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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 Unpublished data suggest that MA is highly associated with the development of neuropsychiatric symptoms (NPS) in patients with AD.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 high prevalence of Alzheimer's dementia in females have long puzzled researchers in the field. Despite similar amyloid levels, females show higher load of neurofibrillary tangles (NFTs). Previous literature proposed that amyloid‐β (Aβ) and phosphorylated tau (p‐tau) synergism accelerates biomarker abnormalities. However, it remains to be answered whether this synergism is the driving force behind faster tau progression in females. The overarching goal of the study wa to investigate whether amyloid‐β aggregates differentially impose tau hyperphosphorylation and neurofibrillary tangles formation in a sex‐specific manner. Method: In this longitudinal study, we assessed 287 participants from TRIAD cohort at McGill University Research Centre for Studies in Aging. Cerebral Aβ and tau deposition were assessed with positron emission tomography (PET) radiotracers [18F]AZD4694 ([18F]NAV4694) and [18F]MK6240, respectively. Cerebrospinal fluid (CSF) p‐tau181 and p‐tau217 were also measured (analysed at the Clinical Neurochemistry Laboratory at the University of Gothenburg, Sweden). Regression and voxel‐based models with interaction terms were used to evaluate baseline tau load and NFT accumulation rate as a function of sex and baseline biomarkers (Aβ and p‐tau). Result: We identified sex difference in the relationships between CSF p‐tau, Aβ and NFT (Fig 1). Specifically, voxelwise analyses demonstrated that female presented stronger positive correlations between CSF p‐tau and AD core biomarkers (Aβ and NFT). Furthermore, we discovered that Aβ and CSF ptau181 interactively potentiated tau accumulation in females but not males (Fig 2, Table 1). Together, the present results support that Aβ load imposes higher tau aggregation in females. Conclusion: Aβ‐dependent tau phosphorylation was the key driver for faster NFT accumulation observed in female. [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]

Background: Neuropathological observations report incipient tau accumulation in the human brain starting in the third decade of life, with the proportion of individuals with some degree of tau deposition increasing with age. Given the high prevalence of tau positive cases among cognitively unimpaired (CU) older adults, one may question whether these individuals constitute an ideal reference group when assessing tau load in symptomatic population. Here, we compare tau biomarker levels of participants with Alzheimer's disease (AD) and CU of different ages. Method: We evaluated 35 CU young individuals (aged <26 years) and 124 amyloid‐beta (Aβ)‐ elderly, considered the two control groups. We also assessed 42 Aβ+ CU and 122 Aβ+ cognitively impaired (CI) individuals, diagnosed with either mild cognitive impairment or AD dementia. Participants were assessed with 18F‐MK6240 positron emission tomography (PET) and CSF and plasma pTau181, 217, 231 and 235. We used linear regression to perform voxel‐wise comparisons of tau‐PET signal between groups. We compared the standardized uptake value ratio (SUVR) in medial‐temporal and Braak‐like regions‐of‐interest (ROI) and fluid biomarkers levels using the Wilcoxon rank sum test. Result: In the voxel‐wise comparisons (Figure 1A‐E), CI participants presented more widespread cortical signal than control groups. Less signal in the parietal cortex was observed in the comparison with CU young. Higher t‐values were observed in Aβ+ CU individuals in the medial temporal region, compared to both control groups, and adjacent neocortex, especially compared to CU young. Temporal and Braak V‐VI SUVR were higher in CI but not in Aβ+ CU individuals compared to controls. Moreover, Braak I‐II and III‐IV SUVR and the fluid biomarkers levels were higher in both Aβ+ groups compared to controls (Figures 2A‐D; 3A‐G). Importantly, Braak I‐II SUVR and the CSF biomarkers levels were higher in CU old Aβ‐ versus young. Conclusion: Here, we provide in vivo evidence that tau‐load in age‐matched Aβ‐ controls constitutes a bias for identifying tau pathology, particularly in individuals at early stages of AD pathophysiology. Age‐related tau load should be considered when selecting control groups to assess tau in symptomatic populations, especially those with early AD, and when defining criteria for tau abnormality. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Plasma biomarkers are promising tools for Alzheimer's disease (AD) diagnosis, but comparisons with more established biomarkers are needed. METHODS: We assessed the diagnostic performance of p‐tau181, p‐tau217, and p‐tau231 in plasma and CSF in 174 individuals evaluated by dementia specialists and assessed with amyloid‐PET and tau‐PET. Receiver operating characteristic (ROC) analyses assessed the performance of plasma and CSF biomarkers to identify amyloid‐PET and tau‐PET positivity. RESULTS: Plasma p‐tau biomarkers had lower dynamic ranges and effect sizes compared to CSF p‐tau. Plasma p‐tau181 (AUC = 76%) and p‐tau231 (AUC = 82%) assessments performed inferior to CSF p‐tau181 (AUC = 87%) and p‐tau231 (AUC = 95%) for amyloid‐PET positivity. However, plasma p‐tau217 (AUC = 91%) had diagnostic performance indistinguishable from CSF (AUC = 94%) for amyloid‐PET positivity. DISCUSSION: Plasma and CSF p‐tau217 had equivalent diagnostic performance for biomarker‐defined AD. Our results suggest that plasma p‐tau217 may help reduce the need for invasive lumbar punctures without compromising accuracy in the identification of AD. Highlights: p‐tau217 in plasma performed equivalent to p‐tau217 in CSF for the diagnosis of AD, suggesting the increased accessibility of plasma p‐tau217 is not offset by lower accuracy.p‐tau biomarkers in plasma had lower mean fold‐changes between amyloid‐PET negative and positive groups than p‐tau biomarkers in CSF.CSF p‐tau biomarkers had greater effect sizes than plasma p‐tau biomarkers when differentiating between amyloid‐PET positive and negative groups.Plasma p‐tau181 and plasma p‐tau231 performed worse than p‐tau181 and p‐tau231 in CSF for AD diagnosis. [ABSTRACT FROM AUTHOR]

Background: Different methods have been proposed to assess vascular dysfunction in Alzheimer's disease (AD), mild cognitive impairment (MCI), and cognitively unimpaired (CU) subjects including quantitative susceptibility mapping (QSM), and recently oxygen extraction fraction (OEF). QSM is sensitive to the presence of iron and is a non‐invasive MR approach to measure local tissue susceptibility with high spatial resolution. OEF is a measure of the percentage of oxygen taken from the brain's blood supply and relates directly to brain oxygen metabolism. Here, we aimed to examine QSM (Figure1) and OEF (Figure1) potential in differentiating AD, MCI, and CU. Method: A cohort of 310 subjects with AD (n = 48), MCI (n = 80), and CU (n = 182) were recruited. All the patients received 3D gradient‐recalled echo sequence MRI. All QSM images were constructed by MEDI+0 and OEF images were constructed by QSM+qBOLD model with CCTV (Temporal clustering, tissue composition, and total variation). Eighty‐two various brain regions of interest (ROI) and 6 Braak ROI were investigated in the current study. ANOVA and Posthoc least significant difference (LSD) tests were implemented for each ROI over AD, MCI, and CU. Result: Over Braak ROI analysis, the ANOVA test showed that the average susceptibility of QSM with Braak 4 ROI is significantly different (p<0.001). LSD test showed that Braak 4 ROI of QSM is significantly different between AD vs. MCI and AD vs. CU (p<0.001). Braak 2 ROI of OEF was significantly different between AD vs. MCI and AD vs. CU (p = 0.21 and p = 0.32, respectively). Over brain ROI, the ANOVA test showed QSM right and left posterior cingulate and right Caudate were significantly different (p<0.001). Besides, these ROIs were significantly different between AD vs. MCI and AD vs. CU, according to the LSD test. Over brain ROI, OEF right Caudate was significantly different (p<0.001) followed by left Caudate and Right transverse temporal with p = 0.002 based on the ANOVA test. However, right and left Caudate were just significantly different between AD vs. CU (p<0.001) based on the LSD test (Table 1 and 2). Conclusion: QSM and OEF are affordable non‐invasive MR approaches to assess vascular dysfunction in the spectrum of clinical presentations of AD. [ABSTRACT FROM AUTHOR]

Background: There is a growing body of evidence suggesting changes in blood flow and metabolism as a trigger of the cascade of events leading to Alzheimer's disease (AD). Oxygen extraction fraction (OEF) MRI images provide valuable information about the brain's metabolism and blood flow in stroke, brain injury, and recently neurodegenerative diseases. However, OEF is a research tool, and its clinical utility is still being evaluated. Here, we aimed to assess brain oxygenation in aging and AD using OEF images. We test the hypothesis that OEF reduction is associated with the clinical stages of AD. Method: A cohort of 310 subjects with cognitively unimpaired (CU) (n = 182), mild cognitive impairment (MCI) (n = 80), and AD (n = 48), were recruited. All participants received 3D gradient‐recalled echo sequence MRI. All OEF images were constructed by QSM+qBOLD model with CCTV (Temporal clustering, tissue composition, and total variation) (Figure1). Eighty‐two various brain regions of interest (ROI) and 6 Braak ROI were investigated in the current study. Result: Our results demonstrated that the OEF mean value in almost all of the brain ROI encompassed the lowest amount of OEF in AD compared with MCI and CU. In most parts of the brain, the OEF mean value was AD

Background: The sequential model predicts synaptic depletion as a downstream of amyloid, tau and neuroinflammation. However, synaptic toxicity might be consequence of toxic forms of amyloid in the absence of tau. In this study we explore the role of synaptic depletion and neuroinflammation as determinants of tau pathology. GAP‐43 and neurogranin are pre‐ and post‐synaptic biomarkers known to be detected at elevated levels in cerebrospinal fluid (CSF) of patients with Alzheimer's disease (AD). Method: We included 126 individuals from TRIAD cohort. Brain inflammation, tau tangle and amyloid‐β (Aβ) deposition were assessed via [11C]PBR28‐PET, [18F]MK6240‐PET and [18F]AZD4694‐PET, respectively. All patients had plasma GFAP quantified, and a subset of 78 individuals had CSF GFAP, CSF Neurogranin and CSF GAP‐43 quantifications available. Voxel and region of interest regression models evaluated the relationship between PET tracers and the fluid biomarkers. Models with [18F]AZD4694‐PET as the outcome were adjusted for [18F]MK6240‐PET voxel‐wise and vice‐versa. A linear regression interaction model evaluated the interaction between CSF GFAP and both synaptic biomarkers with Aβ‐ and tau‐PET as the outcome. Result: Positive associations were found between CSF neurogranin and Aβ‐, tau‐ and brain inflammation‐PET in AD related regions; the strongest associations were found with tau‐pet and CSF neurogranin in the medial temporal lobe. GAP‐43 was also positively associated with tau‐ and TSPO‐PET, but no associations were found with Aβ‐PET. Both plasma and CSF GFAP were associated with Aβ‐, tau‐ and TSPO‐PET in AD related regions, with the strongest t‐values in the model including plasma GFAP and amyloid‐PET. A negative interaction was found between CSF GFAP and both synaptic biomarkers with amyloid‐ and tau‐PET as the outcomes. These associations were stronger with tau‐PET and were found in the temporal, occipital and parietal areas. Conclusion: This study supports the role of synaptic dysfunction and neuroinflammation on tau load. As both synaptic biomarkers and GFAP increase as a function of tangles load, tau accumulation is linked to the relationship between synaptic abnormalities and inflammation in early stages of the disease. Our results suggest that synaptic depletion is a phenomenon that might start prior to tau tangles. [ABSTRACT FROM AUTHOR]

Background: Accumulation of tau neurofibrillary tangles in Alzheimer's disease (AD) follows a stereotypical pattern, known as Braak staging. As individuals show different rates of tau accumulation, depending on their initial stage, this potentially biases drug effects on tau pathology over time. We hypothesized that amyloid would be a driving force behind tau deposition in later Braak regions for those that were at earlier stages of the disease. Method: 79 individuals (CU: 57, MCI: 21, AD: 1) were recruited from the Translational Biomarkers of Aging and Dementia (TRIAD) cohort. All individuals underwent baseline and 2‐year follow‐up amyloid ([18F]AZD4694) and tau ([18F]MK6240) PET imaging, as well as baseline plasma pTau181, pTau217, and pTau231 assessments. Differences in standardized uptake value ratios between the two timepoints in Braak I‐IV were used to separate fast accumulators of tau from slow accumulators, using the standard deviation of a Young group (n = 13). Pearson R's were calculated between tau deposition in Braak regions IV‐VI and the neocortical amyloid load at baseline, within both these groups. Furthermore, a voxelwise analysis was performed to identify specific regional differences in amyloid SUVR between slow and fast progressors, while correcting for age, sex, ApoE4 carriership, as well as the individual's Braak stage. In addition, an independent t‐test was performed to compare the levels of each pTau species at baseline. Result: Fast accumulators had stronger increases (p < 0.01) in tau accumulation in Braak region V and VI, compared to slower accumulators. Furthermore, the level of tau deposition in Braak region IV and V was positively associated (p < 0.01) with the amyloid load in the neocortex, but only in the fast accumulator group (figure 1). The voxelwise analysis confirmed that faster progressors had stronger associations with amyloid‐PET (figure 2). Furthermore, those who accumulated tau at a faster rate also had higher levels of plasma pTau at baseline (figure 3). Conclusion: Tau deposition in later Braak regions is associated with a higher amyloid load and increased values of pTau181, pTau217 and pTau231 at baseline in individuals in early Braak stages that accumulate tau at a more rapid rate. [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: Gold standard diagnostic methods for AD rely on staging systems to measure disease severity, which have not yet been incorporated into the in vivo biological research framework for AD. The topographical information conferred by tau‐PET offers the potential to translate the gold standard histopathological Braak staging system to living individuals. Method: Using the topographical information from [18F]MK6240 tau‐PET, we applied the Braak tau staging system to 324 living individuals. We used PET‐based Braak stage to model the trajectories of amyloid‐b, phosphorylated tau in cerebrospinal fluid (pTau181, pTau217, pTau231, pTau235) and plasma (pTau181, pTau231), neurodegeneration and cognitive symptoms. Result: PET‐based Braak stages were We identified nonlinear AD biomarker trajectories corresponding to the spatial extent of tau‐PET, with modest biomarker changes detectable by Braak stage II and significant changes occurring at stages III‐IV, followed by plateaus. Early Braak stages were associated with isolated memory impairment, while Braak stages V‐VI were incompatible with normal cognition. Follow up tau‐PET scans indicated sequential progression of in vivo Braak stages over time, with progression beyond Braak stage III requiring the presence of amyloid‐beta abnormality. Conclusion: Our results support PET‐based Braak staging as a framework to model the natural history of AD, as well as monitor AD severity from presymptomatic to clinical dementia phases. [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: [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: Glial fibrillary acidic protein (GFAP) is a reactive astrogliosis biomarker, shown to increase in individuals with preclinical Alzheimer's disease (AD). First thought to be a great marker of amyloid‐β (Aβ) pathology, recent post‐mortem research has linked it to tau accumulation only. Here we investigate the independent associations of plasma GFAP with imaging markers of AD along the disease spectrum. Method: 126 individuals from TRIAD cohort underwent [18F]MK6240 tau‐PET and [18F]AZD4694 Aβ‐PET and plasma GFAP assessment using an in‐house assay. Voxel and region of interest regression models evaluated the relationship between PET tracers and plasma GFAP. Models with [18F]AZD4694‐PET as the outcome were adjusted for [18F]MK6240‐PET voxel‐wise and vice‐versa. All models were corrected for age and sex, and RFT was used to correct for multiple comparisons. Result: Plasma GFAP was associated with [18F]AZD4694 signal throughout the cortex (Figure1A), independently of [18F]MK6240. Additionally, it was positively correlated with [18F]MK6240 in the medial temporal and occipital lobes and the anterior cingulate cortex, independently of [18F]AZD4694 (Figure1B). Voxel‐wise findings were confirmed by region‐of‐interest‐based analyses. Conclusion: Our findings indicate that plasma GFAP is independently associated with both Aβ and tau pathologies in AD. Aβ‐PET showed associations throughout the entire cortex, suggesting its effectiveness as a reliable marker of Aβ pathology across the AD spectrum. On the other hand, tau‐PET correlations were observed in specific regions associated with memory and behavioral impairments that exhibit early deposition of tau. Overall, these results demonstrate that GFAP, an astrogliosis marker, is independently associated with Aβ and tau. [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]

Background: The Aggie Figures Learning Test (AFLT) is a visual memory assessment tool, constructed as an analog to the Rey Auditory Verbal Learning Test (RAVLT). The AFLT includes three sequences of abstract drawings as stimuli –a primary set which is repeated across five trials, an interference set, and a recognition set. After about twenty minutes, the test assesses free delayed recall (DR) and delayed recognition of the learned material. This test is very similar to the RAVLT in terms of administration; therefore, the present study will evaluate whether the predictive value of DR scores from both tests is comparable in relation to Tau PET. Method: Tau PET ([18F]‐MK6240) was acquired for 130 individuals for analysis involving only AFLT, 139 for analysis involving only RAVLT, and 127 individuals for analysis including both AFLT and RAVLT. Demographic data is shown on Tables 1, 2, and 3. 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. Voxel‐wise linear regression models were applied, using VoxelStats, with Tau PET as the dependent variable and either DR AFLT or DR RAVLT as predictors. We ran three analyses where one included both DR scores. Additionally, we corrected for age, sex, diagnosis, APOE, and amyloid load. All other variables that were tested did not significantly contribute to predict Tau PET. Result: We found negative associations between tau binding in the medial temporal lobe and both DR scores when looking at each of them separately. More importantly, we found that DR AFLT scores lose their predictive value when including DR RAVLT in the same model. Conclusion: Our results support the use of both tests interchangeably when testing memory in elderly populations, even though they tap into two different modalities. This piece of evidence confirms what was reported by the authors who published the original AFLT article. Nonetheless, that article dealt with a sample whose demographics and clinical presentation strongly differed from those of our sample. [ABSTRACT FROM AUTHOR]

Background: By obtaining a better grasp on the impact of the COVID‐19 pandemic on individuals with cognitive impairment, this knowledge could be used to improve the delivery of information to this particular group. We aimed to assess the relationship between tau deposition and the change in anxiety levels, before and during the pandemic. We hypothesized that since the pandemic, higher tau loads would lower the change in anxiety. Furthermore, we expected these anxiety levels not to be associated with COVID‐19 related stress in participants with cognitive decline. Methods: 63 participants of the Translational Biomarker of Aging and Dementia (TRIAD) cohort (cognitively healthy, N=38; cognitively impaired, N=25, of which 7 had dementia due to Alzheimer's disease), were assessed to evaluate their individual change in anxiety levels (GAD‐7). This was done at three different timepoints, of which the latest fell during the COVID‐19 lockdown period. Two rates of change, one before and one during the pandemic, were determined using the following definition: (next timepoint – current timepoint)/time difference. In addition, at the latest timepoint, subjective stress due to COVID‐19 was measured using the Montreal Assessment of Stress related to COVID‐19 (MASC). To assess the levels of tau, standard uptake value ratios (SUVR) from previously obtained [18F]MK‐6240 PET‐scans were used. Results: [18F]MK‐6240 tracer binding in the lingual gyrus was negatively associated with the rate of change in GAD‐7 scores after correcting for age, sex, years of education and the presence of APOE ε4, but only in cognitively impaired individuals during the pandemic (fig 1A). In addition, the GAD‐7 score at the latest timepoint was associated with stress related to COVID‐19, but only in cognitively healthy individuals (fig 1B and 1C). Conclusions: The presence of tau in the lingual gyrus negatively affected the rate of change in GAD‐7 scores during the COVID‐19 pandemic in individuals with cognitive impairment. This could indicate that information pertaining to the pandemic does not reach these individuals in an efficient manner. The missing association between COVID‐19 induced stress and the latest GAD‐7 scores in these individuals is a further indication of this. [ABSTRACT FROM AUTHOR]

Background: The role that sex plays in Alzheimer's disease (AD) has long been the subject of intense investigation. Considerable amount of literatures showed a disproportionally high prevalence of AD in women. Moreover, sex differences were observed in disease manifestation, rates of cognitive decline, cerebral atrophy, as well as the response to treatments, suggesting that sex serves as a crucial factor in the disease heterogeneity. APOE is the strongest genetic risk factor for sporadic AD, with the ε4 allele conferring increased risk. It was found that female ε4 carriers show stronger risk for clinical AD. Other studies showed that female ε4 carriers have higher p‐tau levels in cerebrospinal fluid and show worse memories than male ε4 carriers. Despite evidence supports APOE has a stronger association among women compared with men, limited work has evaluated the effects of ApoE4 on AD core neuropathology including amyloid, tau and microglial activation in a sex‐specific manner. Method: This was a cross‐sectional study in APOE ε4 carriers with AD (n=31), MCI (n=23), cognitively normal controls (n=47) and young healthy controls (n=9) from the TRIAD study at McGill University Research Centre for Studies in Aging, Canada. Cerebral amyloid load, tau neurofibrillary tangles and microglia activation were assessed using positron emission tomography (PET) radiopharmaceuticals [18F]AZD4694 ([18F]NAV4694), [18F]MK6240 and [11C]PBR28 respectively. Result: No significant difference was found in age, education and MMSE score between male and female subjects. Female ε4 carriers showed significant higher tau burden in hippocampus (P<0.01), entorhinal cortex (P<0.05) and parahippocampal cortex (P<0.05) compared to male ε4 carriers. A sex‐specific vulnerability for tau and neuroinflammation was observed. More specifically, in amyloid‐positive female ε4 carriers, higher tau burden was found to be strongly associated with worse cognitive function assessed by Mini‐Mental State Examination (MMSE). In addition, an positive correlation between amyloid load and microglial activation level was also identified in female APOE ε4 carriers. Conclusion: We provide striking evidence that female is more vulnerable for the effects of APOE ε4 on tau and neuroinflammation, suggesting APOE may modulate AD pathology in a sex‐specific manner, particularly in the presence of amyloidosis. [ABSTRACT FROM AUTHOR]

Background: Neuropsychological evaluations are normally assessed in‐person by a trained psychometrician using a variety of tests representing several domains. The COVID‐19 pandemic has obliged medicine and research to switch to online assessment. However, minimal research has tested the reliability of conducting cognitive evaluations online versus in‐person. This study aims to explore the clinical utility of virtually assisted neuropsychological evaluations in a comparative analysis following the effects of the COVID‐19 pandemic. Method: 62 cognitively unimpaired (CU) individuals from the TRIAD cohort underwent baseline and follow‐up neuropsychological assessments which included the Boston Naming Test (Short Form), BORB‐Object Recognition Task, WASI‐II Matrix Reasoning, WAIS‐III Digit Span, D‐KEFS Category Fluency Tests, Rey Auditory Verbal Learning Test (RAVLT), and Free & Cued Selective Reminding Test (FCSRT). Participants were considered CU when they obtained a CDR score of 0, MMSE ≥ 26, with negative amyloid‐β and tau statuses (global amyloid‐β [18F]AZD4694 <1.55 SUVR and temporal meta‐ROI [18F]MK6240 <1.24 SUVR). Participants were divided into two equally represented groups, both of which completed an in‐person baseline evaluation. 30 participants completed their follow‐up evaluation in‐person and 32 completed their evaluation virtually. A mixed linear regression model was used to assess the difference in the rate of change in scores between cohorts using age, sex, and years of education as covariates. Result: Follow‐up at‐home neuropsychological test results did not significantly differ from in‐person scores across all domains. Participant demographics are shown in table 1. The Boston Naming Test (Short Form), BORB‐Object Recognition Task, WASI‐II Matrix Reasoning, WAIS‐III Digit Span, D‐KEFS Category Fluency Tests, Rey Auditory Verbal Learning Test (RAVLT), and Free & Cued Selective Reminding Test (FCSRT) yielded p values of 0.47, 0.74, 0.17, 0.28, 0.13, 0.53, and 0.77, respectively. Conclusion: Scores from our battery were selected to represent the different cognitive domains. Based on our findings, there was no difference when individuals conducted in‐person versus online assessments. These results will allow for the geriatric community to receive the medical assistance they require without having to impose any inconveniences or unnecessary health risks. Additionally, virtual assessments will assist to increase contact for prospective participants which would otherwise not be possible in‐person. [ABSTRACT FROM AUTHOR]

Background: Amyloid‐β (Aβ) and tau are the two well‐recognised pathological hallmarks of Alzheimer's disease (AD). In the recent decades, increasing evidence supports neuroinflammation as one of the earliest pathomechanistic alterations throughout the AD continuum. However, little is known about the spatial and temporal patterns of neuroinflammatory processes based on AD pathological status. Furthermore, it also remains elusive how longitudinal change of neuroinflammation affects cerebral amyloid and tau load in the trajectory of AD. Method: We examined a total number of 122 subjects (mean age= 65.6 years, 66.4% women, 33.1% APOEɛ4 carriers) from the TRIAD cohort at McGill University Research Centre for Studies in Aging. Neuroinflammation, cerebral Aβ load and tau deposition were assessed with positron emission tomography (PET) radiotracers [11C]PBR28, [18F]AZD4694 ([18F]NAV4694) and [18F]MK6240 respectively. Amyloid‐β positivity was determined by a cortical composite [18F]NAV4694 SUVR threshold of 1.55, based on previously published method. Voxelwise analyses were performed to evaluate the relationships between cerebral amyloid load and neuroinflammation. A subgroup of 42 subjects who had underwent two‐year follow‐up PET scans were used to study how the longitudinal change of neuroinflammation affects other AD hallmarks. Result: At early stages of amyloid pathology, we found a positive linear relationship between neuroinflammation and amyloid load. Voxelwise analyses also revealed a stronger association between amyloid and neuroinflammation among the Aβ‐negative subjects. Longitudinally, the increase of neuroinflammation was linked to the accumulation of cerebral amyloid and tau in Aβ‐negative subjects. Conclusion: Neuroinflammation was associated with amyloid at early stages of amyloid pathology. In addition, elevation of neuroinflammation was associated with the increase of amyloid and tau accumulation in Aβ‐negative subjects. [ABSTRACT FROM AUTHOR]

Background: While fluid phosphorylated tau (pTau) epitopes are interpreted to be biomarkers of tau pathology according to the A/T/(N) framework, it is unclear to what extent they are preferentially associated with the defining histopathological hallmarks of Alzheimer's Disease (AD): amyloid‐β plaques and tau neurofibrillary tangles. Method: We studied 171 individuals, including young adults (n=27), cognitively unimpaired elderly (n=85), individuals with mild cognitive impairment (n=36) and individuals with Alzheimer's clinical syndrome (n=23), who were evaluated with [18F]AZD4694 amyloid‐PET, [18F]MK6240 tau‐PET, four tau phosphorylation sites in CSF (pTau181, pTau217, pTau231, pTau235) and two phosphorylation sites in plasma (pTau181, pTau231). To better understand the role of soluble biomarkers in AD diagnostic and research purposes, we evaluated associations between soluble pTau sites and cerebral amyloid‐PET and tau‐PET concentrations. Voxel‐wise linear regressions between fluid and imaging biomarkers were performed. Results for plasma and CSF pTau181 were replicated in an independent sample of 258 individuals included in the Alzheimer's Disease Neuroimaging Initiative cohort (ADNI). Result: We observed that for all plasma and CSF epitopes, pTau is more closely associated with amyloid‐PET than with tau‐PET. Squared correlation coefficients (Spearman's R2) between CSF pTau epitopes and neocortical [18F]AZD4694 SUVR range from 0.48 to 0.63, while those for the temporal meta‐ROI [18F]MK6240 SUVR vary between 0.33 and 0.45 (p<0.001 for all phosphorylation sites). Using the R package "Cocor", for CSF pTau181, pTau217 and pTau231 the difference in correlation coefficients between both measures of imaging biomarkers appear significant (p<0.01). Voxel‐wise linear regression analyses further support these results, in particular showing sizable associations for CSF pTau231 with amyloid‐PET. In addition, soluble pTau is more closely correlated with medial temporal than with neocortical tau. All soluble pTau concentrations rise significantly with increasing amyloid‐β plaque load. In contrast, soluble pTau plateau as tau‐PET concentrations increase, starting at Braak stage III. These findings were replicated using plasma and CSF pTau181 in the ADNI cohort. Conclusion: Phosphorylated tau epitopes measured in CSF and plasma better reflect cerebral amyloidosis than neurofibrillary tangles in the brain. The current findings support careful interpretation of fluid pTau concentrations when implementing the A/T/(N) framework. [ABSTRACT FROM AUTHOR]

Background: Microglial activation is an important component of the immune response in the brain of AD patients and has been shown to follow a similar propagation pattern to tau tangle accumulation. However, it is unclear to what extent cerebral microglial activation is associated with biofluid concentrations of phosphorylated tau (pTau). The objective was to investigate whether concentrations of pTau181 and pTau231 are correlated with microglial activation indexed by [11C]PBR28 PET across the AD spectrum. Method: The present study was conducted in a population of 130 individuals from the Translational Biomarkers of Aging and Dementia (TRIAD) cohort: 20 young cognitively unimpaired, 65 cognitively unimpaired elderlies, 31 with mild cognitive impairment and 14 with AD dementia. Participants were evaluated with blood biomarkers and [11C]PBR28 PET. Plasma pTau181 and pTau231 concentrations were quantified using a Simoa assay. Microglial activation was assessed via [11C]PBR28 PET, standardized uptake value ratios (SUVRs) were calculated between 0 and 90 minutes post‐injection, using cerebellum grey matter as the reference region. Voxel‐based regression models evaluated the relationship between plasma pTau181 and pTau231 with neuroinflammation as assessed by PET, correcting for age and sex. Result: In the present study, positive correlations were found between concentrations of both pTau181 and pTau231 and neuroinflammation indexed by PET‐imaging. Voxel‐level analyses indicated that these associations prenominated in regions of the default mode network including the precuneus, posterior cingulate cortex and medial prefrontal cortex. These regional associations survived corrections for multiple comparisons. Conclusion: Peripheral phosphorylated tau is associated with neuroinflammation in brain regions associated with AD. Our findings highlight the importance of neuroinflammation in the pathogenesis of AD. [ABSTRACT FROM AUTHOR]

Background: Aggie Figures Learning Test (AFLT) is a visual memory test that was conceived as an analogue of the widespread Rey Auditory Verbal Learning Test (RAVLT), which tests verbal memory. Previous research has indicated that performance may rely on the left medial temporal lobe (lMTL) for RAVLT and on the right medial temporal lobe (rMTL) for AFLT, although evidence is inconclusive. The present study looks into the association between delayed recall (DR) scores in both tests and tau binding in the brain. Method: Tau PET ([18F]‐MK6240) was acquired for 130 individuals for analysis involving AFLT, and 139 for analysis involving RAVLT. Demographic data is shown on Tables 1 and 2. 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. Voxel‐wise linear regression models were applied, using VoxelStats, with either DR AFLT or DR RAVLT as dependent variables and tau as a predictor. We corrected for age, diagnosis, and amyloid load. All other variables that were tested did not significantly contribute to predict DR scores. Results: We found negative associations between tau binding and DR RAVLT in the MTL bilaterally. Interestingly, we found a negative correlation between tau binding and DR AFLT scores that is remarkable in the rMTL and barely reaches significance in the lMTL. Conclusion: Our findings provide evidence in support of the lateralization of memory in the brain based on the learning modality. This dissociation is in line with previous findings; namely, that the rMTL is responsible for visual memory. However, these findings are not entirely in line with previous research since associations with RAVLT are found bilaterally. Of note, most of the previous research has been made in the context of epilepsy and/or patients with anterior MTL lesions. Here, however, we are investigating a totally different population and we are looking at a parameter that is specific to this population. [ABSTRACT FROM AUTHOR]

Background: Decline in executive function has been noted to precede other forms of cognitive decline in the prodromal stage of Alzheimer’s disease (Clark et al., 2011). The D‐KEFS Color‐Word Interference test (CWIT) is a cognitive test that measures executive function across several conditions. Few studies have explored the relationship between tau deposition and executive dysfunction. However, to date, no study has explored this relationship in prodromal AD. This study aimed at exploring such associations. Method: We looked at cognitively unimpaired and impaired elderly individuals from the TRIAD cohort in Montreal, QC who underwent neuropsychological evaluations across 2 time points. In vivo tau accumulation was assessed at baseline with [18F]‐MK6240 PET. Standardized uptake value ratio was calculated 90‐110 minutes post‐injection using cerebellar grey matter as the reference region. Voxel‐wise linear regression models were applied with the rate of change of CWIT condition 3 and 4 completion times as predictor variables with tau tracer binding being the response variable. Age, sex, education, Geriatric Depression Scale score, APOEε4, diagnostic group, and amyloid‐β status were included as covariates in regression models. Results were corrected for multiple comparisons using random field theory with a cluster threshold of p <.001. Result: A total of 105 (CN=65;MCI=36;AD=4) individuals were included in this analysis, with mean follow‐up time of neuropsychological evaluation being 15.9 months. We found that brain [18F]‐MK6240 uptake was correlated with change in D‐KEFS CWIT condition 3 and 4 completion times, with a greater pattern of association in condition 3 (inhibition). For condition 3, associations were strongest in the precuneus, posterior cingulate, and primarily right dorsal frontal and parietal regions. For condition 4 (flexibility), we found a strong association in the left temporal pole and left dorsal frontal regions. Conclusion: These results support previous claims that tau follows a distinct regional distribution similar to that of the dorsal attention network which is related to higher order cognitive function such an inhibition and switching (Hansson et al., 2017). Additionally, given that most individuals in this study were CN or MCI, our findings suggest that tau pathology is associated with a decrease in executive function even in prodromal stages of AD. [ABSTRACT FROM AUTHOR]

Background: Assessments of tau usually come from cerebrospinal fluid or Positron Emission Tomography (PET). However, those methods are expensive and not readily available. Current research is focusing on cost‐effective blood‐based biomarkers, and a novel immunoassay for plasma pTau181 has been created. Even though there are strong associations between plasma pTau181 and PET, no study has yet investigated whether plasma pTau181 can be used to detect early AD‐pathology. Does the status of plasma pTau181 always correlate with tau‐PET status? Method: We assessed 269 individuals from the TRIAD cohort (164 CU, 60 MCI and 45 AD) that underwent plasma pTau181 assessment, [18F]MK6240 tau‐PET scan, [18F]AZD4694 amyloid‐PET scan to assess their amyloid status, an MRI and a neuropsychological evaluation. We conducted statistical analyses using R, first to calculate the threshold values for positivity in both tau assessing methods and to make comparisons between the groups. For tau‐PET, we used [18F]MK6240 SUVR in the temporal meta‐ROI. Result: Using Receiver Operating Characteristic (ROC) curves, we established that the cut‐off for positivity for plasma pTau181 was 11.1060 pg/mL, while for tau‐PET, it was 1.1827 SUVR. 182 individuals had concordant statuses for both plasma pTau181 and tau‐PET, while 87 were discrepant. 64 were plasma+/PET‐, with a majority cognitively unimpaired (CU) and 23 were plasma‐/PET+, with values close to the thresholds, and mostly MCI or AD (Figure1). Moreover, concomitant plasma/PET statuses were usually accompanied by a similar Ab status (Figure2). CU Ab+ individuals were found in high proportion in the plasma+/PET‐ group (Figure3). Conclusion: Most of the participants had concordant statuses for plasma pTau181 and tau‐PET, which correlate well with memory scores and diagnoses. However, there was a significant portion of discordant individuals, which were predominantly plasma+/PET‐. This corroborates findings from comparisons between CSF pTau181 and tau‐PET, with CSF positivity coming before PET. Plasma pTau181 is also a great tool to assess Ab status, even before the onset of tau‐PET abnormalities. Assessing tau through plasma or PET is thought to suggest different stages of pathological progression. [ABSTRACT FROM AUTHOR]

Background: The natural history of Alzheimer's disease (AD) comprises a long preclinical stage characterized by pathological changes that start decades before symptoms arise. Despite that AD is defined based on the presence of amyloid‐β (Aβ) and tau pathology, increasing evidence supports neuroinflammation as one of the earliest pathomechanistic alterations throughout the AD continuum. Microglia and astrocytes are key cellular drivers and regulators of neuroinflammation. However, it remains unclear if there are patterns of spatial and temporal susceptibility to neuroinflammatory processes in the brain that may synergize with Aβ and tau accumulation, which drives neurodegeneration in a self‐reinforcing manner. Method: This was a cross‐sectional study examining a total number of 283 subjects from the TRIAD cohort at McGill University Research Centre for Studies in Aging, Canada. Cerebral amyloid and tau neurofibrillary tangles were assessed using positron emission tomography (PET) radiopharmaceuticals [18F]AZD4694 ([18F]NAV4694) and [18F]MK6240 respectively. Cerebrospinal fluid (CSF) biomarkers including Aβ42, Aβ40, phosphorylated tau (p‐tau), total tau (t‐tau), neurofilament light (NfL), soluble triggering receptor expressed on myeloid cells 2 (sTREM2), YKL40 and glial fibrillary acidic protein (GFAP) were also measured. Voxelwise analyses were performed to evaluate the relationships between cerebral amyloid load, tau burden and neuroinflammation biomarkers. Result: We modelled biomarker changes as a function of amyloid PET standardized uptake value ratio (SUVR) and tau PET SUVR as proxies of disease progression. The earliest changes observed in the AD continuum were the decrease in the Aβ42/40 ratio and the increases in astrocytic biomarkers CSF YKL40 and CSF GFAP. This is followed by a steep increase in CSF pTau231 and, to a lesser extent, CSF pTau217 and CSF pTau181. Voxelwise analyses revealed that YKL40 and GFAP are associated with amyloid and tau load in the brain, after accounting for age, sex, education and pathological status. Conclusion: Neuroinflammation involving astrocytic activation is altered very early in the Alzheimer's continuum and could be targeted as a promising biomarker. [ABSTRACT FROM AUTHOR]

Background: Monitoring pathophysiological stages of Alzheimer's Disease (AD) is important for understanding, forecasting and ultimately treating the disease. One prominent example of such staging is the spread of tau protein manifested in the stage‐wise accumulation of neurofibrillary tangles [1]. With the development of high‐affinity tau PET tracers, it is possible to track the protein accumulation in vivo [3]. Quantification of the spatial continuity of such spread longitudinally could help disentangle the tau propagation mechanism. Method: We introduce "Sub‐stages for Propagation Regions in Alzheimer's Disease" ("SPReAD") as a method to represent Braak stage related tau tracer uptake continuously as a spatial series. To achieve such mapping, we projected tau uptake data to surfaces [2] with discrete Braak stage parcels (Fig. 1, top left), and, by assigning vertex weights recursively according to the neighbourhood relationships of adjacent stages' regions, we made a sub‐stage map (Fig. 1, bottom left); then, we sampled average uptake values within these sub‐stages to obtain each subject's uptake profile. We validated SPReAD using [18F]MK6240 standardized uptake value ratio (SUVR) data from 20 AD subjects at 2 visits; 5 AD subjects at 3 visits; 2 AD subjects at 4 visits, with approximately 12‐month inter‐visit interval, all amyloid positive; Braak stage discordant cases were excluded. Result: The resulting sub‐stage profiles appeared highly correlated across visits for AD patients (r=0.9; p<0.01). The differences between baseline and follow‐up SUVRs were generally less prominent at the early stages, with especially significantly greater SUVR (p<0.05, two‐sample t‐test) at the follow‐up at the latest Braak stage for a given subject (Fig. 1, right shows two such subjects with Braak stage VI). Conclusion: The Braak sub‐stage profile representation using SPReAD helps identify changes within a given Braak stage and across the stages, both in terms of magnitude and spatial progression. It reduces surface manifold data into more interpretable spatial series, at the same time providing information on subtle between‐stage transitions which represents a novel systematic way to quantify tau propagation patterns. References: (1) Braak H & Braak E (1991) Acta Neuropathol 82:239‐59. (2) Lyttelton et al. (2007) Neuroimage 34:1535‐44. (3) Pascoal et al. (2020) Brain 143:2818‐30. [ABSTRACT FROM AUTHOR]

Background: Tau is usually assessed through cerebrospinal fluid or Positron Emission Tomography (PET). However, those methods are expensive and not readily available. Research is now focusing on cost‐effective blood‐based biomarkers to assess Alzheimer's disease (AD) pathophysiologies. A novel immunoassay for plasma pTau181 has been created, and even though there are strong associations between plasma pTau181 and PET, no study has yet investigated which cortical area better reflects plasma tau. Method: We assessed 269 individuals from the TRIAD cohort (164 CU, 60 MCI and 45 AD) that underwent plasma pTau181 assessment, [18F]MK6240 tau‐PET scan, [18F]AZD4694 amyloid‐PET scan to assess their amyloid‐b (Ab) status, an MRI and a neuropsychological evaluation. We conducted statistical analyses using R, first to calculate the threshold values for positivity in both tau assessing methods and to make comparisons between the groups. SUVR values for [18F]MK6240 were either based on Braak1 SUVR or temporal meta‐ROI SUVR. Result: Using Receiver Operating Characteristic (ROC) curves, we established that the cut‐off for positivity for plasma pTau181 was 11.1060 pg/mL. When using Braak1 mask, the cut‐off for positivity was 1.040 SUVR (B1+/‐), while with temporal meta‐ROI it was 1.1827 (TMR+/‐). In both cases, we observed a majority of concordant individuals. However, we obtained 87 discordant individuals in the plasma/TMR, mostly plasma+/TMR‐, and 78 in the plasma/B1 analyses, mostly plasma‐/B1+ (Figure 1). Concomitant status of plasma/TMR was usually accompanied by a similar Ab status. However, in the Braak1 analyses, Ab status seemed to closely follow the PET status (Figure 2). Conclusion: The cut‐off values for positivity using Braak1 mask is significantly smaller than when using temporal meta‐ROI. Using the temporal meta‐ROI mask, we had more discrepant individuals that were plasma+/TMR‐, with plasma‐/TMR+ individuals close to the threshold values. It was accurate at predicting negative biomarker statuses in CU participants, and positive in AD participants. Conversely, we had more plasma‐/B1+ individuals when using Braak1 mask, with values more spread around the plot. Due to low threshold values, portion of CU and MCI individuals were categorized as positive to both biomarkers. Finally, B1 status seemed to follow closely the Ab levels. Plasma pTau181 thus seems to reflect better temporal meta‐ROI tau. [ABSTRACT FROM AUTHOR]

Background: Understanding sex dimorphism in neurodevelopment and neurodegeneration is imperative for therapeutic strategy, clinical trial enrichment, and personalized medicine. However, the cellular underpinning of sex dimorphism in Alzheimer's disease (AD) pathophysiology is still poorly understood. Here, we aimed to investigate the effect of sex on microglial activation and its effect on cognition using the major targets of AD clinical trials – amyloid ([18F]AZD4694), tau ([18F]MK6240), and neuroinflammation ([11C]PBR28) – through a multimodal PET study in humans and rats. Method: A total of 108 participants (70 CN, 25 MCI, and 13 AD; 36 M, 72 F) with a high‐affinity binder for TSPO from the TRIAD cohort underwent 3 PET scans and MMSE for cognitive assessment. Static [18F]AZD4694, [18F]MK6240, and [11C]PBR28 SUVR images were generated. All PET images were normalized to the ADNI template, used cerebellar grey as a reference region. Furthermore, 29 rats (8 WT, 21 Tg; 13 M, 16 F) underwent a 60‐min dynamic [18F]AZD4694 and [11C]PBR28 PET scans. All PET images were normalized to the average template. [18F]AZD4694 and [11C]PBR28 BPND were quantified based on SRTM method using Pons and midbrain as a reference region, respectively. The sex effect on neuroinflammation is evaluated based on a linear regression model in humans and rats. Consequently, sex dimorphism induced neuroinflammation effect on cognition was assessed using MMSE. All the models were corrected for age, APOE, education, amyloid and tau status. Result: In this study, females showed greater [11C]PBR28 binding in basal temporal regions in humans and parietotemporal cortex, hippocampus, and basal forebrain in rats. Consequently, greater neuroinflammation in females showed negative effects on MMSE but not in males, p = 0.033. Conclusion: This study demonstrated the greater microglia activation in females compared to males. Considering the difference in the microglia reaction to amyloidosis in rodents compared to humans, the increased microglial activation effect on cognition was only assessed in humans. Here, microglial sex dimorphism showed deleterious effects on cognition only in females. This study highlights the difference in microglial reactivity leading to greater vulnerability to cognitive decline in females. As such, it is imperative to explore a sex‐specific therapeutic strategy for AD clinical trial. [ABSTRACT FROM AUTHOR]

Background: Reduction in grey matter (GM) is a well‐established neuroimaging finding in Alzheimer's disease (AD). Here, we sought to determine whether baseline tau‐PET using the high‐affinity tracer [18F]MK6240 is predictive of longitudinal changes in GM across the AD spectrum. Method: Baseline [18F]MK6240 PET data and longitudinal structural MRI was acquired for 79 participants in the TRIAD cohort (47 CN, 20 MCI, 12 AD). [18F]MK6240 standardized uptake value ratio (SUVR) were calculated 90‐110 minutes post‐injection using cerebellar GM as the reference region. T1‐weighted MR images were segmented into probabilistic GM and WM maps, which were non‐linearly registered to the ADNI template using DARTEL and smoothed with an 8mm FWHM Gaussian kernel. Voxel‐based morphometry (VBM) was run on GM and WM maps. Longitudinal changes in GM density were indexed by voxel‐wise percentage change in VBM‐derived GM. Voxel‐based regression analyses were conducted to examine associations between baseline [18F]MK6240 SUVR and change in GM density, with age, gender, years of education, diagnosis, and time interval between MRI acquisitions employed as covariates. Result: Baseline [18F]MK6240 SUVRs in Braak I/II, III/IV, and V/VI were significantly correlated with longitudinal decrease in GM density in the lateral and medial temporal lobe, including hippocampal regions. All results survived correction for multiple comparisons using random field theory at p < 0.001. Conclusion: Our results suggest that tau pathology at baseline is associated with the progression of GM atrophy over time in brain regions vulnerable to AD pathological changes, providing evidence that tau‐PET may identify individuals who are more susceptible to atrophy. [ABSTRACT FROM AUTHOR]