Dataset Information

Neuronal dysfunction and disconnection of cortical hubs in non-demented subjects with elevated amyloid burden.

ABSTRACT: Disruption of functional connectivity between brain regions may represent an early functional consequence of ?-amyloid pathology prior to clinical Alzheimer's disease. We aimed to investigate if non-demented older individuals with increased amyloid burden demonstrate disruptions of functional whole-brain connectivity in cortical hubs (brain regions typically highly connected to multiple other brain areas) and if these disruptions are associated with neuronal dysfunction as measured with fluorodeoxyglucose-positron emission tomography. In healthy subjects without cognitive symptoms and patients with mild cognitive impairment, we used positron emission tomography to assess amyloid burden and cerebral glucose metabolism, structural magnetic resonance imaging to quantify atrophy and novel resting state functional magnetic resonance imaging processing methods to calculate whole-brain connectivity. Significant disruptions of whole-brain connectivity were found in amyloid-positive patients with mild cognitive impairment in typical cortical hubs (posterior cingulate cortex/precuneus), strongly overlapping with regional hypometabolism. Subtle connectivity disruptions and hypometabolism were already present in amyloid-positive asymptomatic subjects. Voxel-based morphometry measures indicate that these findings were not solely a consequence of regional atrophy. Whole-brain connectivity values and metabolism showed a positive correlation with each other and a negative correlation with amyloid burden. These results indicate that disruption of functional connectivity and hypometabolism may represent early functional consequences of emerging molecular Alzheimer's disease pathology, evolving prior to clinical onset of dementia. The spatial overlap between hypometabolism and disruption of connectivity in cortical hubs points to a particular susceptibility of these regions to early Alzheimer's-type neurodegeneration and may reflect a link between synaptic dysfunction and functional disconnection.

SUBMITTER: Drzezga A

PROVIDER: S-EPMC3102239 | biostudies-literature | 2011 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Neuronal dysfunction and disconnection of cortical hubs in non-demented subjects with elevated amyloid burden.

Drzezga Alexander A Becker J Alex JA Van Dijk Koene R A KR Sreenivasan Aishwarya A Talukdar Tanveer T Sullivan Caroline C Schultz Aaron P AP Sepulcre Jorge J Putcha Deepti D Greve Doug D Johnson Keith A KA Sperling Reisa A RA

Brain : a journal of neurology 20110413 Pt 6

Disruption of functional connectivity between brain regions may represent an early functional consequence of β-amyloid pathology prior to clinical Alzheimer's disease. We aimed to investigate if non-demented older individuals with increased amyloid burden demonstrate disruptions of functional whole-brain connectivity in cortical hubs (brain regions typically highly connected to multiple other brain areas) and if these disruptions are associated with neuronal dysfunction as measured with fluorode ...[more]

PMID: 21490054

Similar Datasets

Project description:As more biomarkers for Alzheimer's disease and age-related brain conditions become available, more sophisticated analytic approaches are needed to take full advantage of the information they convey. Most work has been done using categorical approaches but the joint relationships of tau PET, amyloid PET and cortical thickness in their continuous distributions to cognition have been under-explored. We evaluated non-demented subjects over age 50 years in the Mayo Clinic Study of Aging, 2037 of whom had undergone 3 T MRI scan, 985 amyloid PET scan with 11C-Pittsburgh compound B (PIB) and MRI, and 577 PIB-PET, 18F-AV1451 flortaucipir PET and MRI. Participants received a nine-test cognitive battery. Three test scores (logical memory delayed recall, visual reproduction delayed recall and auditory verbal learning test delayed recall) were used to generate a memory composite z-score. We used Gradient Boosting Machine models to analyse the relationship between regional cortical thickness, flortaucipir PET signal, PIB-PET signal and memory z-scores. Age, education, sex and number of test exposures were included in the model as covariates. In this population-based study of non-demented subjects, most of the associations between biomarkers and memory z-scores accrued after 70 years of age. Entorhinal cortex exhibited the strongest associations between biomarkers and memory z-scores. Other temporal regions showed similar but attenuated associations, and non-temporal regions had negligible associations between memory z-scores and biomarkers. Entorhinal flortaucipir PET signal, PIB-PET signal and entorhinal cortical thickness were independently and additively associated with declining memory z-scores. In contrast to global PIB-PET signal where only very high amyloid-β levels were associated low memory z-scores, entorhinal flortaucipir PET signal just above background levels was associated with low memory z-scores. The lowest memory z-scores occurred with the confluence of elevated entorhinal flortaucipir PET signal and lower entorhinal cortical thickness.

Project description:Traumatic brain injury affects brain connectivity by producing traumatic axonal injury. This disrupts the function of large-scale networks that support cognition. The best way to describe this relationship is unclear, but one elegant approach is to view networks as graphs. Brain regions become nodes in the graph, and white matter tracts the connections. The overall effect of an injury can then be estimated by calculating graph metrics of network structure and function. Here we test which graph metrics best predict the presence of traumatic axonal injury, as well as which are most highly associated with cognitive impairment. A comprehensive range of graph metrics was calculated from structural connectivity measures for 52 patients with traumatic brain injury, 21 of whom had microbleed evidence of traumatic axonal injury, and 25 age-matched controls. White matter connections between 165 grey matter brain regions were defined using tractography, and structural connectivity matrices calculated from skeletonized diffusion tensor imaging data. This technique estimates injury at the centre of tract, but is insensitive to damage at tract edges. Graph metrics were calculated from the resulting connectivity matrices and machine-learning techniques used to select the metrics that best predicted the presence of traumatic brain injury. In addition, we used regularization and variable selection via the elastic net to predict patient behaviour on tests of information processing speed, executive function and associative memory. Support vector machines trained with graph metrics of white matter connectivity matrices from the microbleed group were able to identify patients with a history of traumatic brain injury with 93.4% accuracy, a result robust to different ways of sampling the data. Graph metrics were significantly associated with cognitive performance: information processing speed (R(2) = 0.64), executive function (R(2) = 0.56) and associative memory (R(2) = 0.25). These results were then replicated in a separate group of patients without microbleeds. The most influential graph metrics were betweenness centrality and eigenvector centrality, which provide measures of the extent to which a given brain region connects other regions in the network. Reductions in betweenness centrality and eigenvector centrality were particularly evident within hub regions including the cingulate cortex and caudate. Our results demonstrate that betweenness centrality and eigenvector centrality are reduced within network hubs, due to the impact of traumatic axonal injury on network connections. The dominance of betweenness centrality and eigenvector centrality suggests that cognitive impairment after traumatic brain injury results from the disconnection of network hubs by traumatic axonal injury.

Project description:ImportanceThe Anti-Amyloid Treatment in Asymptomatic Alzheimer disease (A4) Study is an ongoing prevention trial in clinically normal older individuals with evidence of elevated brain amyloid. The large number of participants screened with amyloid positron emission tomography (PET) and standardized assessments provides an unprecedented opportunity to evaluate factors associated with elevated brain amyloid.ObjectiveTo investigate the association of elevated amyloid with demographic and lifestyle factors, apolipoprotein E (APOE), neuropsychological testing, and self- and study partner reports of cognitive function.Design, setting, and participantsThis cross-sectional study included screening data in the Anti-Amyloid Treatment in Asymptomatic Alzheimer Disease (A4) Study collected from April 2014 to December 2017 and classified by amyloid status. Data were was analyzed from 2018 to 2019 across 67 sites in the US, Canada, Australia, and Japan and included 4486 older individuals (age 65-85 years) who were eligible for amyloid PET (clinically normal [Clinical Dementia Rating = 0] and cognitively unimpaired [Mini-Mental State Examination score, ≥25; logical memory IIa 6-18]).Main outcomes and measuresScreening demographics, lifestyle variables, APOE genotyping, and cognitive testing (Preclinical Alzheimer Cognitive Composite), self- and study partner reports of high-level daily cognitive function (Cognitive Function Index). Florbetapir amyloid PET imaging was used to classify participants as having elevated amyloid (Aβ+) or not having elevated amyloid (Aβ-).ResultsAmyloid PET results were acquired for 4486 participants (mean [SD] age, 71.29 [4.67] years; 2647 women [59%]), with 1323 (29.5%) classified as Aβ+. Aβ+ participants were slightly older than Aβ-, with no observed differences in sex, education, marital or retirement status, or any self-reported lifestyle factors. Aβ+ participants were more likely to have a family history of dementia (3320 Aβ+ [74%] vs 3050 Aβ- [68%]) and at least 1 APOE ε4 allele (2602 Aβ+ [58%] vs 1122 Aβ- [25%]). Aβ+ participants demonstrated worse performance on screening Preclinical Alzheimer Cognitive Composite results and reported higher change scores on the Cognitive Function Index.Conclusions and relevanceAmong a large group of older individuals screening for an Alzheimer disease (AD) prevention trial, elevated brain amyloid was associated with family history and APOE ε4 allele but not with multiple other previously reported risk factors for AD. Elevated amyloid was associated with lower test performance results and increased reports of subtle recent declines in daily cognitive function. These results support the hypothesis that elevated amyloid represents an early stage in the Alzheimer continuum and demonstrate the feasibility of enrolling these high-risk participants in secondary prevention trials aimed at slowing cognitive decline during the preclinical stages of AD.

Project description:ImportanceEmotional and behavioral symptoms in cognitively normal older people may be direct manifestations of Alzheimer disease (AD) pathophysiology at the preclinical stage, prior to the onset of mild cognitive impairment. Loneliness is a perceived state of social and emotional isolation that has been associated with cognitive and functional decline and an increased risk of incident AD dementia. We hypothesized that loneliness might occur in association with elevated cortical amyloid burden, an in vivo research biomarker of AD.ObjectiveTo determine whether cortical amyloid burden is associated with greater loneliness in cognitively normal older adults.Design, setting, and participantsCross-sectional analyses using data from the Harvard Aging Brain Study of 79 cognitively normal, community-dwelling participants. A continuous, aggregate measure of cortical amyloid burden, determined by Pittsburgh Compound B-positron emission tomography (PiB-PET), was examined in association with loneliness in linear regression models adjusting for age, sex, apolipoprotein E ε4 (APOEε4), socioeconomic status, depression, anxiety, and social network (without and with the interaction of amyloid and APOEε4). We also quantified the association of high amyloid burden (amyloid-positive group) to loneliness (lonely group) using logistic regression, controlling for the same covariates, with the amyloid-positive group and the lonely group, each composing 32% of the sample (n = 25).Main outcomes and measuresLoneliness, as determined by the 3-item UCLA Loneliness Scale (possible range, 3-12, with higher score indicating greater loneliness).ResultsThe 79 participants included 43 women and 36 men with a mean (SD) age of 76.4 (6.2) years. Mean (SD) cortical amyloid burden via PiB-PET was 1.230 (0.209), and the mean (SD) UCLA-3 loneliness score was 5.3 (1.8). Twenty-two (28%) had positive APOEε4 carrier status, and 25 (32%) were in the amyloid-positive group with cortical PiB distribution volume ratio greater than 1.2. Controlling for age, sex, APOEε4, socioeconomic status, depression, anxiety, and social network, we found that higher amyloid burden was significantly associated with greater loneliness: compared with individuals in the amyloid-negative group, those in the amyloid-positive group were 7.5-fold (95% CI, 1.7-fold to 34.0-fold) more likely to be classified as lonely than nonlonely (β = 3.3, partial r = 0.4, P = .002). Furthermore, the association of high amyloid burden and loneliness was stronger in APOEε4 carriers than in noncarriers.Conclusions and relevanceWe report a novel association of loneliness with cortical amyloid burden in cognitively normal older adults, suggesting that loneliness is a neuropsychiatric symptom relevant to preclinical AD. This work will inform new research into the neural underpinnings and disease mechanisms involved in loneliness and may enhance early detection and intervention research in AD.

Dataset Information

Neuronal dysfunction and disconnection of cortical hubs in non-demented subjects with elevated amyloid burden.

Publications

Neuronal dysfunction and disconnection of cortical hubs in non-demented subjects with elevated amyloid burden.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets