Therefore, we hypothesised that tau pathology may contribute to impaired network organisation in AD. Intraneuronal tau is thought to be more closely linked to synaptic function, brain integrity and clinical symptoms, than AОІ plaques. Moreover, GM network disruptions have been related to increased AОІ pathology, while influences of tau pathology on GM brain networks remain unknown. Previous studies have shown GM network disruptions in preclinical AD, mild cognitive impairment, and AD dementia.

One method to assess brain connectivity consists of measuring the similarity of cortical grey matter (GM) morphology, based on the notion that brain regions that engage in similar cognitive or behavioural processes tend to develop in a homologous way through functional coactivation and/or axonal connectivity between brain regions. Given that brain network abnormalities can already be observed in pre-dementia stages and contribute to cognitive impairment in AD, further clarification on the interrelations between brain connectivity with key pathological aggregates of AD could increase our understanding on the pathogenesis of AD. However, the sequence and interactions of the pathophysiological processes and structural brain changes that occur during this long pre-dementia period are not well understood. This might reflect a reduced communication between neighbouring brain areas and an altered ability to integrate information from distributed brain regions with tau pathology, indicative of a more random network topology across different AD stages.ДЄlzheimerвЂ™s disease (AD) is generally thought to start with the aggregation of amyloid-ОІ (AОІ) in the brain, followed by deposition of neocortical tau pathology, synaptic dysfunction, atrophy, and cognitive decline. Our data suggest a close relationship between grey matter network disruptions and tau pathology in individuals with abnormal amyloid. Moreover, the association between higher tau load and lower cognitive performance was only partly mediated (9.3 to 9.5%) through small world topology. Already in CU AОІ-positive individuals associations between tau burden and lower clustering and path length were observed, whereas in advanced disease stages elevated tau pathology was progressively associated with more brain network abnormalities. ResultsДЄcross the whole sample, we found that higher tau load in the temporal meta-ROI was associated with significant changes in degree, clustering, path length, and small world values (all p <вЂ‰0.001), indicative of a less optimal network organisation. Finally, we tested whether the association of tau pathology with cognitive performance was mediated by grey matter network disruptions. Associations between tau positron emission tomography (PET) values and global and regional network measures were examined using linear regression models adjusted for age, sex, and total intracranial volume. Single-subject grey matter networks were extracted from T1-weighted images and graph theory properties including degree, clustering coefficient, path length, and small world topology were calculated. We included 533 individuals (178 AОІ-negative cognitively unimpaired (CU) subjects, 105 AОІ-positive CU subjects, 122 AОІ-positive patients with mild cognitive impairment, and 128 patients with AD dementia) from the BioFINDER-2 study.

We aimed to assess the relationship between tau aggregation and grey matter network alterations across the AD continuum. Based on previously reported associations between tau pathology, synaptic density and brain structural measures, tau-related connectivity changes across different stages of AD might be expected.

However, the role of tau pathology on grey matter networks remains unclear. Changes in grey matter covariance networks have been reported in preclinical and clinical stages of AlzheimerвЂ™s disease (AD) and have been associated with amyloid-ОІ (AОІ) deposition and cognitive decline.

Knut Miller Atlas Of Anatomy