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Purpose To examine [18F]RO948 retention in FTD, sampling the underlying protein pathology heterogeneity. Methods A total of 61 individuals with FTD (n = 35), matched cases of AD (n = 13) and Aβ-negative cognitively unimpaired individuals (n = 13) underwent [18F]RO948PET and MRI. FTD included 21 behavioral variant FTD (bvFTD) cases, 11 symptomatic C9orf72 mutation carriers, one patient with non-genetic bvFTD-ALS, one individual with bvFTD due to a GRN mutation, and one due to a MAPT mutation (R406W). Tracer retention was examined using a region-of-interest and voxel-wise approaches. Two individuals (bvFTD due to C9orf72) underwent postmortem neuropathological examination. Tracer binding was additionally assessed in vitro using [3H]RO948 autoradiography in six separate cases. Results [18F]RO948 retention across ROIs was clearly lower than in AD and comparable to that in Aβ-negative cognitively unimpaired individuals. Only minor loci of tracer retention were seen in bvFTD; these did not overlap with the observed cortical atrophy in the cases, the expected pattern of atrophy, nor the expected or verified protein pathology distribution. Autoradiography analyses showed no specific [3H]RO948 binding. The R406W MAPT mutation carriers were clear exceptions with AD-like retention levels and specific in-vitro binding. Conclusion [18F]RO948 uptake is not significantly increased in the majority of FTD patients, with a clear exception being specific MAPT mutations.

The role of microglia in tau accumulation is currently unclear but could provide an important insight into the mechanisms underlying Alzheimer’s disease (AD)1. Here, we measured the microglial marker soluble TREM2 and the disease-associated microglial activation stage 2 markers AXL, MERTK, GAS6, LPL, CST7, SPP1 and CSF1 in nondemented individuals from the Swedish BioFINDER-2 cohort who underwent longitudinal tau-positron emission tomography (PET), amyloid-PET and global cognitive assessment. To assess whether baseline microglial markers had an effect on AD-related changes, we studied three sub-groups of individuals: 121 with evidence of amyloid-PET pathology (A+), 64 with additional evidence of tau-PET pathology (A+T+) and 159 without amyloid- or tau-PET pathology (A−T−). Our results showed that increased levels of TREM2 were associated with slower amyloid accumulation in A+ individuals in addition to slower tau deposition and cognitive decline in A+T+ subjects. Similarly, higher levels of AXL, MERTK, GAS6, LPL, CST7 and CSF1 predicted slower tau accumulation and/or cognitive decline in the A+T+ group. These findings have important implications for future therapeutic strategies aiming to boost microglial protective functions in AD.

Different tau biomarkers become abnormal at different stages of Alzheimer’s disease, with CSF phospho-tau typically becoming elevated at subthreshold levels of tau-PET binding. To capitalize on the temporal order of tau biomarker-abnormality and capture the earliest changes of tau accumulation, we implemented an observational study design to examine longitudinal changes in tau-PET, cortical thickness and cognitive decline in amyloid-β-positive individuals with elevated CSF p-tau levels (P+) but subthreshold Tau-PET retention (T−). To this end, individuals without dementia (i.e. cognitively unimpaired or mild cognitive impairment, n = 231) were selected from the BioFINDER-2 study. Amyloid-β-positive (A+) individuals were categorized into biomarker groups based on cut-offs for abnormal CSF p-tau217 and 18F-RO948 (Tau) PET, yielding groups of tau-concordant-negative (A+P−T−; n = 30), tau-discordant (i.e. A+P+T−; n = 48) and tau-concordant-positive (A+P+T+; n = 18) individuals. In addition, 135 amyloid-β-negative, tau-negative, cognitively unimpaired individuals served as controls. Differences in annual change in regional tau-PET, cortical thickness and cognition between the groups were assessed using general linear models, adjusted for age, sex, clinical diagnosis and (for cognitive measures only) education. Mean follow-up time was ∼2 years. Longitudinal increase in tau-PET was faster in the A+P+T− group than in the control and A+P−T− groups across medial temporal and neocortical regions, with the highest accumulation rates in the medial temporal lobe. The A+P+T− group showed a slower rate of increase in tau-PET compared to the A+P+T+ group, primarily in neocortical regions. We did not detect differences in yearly change in cortical thickness or in cognitive decline between the A+P+T− and A+P−T− groups. The A+P+T+ group, however, showed faster cognitive decline compared to all other groups. Altogether, these findings suggest that the A+P+T− biomarker profile in persons without dementia is associated with an isolated effect on increased tau-PET accumulation rates but not on cortical thinning and cognitive decline. While this suggests that the tau-discordant biomarker profile is not strongly associated with short-term clinical decline, this group does represent an interesting population for monitoring the effects of interventions with disease-modifying agents on tau accumulation in early Alzheimer’s disease, and for examining the emergence of tau aggregates in Alzheimer’s disease. Further, we suggest updating the AT(N) criteria for Alzheimer’s disease biomarker classification to APT(N).

Background: In Alzheimer’s disease (AD), younger symptom onset is associated accelerated cognitive decline and tau spreading, yet the drivers of faster disease manifestation in patients with earlier symptom onset are unknown. Earlier symptom onset is associated with stronger tau pathology in fronto-parietal regions which typically harbor globally connected hubs that are central for cognition. Since tau spreads across connected regions, globally connected hubs may accelerate tau spreading due to their large number of connections to other brain regions. Thus, we hypothesized that a pattern shift of tau pathology towards globally connected brain hubs may facilitate tau spreading and earlier symptom manifestation in AD. Method: We included two independent samples with longitudinal Flortaucipir tau-PET covering the AD spectrum (ADNI: n(controls/AD-preclinical/AD-symptomatic)=93/60/89, BioFINDER, n(controls/AD-preclinical/AD-symptomatic)=16/16/25). In addition, we included resting-state fMRI from human connectome project participants (n=1000), applying a 200-ROI brain atlas to obtain a global connectivity map for assessing brain hubs (Fig.1A-D). Applying the same atlas to tau-PET we transformed SUVRs to tau positivities using a pre-established gaussian-mixture modeling approach (Fig.1E-F). By mapping tau-PET positivities to the fMRI-derived global connectivity map (Fig.1G-L), we assessed the degree to which subject specific tau-PET patterns were shifted towards globally connected hubs or non-hubs, while adjusting for global tau levels. Using linear regression, we then tested whether a stronger shift of tau towards hubs was associated with earlier symptom manifestation and faster longitudinal tau accumulation. Result: In symptomatic AD patients, younger age was associated with a stronger shift of tau-PET towards globally connected brain hubs (p[ADNI/BiOFINDER]=0.024/0.018, Fig.2A&B), and with higher global connectivity of epicenters with highest tau pathology (p[ADNI/BiOFINDER]

Background: Different tau biomarkers become abnormal at different stages of Alzheimer’s disease (AD), with CSF p-tau typically being elevated at subthreshold levels of tau-PET binding. To capitalize on the temporal order of tau biomarker-abnormality and capture the earliest changes of tau accumulation, we selected a group of amyloid-β-positive (A+) individuals with elevated CSF p-tau levels but negative tau-PET scans and assessed longitudinal changes in tau-PET, cortical thickness and cognitive decline. Method: Individuals without dementia (i.e., cognitively unimpaired (CU) or mild cognitive impairment, n=231) were selected from the BioFINDER-2 study. These subjects were categorized into biomarker groups based on Gaussian mixture modelling to determine cut-offs for abnormal CSF Aβ42/40 (A; 217 (P; >110 pg/ml) and [ 18F]RO948 tau-PET SUVR within a temporal meta-ROI (T; SUVR >1.40). Resulting groups were: A+P-T- (concordant, n=30), A+P+T- (discordant, n=48) and A+P+T+ (concordant, n=18). We additionally used 135 A- CU individuals (A- CU) as a reference group (Tables 1 and 2). Differences in annual change in regional tau-PET SUVR, cortical thickness and cognition between the A+P+T- group and the other groups were assessed using general linear models, adjusted for age, sex, clinical diagnosis and (for cognitive measures) education. Result: Longitudinal change in tau-PET was faster in the A+P+T- group than in the A- CU and A+P-T- groups across medial temporal and neocortical regions, with the medial temporal increases being more pronounced. The A+P+T- group showed slower rate of increases in tau-PET compared to the A+P+T+ group, primarily in neocortical regions (Figures 1 and 2). We did not detect differences in yearly change in cortical thickness (Figure 3) or in cognitive decline (Figure 3) between the A+P+T- and A+P-T- groups. The A+P+T+ group, however, showed faster cognitive decline compared to all other groups. Conclusion: These findings suggest that the A+P+T- biomarker profile is associated with early tau accumulation, and with relative sparing of cortical thinning and cognitive decline compared to A+P+T+ individuals. Therefore, the A+P+T- group represents an interesting target-group for early anti-tau interventions and for examining the emergence of tau aggregates in early AD.

Amyloid-beta (Aβ) is hypothesized to facilitate the spread of tau pathology beyond the medial temporal lobe (MTL). However, there is evidence that age-related Aβ-independent tau pathology is present outside the MTL (Kaufman et al., Acta Neuropathol, 2018). We examine tau deposition determined by positron emission tomography (PET) in regions typically involved earlier/later in AD and downstream effects on neurodegeneration and cognition in cognitively unimpaired older adults and a low-Aβ subgroup.MethodsWe included 488 adults (40-91 years; low-Aβ: n=355, 65.2±11.5 years) from the BioFINDER-2 study. MTL volumes (dentate gyrus, subiculum (SUB), cornu ammonis 1) and thickness (entorhinal cortex, Brodmann areas (BA)35/36, and parahippocampal cortex) were obtained, using Automated Segmentation for Hippocampal Subfields packages for T1- and T2-weighted magnetic resonance images. Thickness of early/late neocortical AD-regions (anterior cingulate, precuneus/posterior cingulate (PPC), orbitofrontal, inferior parietal cortex; and middle frontal, lateral occipital, and precentral/postcentral gyrus) was determined using FreeSurfer. [18F]RO948- and [18F]flutemetamol-PET standardized uptake value ratios (SUVRs) were calculated for local tau and global/local Aβ. Aβ status was determined using Aβ-PET or cerebrospinal fluid Aβ-42/40 ratio. Global cognition was measured using delayed word-list recall, trail making test B, and animal fluency.ResultsIncreasing age was associated with higher tau-PET SUVRs primarily in MTL/frontal/parietal regions. A significant association between age and local tau-PET remained even when including Aβ-PET as a mediator (Fig. 1).Age and local tau-PET, but not Aβ-PET, where negatively associated with structure in most examined regions (Figs. 2-3). Age-structure associations were serially mediated via tau-PET in regions with early AD pathology (SUB/BA35/PPC). Also, in the low-Aβ subgroup, tau-PET mediated the age-structure (SUB/BA35/PPC) associations (Fig. 3D). Finally, the age-global cognition relationship was serially mediated via MTL tau-PET and subiculum volume, even when including global Aβ-PET as additional mediator (Fig. 4).ConclusionWe observe partially Aβ-independent associations between age and tau-PET signal across the neocortex. Interestingly, partially Aβ-independent tau-PET signal appears to mediate the age-structure associations in and outside the MTL (PPC), also in the low-Aβ group, and the age-MTL structure-cognition associations. This potentially provides in vivo support for Primary Age-related Tauopathy downstream effects on structure, beyond the MTL, and cognition.

A major unanswered question in the dementia field is whether cognitively unimpaired individuals who harbor both Alzheimer’s disease neuropathological hallmarks (that is, amyloid-β plaques and tau neurofibrillary tangles) can preserve their cognition over time or are destined to decline. In this large multicenter amyloid and tau positron emission tomography (PET) study (n = 1,325), we examined the risk for future progression to mild cognitive impairment and the rate of cognitive decline over time among cognitively unimpaired individuals who were amyloid PET-positive (A+) and tau PET-positive (T+) in the medial temporal lobe (A+TMTL+) and/or in the temporal neocortex (A+TNEO-T+) and compared them with A+T− and A−T− groups. Cox proportional-hazards models showed a substantially increased risk for progression to mild cognitive impairment in the A+TNEO-T+ (hazard ratio (HR) = 19.2, 95% confidence interval (CI) = 10.9–33.7), A+TMTL+ (HR = 14.6, 95% CI = 8.1–26.4) and A+T− (HR = 2.4, 95% CI = 1.4–4.3) groups versus the A−T− (reference) group. Both A+TMTL+ (HR = 6.0, 95% CI = 3.4–10.6) and A+TNEO-T+ (HR = 7.9, 95% CI = 4.7–13.5) groups also showed faster clinical progression to mild cognitive impairment than the A+T− group. Linear mixed-effect models indicated that the A+TNEO-T+ (β = −0.056 ± 0.005, T = −11.55, P +TMTL+ (β = −0.024 ± 0.005, T = −4.72, P +T− (β = −0.008 ± 0.002, T = −3.46, P −T− (reference) group (all P +TNEO-T+ (P +TMTL+ (P = 0.002) groups also progressed faster than the A+T− group. In summary, evidence of advanced Alzheimer’s disease pathological changes provided by a combination of abnormal amyloid and tau PET examinations is strongly associated with short-term (that is, 3–5 years) cognitive decline in cognitively unimpaired individuals and is therefore of high clinical relevance.

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

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

Blood biomarkers indicative of Alzheimer’s disease (AD) pathology are altered in both preclinical and symptomatic stages of the disease. Distinctive biomarkers may be optimal for the identification of AD pathology or monitoring of disease progression. Blood biomarkers that correlate with changes in cognition and atrophy during the course of the disease could be used in clinical trials to identify successful interventions and thereby accelerate the development of efficient therapies. When disease-modifying treatments become approved for use, efficient blood-based biomarkers might also inform on treatment implementation and management in clinical practice. In the BioFINDER-1 cohort, plasma phosphorylated (p)-tau231 and amyloid-β42/40 ratio were more changed at lower thresholds of amyloid pathology. Longitudinally, however, only p-tau217 demonstrated marked amyloid-dependent changes over 4–6 years in both preclinical and symptomatic stages of the disease, with no such changes observed in p-tau231, p-tau181, amyloid-β42/40, glial acidic fibrillary protein or neurofilament light. Only longitudinal increases of p-tau217 were also associated with clinical deterioration and brain atrophy in preclinical AD. The selective longitudinal increase of p-tau217 and its associations with cognitive decline and atrophy was confirmed in an independent cohort (Wisconsin Registry for Alzheimer’s Prevention). These findings support the differential association of plasma biomarkers with disease development and strongly highlight p-tau217 as a surrogate marker of disease progression in preclinical and prodromal AD, with impact for the development of new disease-modifying treatments.

Markers of downstream events are a key component of clinical trials of disease-modifying therapies for Alzheimer’s disease. Morphological metrics like cortical thickness are established measures of atrophy but are not sensitive enough to detect amyloid-beta (Aβ)- related changes that occur before overt atrophy become visible. We aimed to investigate to what extent diffusion MRI can provide sensitive markers of cortical microstructural changes and to test their associations with multiple aspects of the Alzheimer’s disease pathological cascade, including both Aβ and tau accumulation, astrocytic activation and cognitive deficits. We applied the mean apparent diffusion propagator model to diffusion MRI data from 492 cognitively unimpaired elderly and patients with mild cognitive impairment from the Swedish BioFINDER-2 cohort. Participants were stratified in Aβ-negative/tau-negative, Aβ-positive/tau-negative and Aβ-positive/tau-positive based on Aβ- and tau-PET uptake. Cortical regional values of diffusion MRI metrics and cortical thickness were compared across groups. Associations between regional values of diffusion MRI metrics and both Aβ- and tau-PET uptake were also investigated along with the association with plasma level of glial fibrillary acidic protein (GFAP), a marker of astrocyte activation (available in 292 participants). Mean squared displacement revealed widespread microstructural differences already between Aβ-negative/tau-negative and Aβ-positive/tau-negative participants with a spatial distribution that closely resembled the pattern of Aβ accumulation. In contrast, differences in cortical thickness were clearly more limited. Mean squared displacement was also correlated with both Aβ- and tau-PET uptake even independently from one another and from cortical thickness. Further, the same metric exhibited significantly stronger correlations with PET uptake than cortical thickness (P < 0.05). Mean squared displacement was also positively correlated with GFAP with a pattern that resembles Aβ accumulation, and GFAP partially mediated the association between Aβ accumulation and mean squared displacement. Further, impairments in executive functions were significantly more associated with mean squared displacement values extracted from a meta-region of interest encompassing regions accumulating Aβ early in the disease process, than with cortical thickness (P < 0.05). Similarly, impairments in memory functions were significantly more associated with mean squared displacement values extracted from a temporal meta-region of interest than with cortical thickness (P < 0.05). Metrics of cortical microstructural alteration derived from diffusion MRI are highly sensitive to multiple aspects of the Alzheimer’s disease pathological cascade. Of particular interest is the link with both Aβ-PET and GFAP, suggesting diffusion MRI might reflects microstructural changes related to the astrocytic response to Aβ aggregation. Therefore, metrics of cortical diffusion might be important outcome measures in anti-Aβ treatments clinical trials for detecting drug-induced changes in cortical microstructure.

In a longitudinal PET study, Smith et al. show that tau accumulation rates are higher in females, younger Aβ-positive individuals, and those with higher baseline tau load. This is in contrast to Aβ-accumulation rates, which are higher in APOE-ε4 carriers and older individuals., The development of tau-PET allows paired helical filament tau pathology to be visualized in vivo. Increased knowledge about conditions affecting the rate of tau accumulation could guide the development of therapies halting the progression of Alzheimer’s disease. However, the factors modifying the rate of tau accumulation over time in Alzheimer’s disease are still largely unknown. Large-scale longitudinal cohort studies, adjusting for baseline tau load, are needed to establish such risk factors. In the present longitudinal study, 419 participants from four cohorts in the USA (Avid 05e, n = 157; Expedition-3, n = 82; ADNI, n = 123) and Sweden (BioFINDER, n = 57) were scanned repeatedly with tau-PET. The study participants were cognitively unimpaired (n = 153), or patients with mild cognitive impairment (n = 139) or Alzheimer’s disease dementia (n = 127). Participants underwent two to four tau-PET (18F-flortaucipir) scans with a mean (± standard deviation) of 537 (±163) days between the first and last scan. The change in tau-PET signal was estimated in temporal meta- and neocortical regions of interest. Subject specific tau-PET slopes were predicted simultaneously by age, sex, amyloid status (determined by amyloid-β PET), APOE ε4 genotype, study cohort, diagnosis and baseline tau load. We found that accelerated increase in tau-PET signal was observed in amyloid-β-positive mild cognitive impairment (3.0 ± 5.3%) and Alzheimer’s disease dementia (2.9 ± 5.7%), respectively, when compared to either amyloid-β-negative cognitively unimpaired (0.4 ± 2.7%), amyloid-β-negative mild cognitive impairment (−0.4 ± 2.3%) or amyloid-β-positive cognitively unimpaired (1.2 ± 2.8%). Tau-PET uptake was accelerated in females (temporal region of interest: t = 2.86, P = 0.005; neocortical region of interest: t = 2.90, P = 0.004), younger individuals (temporal region of interest: t = −2.49, P = 0.013), and individuals with higher baseline tau-PET signal (temporal region of interest: t = 3.83, P

Introduction Differential patterns of brain atrophy on structural magnetic resonance imaging (MRI) revealed four reproducible subtypes of Alzheimer's disease (AD): (1) "typical", (2) "limbic-predominant", (3) "hippocampal-sparing", and (4) "mild atrophy". We examined the neurobiological characteristics and clinical progression of these atrophy-defined subtypes. Methods The four subtypes were replicated using a clustering method on MRI data in 260 amyloid-β–positive patients with mild cognitive impairment or AD dementia, and we subsequently tested whether the subtypes differed on [18F]flortaucipir (tau) positron emission tomography, white matter hyperintensity burden, and rate of global cognitive decline. Results Voxel-wise and region-of-interest analyses revealed the greatest neocortical tau load in hippocampal-sparing (frontoparietal-predominant) and typical (temporal-predominant) patients, while limbic-predominant patients showed particularly high entorhinal tau. Typical patients with AD had the most pronounced white matter hyperintensity load, and hippocampal-sparing patients showed the most rapid global cognitive decline. Discussion Our data suggest that structural MRI can be used to identify biologically and clinically meaningful subtypes of AD.

Subregions in the medial temporal lobe (MTL) are affected early by Alzheimer’s disease (AD) pathology and subject to grey matter atrophy. Measuring the earliest AD-related atrophy in the hippocampus is challenging as region-of-interest (ROI) analyses of hippocampal subregional volumes collapse across voxels within anatomical subregions. PET imaging studies, however, report accumulation of tau pathology between anatomical subregions in the earliest disease stages (Berron et al., 2021) fitting reports from the neuropathological literature (Lace et al., 2019; Ravikumar et al., 2021). Thus, sensitive in vivo methods of point-wise structural measures are needed in order to detect the earliest hippocampal thinning in AD along the anterior-posterior as well as the medial-lateral hippocampal axis.MethodHere we analyzed data from 76 amyloid-beta negative (Ab-) cognitively normal (CN), 46 Ab+ CN individuals and 25 Ab+ patients with mild cognitive impairment (MCI) from the BioFINDER-2 study, who underwent 7 Tesla T2-weighted structural magnetic resonance imaging, tau positron emission tomography imaging (using 18F-RO-948) and cognitive assessments. First, we segmented hippocampal subfields and extrahippocampal subregions. Second, we calculated point-wise hippocampal thickness estimates (Diers et al.) of hippocampal subfields subiculum, cornu ammonis (CA)1, CA2 and CA3 on the level of the hippocampal body. Thirdly, we extracted local tau-PET SUVR from Area 35 (A35), entorhinal cortex and amygdala. Finally, we assessed relationships between hippocampal local thickness and tau accumulation as well as cognitive performance.ResultOur analyses revealed earliest hippocampal thinning associated with tau accumulation in an area spanning the boundary of subiculum and CA1 at the level of the anterior hippocampal body. Ab+ MCI patients showed more posterior thinning in comparison to Ab- CU participants. Median thickness in an ROI comprising vertices with A35 tau-related thinning (A35-TauThinning-ROI) was significantly lower in MCI Ab+ and tended to be lower in CU Ab+ compared to CU Ab-. Higher median thickness in the hippocampal A35-TauThinning-ROI, but not whole CA1 nor subiculum thickness, was associated with better 10-Word-Delayed-Recall and higher PACC scores.ConclusionOur results suggest that tau-related thinning of hippocampal subregions can be observed already in early disease stages. Tau-related point-wise thickness measures were more sensitive compared to volumetric measures of anatomical subregions.

This cohort study describes longitudinal tau positron emission tomography findings using [18F]RO948 across the different clinical stages of Alzheimer disease., Key Points Question Which biomarkers best predict longitudinal tau accumulation at different clinical stages of Alzheimer disease? Findings In this cohort study of 343 participants including amyloid-β–positive individuals who were cognitively unimpaired or had mild cognitive impairment, the largest annual increase in [18F]RO948 tau positron emission tomography (PET) was seen across the entorhinal cortex, hippocampus, and amygdala and in temporal cortical regions, respectively. In a power analysis, plasma phosphorylated tau217 with tau PET at baseline in stage I and II, respectively, resulted in sample size reductions. Meaning In trials using tau PET as a main outcome, plasma phosphorylated tau217 with tau PET may prove optimal for enrichment in both preclinical and prodromal Alzheimer disease., Importance There is currently no consensus as to which biomarkers best predict longitudinal tau accumulation at different clinical stages of Alzheimer disease (AD). Objective To describe longitudinal [18F]RO948 tau positron emission tomography (PET) findings across the clinical continuum of AD and determine which biomarker combinations showed the strongest associations with longitudinal tau PET and best optimized clinical trial enrichment. Design, Setting, and Participants This longitudinal cohort study consecutively enrolled amyloid-β (Aβ)–negative cognitively unimpaired (CU) participants, Aβ-positive CU individuals, Aβ-positive individuals with mild cognitive impairment (MCI), and individuals with AD dementia between September 2017 and November 2020 from the Swedish BioFINDER-2 (discovery cohort) and BioFINDER-1 (validation cohort) studies. Exposures Baseline plasma and cerebrospinal fluid Aβ42/Aβ40, tau phosphorylated at threonine-217 (p-tau217), p-tau181 and neurofilament light, magnetic resonance imaging, amyloid PET ([18F]flutemetamol), and tau PET ([18F]RO948 in the BioFINDER-2 study; [18F]flortaucipir in the BioFINDER-1 study). Main Outcomes and Measures Baseline tau PET standardized uptake value ratio (SUVR) and annual percent change in tau PET SUVR across regions of interest derived using a data-driven approach combining clustering and event-based modeling. Regression models were used to examine associations between individual biomarkers and longitudinal tau PET and to identify which combinations best predicted longitudinal tau PET. These combinations were then entered in a power analysis to examine how their use as an enrichment strategy would affect sample size in a simulated clinical trial. Results Of 343 participants, the mean (SD) age was 72.56 (7.24) years, and 157 (51.1%) were female. The clustering/event-based modeling–based approach identified 5 regions of interest (stages). In Aβ-positive CU individuals, the largest annual increase in tau PET SUVR was seen in stage I (entorhinal cortex, hippocampus, and amygdala; 4.04% [95% CI, 2.67%-5.32%]). In Aβ-positive individuals with MCI and with AD dementia, the greatest increases were seen in stages II (temporal cortical regions; 4.45% [95% CI, 3.41%-5.49%]) and IV (certain frontal regions; 5.22% [95% CI, 3.95%-6.49%]), respectively. In Aβ-negative CU individuals and those with MCI, modest change was seen in stage I (1.38% [95% CI, 0.78%-1.99%] and 1.80% [95% CI, 0.76%-2.84%], respectively). When looking at individual predictors and longitudinal tau PET in the stages that showed most change, plasma p-tau217 (R2 = 0.27, P

Supplementary data: Harper_et_al_Supplementary_211111_bhab457 (docx file) - available online at https://doi.org/10.1093/cercor/bhab457 . Copyright © The Author(s) 2022. The paracingulate sulcus is a tertiary sulcus formed during the third trimester. In healthy individuals paracingulate sulcation is more prevalent in the left hemisphere. The anterior cingulate and paracingulate gyri are focal points of neurodegeneration in behavioral variant frontotemporal dementia (bvFTD). This study aims to determine the prevalence and impact of paracingulate sulcation in bvFTD. Structural magnetic resonance images of individuals with bvFTD (n = 105, mean age 66.9 years), Alzheimer’s disease (n = 92, 73.3), and healthy controls (n = 110, 62.4) were evaluated using standard protocol for hemispheric paracingulate sulcal presence. No difference in left hemisphere paracingulate sulcal frequency was observed between groups; 0.72, 0.79, and 0.70, respectively, in the bvFTD, Alzheimer’s disease, and healthy control groups, (P = 0.3). A significant impact of right (but not left) hemispheric paracingulate sulcation on age at disease onset was identified in bvFTD (mean 60.4 years where absent vs. 63.8 where present [P = 0.04, Cohen’s d = 0.42]). This relationship was not observed in Alzheimer’s disease. These findings demonstrate a relationship between prenatal neuronal development and the expression of a neurodegenerative disease providing a gross morphological example of brain reserve. Work at the Clinical Memory Research Unit Lund University was supported by the Swedish Research Council (2016–00906); the Knut and Alice Wallenberg foundation (2017–0383); the Marianne and Marcus Wallenberg foundation (2015.0125); the Strategic Research Area MultiPark (Multidisciplinary Research in Parkinson’s disease) at Lund University, the Swedish Alzheimer Foundation (AF-939932); the Swedish Brain Foundation (FO2019–0326); The Parkinson foundation of Sweden (1280/20); the Skåne University Hospital Foundation (2020-O000028); Regionalt Forskningsstöd (2020–0314); and the Swedish Federal Government under the ALF Agreement (2018-Projekt0279). Additional funding to A.F.S. was provided by the Swedish Society for Medical Research and the Bente Rexed Gersteds Foundation for Brain Research. L.H., A.F.S., and O.L. are all supported by the Schörling foundation. The UCL Dementia Research Centre is supported by Alzheimer’s Research UK, Alzheimer’s Society, Brain Research UK, and The Wolfson Foundation. This work was supported by the National Institute of Health Research UCL/H Biomedical Research Centre and the UK Dementia Research Institute, which receives its funding from UK DRI Ltd, funded by the UK Medical Research Council, Alzheimer’s Society and Alzheimer’s Research UK. J.D.R. is supported by the Miriam Marks Brain Research UK Senior Fellowship and has received funding from an Medical Research Council Clinician Scientist Fellowship (MR/M008525/1) and the NIHR Rare Disease Translational Research Collaboration (BRC149/NS/MH); the Alzheimer’s Society, UK (AS-JF-19a-004-517 to M.B.). The funding sources had no role in the design and conduct of the study; in the collection, analysis, interpretation of the data; or in the preparation, review, or approval of the manuscript.

PET, CSF and plasma biomarkers of tau pathology may be differentially associated with Alzheimer's disease (AD)‐related demographic, cognitive, genetic and neuroimaging markers. We examined 771 participants with normal cognition, mild cognitive impairment or dementia from BioFINDER‐2 (n = 400) and ADNI (n = 371). All had tau‐PET ([18F]RO948 in BioFINDER‐2, [18F]flortaucipir in ADNI) and CSF p‐tau181 biomarkers available. Plasma p‐tau181 and plasma/CSF p‐tau217 were available in BioFINDER‐2 only. Concordance between PET, CSF and plasma tau biomarkers ranged between 66 and 95%. Across the whole group, ridge regression models showed that increased CSF and plasma p‐tau181 and p‐tau217 levels were independently of tau PET associated with higher age, and APOEɛ4‐carriership and Aβ‐positivity, while increased tau‐PET signal in the temporal cortex was associated with worse cognitive performance and reduced cortical thickness. We conclude that biofluid and neuroimaging markers of tau pathology convey partly independent information, with CSF and plasma p‐tau181 and p‐tau217 levels being more tightly linked with early markers of AD (especially Aβ‐pathology), while tau‐PET shows the strongest associations with cognitive and neurodegenerative markers of disease progression., Tau pathology in Alzheimer's disease (AD) can be measured using neuroimaging (PET) and biofluid (CSF and plasma) markers. This study explores whether the tau biomarkers are comparable to each other or carry unique information about AD‐related demographic, cognitive, genetic and neuroimaging markers.

Although several studies have shown decreased cerebral blood flow (CBF) in Alzheimers disease (AD), the role of hypoperfusion in the disease pathogenesis remains unclear. Combining arterial spin labeling MRI, positron emission tomography, and biomarkers of cerebrospinal fluid, we investigated the associations between CBF and the key mechanisms in AD including amyloid-{beta} (A{beta}) and tau pathology, synaptic dysfunction and axonal degeneration. Further, we applied a disease progression modeling to characterize the temporal sequence of different AD biomarkers. Lower perfusion was observed in the temporo-occipito-parietal regions in the A{beta}-positive cognitively impaired compared to both the A{beta}-positive and A{beta}-negative cognitively unimpaired individuals. In participants along the AD spectrum (those with A{beta} pathology regardless of their cognitive status), CBF was inversely associated with tau and synaptic dysfunction, but not A{beta}, in similar cortical regions. Moreover, the disease progression modeling revealed that CBF disruption followed the abnormality of biomarkers of A{beta}, tau and brain atrophy. These findings indicate that tau tangles and synaptic degeneration are more closely connected with CBF changes rather than A{beta} pathology. This supports the notion that hypoperfusion is not an early event associated with the build-up of A{beta} during the preclinical phase of AD.

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

Purpose [18F]flortaucipir binds to paired helical filament tau and accurately identifies tau in Alzheimer’s disease (AD). However, “off-target” binding interferes with the quantification of [18F]flortaucipir in several brain regions. Recently, other tau PET tracers have been developed. Here, we compare [18F]flortaucipir with the novel tau tracer [18F]RO948 head-to-head in vivo. Methods We included 18 participants with AD, three with amyloid-β-positive amnestic mild cognitive impairment, and four healthy controls. All underwent [18F]flortaucipir (80–100 min) and [18F]RO948 (70–90) PET scans within approximately 1 month. Four study participants underwent 0–100-min dynamic scanning. Standardized uptake value ratios (SUVRs) were created using an inferior cerebellar reference region. Results Neocortical tracer retention was highly comparable using both SUVR and distribution volume ratio-1 values obtained from dynamic scans. However, [18F]RO948 retention was significantly higher in the entorhinal cortex and lower in the basal ganglia, thalamus, and choroid plexus compared with [18F]flortaucipir. Increased off-target binding was observed with age for both tracers. Several cases exhibited strong [18F]RO948 retention in the skull/meninges. This extra-cerebral signal, however, did not affect diagnostic accuracy and remained relatively unchanged when re-examining a subsample after 1 year. Kinetic modeling showed an increase in [18F]flortaucipir SUVR over the scanning interval, compared with a plateau for [18F]RO948. Conclusion [18F]RO948 and [18F]flortaucipir bound comparably in neocortical regions, but [18F]RO948 showed higher retention in the medial temporal lobe and lower intracerebral “off-target” binding. Time-dependent bias of SUVR estimates may prove less of a factor with [18F]RO948, compared with previous tau ligands.

Alterations in cognitive performance have been noted in nondemented subjects with elevated accumulation of amyloid-β (Aβ) fibrils. However, it is not yet understood whether brain function is already influenced by Aβ deposition during the very earliest stages of the disease. We therefore investigated associations between [18F]Flutemetamol PET, resting-state functional connectivity, gray and white matter structure and cognitive performance in 133 cognitively normal elderly that exhibited normal global Aβ PET levels. [18F]Flutemetamol uptake in regions known to accumulate Aβ fibrils early in preclinical AD (i.e., mainly certain parts of the default-mode network) was positively associated with dynamic but not static functional connectivity (r = 0.77). Dynamic functional connectivity was further related to better cognitive performance (r = 0.21–0.72). No significant associations were found for Aβ uptake with gray matter volume or white matter diffusivity. The findings demonstrate that the earliest accumulation of Aβ fibrils is associated with increased functional connectivity, which occurs before any structural alterations. The enhanced functional connectivity may reflect a compensatory mechanism to maintain high cognitive performance in the presence of increasing amyloid accumulation during the earliest phases of AD.