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Compelling experimental evidence suggests that microglial activation is involved in the spread of tau tangles over the neocortex in Alzheimer's disease (AD). We tested the hypothesis that the spatial propagation of microglial activation and tau accumulation colocalize in a Braak-like pattern in the living human brain. We studied 130 individuals across the aging and AD clinical spectrum with positron emission tomography brain imaging for microglial activation ([.sup.11C]PBR28), amyloid-[beta] (A[beta]) ([.sup.18F]AZD4694) and tau ([.sup.18F]MK-6240) pathologies. We further assessed microglial triggering receptor expressed on myeloid cells 2 (TREM2) cerebrospinal fluid (CSF) concentrations and brain gene expression patterns. We found that [.sup.11C]PBR28 correlated with CSF soluble TREM2 and showed regional distribution resembling TREM2 gene expression. Network analysis revealed that microglial activation and tau correlated hierarchically with each other following Braak-like stages. Regression analysis revealed that the longitudinal tau propagation pathways depended on the baseline microglia network rather than the tau network circuits. The co-occurrence of A[beta], tau and microglia abnormalities was the strongest predictor of cognitive impairment in our study population. Our findings support a model where an interaction between A[beta] and activated microglia sets the pace for tau spread across Braak stages. Microglial activation and tau accumulation propagate together in patients with Alzheimer's disease, suggesting an interaction that determines disease progression., Author(s): Tharick A. Pascoal [sup.1] [sup.2] [sup.3] [sup.4] , Andrea L. Benedet [sup.3] , Nicholas J. Ashton [sup.5] [sup.6] [sup.7] , Min Su Kang [sup.3] [sup.4] , Joseph Therriault [sup.3] [...]

This document is a letter published in the journal Translational Neurodegeneration that investigates the relationship between synaptic biomarkers and Alzheimer's disease (AD) pathologies. The study includes 144 participants and uses imaging assessments and statistical analyses to examine these relationships. The results suggest that cerebrospinal fluid (CSF) synaptic biomarkers can indicate synaptic degeneration in regions affected by AD pathologies and are linked to glial activity and future cognitive deficits. The study highlights the potential use of these biomarkers for diagnosing synaptic dysfunction and degeneration in AD. The researchers also found that the CSF biomarker SNAP25 may be a superior biomarker for assessing synaptic dysfunction. The authors express gratitude to the participants and various institutions involved in the study, and funding was provided by several organizations. The data from the study are available upon request to protect participant privacy. [Extracted from the article]

INTRODUCTION: We set out to identify tau PET‐positive (A+T+) individuals among amyloid‐beta (Aβ) positive participants using plasma biomarkers. METHODS: In this cross‐sectional study we assessed 234 participants across the AD continuum who were evaluated by amyloid PET with [18F]AZD4694 and tau‐PET with [18F]MK6240 and measured plasma levels of total tau, pTau‐181, pTau‐217, pTau‐231, and N‐terminal tau (NTA‐tau). We evaluated the performances of plasma biomarkers to predict tau positivity in Aβ+ individuals. RESULTS: Highest associations with tau positivity in Aβ+ individuals were found for plasma pTau‐217 (AUC [CI95%] = 0.89 [0.82, 0.96]) and NTA‐tau (AUC [CI95%] = 0.88 [0.91, 0.95]). Combining pTau‐217 and NTA‐tau resulted in the strongest agreement (Cohen's Kappa = 0.74, CI95% = 0.57/0.90, sensitivity = 92%, specificity = 81%) with PET for classifying tau positivity. DISCUSSION: The potential for identifying tau accumulation in later Braak stages will be useful for patient stratification and prognostication in treatment trials and in clinical practice. Highlights: We found that in a cohort without pre‐selection pTau‐181, pTau‐217, and NTA‐tau showed the highest association with tau PET positivity.We found that in Aβ+ individuals pTau‐217 and NTA‐tau showed the highest association with tau PET positivity.Combining pTau‐217 and NTA‐tau resulted in the strongest agreement with the tau PET‐based classification. [ABSTRACT FROM AUTHOR]

Background: Previous studies have shown that microglial activation (MA) plays a key role in the physiopathology and progression of Alzheimer's disease (AD). Unpublished data suggest that MA is highly associated with the development of neuropsychiatric symptoms (NPS) in patients with AD. Thus, we aim to investigate here the contribution of each NPS domain to this association across individuals in the AD continuum. Method: We assessed 132 individuals (86 cognitively unimpaired (CU), 28 MCI, and 18 AD dementia) from the TRIAD cohort who underwent clinical assessments with the Neuropsychiatry Inventory Questionnaire (NPI‐Q), and had positron emission tomography (PET) for amyloid‐β (Aβ) ([18F]AZD4694), tau tangles ([18F]MK6240) and MA ([11C]PBR28) at the same visit. Regions were tailored using Desikan‐Killiany (DK) atlas. SUVRs were calculated using the cerebellum gray matter as a reference. Linear regression tested the association between biomarkers accounting for age, sex, and cognitive status. Result: NPI‐Q total score was significantly associated with [11C]PBR28 in the cingulate, inferior temporal, and precuneus accounting for age, sex, and after false discovery rate (FDR) correction for multiple comparisons (Figure 1A). This association was independent of Aβ and tau levels (Table 1). When we stratify NPI‐Q domains (agitation, irritability, motor disturbance, disinhibition, elation, delusion, hallucinations, nighttime disturbance, depression, anxiety, apathy, and appetite disturbance) severity score, we found that the hyperactivity subdomain (agitation, irritability, motor disturbance, disinhibition, and elation) showed the larger contribution to the results (Figure 1B). Bootstrapping each NPI‐Q domain from the NPI‐Q total score, linear regression analysis reveals that irritability, nighttime disturbance, and agitation are the main contributors to the association between NPS and MA (Figure 1C). Removing these domains, but no other combination of two or three NPI‐Q domains, from the NPI‐Q total score, abolishes this association (Figure 1D). Conclusion: Our results suggest that MA is associated with neuropsychiatric dysfunction in AD. Notably, we found that irritability, nighttime disturbance, and agitation drive the association between NPS and MA. [ABSTRACT FROM AUTHOR]

Background: The use of enrichment strategies is crucial for selecting individuals with the highest probability of Alzheimer's disease (AD)‐related progression in typical clinical trial time frames. Although both amyloid‐β (Aβ) pathology and the apolipoprotein E ε4 (APOEε4) genotype have been shown to accelerate tau accumulation, it is still not clear whether assessing both APOEε4 genotype and Aβ positivity is useful to enrich tau‐targeting trials using tau positron emission tomography (PET) as outcome. Here, we investigated the implications of considering APOEε4 carriership for population enrichment in trials testing drug effects on tau tangle deposition in cognitively impaired (CI) individuals across the AD continuum. Method: We studied 29 Aβ positive CI individuals (16 with mild cognitive impairment [MCI] and 13 with AD dementia) from the McGill Translational Biomarkers in Aging and Dementia (TRIAD) cohort. Study participants underwent clinical assessments, APOE genotyping, magnetic resonance imaging, PET for Aβ ([18F]AZD4694) and tau ([18F]MK6240) at baseline, as well as a follow‐up tau‐PET scan (mean follow‐up, 2.2 years). Aβ positivity was determined as global [18F]AZD4694 SUVR ≥ 1.55. Result: No demographic differences were observed between APOEε4 carriers and noncarriers (Table 1). Regression analysis revealed that APOEε4 carriers had higher tau‐PET SUVR increase in temporal regions compared to APOEε4 noncarriers (Figure 1). The use of Aβ positivity alone for population enrichment of a clinical trial focusing on CI individuals would require a sample size of 436 individuals per study arm to test a 25% drug effect on tau‐PET accumulation (Figure 2). A similar clinical trial with a population enrichment strategy using Aβ positivity plus APOEε4 carriership would require a sample size of as few as 158 individuals per study arm (reduction of 64% in relation to using only Aβ positivity) to test the same drug effect (Figure 2). Conclusion: Our results reveal that APOEε4 carriership is associated with increased tau tangle accumulation in CI individuals who are Aβ positive. Clinical trials testing drug effects on tangle deposition may benefit from assessing both APOEε4 carriership and Aβ positivity statuses as enrollment criteria to select individuals at higher risk of fast tau accumulation, resulting in a more cost‐effective trial. [ABSTRACT FROM AUTHOR]

Background: The mechanisms by which the apolipoprotein E ε4 (APOEε4) allele influences Alzheimer's disease (AD) pathophysiological progression are poorly understood. Here, we tested the association of APOEε4 carriership and amyloid‐β (Aβ) burden with longitudinal tau pathology progression. Method: We studied 104 individuals across the aging and AD clinical spectrum from the McGill TRIAD cohort. Study participants underwent clinical assessments, APOE genotyping, magnetic resonance imaging, positron emission tomography (PET) for Aβ ([18F]AZD4694) and tau ([18F]MK6240) at baseline, as well as an additional follow‐up tau‐PET scan (mean follow‐up, 2.4 years). We further assessed longitudinal changes in tau phosphorylation (plasma phosphorylated tau at threonine 217 [p‐tau217+]), brain atrophy (gray matter density), and clinical function (clinical dementia rating scale sum of boxes). Result: We found that APOEε4 carriership potentiates Aβ effects on longitudinal tau tangle accumulation over two years (Figure 1). Interestingly, the APOEε4‐potentiated Aβ effects on tangles were mediated by longitudinal plasma p‐tau217+ increase (Figure 2). In addition, this longitudinal tau accumulation as measured by PET was accompanied by brain atrophy and clinical decline during the follow‐up period (Figure 3). Conclusion: Our results support a model in which the APOEε4 allele plays a key role in Aβ downstream effects on the aggregation of phosphorylated tau in the form of neurofibrillary tangles in the living human brain, which is a key factor in the development of dementia. These observations have important implications for the design of future trials by suggesting that the combination of therapies targeting both ApoeE4 and Aβ pathology might have the potential to synergistically halt tau progression in AD. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Fluid biomarkers capable of specifically tracking tau tangle pathology in vivo are greatly needed. METHODS: We measured cerebrospinal fluid (CSF) and plasma concentrations of N‐terminal tau fragments (NTA‐tau), using a novel immunoassay (NTA) in the TRIAD cohort, consisting of 272 individuals assessed with amyloid beta (Aβ) positron emission tomography (PET), tau PET, magnetic resonance imaging (MRI) and cognitive assessments. RESULTS: CSF and plasma NTA‐tau concentrations were specifically increased in cognitively impaired Aβ‐positive groups. CSF and plasma NTA‐tau concentrations displayed stronger correlations with tau PET than with Aβ PET and MRI, both in global uptake and at the voxel level. Regression models demonstrated that both CSF and plasma NTA‐tau are preferentially associated with tau pathology. Moreover, plasma NTA‐tau was associated with longitudinal tau PET accumulation across the aging and Alzheimer's disease (AD) spectrum. DISCUSSION: NTA‐tau is a biomarker closely associated with in vivo tau deposition in the AD continuum and has potential as a tau tangle biomarker in clinical settings and trials. Highlights: An assay for detecting N‐terminal tau fragments (NTA‐tau) in plasma and CSF was evaluated.NTA‐tau is more closely associated with tau PET than amyloid PET or neurodegeneration.NTA‐tau can successfully track in vivo tau deposition across the AD continuum.Plasma NTA‐tau increased over time only in cognitively impaired amyloid‐β positive individuals. [ABSTRACT FROM AUTHOR]

Author(s): Tharick A. Pascoal [sup.1] [sup.2] [sup.3] [sup.4], Andrea L. Benedet [sup.3], Nicholas J. Ashton [sup.5] [sup.6] [sup.7], Min Su Kang [sup.3] [sup.4], Joseph Therriault [sup.3], Mira Chamoun [sup.3], Melissa [...]

INTRODUCTION: Amyloid‐β (Aβ) and tau can be quantified in blood. However, biological factors can influence the levels of brain‐derived proteins in the blood. The blood‐brain barrier (BBB) regulates protein transport between cerebrospinal fluid (CSF) and blood. BBB altered permeability might affect the relationship between brain and blood biomarkers. METHODS: We assessed 224 participants in research (TRIAD, n = 96) and clinical (BIODEGMAR, n = 128) cohorts with plasma and CSF/positron emission tomography Aβ, p‐tau, and albumin measures. RESULTS: Plasma Aβ42/40 better identified CSF Aβ42/40 and Aβ‐PET positivity in individuals with high BBB permeability. An interaction between plasma Aβ42/40 and BBB permeability on CSF Aβ42/40 was observed. Voxel‐wise models estimated that the association of positron emission tomography (PET), with plasma Aβ was most affected by BBB permeability in AD‐related brain regions. BBB permeability did not significantly impact the relationship between brain and plasma p‐tau levels. DISCUSSION: These findings suggest that BBB integrity may influence the performance of plasma Aβ, but not p‐tau, biomarkers in research and clinical settings. HIGHLIGHTS: BBB permeability affects the association between brain and plasma Aβ levels.BBB integrity does not affect the association between brain and plasma p‐tau levels.Plasma Aβ was most affected by BBB permeability in AD‐related brain regions.BBB permeability increases with age but not according to cognitive status. [ABSTRACT FROM AUTHOR]

Introduction: [18F]AZD4694 is an amyloid beta (Aβ) imaging agent used in several observational studies and clinical trials. However, no studies have yet published data on longitudinal Aβ accumulation measured with [18F]AZD4694. Methods: We assessed 146 individuals who were evaluated with [18F]AZD4694 at baseline and 2‐year follow‐up. We calculated annual rates of [18F]AZD4694 change for clinically defined and biomarker‐defined groups Results: Cognitively unimpaired (CU) older adults displayed subtle [18F]AZD4694 standardized uptake value ratio (SUVR) accumulation over the follow‐up period. In contrast, Aβ positive CU older adults displayed higher annual [18F]AZD4694 SUVR increases. [18F]AZD4694 SUVR accumulation in Aβ positive mild cognitive impairment (MCI) and dementia was modest across the neocortex Discussion: Larger increases in [18F]AZD4694 SUVR were observed in CU individuals who had abnormal amyloid positron emission tomography levels at baseline. [18F]AZD4694 can be used to monitor Aβ levels in therapeutic trials as well as clinical settings, particularly prior to initiating anti‐amyloid therapies. [ABSTRACT FROM AUTHOR]

Background: The integrity and function of catecholamine neurotransmitter systems can be assessed using neuromelanin‐sensitive MRI (NM‐MRI). The relevance of this method to neurodegenerative and psychiatric disorders is becoming increasingly evident, and it has potential as a clinical biomarker. Purpose: To support future application of NM‐MRI as a clinical biomarker by defining the normative range of NM‐MRI signal and volume metrics in cognitively normal older adults. Study Type: Prospective. Population: A total of 152 cognitively normal older adults aged 53–86 years old, including 41 participants who had follow‐up NM‐MRI data collected 9–16 months later. Field Strength/Sequence: A 3.0 T; NM‐MRI turbo spin echo and T1‐weighted magnetization‐prepared rapid acquisition with gradient echo sequences. Assessment: NM‐MRI images were processed to yield summary measures of volume and signal (contrast‐to‐noise ratio, CNR) for the substantia nigra (SN) and locus coeruleus (LC) using a recently developed software employing a fully automated algorithm. Change in these metrics over time was also assessed. Statistical Tests: Mean and standard deviation of NM‐MRI metrics were calculated; change over time was tested for significance using 1‐sample t‐tests. P values < 0.05 were considered statistically significant. Results: At baseline SN signal (CNR) was 10.02% (left) and 10.28% (right) and LC signal was 24.71% (left) and 20.42% (right). Baseline SN volume was 576 mm3 (left) and 540 mm3 (right) and LC volume was 6.31 mm3 (left) and 6.30 mm3 (right). The only NM‐MRI metric showing significant change was a decrease in left SN volume (t40 = −2.57, P = 0.014). Data Conclusion: We report normative values for NM‐MRI signal and volume in the SN and LC of cognitively normal older adults and explore their change over time. These values may help future efforts to use NM‐MRI as a clinical biomarker by facilitating identification of patients with extreme NM‐MRI values. Level of Evidence: 2. Technical Efficacy Stage: 1. [ABSTRACT FROM AUTHOR]

Following the development of magnetic resonance imaging (MRI) methods to assay the integrity of catecholamine nuclei, including the locus coeruleus (LC), there has been an effort to develop automated methods that can accurately segment this small structure in an automated manner to promote its widespread use and overcome limitations of manual segmentation. Here we characterize an automated LC segmentation approach (referred to as the funnel-tip [FT] method) in healthy individuals and individuals with LC degeneration in the context of Alzheimer's disease (AD, confirmed with tau-PET imaging using [18F]MK6240). The first sample included n = 190 individuals across the AD spectrum from cognitively normal to moderate AD. LC signal assayed with FT segmentation showed excellent agreement with manual segmentation (intraclass correlation coefficient [ICC] = 0.91). Compared to other methods, the FT method showed numerically higher correlation to AD status (defined by presence of tau: Cohen's d = 0.64) and AD severity (Braak stage: Pearson R = -.35, cognitive function: R = .25). In a separate sample of n = 12 control participants, the FT method showed excellent scan--rescan reliability (ICC = 0.82). In another sample of n = 30 control participants, we found that the structure of the LC defined by FT segmentation approximated its expected shape as a contiguous line: <5% of LC voxels strayed >1 voxel (0.69 mm) from this line. The FT LC segmentation shows high agreement with manual segmentation and captures LC degeneration in AD. This practical method may facilitate larger research studies of the human LC-norepinephrine system and has potential to support future use of neuromelanin-sensitive MRI as a clinical biomarker. [ABSTRACT FROM AUTHOR]

Background: Glial contributions to Alzheimer's disease (AD) etiology and progression have been increasingly recognized. Experimental and clinical evidence suggests that both microglial activation and astrocyte reactivity have pivotal roles in the progression of tau pathology. However, it remains to be elucidated how microglia and astrocytes complement each other in AD pathogenesis. Here, we tested the associations between reactive astrogliosis and microglial activation with tau phosphorylation and aggregation in individuals across the aging and AD spectrum. Method: We studied 95 participants (14 cognitively unimpaired [CU] young, 46 CU elderly, and 35 cognitively impaired [CI]) from the Translational Biomarkers in Aging and Dementia (TRIAD) cohort. Individuals had available positron emission tomography (PET) for Aβ ([18F]AZD4694), tau tangles ([18F]MK6240), and microglial activation ([11C]PBR28). We further assessed reactive astrogliosis (plasma glial fibrillary acidic protein [GFAP]) and pathological tau phosphorylation (plasma phosphorylated tau [p‐tau] at threonine 231, 181, and 217). Result: Demographic characteristics of the study population are reported in Table 1. Regression analyses revealed that reactive astrogliosis and microglial activation were synergistically associated with higher plasma phosphorylated tau levels independently of Aβ pathology in CU but not CI individuals (Figure 1A). On the other hand, no interactive effects of reactive astrogliosis and microglial activation on tau‐PET burden were observed in either CU or CI individuals (Figure 1B). Similar findings were observed in sensitivity analyses excluding CU young participants. Conclusion: Our results suggest that reactive astrocytes and activated microglia have Aβ‐independent synergistic effects on the early progression of AD pathophysiology by contributing to tau phosphorylation but not tau aggregation. These findings can help to better understand the complementary roles of glial cells in neurodegenerative diseases, as well as provide insights for the development novel therapeutic strategies for AD targeting the interplay between astrocyte and microglial reactivity. [ABSTRACT FROM AUTHOR]

Background: Midlife hypertension (HTN) is a known risk factor for Alzheimer's Disease (AD) development. However, whether the same effect is observed in older individuals, at risk for AD, remains to be elucidated. Here, we aimed to assess whether late‐life HTN and the presence of amyloid‐β pathology (Aβ) interact to promote longitudinal cognitive decline in cognitively unimpaired (CU) individuals, and if systolic blood pressure (SBP) levels moderate this interaction. Interactive effect of disease pathophysiology is crucial for dementia prevention strategies. Method: We used two independent cohorts. We evaluated 475 CU individuals over 65 years of age from the ADNI cohort, with available baseline medical data and CSF Elecsys biomarkers (Aβ1‐42 and p‐tau181), as well as longitudinal clinical assessments with neuropsychological testing (up to 6 years); the individuals were classified as (A)+ or (A)‐ based on a previously proposed cut‐off of CSF p‐tau181/Aβ1‐42 lower than 0.025. We also evaluated 162 CU individuals over 65 years of age from the TRIAD cohort with baseline clinical data and Aβ‐PET, as well as longitudinal clinical assessments with neuropsychological testing (up to 3 years). The individuals were classified as (A)+ or (A)‐ based on Aβ‐PET positivity. All individuals were classified as positive or negative for hypertension based on medical history. For the ADNI cohort, we could also evaluate the SBP levels as a continuous variable. Result: Linear mixed‐effects (LME) models showed that HTN and Aβ acted together to promote longitudinal cognitive decline (ADNI: HTN X Aβ X Time, β = ‐0.44, p = 0.001, figure 1, TRIAD: HTN X Aβ X Time, β = ‐0.64, p < 0.001, figure 2). Also, we could see that higher SBP levels acted together with Aβ to promote further cognitive decline (SBP values X Aβ X Time, β = ‐0.011, p = 0.03, figure 3). Conclusion: Our results support a framework in which late‐life HTN is a modifiable risk factor for cognitive decline in CU individuals at increased risk for AD. This supports further investigation in determining the best target of SBP levels for individuals at risk for AD, in the context of offering precision medicine for this population. [ABSTRACT FROM AUTHOR]

Background: Growing evidence suggests an increased prevalence of Alzheimer's disease (AD) in females compared to males. Elucidating how disease biomarkers correlate in females and males is critical to understanding the basis of sex differences in AD. Our aim was to evaluate sex‐related differences in the association of plasma Glial fibrillary acidic protein (GFAP) levels, a biomarker of astrocyte reactivity, with downstream neurodegeneration in Alzheimer's disease (AD) pathophysiology. Method: We cross‐sectionally assessed participants from TRIAD cohorts. Unpaired t‐test compare the difference in plasma GFAP levels between females and males. We performed linear regression with an interaction term for sex to compare the association of plasma GFAP with neurodegeneration measured with hippocampal volume (HCV) between cognitively impaired females and males. Result: We assessed 308 participants (MCI = 63, AD = 45 CN = 200, mean age = 69.8 (8)). Females showed significantly higher GFAP levels than males (Fig 1). We found a significant interaction term and strong correlation between plasma GFAP and neurodegeneration (HCV atrophy) (R‐squared = 0.13; P = 0.003) only in females. No association was found between GFAP and AD biomarkers in females or males without cognitive impairment (Fig 2). Conclusion: Our results suggest astrocyte reactivity is highly associated with neurodegeneration, a process known to play a key role in AD pathophysiology, in females than males. This may have important implications for elucidating the basis of the higher prevalence of AD in females. Yet, these results were generated with a limited number of subjects and using a cross‐sectional design. Therefore, replication in larger, independent longitudinal datasets is needed to better understand the association of GFAP levels, sex, and AD pathophysiology. [ABSTRACT FROM AUTHOR]

Introduction: The optimal combination of amyloid‐β/tau/neurodegeneration (A/T/N) biomarker profiles for the diagnosis of Alzheimer's disease (AD) dementia is unclear. Methods: We examined the discriminative accuracy of A/T/N combinations assessed with neuroimaging biomarkers for the differentiation of AD from cognitively unimpaired (CU) elderly and non‐AD neurodegenerative diseases in the TRIAD, BioFINDER‐1 and BioFINDER‐2 cohorts (total n = 832) using area under the receiver operating characteristic curves (AUC). Results: For the diagnosis of AD dementia (vs. CU elderly), T biomarkers performed as well as the complete A/T/N system (AUC range: 0.90–0.99). A and T biomarkers in isolation performed as well as the complete A/T/N system in differentiating AD dementia from non‐AD neurodegenerative diseases (AUC range; A biomarker: 0.84–1; T biomarker: 0.83–1). Discussion: In diagnostic settings, the use of A or T neuroimaging biomarkers alone can reduce patient burden and medical costs compared with using their combination, without significantly compromising accuracy. [ABSTRACT FROM AUTHOR]

Background: Although it has been alredy demonstrated that plasma amyloid‐β (Aβ), phosphorylated tau (p‐tau), and glial fibrillar protein (GFAP) can predict with high accuracy Alzheimer's disease (AD) pathophysiology, no previous study has compared their performance in the same set of individuals. Here, we compare the performance of plasma Aβ42/40, p‐tau, GFAP, and NfL against Aβ and tau PET across the AD spectrum. Method: We used the ROC curve to test the predictive performance of Simoa plasma Aβ42/40, p‐tau (at threonine 181 and 231), NfL, and GFAP to identify Aβ and Pau PET positivity in 138 cognitive unimpaired (CU) and 87 cognitive impaired (CI) from the McGill TRIAD cohort. Pearson correlation and linear regression tested the association between markers. Result: We showed that plasma p‐tau231, p‐tau181, GFAP, and NfL correlated with each other (Figure 1), while Aβ42/40 did not. In CU, voxel‐wise linear regressions (Figure 2A) showed that p‐tau231, p‐tau181, and GFAP concentrations were significantly associated with Aβ‐PET (Figure 2A). While for Tau‐PET (Figure 2B), there was a significant association only with p‐tau231 and p‐tau181 (Figure 2B). P‐tau231 outperformed the other plasma biomarkers to identify both Aβ‐ and Tau‐PET positivity (AUC 0.877 and 0.796, respectively) in CU individuals. In CI, Aβ‐ and Tau‐PET were significantly associated with p‐tau231, p‐tau181, and GFAP, whereas NfL was only associated with Tau‐PET. The discriminative accuracy of GFAP in identifying both Aβ‐PET and Tau positivity (AUC 0.936 and 0.944, respectively) outperformed the other plasma biomarkers in CI individuals (Figure 3, Table 1). Conclusion: We showed that plasma p‐tau231, a novel biomarker of early AD, best depicted AD pathophysiology in CU individuals. Interestingly, GFAP, an astrocyte reactivity marker, was better associated with brain Aβ and tau pathologies than plasma p‐tau and Aβ markers in CI individuals. Our results highlight that the performance of the novel plasma biomarkers of amyloid, tau and neuroinflammation to detect brain AD pathophysiology is disease stage specific. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) phenotypes might result from differences in selective vulnerability. Evidence from preclinical models suggests that tau pathology has cell-to-cell propagation properties. Therefore, here, we tested the cell-to-cell propagation framework in the amnestic, visuospatial, language, and behavioral/dysexecutive phenotypes of AD. We report that each AD phenotype is associated with a distinct network-specific pattern of tau aggregation, where tau aggregation is concentrated in brain network hubs. In all AD phenotypes, regional tau load could be predicted by connectivity patterns of the human brain. Furthermore, regions with greater connectivity displayed similar rates of longitudinal tau accumulation in an independent cohort. Connectivity-based tau deposition was not restricted to a specific vulnerable network but was rather a general property of brain organization, linking selective vulnerability and transneuronal spreading models of neurodegeneration. Together, this study indicates that intrinsic brain connectivity provides a framework for tau aggregation across diverse phenotypic manifestations of AD. Determining behavior by following tau: Although some of the symptoms of Alzheimer's disease (AD) are conserved among patients, multiple phenotypes exist, including amnestic, visuospatial, language, and behavioral/dysexecutive. Understanding the mechanisms mediating the different behavioral phenotypes will help the development of specific treatments. Here, Therriault and colleagues studied the pattern of tau pathology spreading in multiple cohorts of patients with different phenotypes and showed that each phenotype was associated with a specific connectivity-based pattern of tau aggregation. The results suggest that intrinsic brain connectivity drives tau aggregation pattern, thus determining the behavioral phenotype of the disease. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is characterized by the brain accumulation of amyloid-β and tau proteins. A growing body of literature suggests that epigenetic dysregulations play a role in the interplay of hallmark proteinopathies with neurodegeneration and cognitive impairment. Here, we aim to characterize an epigenetic dysregulation associated with the brain deposition of amyloid-β and tau proteins. Using positron emission tomography (PET) tracers selective for amyloid-β, tau, and class I histone deacetylase (HDAC I isoforms 1–3), we find that HDAC I levels are reduced in patients with AD. HDAC I PET reduction is associated with elevated amyloid-β PET and tau PET concentrations. Notably, HDAC I reduction mediates the deleterious effects of amyloid-β and tau on brain atrophy and cognitive impairment. HDAC I PET reduction is associated with 2-year longitudinal neurodegeneration and cognitive decline. We also find HDAC I reduction in the postmortem brain tissue of patients with AD and in a transgenic rat model expressing human amyloid-β plus tau pathology in the same brain regions identified in vivo using PET. These observations highlight HDAC I reduction as an element associated with AD pathophysiology. The link between amyloid and tau proteins with Alzheimer's disease progression remains unclear. Here, the authors propose HDACs I downregulation as an element linking the deleterious effects of brain proteinopathies with disease progression. [ABSTRACT FROM AUTHOR]

The core cerebrospinal fluid (CSF) biomarkers; total tau (tTau), phospho-tau (pTau), amyloid β 1-42 (Aβ 1-42), and the Aβ 1-42/Aβ 1-40 ratio have transformed Alzheimer's disease (AD) research and are today increasingly used in clinical routine laboratories as diagnostic tools. Fully automated immunoassay instruments with ready-to-use assay kits and calibrators has simplified their analysis and improved reproducibility of measurements. We evaluated the analytical performance of the fully automated immunoassay instrument LUMIPULSE G (Fujirebio) for measurement of the four core AD CSF biomarkers and determined cutpoints for AD diagnosis. Comparison of the LUMIPULSE G assays was performed with the established INNOTEST ELISAs (Fujirebio) for hTau Ag, pTau 181, β-amyloid 1-42, and with V-PLEX Plus Aβ Peptide Panel 1 (6E10) (Meso Scale Discovery) for Aβ 1-42/Aβ 1-40, as well as with a LC-MS reference method for Aβ 1-42. Intra- and inter-laboratory reproducibility was evaluated for all assays. Clinical cutpoints for Aβ 1-42, tTau, and pTau was determined by analysis of three cohorts of clinically diagnosed patients, comprising 651 CSF samples. For the Aβ 1-42/Aβ 1-40 ratio, the cutpoint was determined by mixture model analysis of 2,782 CSF samples. The LUMIPULSE G assays showed strong correlation to all other immunoassays (r>0.93 for all assays). The repeatability (intra-laboratory) CVs ranged between 2.0 and 5.6%, with the highest variation observed for β-amyloid 1-40. The reproducibility (inter-laboratory) CVs ranged between 2.1 and 6.5%, with the highest variation observed for β-amyloid 1-42. The clinical cutpoints for AD were determined to be 409 ng/L for total tau, 50.2 ng/L for pTau 181, 526 ng/L for β-amyloid 1-42, and 0.072 for the Aβ 1-42/Aβ 1-40 ratio. Our results suggest that the LUMIPULSE G assays for the CSF AD biomarkers are fit for purpose in clinical laboratory practice. Further, they corroborate earlier presented reference limits for the biomarkers. [ABSTRACT FROM AUTHOR]

Background: Episodic memory decline is a hallmark of cognitive impairment due to Alzheimer's Disease (AD). Literature has consistently indicated that delayed recall is compromised early in the disease. Recognition memory seems disrupted at late stages, although findings are mixed. Recent PET studies have demonstrated that the presence of tau in the medial temporal lobe (MTL) relates to early deterioration of delayed recall, but no PET studies have assessed how recognition memory relates to tau. We sought to investigate this relationship across the Braak staging continuum. Method: Tau PET ([18F]‐MK6240) was acquired for 140 cognitively unimpaired elderly (CU), 54 MCI patients and 33 AD patients. Participants were segregated into Braak stages, based on in vivo PET neuroimaging of tau. Episodic memory was assessed using RAVLT delayed recall and recognition tests. MRI were segmented into probabilistic grey (GM) and white (WM) maps, non‐linearly registered to the ADNI template using Dartel and smoothed with an 8mm FWHM gaussian kernel. Independent samples t‐tests or their nonparametric counterparts were conducted to evaluate differences in memory scores by Braak stage. Voxel‐wise linear regression models were applied, using VoxelStats, with either delayed recall or recognition scores as dependent variables and tau PET as a predictor. Global amyloid, age, sex, education and APOE genotype were entered as covariates. Results: Pairwise comparisons revealed that recognition memory is spared in early Braak stages. Voxel‐wise analyses in the whole sample unveiled that delayed recall and recognition memory relate to tau in virtually the same cortical areas. However, the strength of the relationships widely varied by memory type. Tau‐PET in anterior MTL and posterior hippocampus shows stronger associations with delayed recall, while tau binding in lateral temporal, temporooccipital and posterior areas exhibits stronger associations with recognition memory. Conclusion: Our findings support the differentiation between delayed recall and recognition across the AD spectrum. Relationships between delayed recall and tau in the MTL are in concordance with previous research. Moreover, the contrast in the strength of the associations between memory and tau aggregation further supports the notion that delayed recall is already impaired in early Braak stages while recognition is damaged in later Braak stages. [ABSTRACT FROM AUTHOR]

Background: Mild behavioral impairment (MBI) is a neurobehavioral syndrome characterized by the emergence of persistent non‐cognitive neuropsychiatric symptoms (NPS) in older adults, representing an at‐risk state for dementia and a potential marker of Alzheimer's disease (AD). However, few studies have investigated associations between MBI and plasma biomarkers of AD pathophysiology, specifically tau hyperphosphorylation. Method: Individuals across the AD spectrum (cognitively unimpaired (CU) and impaired (CI)) were selected from the Translational Biomarkers of Aging and Dementia (TRIAD) cohort. MBI was assessed using the MBI‐Checklist (MBI‐C), which assesses NPS severity in five subdomains: decreased motivation (apathy), emotional dysregulation (mood/anxiety symptoms), impulse dyscontrol (agitation, impulsivity, abnormal reward salience), social inappropriateness (impaired social cognition), and abnormal thoughts/perception (psychosis). Plasma levels of p‐tau181 were quantified in all individual, and log‐transformed due to right skew. Spearman correlation analysis investigated cross‐sectional associations between plasma p‐tau181 and MBI‐C scores, and between baseline plasma p‐tau181 and annual change in MBI‐C. Multivariable linear regression analyses assessed the ability of cross‐sectional and longitudinal MBI‐C scores to predict plasma p‐tau181, adjusting for age, sex, education, and diagnostic group (CU/CI, Aβ +/‐). Result: Cross‐sectional MBI data were available for 211 individuals, with longitudinal data available for 128 individuals (). Significant correlations were found between plasma p‐tau181 and MBI‐C total and apathy scores in the cross‐sectional sample (Figure A). Further, significant correlations were found with plasma p‐tau181 and the annual change in MBI‐C total and apathy scores (Figure B). These associations were corroborated by significant standardized and adjusted regression coefficients from multivariate regression models, which showed that baseline and longitudinal MBI‐C total and apathy score predicted plasma level of p‐tau181 (Figure C). Conclusion: Our study provides novel findings on the association between MBI and tau hyperphosphorylation assessed using plasma biomarkers in an AD cohort. These results add to the existing evidence for MBI as a clinical manifestation of AD pathology and support the use of the MBI‐C as an enrichment tool for clinical trial enrollment and therapeutic intervention. [ABSTRACT FROM AUTHOR]

Background: [18F]MK6240 tau‐PET can detect changes in the early and late stages of tau tangles accumulation. However, off‐target binding, often observed in the meninges and neuromelanin‐containing cells, can interfere with longitudinal tracer quantification. Here, we investigated the association of longitudinal changes in off‐target and target signals using [18F]MK6240. Method: We assessed individuals from the TRIAD cohort with [18F]MK6240 tau‐PET and clinical evaluation. Longitudinal analyses included 83 cognitively unimpaired (CU) and 37 cognitively impaired (CI) individuals. Age‐related off‐target binding was estimated comparing 36 CU young individuals (<25 y.o) and 28 CU elderly amyloid/tau negative (40‐65 y.o). A t‐test was used to compare both groups. The ratio between baseline and follow‐up SUVR measured changes in off‐target and target regions. Pearson correlations tested the associations between regions, and Bonferroni analysis corrected for multiple comparisons. Result: Although averaged images did not present a striking visual difference in [18F]MK6240 uptake between CU young and elderlies, t‐test revealed significant differences between groups in the cerebellar white matter and subcortical regions (Figure 1). Table 1 depicts the percentage of area of selected regions overlapping with the age‐related off‐target binding. Notably, we did not observe a significant association between longitudinal changes in age‐related or meningeal off‐target binding with longitudinal change in target regions (Braak‐II, BraakIII‐IV, BraakV‐VI), whereas changes in target regions were highly correlated (Figure 2). Conclusion: Despite not being visually perceptible, [18F]MK6240 presents age‐related off‐target binding in subcortical regions, similar to regions reported using [18F]Flortaupicir. The overlap between age‐related off‐target and Braak IV region (∼3%) may lead to the confounding results in quantifying this region. The lack of correlation between off‐target and target [18F]MK6240 changes suggests little influence of the off‐target binding on longitudinal tracer quantification. Our results suggest that although off‐target uptake appears to have a modest influence on longitudinal quantification, it is necessary to consider both age‐related and meningeal off‐target signals for an accurate tracer assessment. [ABSTRACT FROM AUTHOR]

Background: Recent evidence suggests that microglial activation sets the stage for tau spread in Alzheimer's disease (AD). However, the underpinnings of microglial activation in early regions of tau accumulation are poorly understood. The apolipoprotein E (APOE) ε4 allele is the strongest genetic risk factor for sporadic AD and influences microglial response in animal models of AD. Here, we tested the hypothesis that APOE ε4 carriership is associated with microglial activation in early Braak regions independently of amyloid‐β (Aβ) and tau pathologies. Method: We assessed 118 participants [79 cognitively unimpaired (CU), 23 with mild cognitive impairment (MCI), and 16 with AD dementia] with 50 years of age or older from the McGill TRIAD cohort. Individuals had available positron emission tomography (PET) for Aβ ([18F]AZD4694), tau tangles ([18F]MK6240), and microglial activation ([11C]PBR28), as well as magnetic resonance imaging (MRI) and APOE genotyping. Braak I (transentorhinal) and Braak II (entorhinal and hippocampus) were defined as early regions of tau tangles accumulation. Result: Voxel‐wise analysis revealed that APOE ε4 carriership was associated with microglial activation mainly in regions corresponding to early Braak stages (e.g., transentorhinal, entorhinal, and hippocampus; Figure 1). In these regions, we observed that APOE ε4 carriership was associated with microglial activation independently of Aβ and tau pathologies (Braak I: β = 0.087, P < 0.001; Braak II: β = 0.053, P = 0.026; Table 1). Furthermore, structural equation modeling demonstrated that microglial activation mediated the Aβ‐independent effect of APOE ε4 carriership on tau accumulation in regions corresponding to Braak I‐II (mediation effect size = 34.1%; Figure 2). Conclusion: Our results suggest a deleterious effect of APOE ε4 carriership on AD progression by contributing to microglial activation in regions of early tau accumulation (transentorhinal, entorhinal, and hippocampus). These findings can help to understand the influence of the APOE ε4 allele on AD pathogenesis, as well as provide insights for the development of drugs targeting the interplay between APOE ε4 and microglial activation. [ABSTRACT FROM AUTHOR]

Background: The presence of p‐tau in biofluids has previously been proposed to be a response to neurofibrillary tangle pathology, one of the hallmarks of Alzheimer's disease (AD). However, the increase of p‐tau in cerebrospinal fluid (CSF) precedes detectable neurofibrillary tangle pathology, as indexed by tau Positron Emission Tomography (PET), by up to a decade, suggesting that soluble tau could be an indication of early tau pathology. With this study, we investigated the heterogeneity of p‐tau species in CSF to assess the disease status of participants of the Translational Biomarkers of Aging and Dementia (TRIAD) cohort. Methods: Support vector machines were used to determine cutoff values of p‐tau181, p‐tau217, p‐tau231 and p‐tau235 in CSF, identifying a group of participants that were amyloid positive (58 from a total of 165 participants). Amyloid positivity was determined by using an [18F]AZD4694 SUVR threshold value of 1.55 in the neocortex. Using these cutoff values, signatures were calculated on an individual level to identify the number of phosphorylated sites. Based on the number of phosphorylated sites, [18F]MK6240 SUVR maps and [18F]AZD4694 SUVR maps were calculated. Results: When combining different CSF p‐tau species, the largest contribution in identifying amyloid positivity came from p‐tau217, followed by p‐tau231, p‐tau181 and p‐tau235. Achieving the cutoff for multiple p‐tau species was associated with more tau pathology particularly in the later Braak stages (fig 1) and increased amyloid‐β plaque accumulation (fig 2). Conclusion: Our findings suggest that heterogeneity in p‐tau species carries predictive power in the identification of disease severity in incipient Alzheimer's Disease. [ABSTRACT FROM AUTHOR]

Background: Inflammation has long been pointed out as a key feature in Alzheimer's disease (AD). However, the heterogeneity of AD pathology might trigger different aspects of the immune response. Here, we aimed to study the association of the newly proposed concept of inflammatory composite indexes with Aβ and tau pathologies across the aging and AD spectra. We hypothesize that distinct inflammatory pathways are associated with the different hallmarks of AD. Method: A panel of 92 inflammation‐related markers was measured in the CSF of 60 individuals (35 cognitively unimpaired and 25 cognitively impaired) from the McGill TRIAD cohort. These 92 proteins were clustered by ontogenetic similarity and physical interaction using STRING. A z‐scored composite value representing each cluster was created for each individual. Individuals were classified as Aβ‐ and tau‐positive using global [18F]AZD4694 and temporal meta‐ROI [18F]MK6240 PET, respectively. Linear regressions (corrected by diagnosis, age, sex, and APOEɛ4 status) and receiver operating characteristic (ROC) analyses evaluated clusters' performance. Result: Of the six clusters identified in our protein network analysis, three positively correlated with global Aβ‐PET (C4,C5, and C6) and three with meta‐ROI tau PET (C2,C4, and C5;Fig.1). However, controlling for Aβ PET, tau PET was only associated with C2, indicating that the association with the other two clusters (C4 and C5) was dependent of Aβ pathology. The cluster exclusively associated with tau (C2), represents tumor necrosis factor‐mediated signaling pathways. On the other hand, C6, related to the stimulation of interferon‐gamma production, and C5, related to glial cell‐derived neurotrophic receptor binding, are exclusively associated with Aβ. ROC analysis showed that all clusters presented a better performance predicting Aβ‐PET positivity than tau‐PET positivity (Fig.2A,B). Additionally, overall the clusters showed a better performance than sTREM2, a classical inflammatory biomarker. Conclusion: Our novel clustering approach supports that Aβ and tau proteinopathies are associated with distinct aspects of the inflammatory cascade. Our results suggest that a composite of inflammatory proteins better identifies AD pathology than a single marker. Finally, this suggested cluster approach helps to understand the inflammatory response to Aβ and tau and can uncover inflammation‐related AD pathways. [ABSTRACT FROM AUTHOR]

Background: The spread of abnormal tau along connectivity‐based networks is a hallmark of Alzheimer's disease (AD). In addition, activated microglia was shown to affect tau spread across networks. However, traditional network approaches using atlas‐defined regions suffer from assuming within‐region homogenous connectivity, as well as abrupt and linear connectivity changes between the regions; while, in fact, brain structure and function exist as complex overlapping axes of connectivity variation. Here, we studied smooth/continuous spatial transitions or 'gradients' of connectivity and their link to gradients of pathology in AD. This work provides novel insights into brain architecture driving pathology spread. Method: We enrolled 220 individuals including 106 cognitively normal Aβ‐negative (A‐) and 37 A+, and 77 MCI/AD A+ (TRIAD). From diffusion‐weighted MRI and fMRI data, we estimated region‐to‐region fiber count and correlated timeseries, respectively, and averaged subject‐wise connectivity matrices to create structural and functional 'template connectomes'. From 18F‐MK6240 and 11C‐PBR28 PET data, we extracted regional tau and neuroinflammation SUVR values, respectively, and created covariance matrices for each disease stage. Next, the template connectomes/covariance matrices were subjected to non‐linear dimensionality reduction to extract embedded components ('gradients'). We correlated the primary gradients of functional or structural connectivity (G1FC/G1SC) with the primary and secondary gradients of tau or neuroinflammation (G1TAU/G2TAU; G1INFLAM/G2INFLAM). We employed three brain atlases for validation: high‐resolution customized Glasser‐atlas (1332 equally‐sized subregions), DKT, and Schaefer‐100. Result: G1FC replicated the previously reported 'uni‐to‐transmodal' functional gradient (Margulies 2016) and correlated strongly with G1TAU in cognitively impaired A+ (Fig.1 A); illustrating a common topographic variation in tau spread and functional connectivity in symptomatic stages. Conversely, G1SC ran between medial‐temporal‐lobe (MTL)/posterior and frontal/anterior regions, and correlated strongly with both G2TAU (Fig.1 B) and G1INFLAM (Fig.1 C) in cognitively (un)impaired A+; illustrating a common topographic variation in tau/microglia and structural connectivity already present at early disease stages. Different brain atlases led to similar results. Conclusion: We identified two gradients of continuous topographic variation in tau and neuroinflammation, potentially reflecting heterogeneity of AD‐subgroups. While microglial activation and early‐stage tau propagation may be largely dominated by structural organisation, later‐stage tau propagation may be more heterogeneously associated with variation in structural and particularly functional connectivity. [ABSTRACT FROM AUTHOR]

Background: It has already been shown that longitudinal changes in plasma phosphorylated tau 181 (p‐tau181) correlate with longitudinal Alzheimer's disease (AD) progression. However, it is unclear whether longitudinal plasma p‐tau181 is a suitable measure to be used as a surrogate variable in clinical trials. This study aims to evaluate the utility of using longitudinal changes in plasma p‐tau181 to monitor drug effects in AD clinical trials. Method: We evaluated 715 individuals (227 cognitively unimpaired (CU) amyloid‐beta (Aβ) negative, 103 CU Aβ positive, 265 mild cognitive impairment (MCI) Aβ positive, and 120 Alzheimer's disease (AD) dementia Aβ positive) from the Alzheimer's Disease Neuroimaging Initiative. Individuals diagnosed with AD or MCI were classified as cognitive impaired (CI). The subjects had [18F]florbetapir Aβ PET at baseline and longitudinal plasma p‐tau181 (up to 4‐year follow‐up duration). We determined the longitudinal rates of change in plasma p‐tau181 concentrations and its effect sizes, calculated as mean change divided by the standard deviation. Logistic regression tested whether the longitudinal change in p‐tau181 status was associated with individuals' clinical deterioration. Result: Plasma p‐tau181 slope of change was positively associated with baseline plasma p‐tau concentrations (Fig 1). Longitudinal increase in plasma p‐tau181 was correlated with longitudinal worsening in cognition. Long‐term increase in plasma p‐tau181 values was more consistent in CU Aβ negative (48‐month effects size=0.4) and CU Aβ positive (48‐month effects size=0.6) than in CI Aβ positive (48‐month effects size=0.2) individuals (Fig 2). Conclusion: Monitoring change in plasma p‐tau181 status from negative to positive can be helpful to identify individuals on the verge of cognitive deterioration in clinical practice. Longitudinal changes in plasma p‐tau181 values can open a new frontier in AD research offering a cost‐effective and scalable alternative to be used as a surrogate variable in large‐scale trials designed to test the effects of population interventions on the natural history of tau pathology in elderly populations. [ABSTRACT FROM AUTHOR]

Tracking longitudinal tau tangles accumulation across the Alzheimer's disease continuum is crucial to better understand the natural history of tau pathology and for clinical trials. Although the available first-generation tau PET tracers detect tau accumulation in symptomatic individuals, their nanomolar affinity offers limited sensitivity to detect early tau accumulation in asymptomatic subjects. Here, we hypothesized the novel subnanomolar affinity tau tangles tracer 18F-MK-6240 can detect longitudinal tau accumulation in asymptomatic and symptomatic subjects. We studied 125 living individuals (65 cognitively unimpaired elderly amyloid-β-negative, 22 cognitively unimpaired elderly amyloid-β-positive, 21 mild cognitive impairment amyloid-β-positive and 17 Alzheimer's disease dementia amyloid-β-positive individuals) with baseline amyloid-β 18F-AZD4694 PET and baseline and follow-up tau 18F-MK-6240 PET. The 18F-MK-6240 standardized uptake value ratio (SUVR) was calculated at 90-110 min after tracer injection and the cerebellar crus I was used as the reference region. In addition, we assessed the in vivo18F-MK-6240 SUVR and post-mortem phosphorylated tau pathology in two participants with Alzheimer's disease dementia who died after the PET scans. We found that the cognitively unimpaired amyloid-β-negative individuals had significant longitudinal tau accumulation confined to the PET Braak-like stage I (3.9%) and II (2.8%) areas. The cognitively unimpaired amyloid-β-positive individuals showed greater tau accumulation in Braak-like stage I (8.9%) compared with later Braak stages. The patients with mild cognitive impairment and those who were Alzheimer's dementia amyloid-β-positive exhibited tau accumulation in Braak regions III-VI but not I-II. Cognitively impaired amyloid-β-positive individuals that were Braak II-IV at baseline displayed a 4.6-7.5% annual increase in tau accumulation in the Braak III-IV regions, whereas those who were cognitively impaired amyloid-β-positive Braak V-VI at baseline showed an 8.3-10.7% annual increase in the Braak regions V-VI. Neuropathological assessments confirmed PET-based Braak stages V-VI in the two brain donors. Our results suggest that the 18F-MK-6240 SUVR is able to detect longitudinal tau accumulation in asymptomatic and symptomatic Alzheimer's disease. The highest magnitude of 18F-MK-6240 SUVR accumulation moved from the medial temporal to sensorimotor cortex across the disease clinical spectrum. Trials using the 18F-MK-6240 SUVR in cognitively unimpaired individuals would be required to use regions of interest corresponding to early Braak stages, whereas trials in cognitively impaired subjects would benefit from using regions of interest associated with late Braak stages. Anti-tau trials should take into consideration an individual's baseline PET Braak-like stage to minimize the variability introduced by the hierarchical accumulation of tau tangles in the human brain. Finally, our post-mortem findings supported use of the 18F-MK-6240 SUVR as a biomarker to stage tau pathology in patients with Alzheimer's disease. [ABSTRACT FROM AUTHOR]

Objective: To investigate the relationship between the topography of amyloid‐β plaques, tau neurofibrillary tangles, and the overlap between the two, with cognitive dysfunction in individuals without dementia. Methods: We evaluated 154 individuals who were assessed with amyloid‐β PET with [18F]AZD4694, tau‐PET with [18F]MK6240, structural MRI, and neuropsychological testing. We also evaluated an independent cohort of 240 individuals who were assessed with amyloid‐β PET with [18F]Florbetapir, tau‐PET with [18F]Flortaucipir, structural MRI, and neuropsychological testing. Using the VoxelStats toolbox, we conducted voxel‐wise linear regressions between amyloid‐PET, tau‐PET, and their interaction with cognitive function, correcting for age, sex, and years of education. Results: In both cohorts, we observed that tau‐PET standardized uptake value ratio in medial temporal lobes was associated with clinical dementia rating Sum of Boxes (CDR‐SoB) scores independently of local amyloid‐PET uptake (FWE corrected at p < 0.001). We also observed in both cohorts that in regions of the neocortex, associations between neocortical tau‐PET and clinical function were dependent on local amyloid‐PET (FWE corrected at p < 0.001). Interpretation: In medial temporal brain regions, characterized by the accumulation of tau pathology in the absence of amyloid‐β, tau had direct associations with cognitive dysfunction. In brain regions characterized by the accumulation of both amyloid‐β and tau pathologies such as the posterior cingulate and medial frontal cortices, tau's relationship with cognitive dysfunction was dependent on local amyloid‐β concentrations. Our results provide evidence that amyloid‐β in Alzheimer's disease influences cognition by potentiating the deleterious effects of tau pathology. [ABSTRACT FROM AUTHOR]

Background: Plasma markers of tau are currently being studied as proxies of cerebral neurofibrillary tangle (NFT) accumulation. Phosphorylated tau (pTau) and N‐terminal tau fragment (NTA) assays are associated with present and future tau‐PET load. Our aim was to investigate whether plasma markers could predict whether someone will be a slow or fast accumulator. Method: We assessed 143 individuals [72 CU, 54 MCI, 17 AD] from the TRIAD cohort, with two available [18F]MK6240 tau‐PET scans and calculated the relative change (Δ[18F]MK6240) between baseline and follow‐up [mean follow‐up time: 2.1 ± 0.7 years]. We used tertiles to divide individuals as slow, medium and fast accumulators. Additionally, we measured baseline plasma pTau181, pTau217, pTau231 and NTA concentrations. We computed the effect size (Cohen's d) and area under the curve (AUC) for each plasma marker for Δ[18F]MK6240 between slow and fast accumulators. Δ[18F]MK6240 was calculated in Braak stages I/II, III/IV and V/VI. Result: We first observed that the highest effect size for Δ[18F]MK6240 in Braak I/II was depicted by pTau231. For Δ[18F]MK6240 in Braak III/IV and Braak V/VI, pTau217 presented the highest effect size (Figure 1). Moreover, AUC values were the highest, and highly similar, in ΔBraak I/II for pTau181, pTau217 and pTau231. For ΔBraak III/IV, pTau181 and pTau217 presented the highest values. Finally, AUC for ΔBraak V/VI, pTau231 and NTA had the highest values, which were also similar (Figure 2). Conclusion: Plasma pTau biomarkers (181, 217 and 231) are great predictors of fast accumulation in early to middle Braak regions. For late Braak regions, fast accumulation was best predicted by pTau217 and NTA. Plasma markers are able to determine whether someone will be a fast accumulator in a stage‐specific manner. The currently available tau biofluid measures could be used in the clinical and clinical trial settings, as these are less invasive and cheaper than CSF or PET assessments. Especially in the recruitment phase, pTau217 could be used for screening individuals that are more likely to accumulate tau fast. [ABSTRACT FROM AUTHOR]