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

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

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

Background: 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: Neuroinflammation typically involves the activation of microglial cells in the brain and has been linked to Alzheimer's disease (AD) pathology. However, how microglial activation influences brain neurodegeneration in individuals across the AD continuum is still poorly understood. Here, we aimed to investigate the influence of microglial activation in longitudinal brain atrophy in individuals across the AD continuum. We hypothesize that high levels of regional brain inflammation predict widespread brain atrophy. Method: We assessed 95 individuals from the TRIAD cohort (60 cognitively unimpaired and 35 cognitively impaired) with available [11C]PBR28‐PET, a measure of microglial activation, and a 2‐year longitudinal MRI (mean = 2.07 years). We generated grey matter voxel‐based morphometry (VBM) images using SPM12 and DARTEL, smoothed with a Gaussian kernel of full‐width half maximum of 8mm. We built the uncorrected (p < 0.05) association matrix between the [11C]PBR28‐PET SUVR and longitudinal VBM ROIs (z‐score) with the β‐estimates from linear regressions accounting for age, sex, and diagnosis. We divided the [11C]PBR28‐PET levels into terciles (low, intermediate, and high) to generate the averages of longitudinal VBM changes. Result: Baseline ROI‐based [11C]PBR28‐PET levels associate with longitudinal brain atrophy not only locally but also in distinct brain regions (Fig 1a). After FDR‐correction, the inferior temporal cortex was the region where [11C]PBR28‐PET levels were better associated with widespread longitudinal brain atrophy (Fig. 1b). Brain atrophy was observed in AD‐related regions, including the amygdala, insula, and the superior temporal cortex, independently of global amyloid load and tau (Fig. 1b). Accordingly, individuals with higher [11C]PBR28‐PET levels in the inferior temporal cortex presented increased longitudinal brain atrophy compared to individuals with lower [11C]PBR28‐PET (Fig. 1c). Conclusion: We identified increased baseline [11C]PBR28‐PET levels in the inferior temporal cortex that were highly associated with longitudinal brain atrophy in individuals across the AD continuum. Our results demonstrated that higher levels of inflammation in key brain regions could predict widespread longitudinal brain atrophy, suggesting that microglial activation has a detrimental impact on AD‐related neurodegeneration progression. [ABSTRACT FROM AUTHOR]

Background: To investigate the association of plasma pTau181, assessed with a new immunoassay, with neurodegeneration of white matter and gray matter cross-sectionally and longitudinally, in aging and Alzheimer's disease. Methods: Observational data was obtained from the Alzheimer's Disease Neuroimaging Initiative, in which participants underwent plasma assessment and magnetic resonance imaging. Based on their clinical diagnosis, participants were classified as cognitively unimpaired and cognitively impaired. Linear regressions and linear mixed-effect models were used to test the cross-sectional and longitudinal associations between baseline plasma pTau181 and neurodegeneration using voxel-based morphometry. Results: We observed a negative correlation at baseline between plasma pTau181 and gray matter volume in cognitively unimpaired individuals. In cognitively impaired individuals, we observed a negative association between plasma pTau181 and both gray and white matter volume. In longitudinal analyses conducted in the cognitively unimpaired group, plasma pTau181 was negatively correlated with gray matter volume, starting 36 months after baseline assessments. Finally, in cognitively impaired individuals, plasma pTau181 concentrations were negatively correlated with both gray and white matter volume as early as 12 months after baseline, and neurodegeneration increased in an incremental manner until 48 months. Conclusions: Higher levels of plasma pTau181 correlate with neurodegeneration and predict further brain atrophy in aging and Alzheimer's disease. Plasma pTau181 may be useful in predicting AD-related neurodegeneration, comparable to positron emission tomography or cerebrospinal fluid assessment with high specificity for AD neurodegeneration. [ABSTRACT FROM AUTHOR]

Background: Postmortem Braak staging provides an index of disease stage and has therefore been incorporated as a core neuropathological criterion for the diagnosis of Alzheimer's disease (AD). Recent in vivo studies using the tau positron emission tomography agent [18F]flortaucipir have shown low sensitivity to detect tau pathology in early Braak stages. These studies report Braak I‐II or greater in ∼20% of cognitively unimpaired elderly, in contrast to the ∼70‐90% of non‐zero Braak stage reported in postmortem studies. Here, we tested whether the novel high‐affinity tau tangles tracer [18F]MK‐6240 (6 fold > [18F]flortaucipir)can better identify individuals in the early stages of tau accumulation. Method: To this end, we studied 301 individuals (30 young adults, 138 cognitively unimpaired (CU) elderly, 67 mild cognitive impairment (MCI), 54 AD dementia, and 12 frontotemporal dementia (FTD)) with amyloid‐b[18F]NAV4694, tau [18F]MK‐6240, magnetic resonance imaging, and clinical assessments. Results: [18F]MK‐6240 discriminated AD from FTD dementia as well as predicted amyloid‐b positivity with the highest area under the curve in Braak I‐II region (=∼95‐100%)(Fig.1 and 2). [18F]MK‐6240 accumulation hierarchically followed the 6 Braak stages (Fig.3)in 98% of our population (Fig.4).91% of the elderly amyloid‐b positive and 46% of the elderly amyloid‐b negative displayed tau deposition, at least in the transentorhinal cortex (Braak I)(Fig.4). Cognition and amyloid‐b status explained most of the Braak stages variance (P<0.0001, R2=0.75). Tau deposition solely in the transentorhinal cortex was associated with an elevated prevalence of amyloid‐b, neurodegeneration, and cognitive impairment (P<0.0001). No single region‐of‐interest accurately segregated individuals into the 6 Braak stages (Fig.5). However, classification decision tree analysis suggested that a composite of transentorhinal, entorhinal, and hippocampal cortices(Braak I‐II) was the region‐of‐interest that best represented [18F]MK‐6240Braak stages (capacity of a region' SUVR cutoff segregating individuals in 7 levels (Braak 0‐VI)) (accuracy=86.2%)(Fig.6). Conclusion: Our results highlight that the hierarchical 6‐stage Braak model using [18F]MK‐6240 provides a robust index of early and late tau accumulation as well as disease stages in preclinical and symptomatic individuals. Tau positron emission tomography Braak staging using high‐affinity tracers has the potential to be incorporated in the diagnosis of living patients with AD. [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: 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: 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: Cognitive reserve (CR), a protective mechanism, allows for sustained cognitive functioning in older adults with greater experiential resources. Bilingualism, an indicator of greater cognitive reserve, has been found to preserve cognitive performance in older adults despite significant disease pathology. While the association with amyloid has been well acknowledged, the effect of tau is still under investigation. In the present study, we aim to evaluate the effect of bilingualism on individuals' cognition and tau load. Method: This study was conducted in 331 individuals (213 cognitively unimpaired (CU)) and 116 cognitively impaired (CI; 81 MCI and 35 AD) from the TRIAD cohort. 40% of the study participants were monolingual. Wechsler Abbreviated Scale of Intelligence ‐ Second Edition (WASI‐II) was used to measure cognitive ability and reasoning in individuals. Accumulation of tau was assessed with [18F]MK6240 PET and standardized uptake value ratio (SUVRs) were calculated between 90 to 110 min post‐injection, using cerebellum grey matter as the reference region. A voxel‐based regression model evaluated the relationship between the WASI‐II score and the PET markers [18F]MK6240, correcting for age, sex, education, APOE, diagnosis and RFT was used to account for multiple comparisons. Result: Our data showed that bilingual individuals demonstrated significantly higher scores on the Wechsler Abbreviated Scale of Intelligence ‐ Second Edition (WASI‐II) in comparison to monolingual individuals. A negative association between the cognitive score and tau accumulation was found in both monolingual and bilingual groupings. In the bilingual individuals, the associated regions were precuneus area, medial and lateral lobes. In the monolingual group, the associated regions were right frontal lobe, parietal lobe and cuneus areas. Conclusion: Our results demonstrate that bilingual individuals are more resilient to the accumulation of tau; shown in higher scores in cognitive ability and reasoning despite having more regions affected than their monolingual counterparts. [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]

Background: Evidence suggests that Alzheimer's disease (AD) pathology may appear many years prior to the manifestation of clinical symptoms. While autosomal‐dominant AD (ADAD) only accounts for approximately 1% of AD cases, evidence shows it has similar pathophysiological features to sporadic AD. ADAD provides a unique and powerful means to model the pathophysiological cascade of events leading to clinical dementia during this asymptomatic stage, due to the complete penetrance of ADAD genetic mutations and the consistency of age at symptom onset between generations. Objective: To investigate tau deposition in vivo across the course of ADAD in mutation carriers (MC) and noncarriers (NC) using the high‐affinity tau PET tracer [18F]MK6240. Method: Cross‐sectional data was acquired for 12 MC, 6 of whom were symptomatic, and 11 asymptomatic NC. The majority of participants (91%) were from families with PSEN1 mutations. Estimated years from symptom onset (EYO) was obtained by subtracting the age at symptom onset of a parent or sibling from the participant's age at assessment. [18F]MK6240 standardized uptake value ratio (SUVR) was calculated 90‐110 minutes post‐injection using inferior cerebellar grey matter as the reference region. Statistical analyses performed included ROI‐based and voxel‐based regressions to examine the association between tau load and EYO in MC and NC. Result: ROI‐based analyses of [18F]MK6240 SUVR as a function of EYO in mutation carriers revealed strong positive correlations for Braak I‐II, III‐IV, and V‐VI. None of the associations between [18F]MK6240 SUVR and EYO were significant in NC. Voxel‐based analyses showed significant correlation between [18F]MK6240 retention and EYO bilaterally in the entorhinal cortex and in the right posterior cingulate and precuneus in MC, while no associations survived correction for multiple comparisons in NC. Conclusion: Our results support a common pathophysiological cascade between ADAD and sporadic AD, as tau aggregation appears to follow Braak stages in both cases. Our study suggests that tau pathology appears up to 10 years before the onset of clinical symptoms. The identification of affected individuals using biomarkers early in the course of disease is crucial for better clinical outcomes. These results support the applications of disease‐modifying therapeutic interventions in the preclinical stage of AD. [ABSTRACT FROM AUTHOR]