two multicenter cohorts: King's College London (n = 805) and the Swedish BioFINDER study (n = 1,464). Plasma NfL was significantly increased in all cortical neurodegenerative disorders, amyotrophic lateral sclerosis and atypical parkinsonian disorders. We demonstrate that plasma NfL is clinically useful in identifying atypical parkinsonian disorders in patients with parkinsonism, dementia in individuals with Down syndrome, dementia among psychiatric disorders, and frontotemporal dementia in patients with cognitive impairment. Data-driven cut-offs highlighted the fundamental importance of age-related clinical cut-offs for disorders with a younger age of onset. Finally, plasma NfL performs best when applied to indicate no underlying neurodegeneration, with low false positives, in all age-related cut-offs.

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. [ABSTRACT FROM AUTHOR]

Background: Tau positron emission tomography (PET) is increasingly used in the clinical evaluation of patients and as an outcome measure in Alzheimer's disease (AD) clinical trials. Due to differences in tracer properties, instrumentation, and methods of analysis, however, tau‐PET outcome data cannot currently be meaningfully compared or combined. Here, we tested i) the feasibility of adapting the Centiloid method—an approach originally developed to standardize amyloid PET—to harmonize tau‐PET quantification (CenTauRs); ii) the performance of a non‐linear mixed model‐based approach (Joint Propagation Model) that does not require the use of a reference tracer. Methods: Head‐to‐head tau‐PET data (Table 1) was included from two cohorts ([18F]RO948 vs [18F]flortaucipir, n = 37 [BioFINDER‐2]; [18F]flortaucipir [Avid A05] vs [18F]MK‐6240, n = 15, University of Pittsburgh) in which each participant was scanned with two tau‐PET tracers. Standardized uptake value ratio (SUVR) values were calculated using the inferior cerebellar cortex as the reference region. Anchor point data (Table 1) was derived for each tracer using the following criteria: CenTauR‐0, cognitively unimpaired (CU), amyloid PET negative (<10 Centiloids); CenTauR‐100, amyloid PET positive (>50 Centiloids), typical (temporoparietal) AD pattern on tau‐PET visual read, age<65 andMMSE>20. Regions‐of‐interest (ROIs) included a universal tau‐PET ROI—based on the intersection of tracer specific ([18F]flortaucipir, [18F]MK‐6240, [18F]PI‐2620, [18F]PM‐PBB3, [18F]GTP1 and [18F]RO948) masks that had been derived by subtracting average of amyloid‐negative CU images from the average AD image—as well as four subregions delineated within this ROI (medial temporal, meta‐temporal, temporoparietal and frontal) (Figure 1A). An overview of the adapted Centiloid‐like approach and the joint propagation model is shown in Figure 1B. Results: High R2 values were observed between tracers across all ROIs: [18F]RO948 vs [18F]flortaucipir, average 0.965 [range 0.923 (frontal) to 0.986 (universal)]; [18F]MK‐6240 vs [18F]flortaucipir, average 0.985 [range, 0.923 (medial temporal) to 0.991 (frontal)]. The Centiloid‐like and joint propagation model approaches provided near identical CenTauR values (Figure 2). Conclusions: Preliminary findings support the development of standardized scale for tau‐PET using both a Centiloid‐like or joint propagation model approach. Additional data and consideration of the advantages and disadvantages of each will be needed to recommend one approach over the other. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Recently, an increasing number of tau tracers have become available. There is a need to standardize quantitative tau measures across tracers, supporting a universal scale. We developed several cortical tau masks and applied them to generate a tau imaging universal scale. METHOD: One thousand forty‐five participants underwent tau scans with either 18F‐flortaucipir, 18F‐MK6240, 18F‐PI2620, 18F‐PM‐PBB3, 18F‐GTP1, or 18F‐RO948. The universal mask was generated from cognitively unimpaired amyloid beta (Aβ)− subjects and Alzheimer's disease (AD) patients with Aβ+. Four additional regional cortical masks were defined within the constraints of the universal mask. A universal scale, the CenTauRz, was constructed. RESULTS: None of the regions known to display off‐target signal were included in the masks. The CenTauRz allows robust discrimination between low and high levels of tau deposits. DISCUSSION: We constructed several tau‐specific cortical masks for the AD continuum and a universal standard scale designed to capture the location and degree of abnormality that can be applied across tracers and across centers. The masks are freely available at https://www.gaain.org/centaur‐project. [ABSTRACT FROM AUTHOR]