Background: Imaging studies in Alzheimer’s disease (AD) have yet to answer the underlying questions concerning the relationship among tau retention, neuroinflammation, network disruption and cognitive decline. We compared the spatial retention patterns of 18F-THK5351 and resting state network (RSN) disruption in patients with early AD and healthy controls.Methods: We enrolled 23 11C-Pittsburgh compound B (PiB)-positive patients with early AD and 24 11C-PiB-negative participants as healthy controls. All participants underwent resting state functional MRI and 18F-THK5351 PET scans. We used scaled subprofile modeling/principal component analysis (SSM/PCA) to reduce the complexity of multivariate data and to identify patterns that exhibited the largest statistical effects (variances) in THK5351 concentration in AD and healthy controls.Findings: SSM/PCA identified a significant spatial THK5351 pattern composed by mainly three clusters including precuneus/posterior cingulate cortex (PCC), right and left dorsolateral prefrontal cortex (DLPFC) which accounted for 23.6% of the total subject voxel variance of the data and had 82.6% sensitivity and 79.1% specificity in discriminating AD from healthy controls. There was a significant relationship between the intensity of the 18F-THK5351 covariation pattern and cognitive scores in AD. The spatial patterns of 18F-THK5351 uptake showed significant similarity with intrinsic functional connectivity, especially in the PCC network. Seed-based connectivity analysis from the PCC showed significant decrease in connectivity over widespread brain regions in AD patients. An evaluation of an autopsied AD patient with Braak V showed that 18F-THK5351 retention corresponded to tau deposition, monoamine oxidase-B (MAO-B) and astrogliosis in the precuneus/PCC.Interpretation: We identified an AD-specific spatial pattern of 18F-THK5351 retention in the precuneus/PCC, an important connectivity hub region in the brain. Disruption of the functional connections of this important network hub may play an important role in developing dementia in AD.

Healthy aging is associated with structural and functional changes in the brain even in individuals who are free of neurodegenerative diseases. Using resting state functional magnetic resonance imaging data from a carefully selected cohort of participants, we examined cross sectional changes in the functional organization of several large-scale brain networks over the adult lifespan and its potential association with general cognitive performance. Converging results from multiple analyses at the voxel, node, and network levels showed widespread reorganization of functional brain networks with increasing age. Specifically, the primary processing (visual and sensorimotor) and visuospatial (dorsal attention) networks showed diminished network integrity, while the so-called core neurocognitive (executive control, salience, and default mode) and basal ganglia networks exhibited relatively preserved between-network connections. The visuospatial and precuneus networks also showed significantly more widespread increased connectivity with other networks. Graph analysis suggested that this reorganization progressed towards a more integrated network topology. General cognitive performance, assessed by Addenbrooke’s Cognitive Examination-Revised total score, was positively correlated with between-network connectivity among the core neurocognitive and basal ganglia networks and the integrity of the primary processing and visuospatial networks. Mediation analyses further indicated that the observed association between aging and relative decline in cognitive performance could be mediated by changes in relevant functional connectivity measures. Overall, these findings provided further evidence supporting widespread age-related brain network reorganization and its potential association with general cognitive performance during healthy aging.

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Cognitive deficits in Parkinson's disease (PD) are heterogeneous entities, but a relationship between the heterogeneity of cognitive deficits and resting-state network (RSN) changes remains elusive. In this study, we examined five sub-domain scores according to Addenbrooke's Cognitive Examination-Revised (ACE-R) for the cognitive evaluation and classification of 72 non-demented patients with PD. Twenty-eight patients were classified as PD with normal cognition (PD-NC). The remaining 44 were subdivided into the following 2 groups using a hierarchical cluster analysis: 20 with a predominant decrease in memory (PD with amnestic cognitive deficits: PD-A) and 24 with good memory who exhibited a decrease in other sub-domains (PD with non-amnestic cognitive deficits: PD-NA). We used an independent component analysis of RS-fMRI data to investigate the inter-group differences of RSN. Compared to the controls, the PD-A showed lower FC within the ventral default mode network (vDMN) and the visuospatial network. On the other hand, the PD-NA showed lower FC within the visual networks and the cerebellum-brainstem network. Significant differences in the FC within the vDMN and cerebellum-brainstem network were observed between the PD-A and PD-NA, which provided a good discrimination between PD-A and PD-NA using a support vector machine. Distinct patterns of cognitive deficits correspond to different RSN changes.

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