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The recent development of tau-specific positron emission tomography (PET) tracers enables in vivo quantification of regional tau pathology, one of the key lesions in Alzheimer's disease (AD). Tau PET imaging may become a useful biomarker for clinical diagnosis and tracking of disease progression but there is no consensus yet on how tau PET signal is best quantified. The goal of the current study was to evaluate multiple whole-brain and region-specific approaches to detect clinically relevant tau PET signal. Two independent cohorts of cognitively normal adults and amyloid-positive (Aβ+) patients with mild cognitive impairment (MCI) or AD-dementia underwent [18F]AV-1451 PET. Methods for tau tracer quantification included: (i) in vivo Braak staging, (ii) regional uptake in Braak composite regions, (iii) several whole-brain measures of tracer uptake, (iv) regional uptake in AD-vulnerable voxels, and (v) uptake in a priori defined regions. Receiver operating curves characterized accuracy in distinguishing Aβ- controls from AD/MCI patients and yielded tau positivity cutoffs. Clinical relevance of tau PET measures was assessed by regressions against cognition and MR imaging measures. Key tracer uptake patterns were identified by a factor analysis and voxel-wise contrasts. Braak staging, global and region-specific tau measures yielded similar diagnostic accuracies, which differed between cohorts. While all tau measures were related to amyloid and global cognition, memory and hippocampal/entorhinal volume/thickness were associated with regional tracer retention in the medial temporal lobe. Key regions of tau accumulation included medial temporal and inferior/middle temporal regions, retrosplenial cortex, and banks of the superior temporal sulcus. Our data indicate that whole-brain tau PET measures might be adequate biomarkers to detect AD-related tau pathology. However, regional measures covering AD-vulnerable regions may increase sensitivity to early tau PET signal, atrophy and memory decline. [Display omitted] •10 different tau PET measures were evaluated in 2 independent samples.•Global and region-specific tau measures yielded similar diagnostic accuracies.•Correlations to clinical variables were stronger for regional than global measures.•Tau deposition showed typical patterns captured by several different approaches.•Neocortical tau deposition was greater for early- than late-onset AD cases.

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 + T MTL + ) and/or in the temporal neocortex (A + T NEO-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 + T NEO-T + (hazard ratio (HR) = 19.2, 95% confidence interval (CI) = 10.9–33.7), A + T MTL + (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 + T MTL + (HR = 6.0, 95% CI = 3.4–10.6) and A + T NEO-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 + T NEO-T + ( β  = −0.056 ± 0.005, T  = −11.55, P  < 0.001), A + T MTL + ( β  = −0.024 ± 0.005, T  = −4.72, P  < 0.001) and A + T − ( β  = −0.008 ± 0.002, T  = −3.46, P  < 0.001) groups showed significantly faster longitudinal global cognitive decline compared to the A − T − (reference) group (all P  < 0.001). Both A + T NEO-T + ( P  < 0.001) and A + T MTL + ( 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. Abnormal amyloid and tau PET in cognitively unimpaired individuals is strongly associated with short-term cognitive decline and subsequent development of dementia.

In 2010, we put forward a hypothetical model of the major biomarkers of Alzheimer's disease (AD). The model was received with interest because we described the temporal evolution of AD biomarkers in relation to each other and to the onset and progression of clinical symptoms. Since then, evidence has accumulated that supports the major assumptions of this model. Evidence has also appeared that challenges some of our assumptions, which has allowed us to modify our original model. Refinements to our model include indexing of individuals by time rather than clinical symptom severity; incorporation of interindividual variability in cognitive impairment associated with progression of AD pathophysiology; modifications of the specific temporal ordering of some biomarkers; and recognition that the two major proteinopathies underlying AD biomarker changes, amyloid β (Aβ) and tau, might be initiated independently in sporadic AD, in which we hypothesise that an incident Aβ pathophysiology can accelerate antecedent limbic and brainstem tauopathy.

Tau pathology first appears in the transentorhinal and anterolateral entorhinal cortex (alEC) in the aging brain. The transition to Alzheimer’s disease (AD) is hypothesized to involve amyloid-β (Aβ) facilitated tau spread through neural connections. We contrasted functional connectivity (FC) of alEC and posteromedial EC (pmEC), subregions of EC that differ in functional specialization and cortical connectivity, with the hypothesis that alEC-connected cortex would show greater tau deposition than pmEC-connected cortex. We used resting state fMRI to measure FC, and PET to measure tau and Aβ in cognitively normal older adults. Tau preferentially deposited in alEC-connected cortex compared to pmEC-connected or non-connected cortex, and stronger connectivity was associated with increased tau deposition. FC-tau relationships were present regardless of Aβ, although strengthened with Aβ. These results provide an explanation for the anatomic specificity of neocortical tau deposition in the aging brain and reveal relationships between normal aging and the evolution of AD. The changes in the brain that cause Alzheimer's disease begin up to 25 years before the first symptoms appear. During this long incubation period, two proteins accumulate in brain tissue: amyloid-β and tau. Amyloid-β forms clumps known as plaques, while tau forms structures called tangles. But whereas amyloid plaques accumulate evenly throughout the brain, this is not the case for tau. Instead tau accumulates first within a region called the entorhinal cortex, which is important for memory. Findings in animals suggest that tau then spreads out of the entorhinal cortex to other brain regions through neural connections. The entorhinal cortex itself consists of two subregions, which each accumulate tau at different times. The anterolateral subregion (or alEC for short) develops tau first, followed by the posteromedial subregion (pmEC). These two subregions process different types of memory and so have connections to different areas of the brain. Does tau therefore spread to brain regions connected to the alEC before it spreads to regions connected to the pmEC? To test this prediction, Adams et al. scanned the brains of healthy young adults to map their brain connectivity patterns. Young adults were chosen because the aging process itself can alter this connectivity. The brains of healthy older adults, aged 60 or more, were then scanned to measure amyloid-β and tau. None of the older adults had cognitive symptoms of Alzheimer's disease. Despite this, many showed deposits of amyloid-β and tau in their brains. As predicted, alEC-connected regions contained more tau than pmEC-connected regions. Indeed, the stronger the connection between a brain region and the alEC, the more tau that region contained. These relationships occurred in older adults with and without amyloid-β in their brains. However, they were stronger in the individuals with amyloid-β. This adds to evidence suggesting that amyloid-β promotes the spread of tau. Future experiments should measure how tau spreads within an individual's network of connections over time. In the long run, researchers may even find that therapies that stop tau from spreading out of the alEC could help prevent Alzheimer's disease from taking hold.

The tau protein aggregates in aging and Alzheimer disease and may lead to memory loss through disruption of medial temporal lobe (MTL)-dependent memory systems. Here, we investigated tau-mediated mechanisms of hippocampal dysfunction that underlie the expression of episodic memory decline using fMRI measures of hippocampal local coherence (regional homogeneity; ReHo), distant functional connectivity and tau-PET. We show that age and tau pathology are related to higher hippocampal ReHo. Functional disconnection between the hippocampus and other components of the MTL memory system, particularly an anterior-temporal network specialized for object memory, is also associated with higher hippocampal ReHo and greater tau burden in anterior-temporal regions. These associations are not observed in the posteromedial network, specialized for context/spatial information. Higher hippocampal ReHo predicts worse memory performance. These findings suggest that tau pathology plays a role in disconnecting the hippocampus from specific MTL memory systems leading to increased local coherence and memory decline. Deposition of tau protein aggregates occurs during aging and Alzheimer disease. Here, the authors show that tau burden in the anterior-temporal memory network is associated with disrupted fMRI connectivity and functional isolation of the hippocampus from other memory network components.

Background Inconsistent positivity thresholds, image analysis pipelines, and quantitative outcomes are key challenges of multisite studies using more than one β-amyloid (Aβ) radiotracer in positron emission tomography (PET). Variability related to these factors contributes to disagreement and lack of replicability in research and clinical trials. To address these problems and promote Aβ PET harmonization, we used [ 18 F]florbetaben (FBB) and [ 18 F]florbetapir (FBP) data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) to derive (1) standardized Centiloid (CL) transformations and (2) internally consistent positivity thresholds based on separate young control samples. Methods We analyzed Aβ PET data using a native-space, automated image processing pipeline that is used for PET quantification in many large, multisite AD studies and trials and made available to the research community. With this pipeline, we derived SUVR-to-CL transformations using the Global Alzheimer’s Association Interactive Network data; we used reference regions for cross-sectional (whole cerebellum) and longitudinal (subcortical white matter, brain stem, whole cerebellum) analyses. Finally, we developed a FBB positivity threshold using an independent young control sample ( N =62) with methods parallel to our existing FBP positivity threshold and validated the FBB threshold using a data-driven approach in ADNI participants ( N =295). Results The FBB threshold based on the young sample (1.08; 18 CL) was consistent with that of the data-driven approach (1.10; 21 CL), and the existing FBP threshold converted to CL with the derived transformation (1.11; 20 CL). The following equations can be used to convert whole cerebellum- (cross-sectional) and composite- (longitudinal) normalized FBB and FBP data quantified with the native-space pipeline to CL units: [ 18 F]FBB: CL whole cerebellum  = 157.15 × SUVR FBB  − 151.87; threshold=1.08, 18 CL [ 18 F]FBP: CL whole cerebellum  = 188.22 × SUVR FBP  − 189.16; threshold=1.11, 20 CL [ 18 F]FBB: CL composite  = 244.20 × SUVR FBB  − 170.80 [ 18 F]FBP: CL composite  = 300.66 × SUVR FBP  − 208.84 Conclusions FBB and FBP positivity thresholds derived from independent young control samples and quantified using an automated, native-space approach result in similar CL values. These findings are applicable to thousands of available and anticipated outcomes analyzed using this pipeline and shared with the scientific community. This work demonstrates the feasibility of harmonized PET acquisition and analysis in multisite PET studies and internal consistency of positivity thresholds in standardized units.

[18F]THK5351, a recently-developed positron emission tomography (PET) tracer for measuring tau neurofibrillary tangle accumulation, may help researchers examine aging, disease, and tau pathology in living human brains. We examined THK5351 tracer pharmacokinetics to define an optimal acquisition time for static late images. Primary measurements were calculation of regional values of distribution volume ratios (DVR) and standardized uptake value ratios (SUVR) in 6 healthy older control and 10 Alzheimer's disease (AD) participants. We examined associations between DVR and SUVR, searching for a 20 min SUVR time window that was stable and comparable to DVR. We additionally examined diagnostic group differences in this 20 min SUVR. In healthy controls, [18F]THK5351 uptake was low, with increased temporal relative to frontal binding. In AD, regional uptake was substantially higher than in healthy controls, with temporal exceeding frontal binding. Retention in cerebellar gray matter, which was used as the reference region, was low compared to other regions. Both DVR and SUVR values showed minimal change over time after 40 min. SUVR 20-40, 30-50, and 40-60 min were most consistently correlated with DVR; SUVR 40-60 min, the most stable time window, was used in further analyses. Significant (AD > healthy control) group differences existed in temporoparietal regions, with marginal medial temporal differences. We found high basal ganglia SUVR 40-60 min signal, with no group differences. We examined THK5351, a new PET tracer for measuring tau accumulation, and compared multiple analysis methods for quantifying regional tracer uptake. SUVR 40-60 min performed optimally when examining 20 min SUVR windows, and appears to be a practical method for quantifying relative regional tracer retention. The results of this study offer clinical potential, given the usefulness of THK5351-PET as a biomarker of tau pathology in aging and disease.

Background Alzheimer’s disease (AD) pathology impairs cognitive function. Yet some individuals with high amounts of AD pathology suffer marked memory impairment, while others with the same degree of pathology burden show little impairment. Why is this? One proposed explanation is cognitive reserve i.e., factors that confer resilience against, or compensation for the effects of AD pathology. Deep NREM slow wave sleep (SWS) is recognized to enhance functions of learning and memory in healthy older adults. However, that the quality of NREM SWS (NREM slow wave activity, SWA) represents a novel cognitive reserve factor in older adults with AD pathology, thereby providing compensation against memory dysfunction otherwise caused by high AD pathology burden, remains unknown. Methods Here, we tested this hypothesis in cognitively normal older adults ( N = 62) by combining 11 C-PiB (Pittsburgh compound B) positron emission tomography (PET) scanning for the quantification of β-amyloid (Aβ) with sleep electroencephalography (EEG) recordings to quantify NREM SWA and a hippocampal-dependent face-name learning task. Results We demonstrated that NREM SWA significantly moderates the effect of Aβ status on memory function. Specifically, NREM SWA selectively supported superior memory function in individuals suffering high Aβ burden, i.e., those most in need of cognitive reserve ( B = 2.694, p = 0.019). In contrast, those without significant Aβ pathological burden, and thus without the same  need for cognitive reserve, did not similarly benefit from the presence of NREM SWA ( B = -0.115, p = 0.876). This interaction between NREM SWA and Aβ status predicting memory function was significant after correcting for age, sex, Body Mass Index, gray matter atrophy, and previously identified cognitive reserve factors, such as education and physical activity ( p = 0.042). Conclusions These findings indicate that NREM SWA is a novel cognitive reserve factor providing resilience against the memory impairment otherwise caused by high AD pathology burden. Furthermore, this cognitive reserve function of NREM SWA remained significant when accounting both for covariates, and factors previously linked to resilience, suggesting that sleep might be an independent cognitive reserve resource. Beyond such mechanistic insights are potential therapeutic implications. Unlike many other cognitive reserve factors (e.g., years of education, prior job complexity), sleep is a modifiable factor. As such, it represents an intervention possibility that may aid the preservation of cognitive function in the face of AD pathology, both present moment and longitudinally.

Over the last 20years, there has been extraordinary progress in brain imaging research and its application to the study of Alzheimer's disease (AD). Brain imaging researchers have contributed to the scientific understanding, early detection and tracking of AD. They have set the stage for imaging techniques to play growing roles in the clinical setting, the evaluation of disease-modifying treatments, and the identification of demonstrably effective prevention therapies. They have developed ground-breaking methods, including positron emission tomography (PET) ligands to measure fibrillar amyloid-β (Aβ) deposition, new magnetic resonance imaging (MRI) pulse sequences, and powerful image analysis techniques, to help in these endeavors. Additional work is needed to develop even more powerful imaging methods, to further clarify the relationship and time course of Aβ and other disease processes in the predisposition to AD, to establish the role of brain imaging methods in the clinical setting, and to provide the scientific means and regulatory approval pathway needed to evaluate the range of promising disease-modifying and prevention therapies as quickly as possible. Twenty years from now, AD may not yet be a distant memory, but the best is yet to come. ► We briefly review progress in brain imaging studies of Alzheimer's disease (AD). ► Imaging techniques have contributed to the early detection and tracking of AD. ► They have emerging roles in the evaluation of disease-modifying treatments. ► They will play critical roles in the evaluation of pre-symptomatic AD treatments. ► They have growing promise in the research and clinical settings.

Currently available evidence strongly supports the position that the initiating event in Alzheimer's disease (AD) is related to abnormal processing of β-amyloid (Aβ) peptide, ultimately leading to formation of Aβ plaques in the brain. This process occurs while individuals are still cognitively normal. Biomarkers of brain β-amyloidosis are reductions in CSF Aβ 42 and increased amyloid PET tracer retention. After a lag period, which varies from patient to patient, neuronal dysfunction and neurodegeneration become the dominant pathological processes. Biomarkers of neuronal injury and neurodegeneration are increased CSF tau and structural MRI measures of cerebral atrophy. Neurodegeneration is accompanied by synaptic dysfunction, which is indicated by decreased fluorodeoxyglucose uptake on PET. We propose a model that relates disease stage to AD biomarkers in which Aβ biomarkers become abnormal first, before neurodegenerative biomarkers and cognitive symptoms, and neurodegenerative biomarkers become abnormal later, and correlate with clinical symptom severity.