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

ObjectiveTo identify the pathophysiologic mechanisms and clinical significance of anosognosia for cognitive decline in mild cognitive impairment.MethodsWe stratified 468 patients with amnestic mild cognitive impairment into intact and impaired awareness groups, determined by the discrepancy between the patient and the informant score on the Everyday Cognition questionnaire. Voxel-based linear regression models evaluated the associations between self-awareness status and baseline β-amyloid load, measured by [18F]florbetapir, and the relationships between awareness status and regional brain glucose metabolism measured by [18F]fluorodeoxyglucose at baseline and at 24-month follow-up. Multivariate logistic regression tested the association of awareness status with conversion from amnestic mild cognitive impairment to dementia.ResultsWe found that participants with impaired awareness had lower [18F]fluorodeoxyglucose uptake and increased [18F]florbetapir uptake in the posterior cingulate cortex at baseline. In addition, impaired awareness in mild cognitive impairment predicted [18F]fluorodeoxyglucose hypometabolism in the posterior cingulate cortex, left basal forebrain, bilateral medial temporal lobes, and right lateral temporal lobe over 24 months. Furthermore, participants with impaired awareness had a nearly 3-fold increase in likelihood of conversion to dementia within a 2-year time frame.ConclusionsOur results suggest that anosognosia is linked to Alzheimer disease pathophysiology in vulnerable structures, and predicts subsequent hypometabolism in the default mode network, accompanied by an increased risk of progression to dementia. This highlights the importance of assessing awareness of cognitive decline in the clinical evaluation and management of individuals with amnestic mild cognitive impairment.

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] [...]

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]

INTRODUCTION: Blood biomarkers have proven useful in Alzheimer's disease (AD) research. However, little is known about their biological variation (BV), which improves the interpretation of individual‐level data. METHODS: We measured plasma amyloid beta (Aβ42, Aβ40), phosphorylated tau (p‐tau181, p‐tau217, p‐tau231), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL) in plasma samples collected weekly over 10 weeks from 20 participants aged 40 to 60 years from the European Biological Variation Study. We estimated within‐ (CVI) and between‐subject (CVG) BV, analytical variation, and reference change values (RCV). RESULTS: Biomarkers presented considerable variability in CVI and CVG. Aβ42/Aβ40 had the lowest CVI (≈ 3%) and p‐tau181 the highest (≈ 16%), while others ranged from 6% to 10%. Most RCVs ranged from 20% to 30% (decrease) and 25% to 40% (increase). DISCUSSION: BV estimates for AD plasma biomarkers can potentially refine their clinical and research interpretation. RCVs might be useful for detecting significant changes between serial measurements when monitoring early disease progression or interventions. Highlights: Plasma amyloid beta (Aβ42/Aβ40) presents the lowest between‐ and within‐subject biological variation, but also changes the least in Alzheimer's disease (AD) patients versus controls.Plasma phosphorylated tau variants significantly vary in their within‐subject biological variation, but their substantial fold‐changes in AD likely limits the impact of their variability.Plasma neurofilament light chain and glial fibrillary acidic protein demonstrate high between‐subject variation, the impact of which will depend on clinical context.Reference change values can potentially be useful in monitoring early disease progression and the safety/efficacy of interventions on an individual level.Serial sampling revealed that unexpectedly high values in heathy individuals can be observed, which urges caution when interpreting AD plasma biomarkers based on a single test result. [ABSTRACT FROM AUTHOR]

Background: Blood biomarkers have gained much attention in recent years given their increasing ability to indicate amyloid pathology and excellent performance in distinguishing diagnostic groups in the context of Alzheimer's disease (AD). Plasma pTau217 has been considered the best candidate biomarker to serve as diagnostic and prognostic tool for clinical trials. However, biomarker assays targeting tau phosphorylation on Thr217 may differ because of their composition (e.g., targeting multiple or single phosphorylation sites) which may lead to distinct associations with pathology. Thus, we aimed to compare two plasma pTau217 immunoassays that differ in regard to their target specificity. Method: Participants from the TRIAD cohort with available cross‐sectional plasma and imaging data, incorporating within the AD spectrum, were included in this study (Young = 25;CU‐ = 107;CU+ = 32;MCI+ = 42;AD+ = 47;MCI‐ = 19). Plasma pTau was quantified using the assays from Janssen (pTau217+; which exhibits enhanced signal with co‐phosphorylation of pTau212) and from ALZpath (single phosphorylation on pTau217), both performed on the Simoa platform. Amyloid and tau pathologies were indexed by PET using [18F]AZD4694 and [18F]MK6240, respectively. ANCOVA compared biomarker values across groups, Spearman rank tested the correlations between them. Linear regression models (LM) evaluated the association between plasma and PET biomarkers globally and at the voxel level. Result: Biomarker levels (fold mean of CU‐) were comparable across diagnostic groups, showing the expected increases in amyloid positive groups. Both plasma assays were highly correlated with amyloid (Fig.1), which was also observed on the LM adjusted by age and sex, and on the voxel‐wise analysis (Fig.2). Associations with tau PET SUVR (medial temporal) were also significant and showed similar distribution between the two pTau assays. When neocortical tau was evaluated, however, pTau217+ had a better association as well as higher correlation coefficients within amyloid+ (Fig.3) and neocortical tau+ groups than did ALZpath pTau217. Conclusion: In general, pTau217 assays with different antibody specificity showed very similar associations with PET. However, pTau217+ achieved a better association with neocortical tau as compared to ALZpath pTau217. A biomarker targeting multiple phosphorylation sites might be a better proxy of advanced tau, therefore may offer improved ability to detect and exclude participants with advanced AD pathology for clinical trials. [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: Previous studies have shown that microglial activation (MA) plays a key role in the pathophysiological and clinical progressions of Alzheimer's disease (AD). However, little is known whether MA is also associated with the development of neuropsychiatric symptoms typically found in patients with AD. Thus, we aim to investigate here the association of MA with neuropsychiatric symptoms (NPS) of individuals across 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 (Figures 1A, 1B, 1C). This association was independent of Aβ and tau levels (Table 1). Notably, MA predicted neuropsychiatric dysfunction with higher magnitude than Aß or tau using PET values from overlap region (regional SUVR) and if we use a global measure for all tracers (global SUVR) (Figure 2A). 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 2B). Conclusion: Our results suggest MA as a key element associated with neuropsychiatric dysfunction in AD independent of Aβ and tau pathologies. These findings provide additional rationale for the therapeutics targeting glial cells activation in AD patients. [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 ATN classification system assumes a sequential model of disease progression. However, there are groups of individuals in the same ATN category that exhibit a predominance of abnormality (higher burden) of one of the biomarkers, creating heterogeneous ATN groups regarding pathological predominance. Thus, we tested the hypothesis that individuals clustered by ATN biomarker abnormality predominance may offer an alternative to groups defined using biomarkers cut‐offs. Method: We assessed 103 cognitively impaired individuals(CDR> = 0.5) from the TRIAD cohort with available measures of plasma phosphorylated tau‐181, brain MRI, amyloid PET, and tau PET. We used the K‐means algorithm to stratify participants into three clusters. We compared the clusters on composite measures of memory, executive functioning, language, and visuospatial processing. To examine the utility of the discovered clusters, we compared them to traditional ATN categories in the prediction of neuropsychological measures. We did so by creating three categories: patients positive on all three ATN biomarkers, patients positive on two of the three biomarkers, and patients positive on either one or none. Additionally, we created an inflammation, amyloid and tau deposition probabilistic map anchored on young controls(n = 51, mean age = 23.74). Results: We uncovered 3 clusters: an amyloid predominant (AP) cluster, a tau/phosphor‐tau predominant cluster (TP), and a cluster showing no predominance with low levels on all biomarkers (CN)(figure 1). Notably, levels of neurodegeneration and inflammation were similar between the AP and TP clusters. The AP cluster significantly differed from the CN cluster in memory only. Participants in the TP cluster had significantly lower scores in memory, executive functioning, language, and visuospatial processing than the other two clusters. In comparison, using threshold‐based ATN groups showed milder differences in memory and executive functioning, and no differences in language and visuospatial processing(figure 2). Furthermore, cluster membership moderated the relationship between various biomarkers, to the point of reversing the direction of correlation(figure 3). Conclusion: Our results highlight the biological heterogeneity present within the Alzheimer's disease continuum and that the pathological predominance of amyloid and tau is associated with different disease phenotypes. Approaching dementia patients with an eye on the predominance of pathology rather than cutoffs for abnormality may provide a better understanding of AD pathological subtypes. [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]

Background: Healthy synapses are the key to proper brain function, ensuring communication between neurons. Recent studies have associated synaptic dysfunction with Alzheimer's disease (AD) proteins, however, little is known about the role of glial reactivity, another pathology closely linked to AD, in brain synaptic dysfunction (Figure 1). Method: We evaluated 123 individuals (67 cognitively unimpaired (CU) and 56 cognitively impaired (CI)) who had available Aβ‐ and Tau‐PET as well as cerebrospinal fluid measures of glial fibrillary acidic protein (GFAP), chitinase‐3‐like protein 1 (YKL‐40), soluble triggering receptor expressed on myeloid cells 2 (sTREM2), synaptic markers (growth‐associated protein 43 (GAP‐43), neurogranin (Ng), synaptotagmin 1 (SYT1), and presynaptic protein synaptosomal‐associated protein 25 (SNAP‐25)). ANCOVA adjusted for clinical diagnosis, age, and sex was used to compare levels of CSF biomarkers; whereas linear regressions adjusted for age, sex, clinical diagnosis, and Aβ/tau‐PET were used to test the associations between glial reactivity and synaptic markers. Result: Demographic information is shown in Table 1. Increased levels of GAP‐43, SNAP‐25, and Ng were observed in CI compared to CU individuals. CSF GFAP was highly associated with both presynaptic and postsynaptic biomarkers in CU and CI groups. CSF YKL‐40 was associated only with presynaptic biomarkers in both clinical groups. On the other hand, CSF sTREM2 showed an association with all synaptic markers but only in the CI group (Figure 2). Conclusion: We found a heterogeneous association between synaptic markers and glial activation. The presence of GFAP+ astrocytes was associated with dysfunction of presynaptic/postsynaptic markers, whereas YKL‐40+ astrocytes specifically reflected presynaptic dysfunction across aging and AD spectrums. On the other hand, microglial activation reflected synaptic dysfunction associated with dementia symptoms. Our results support recent experimental observations suggesting that clarifying the heterogeneity of different glial cell phenotypes is crucial to advancing our understanding of the role of immune cells in cognitive decline. [ABSTRACT FROM AUTHOR]

Background: Tau plays a prominent role in the synapse and has been shown to be closely related to neurodegeneration. Recent evidence show that cerebrospinal fluid (CSF) synaptic markers are related to CSF tau and degeneration. However, it is not clear whether synaptic dysfunction in combination with tau tangles is associated with neurodegeneration in the same brain regions. Our study aims to map in the brain the association of synaptic markers with tau and degeneration. Method: We evaluated 147 individuals from the TRIAD cohort with CSF GAP43, SYT1, SNAP25, neurogranin (Ng), ptau217, neurofilament light protein (NfL) quantification, as well as tau positron emission tomography (PET), magnetic resonance imaging, and clinical assessments. One‐way ANOVA tested group differences on synaptic levels. Spearman correlation tested the association among synaptic proteins. Linear regressions tested the association between biomarkers. Voxel‐based morphometry (VBM) was considered as an index of neurodegeneration. Result: We observed an increase in synaptic markers across age and the AD spectrum, reaching a plateau when cognition is affected (Figure 1A). Among the synaptic markers, SNAP25 showed the greatest magnitude of change, on average, between young, aged cognitively unimpaired, mild cognitive impaired, and AD individuals (mean 62.44%). (Figure 1B‐C). In addition, we found that all synaptic markers are significantly intercorrelated (Figure 1D). Moreover, CSF ptau217 correlated with all synaptic biomarkers, GAP43 (β = ‐044), SYT1 (β = ‐0.41), SNAP25 (β = ‐0.59) and Ng (β = ‐0.25). Conversely, CSF NfL was strongly but only correlated with GAP43 (β = 0.62) (Figure 2). Voxel‐wise correlation revealed that tau tangles measured by [18F]‐MK6240 PET, was positively associated with SNAP25 in AD‐related regions, and VBM was associated with all synaptic markers, but more closely with GAP43. Furthermore, the interaction between synaptic markers and temporal meta‐ROI [18F]‐MK6240 on VBM was significant for Ng and GAP43 (Figure 3). Conclusion: Our results support a heterogenous role of synaptic markers in the AD continuum and suggest that synaptic dysfunction in the presence of tau pathology may not be driving atrophy. [ABSTRACT FROM AUTHOR]

Background: Whether plasma biomarkers steadily increase during the preclinical stage of Alzheimer's disease (AD) is unknown. Herein, we aimed to determine the rate‐of‐change of plasma biomarkers throughout preclinical AD. This may be important to determine the optimal time window for treatment. Method: We included baseline and follow‐up plasma biomarkers measurements (follow‐up: 3.37±0.40 years) of 240 cognitively unimpaired participants of the ALFA+ cohort (mean age: 60.75±4.85 years). Plasma Aβ40, Aβ42, GFAP and NfL were measured with the Simoa N4PE Advantage Kit, and plasma p‐tau231 with a Simoa‐validated in‐house assay. For each participant we calculated the difference between follow‐up and baseline levels, and corrected for sex, time between measurements, and age. We computed z‐scores from the corrected values, and we applied a bootstrapped regression approach to model the rate‐of‐change of each plasma biomarker as a function of baseline age or Aβ PET centiloids (CL). Moreover, we also computed the plasma biomarkers rate‐of‐change in three stages of preclinical AD: (I) CSF/PET Aβ‐negative group, (II) CSF Aβ‐positive/PET Aβ‐negative (CL < 30), and (III) CSF/PET Aβ‐positive. Significance was determined if the 95% confidence interval of the rate‐of‐change did not overlap with zero. Result: Significant acceleration in the rate‐of‐change of plasma GFAP was observed with ageing (Fig. 1), becoming significant at 60 years. There was also a significant accelerated change of p‐tau231 from 55 to 68 years. Plasma NfL was the only biomarker whose rate‐of‐change accelerated with Aβ accumulation, and that rate became significant at 40CL (Fig. 2). Consistently, we observed a significant acceleration of plasma NfL when there was overt Aβ pathology (CSF/PET Aβ‐positive group; Fig. 3) The rest of plasma biomarker rates‐of‐change did not significantly increase, some were even deaccelerating (plasma Aβ42/40 and p‐tau231), as Aβ accumulated (Fig. 2 and 3). Conclusion: Plasma biomarkers rate‐of‐change throughout the preclinical AD continuum differ. Plasma NfL rate‐of‐change accelerates in the later stage of preclinical AD, when overt Aβ pathology is present. The deceleration on the rate‐of‐change of plasma Aβ42/40 and p‐tau231 may explain why their early increase in the preclinical AD continuum tends to plateau in later stages. [ABSTRACT FROM AUTHOR]

Background: Astrocyte reactivity is a common finding in individuals across the Alzheimer's disease (AD) continuum. Recently, we demonstrated that individuals with higher levels of plasma glial fibrillary acidic protein (GFAP), a marker of astrocyte reactivity, present a stronger association between amyloid‐β (Aβ) and tau pathologies in preclinical AD. Because cohort studies and clinical trials show sex differences in AD biomarkers, we investigated whether the effects of astrocyte reactivity on the association between Aβ and tau differs in men and women Method: We assessed 1,016 CU individuals from three cohorts with available Aβ (plasma/PET), plasma p‐tau181 and GFAP measures. A subset of individuals also has plasma p‐tau217 available (n = 136).Individuals were classified as positive (Ast+) or negative (Ast‐) for astrocyte reactivity using a cutoff based on plasma GFAP of younger Aβ‐ individuals.Linear regressions accounting for age and sex were used to evaluate the association between plasma p‐tau epitopes and Aβ burden.An interaction between term between Aβ*sex was also added to the models.Voxel‐wise associations between biomarkers were tested using linear regressions accounting for age, sex, and adjusting for multiple comparisons. Result: We found that Aβ burden was associated with plasma p‐tau in Ast+ but not in Ast‐. Men in the Ast+ group presented a much increased association between Aβ with plasma p‐tau181 (β = 0.71,p<0.0001,Fig.1a) or p‐tau217 (β = 1.23,p = 0.00086,Fig.1b) compared to women. Similarly, a significant interaction between Aβ and sex on plasma p‐tau181 (β = 0.47,p = 0.005,Fig1a) and p‐tau217 (β = 1.01,p = 0.002,Fig.1b) was observed only in the Ast+ individuals. Voxel‐wise analysis showed the differences in the topographical association between Aβ and plasma p‐tau epitopes between men and women. In men but not women, Aβ‐PET associates with plasma p‐tau181 (Fig.2) and plasma p‐tau217 (Fig.3) in important AD regions such as precuneus, posterior cingulate and orbitofrontal cortex. Conclusion: A sex effect was observed in the association between Aβ burden and plasma p‐tau epitopes in individuals with increased astrocyte reactivity, with the association being stronger in men than women. The greater effect of Aβ on tau phosphorylation in the presence of Ast+ in men than in women may have implications for interpretation of biomarkers in clinical trials testing as anti‐Aβ therapies already showed different effects between men and women. [ABSTRACT FROM AUTHOR]

Background: A significant percentage of Aβ‐positive cognitively unimpaired (CU) individuals do not develop detectable downstream tau pathology and, consequently, cognitive decline.Experimental literature suggest that reactive astrocytes are necessary to unleashing Aβ effects in pathological tau phosphorylation.Here we aimed to investigate whether astrocyte reactivity is key to determining the association of Aβ burden with early tau phosphorylation in preclinical Alzheimer's disease (AD). Method: We assessed 1,016 CU individuals from two research and one population‐based cohort (TRIAD, Pittsburgh and MYHAT) with Aβ (plasma or PET), plasma p‐tau and GFAP measures. Individuals were classified as positive (Ast+) or negative (Ast‐) for astrocyte reactivity using a cutoff based on plasma GFAP of younger Aβ‐ individuals.Lowess method and linear regressions accounting for age and sex were used to model the trajectories of plasma p‐tau epitopes as a function of Aβ burden. Cohen's d corrected for age and sex was used to estimate effect sizes between groups. Result: We observed that plasma p‐tau181 levels increased as a function of Aβ only in CU Ast+ individuals from Pittsburgh (β = ‐0.35,t = 3.10,p = 0.003,Fig.1a,b), MYHAT (β = ‐0.20,t = 2.26,p = 0.026, Fig.1d,e) and TRIAD (β = 0.46,t = 2.92,p = 0.004;Fig.1g,h) cohorts. A significant interaction between Aβ burden and astrocyte reactivity status on plasma p‐tau181 levels was observed in the Pittsburgh (β = ‐0.29,t = 2.30,p = 0.022;Fig.1b), MYHAT (β = ‐0.19,t = 2.07,p = 0.038;Fig.1e) and TRIAD (β = 0.46,t = 2.92,p = 0.004;Fig.1h) cohorts.Cohen's d analysis revealed that the presence of Aβ+ and Ast+ has a large magnitude of effect on tau phosphorylation (Cohen's d:Pittsburgh = 0.67; MYHAT = 0.69;TRIAD = 0.98;Fig.1c,f,i), whereas Aβ+ in the absence of Ast+ presented a negligible effect size. Similar results were observed for plasma p‐tau231 and p‐tau217.Voxel‐wise analysis confirmed that Aβ levels in brain regions known to present early Aβ accumulation in AD associated with plasma p‐tau181 only in Ast+ individuals (Fig.2).Tau‐PET deposition occurred as a function of Aβ burden only in CU Ast+ (Fig.3a), affecting 100% and 62% of the extension of the Braak I and II regions, respectively (Fig.3b) Conclusion: We observed biomarker evidence across multiple cohorts that the presence of astrocyte reactivity, measured by plasma GFAP, plays a key role in the association of Aβ with early tau pathology in preclinical AD.Our results might have implications for the biological definition of preclinical AD and selecting individuals for early preventive clinical trials. [ABSTRACT FROM AUTHOR]

Background: It has been suggested that phosphorylated tau(p‐tau) at threonine 231 and 217 are markers of amyloid‐β(Aβ) rather than tau pathology. However, most of the studies were conducted in cohorts composed mainly of preclinical Alzheimer Disease(AD) individuals. It remains to be elucidated if p‐tau is still more associated with Aβ than tau pathology in symptomatic individuals. Here, we evaluate the contribution of each plasma biomarker to the demographics in identifying brain Aβ and tau pathologies across the AD spectrum. Method: We evaluated 138 cognitively unimpaired(CU) and 87 cognitively impaired(CI) individuals with available Aβ[18F]AZD4694 PET and tau[18F]MK‐6340 PET, plasma Aβ42/40, p‐tau (at threonine 181, 217, and 231), neurofilament light chain, and glial fibrillary acidic protein(GFAP), from the McGill TRIAD cohort(Table1). The performance of plasma biomarkers in predicting Aβ‐ and tau‐PET abnormalities over that one provided by demographics‐only(age and sex) was evaluated using logistic and linear regression, receiver operating characteristic analysis, and goodness‐of‐fit metrics. Using voxel‐wise linear regression models, we assessed the brain regions where plasma biomarker contribution to the demographic‐only model overlapped to detect Aβ and tau‐PET signals. Result: Our results demonstrated that in the CU only plasma p‐tau231 and p‐tau217+ significantly added to the demographics‐only model to detect Aβ pathology(Figure 1A), while no plasma biomarker added information to identify tau pathology(Figure 1B). In the CI, plasma p‐tau217+ and GFAP significantly added to the demographic‐only model to identify tau and Aβ pathology(Figure 1C), while p‐tau231 only added to detect tau deposition(Figure 1D). P‐tau181, Aβ42/40, and NfL did not significantly add to the demographics‐only in CU or CI group (Figure 1). Voxel‐wise analysis demonstrated that in CU, p‐tau231 and p‐tau217+ were only regionally associated with Aβ‐PET(Figure 2A‐C). In CI, p‐tau231 provided additional information on tau tangle accumulation in AD‐related regions(Figure 2D). On the other hand, for p‐tau217+, 3% of brain regions were only associated with Aβ‐PET, 35% with only tau‐PET, and 39% overlapped with both(Figure 2E). Conclusion: Our results support plasma p‐tau231 and p‐tau217+ as state markers of Aβ deposition in preclinical AD. In CI, plasma p‐tau231 is mainly related to tau pathology, and p‐tau217+ appears to be linked to both Aβ and tau pathology. [ABSTRACT FROM AUTHOR]

Background: Tau plays a prominent role in the synapse and has been shown to be closely related to neurodegeneration. Recent evidence show that cerebrospinal fluid (CSF) synaptic markers are related to CSF tau and degeneration. However, it is not clear whether synaptic dysfunction in combination with tau tangles is associated with neurodegeneration in the same brain regions. Our study aims to map in the brain the association of synaptic markers with tau and degeneration. Method: We evaluated 147 individuals from the TRIAD cohort with CSF GAP43, SYT1, SNAP25, neurogranin (Ng), ptau217, neurofilament light protein (NfL) quantification, as well as tau positron emission tomography (PET), magnetic resonance imaging, and clinical assessments. One‐way ANOVA tested group differences on synaptic levels. Spearman correlation tested the association among synaptic proteins. Linear regressions tested the association between biomarkers. Voxel‐based morphometry (VBM) was considered as an index of neurodegeneration. Result: We observed an increase in synaptic markers across age and the AD spectrum, reaching a plateau when cognition is affected (Figure 1A). Among the synaptic markers, SNAP25 showed the greatest magnitude of change, on average, between young, aged cognitively unimpaired, mild cognitive impaired, and AD individuals (mean 62.44%). (Figure 1B‐C). In addition, we found that all synaptic markers are significantly intercorrelated (Figure 1D). Moreover, CSF ptau217 correlated with all synaptic biomarkers, GAP43 (ß = ‐044), SYT1 (ß = ‐0.41), SNAP25 (ß = ‐0.59) and Ng (ß = ‐0.25). Conversely, CSF NfL was strongly but only correlated with GAP43 (ß = 0.62) (Figure 2). Voxel‐wise correlation revealed that tau tangles measured by [18F]‐MK6240 PET, was positively associated with SNAP25 in AD‐related regions, and VBM was associated with all synaptic markers, but more closely with GAP43. Furthermore, the interaction between synaptic markers and temporal meta‐ROI [18F]‐MK6240 on VBM was significant for Ng and GAP43 (Figure 3). Conclusion: Our results support a heterogenous role of synaptic markers in the AD continuum and suggest that synaptic dysfunction in the presence of tau pathology may not be driving atrophy. [ABSTRACT FROM AUTHOR]