Dataset Information

Distinct network topology in Alzheimer's disease and behavioral variant frontotemporal dementia.

ABSTRACT:

Background

Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) cause distinct atrophy and functional disruptions within two major intrinsic brain networks, namely the default network and the salience network, respectively. It remains unclear if inter-network relationships and whole-brain network topology are also altered and underpin cognitive and social-emotional functional deficits.

Methods

In total, 111 participants (50?AD, 14 bvFTD, and 47 age- and gender-matched healthy controls) underwent resting-state functional magnetic resonance imaging (fMRI) and neuropsychological assessments. Functional connectivity was derived among 144 brain regions of interest. Graph theoretical analysis was applied to characterize network integration, segregation, and module distinctiveness (degree centrality, nodal efficiency, within-module degree, and participation coefficient) in AD, bvFTD, and healthy participants. Group differences in graph theoretical measures and empirically derived network community structures, as well as the associations between these indices and cognitive performance and neuropsychiatric symptoms, were subject to general linear models, with age, gender, education, motion, and scanner type controlled.

Results

Our results suggested that AD had lower integration in the default and control networks, while bvFTD exhibited disrupted integration in the salience network. Interestingly, AD and bvFTD had the highest and lowest degree of integration in the thalamus, respectively. Such divergence in topological aberration was recapitulated in network segregation and module distinctiveness loss, with AD showing poorer modular structure between the default and control networks, and bvFTD having more fragmented modules in the salience network and subcortical regions. Importantly, aberrations in network topology were related to worse attention deficits and greater severity in neuropsychiatric symptoms across syndromes.

Conclusions

Our findings underscore the reciprocal relationships between the default, control, and salience networks that may account for the cognitive decline and neuropsychiatric symptoms in dementia.

SUBMITTER: Ng ASL

PROVIDER: S-EPMC7786961 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Distinct network topology in Alzheimer's disease and behavioral variant frontotemporal dementia.

Ng Adeline Su Lyn ASL Wang Juan J Ng Kwun Kei KK Chong Joanna Su Xian JSX Qian Xing X Lim Joseph Kai Wei JKW Tan Yi Jayne YJ Yong Alisa Cui Wen ACW Chander Russell Jude RJ Hameed Shahul S Ting Simon Kang Seng SKS Kandiah Nagaendran N Zhou Juan Helen JH

Alzheimer's research & therapy 20210106 1

<h4>Background</h4>Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) cause distinct atrophy and functional disruptions within two major intrinsic brain networks, namely the default network and the salience network, respectively. It remains unclear if inter-network relationships and whole-brain network topology are also altered and underpin cognitive and social-emotional functional deficits.<h4>Methods</h4>In total, 111 participants (50 AD, 14 bvFTD, and 47 age- and ...[more]

PMID: 33407913

Similar Datasets

Project description:ImportanceClearer delineation of the phenotypic heterogeneity within behavioral variant frontotemporal dementia (bvFTD) will help uncover underlying biological mechanisms and improve clinicians' ability to predict disease course and to design targeted management strategies.ObjectiveTo identify subtypes of bvFTD syndrome based on distinctive patterns of atrophy defined by selective vulnerability of specific functional networks targeted in bvFTD using statistical classification approaches.Design, setting and participantsIn this retrospective observational study, 90 patients meeting the Frontotemporal Dementia Consortium consensus criteria for bvFTD underwent evaluation at the Memory and Aging Center of the Department of Neurology at University of California, San Francisco. Patients underwent a multidisciplinary clinical evaluation, including clinical demographics, genetic testing, symptom evaluation, neurologic examination, neuropsychological bedside testing, and socioemotional assessments. All patients underwent structural magnetic resonance imaging at their earliest evaluation at the memory clinic. From each patient's structural imaging scans, the mean volumes of 18 regions of interest (ROI) constituting the functional networks specifically vulnerable in bvFTD, including the salience network (SN), with key nodes in the frontoinsula and pregenual anterior cingulate, and the semantic appraisal network (SAN), anchored in the anterior temporal lobe and subgenual cingulate, were estimated. Principal component and cluster analyses of ROI volumes were used to identify patient clusters with anatomically distinct atrophy patterns. Data were collected from from June 19, 2002, to January 13, 2015.Main outcomes and measuresEvaluation of brain morphology and other clinical features, including presenting symptoms, neurologic examination signs, neuropsychological performance, rate of dementia progression, and socioemotional function, in each patient cluster.ResultsNinety patients (54 men [60%]; 36 women [40%]; mean [SD] age at evaluation, 55.1 [9.7] years) were included in the analysis. Four subgroups of patients with bvFTD with distinct anatomic patterns of network degeneration were identified, including 2 salience network-predominant subgroups (frontal/temporal [SN-FT] and frontal [SN-F]), a semantic appraisal network-predominant group (SAN), and a subcortical-predominant group. Subgroups demonstrated distinct patterns of cognitive, socioemotional, and motor symptoms, as well as genetic compositions and estimated rates of disease progression.Conclusions and relevanceDivergent patterns of vulnerability in specific functional network components make an important contribution to the clinical heterogeneity of bvFTD. The data-driven anatomic classification identifies biologically meaningful anatomic phenotypes and provides a replicable approach to disambiguate the bvFTD syndrome.

Project description:Resting-state or intrinsic connectivity network functional magnetic resonance imaging provides a new tool for mapping large-scale neural network function and dysfunction. Recently, we showed that behavioural variant frontotemporal dementia and Alzheimer's disease cause atrophy within two major networks, an anterior 'Salience Network' (atrophied in behavioural variant frontotemporal dementia) and a posterior 'Default Mode Network' (atrophied in Alzheimer's disease). These networks exhibit an anti-correlated relationship with each other in the healthy brain. The two diseases also feature divergent symptom-deficit profiles, with behavioural variant frontotemporal dementia undermining social-emotional function and preserving or enhancing visuospatial skills, and Alzheimer's disease showing the inverse pattern. We hypothesized that these disorders would exert opposing connectivity effects within the Salience Network (disrupted in behavioural variant frontotemporal dementia but enhanced in Alzheimer's disease) and the Default Mode Network (disrupted in Alzheimer's disease but enhanced in behavioural variant frontotemporal dementia). With task-free functional magnetic resonance imaging, we tested these ideas in behavioural variant frontotemporal dementia, Alzheimer's disease and healthy age-matched controls (n = 12 per group), using independent component analyses to generate group-level network contrasts. As predicted, behavioural variant frontotemporal dementia attenuated Salience Network connectivity, most notably in frontoinsular, cingulate, striatal, thalamic and brainstem nodes, but enhanced connectivity within the Default Mode Network. Alzheimer's disease, in contrast, reduced Default Mode Network connectivity to posterior hippocampus, medial cingulo-parieto-occipital regions and the dorsal raphe nucleus, but intensified Salience Network connectivity. Specific regions of connectivity disruption within each targeted network predicted intrinsic connectivity enhancement within the reciprocal network. In behavioural variant frontotemporal dementia, clinical severity correlated with loss of right frontoinsular Salience Network connectivity and with biparietal Default Mode Network connectivity enhancement. Based on these results, we explored whether a combined index of Salience Network and Default Mode Network connectivity might discriminate between the three groups. Linear discriminant analysis achieved 92% clinical classification accuracy, including 100% separation of behavioural variant frontotemporal dementia and Alzheimer's disease. Patients whose clinical diagnoses were supported by molecular imaging, genetics, or pathology showed 100% separation using this method, including four diagnostically equivocal 'test' patients not used to train the algorithm. Overall, the findings suggest that behavioural variant frontotemporal dementia and Alzheimer's disease lead to divergent network connectivity patterns, consistent with known reciprocal network interactions and the strength and deficit profiles of the two disorders. Further developed, intrinsic connectivity network signatures may provide simple, inexpensive, and non-invasive biomarkers for dementia differential diagnosis and disease monitoring.

Dataset Information

Distinct network topology in Alzheimer's disease and behavioral variant frontotemporal dementia.

Background

Methods

Results

Conclusions

Publications

Distinct network topology in Alzheimer's disease and behavioral variant frontotemporal dementia.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure