The extent to which the tau tracer [18F]AV-1451 can differentiate between tauopathies is unknown. By comparing patients with Alzheimer’s disease and progressive supranuclear palsy (PSP), Passamonti et al. show that [18F]AV-1451 displays greater specificity for Alzheimer-related tau pathology than PSP-related pathology. A machine learning algorithm correctly diagnosed 94% of cases.

Prion-like, trans-neuronal spread of tau pathology in humans is controversial. By evaluating tau burden and functional connectivity in living patients, Cope et al. demonstrate relationships consistent with this in Alzheimer's disease but not progressive supranuclear palsy. Tau distribution in the latter is better explained by metabolic demand and trophic support.

Neuroinflammation is a key part of the etio-pathogenesis of Alzheimer's disease (AD). We tested the relationship between neuroinflammation and the disruption of functional connectivity in large-scale networks, and their joint influence on cognitive impairment. We combined [11C]PK11195 positron emission tomography (PET) and resting-state functional magnetic resonance imaging (rs-fMRI) in 28 patients (12 females/16 males) with clinical diagnosis of probable AD or mild cognitive impairment with positive PET biomarker for amyloid, and 14 age-, sex-, and education-matched healthy controls (8 females/6 males). Source-based “inflammetry” was used to extract principal components of [11C]PK11195 PET signal variance across all participants. rs-fMRI data were preprocessed via independent component analyses to classify neuronal and non-neuronal signals. Multiple linear regression models identified sources of signal covariance between neuroinflammation and brain connectivity profiles, in relation to the diagnostic group (patients, controls) and cognitive status.Patients showed significantly higher [11C]PK11195 binding relative to controls, in a distributed spatial pattern including the hippocampus, frontal, and inferior temporal cortex. Patients with enhanced loading on this [11C]PK11195 binding distribution displayed diffuse abnormal functional connectivity. The expression of a stronger association between such abnormal connectivity and higher levels of neuroinflammation correlated with worse cognitive deficits.Our study suggests that neuroinflammation relates to the pathophysiological changes in network function that underlie cognitive deficits in Alzheimer's disease. Neuroinflammation, and its association with functionally-relevant reorganization of brain networks, is proposed as a target for emerging immunotherapeutic strategies aimed at preventing or slowing the emergence of dementia.SIGNIFICANCE STATEMENT Neuroinflammation is an important aspect of Alzheimer's disease (AD), but it was not known whether the influence of neuroinflammation on brain network function in humans was important for cognitive deficit. Our study provides clear evidence that in vivo neuroinflammation in AD impairs large-scale network connectivity; and that the link between neuro inflammation and functional network connectivity is relevant to cognitive impairment. We suggest that future studies should address how neuroinflammation relates to network function as AD progresses, and whether the neuroinflammation in AD is reversible, as the basis of immunotherapeutic strategies to slow the progression of AD.

Tau pathology, neuroinflammation, and neurodegeneration are key aspects of Alzheimer’s disease. Understanding whether these features predict cognitive decline, alone or in combination, is crucial to develop new prognostic measures and enhanced stratification for clinical trials. Here, we studied how baseline assessments of in vivo tau pathology (measured by 18F-AV-1451 PET), neuroinflammation (measured by 11C-PK11195 PET) and brain atrophy (derived from structural MRI) predicted longitudinal cognitive changes in patients with Alzheimer’s disease pathology. Twenty-six patients (n = 12 with clinically probable Alzheimer’s dementia and n = 14 with amyloid-positive mild cognitive impairment) and 29 healthy control subjects underwent baseline assessment with 18F-AV-1451 PET, 11C-PK11195 PET, and structural MRI. Cognition was examined annually over the subsequent 3 years using the revised Addenbrooke’s Cognitive Examination. Regional grey matter volumes, and regional binding of 18F-AV-1451 and 11C-PK11195 were derived from 15 temporo-parietal regions characteristically affected by Alzheimer’s disease pathology. A principal component analysis was used on each imaging modality separately, to identify the main spatial distributions of pathology. A latent growth curve model was applied across the whole sample on longitudinal cognitive scores to estimate the rate of annual decline in each participant. We regressed the individuals’ estimated rate of cognitive decline on the neuroimaging components and examined univariable predictive models with single-modality predictors, and a multi-modality predictive model, to identify the independent and combined prognostic value of the different neuroimaging markers. Principal component analysis identified a single component for the grey matter atrophy, while two components were found for each PET ligand: one weighted to the anterior temporal lobe, and another weighted to posterior temporo-parietal regions. Across the whole-sample, the single-modality models indicated significant correlations between the rate of cognitive decline and the first component of each imaging modality. In patients, both stepwise backward elimination and Bayesian model selection revealed an optimal predictive model that included both components of 18F-AV-1451 and the first (i.e. anterior temporal) component for 11C-PK11195. However, the MRI-derived atrophy component and demographic variables were excluded from the optimal predictive model of cognitive decline. We conclude that temporo-parietal tau pathology and anterior temporal neuroinflammation predict cognitive decline in patients with symptomatic Alzheimer’s disease pathology. This indicates the added value of PET biomarkers in predicting cognitive decline in Alzheimer’s disease, over and above MRI measures of brain atrophy and demographic data. Our findings also support the strategy for targeting tau and neuroinflammation in disease-modifying therapy against Alzheimer’s disease.

ObjectiveWe tested whether in vivo neuroinflammation relates to the distinctive distributions of pathology in Alzheimer disease (AD) and progressive supranuclear palsy (PSP).MethodsSixteen patients with symptomatic AD (including amnestic mild cognitive impairment with amyloid-positive PET scan), 16 patients with PSP–Richardson syndrome, and 13 age-, sex-, and education-matched healthy controls were included in this case-control study. Participants underwent [11C]PK11195 PET scanning, which was used as an in vivo index of neuroinflammation.Results[11C]PK11195 binding in the medial temporal lobe and occipital, temporal, and parietal cortices was increased in patients with AD, relative both to patients with PSP and to controls. Compared to controls, patients with PSP showed elevated [11C]PK11195 binding in the thalamus, putamen, and pallidum. [11C]PK11195 binding in the cuneus/precuneus correlated with episodic memory impairment in AD, while [11C]PK11195 binding in the pallidum, midbrain, and pons correlated with disease severity in PSP.ConclusionsTogether, our results suggest that neuroinflammation has an important pathogenic role in the 2 very different human neurodegenerative disorders of AD and PSP. The increase and distribution of microglial activation suggest that immunotherapeutic strategies may be useful in slowing the progression of both diseases.