Dataset Information

Divergent patterns of loss of interpersonal warmth in frontotemporal dementia syndromes are predicted by altered intrinsic network connectivity.

ABSTRACT: Loss of warmth is well-documented in behavioral variant frontotemporal dementia (bvFTD) and semantic variant primary progressive aphasia (svPPA) at a group level, and has been linked to salience (SN) and semantic-appraisal (SAN) network atrophy. However, clinical observations of individual patients show much greater heterogeneity, thus measuring this clinical variability and identifying the underlying neurologic mechanisms is a critical step for understanding the symptom profile of any one patient. We used reliable change indexes with premorbid and current informant-based evaluations to characterize patterns of change on the warmth subscale of the Interpersonal Adjective Scale (IAS) questionnaire in 132 patients (21 bvFTD, 19 svPPA, 22 nonfluent variant primary progressive aphasia [nfvPPA], 37 Alzheimer's disease [AD]) and 33 healthy older adults. We investigated whether individual differences in warmth change were reflected in SN or SAN functional connectivity, or structural volume of individual brain regions in these two networks. Though one subset of patients showed significant drop in warmth to abnormally low levels (bvFTD: 38%; svPPA: 21%; nfvPPA: 5%; AD: 11%), a second subset significantly dropped but remained within the clinically normal range (bvFTD: 33%; svPPA: 21%; nfvPPA: 9%; AD: 5%), and a third subset did not drop and stayed in the clinically normal range (bvFTD: 29%; svPPA: 58%; nfvPPA: 86%; AD: 84%). Furthermore, interpersonal warmth score was strongly predicted by SN functional connectivity (p?

SUBMITTER: Toller G

PROVIDER: S-EPMC6403437 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Divergent patterns of loss of interpersonal warmth in frontotemporal dementia syndromes are predicted by altered intrinsic network connectivity.

Toller Gianina G Yang Winson F Z WFZ Brown Jesse A JA Ranasinghe Kamalini G KG Shdo Suzanne M SM Kramer Joel H JH Seeley William W WW Miller Bruce L BL Rankin Katherine P KP

NeuroImage. Clinical 20190223

Loss of warmth is well-documented in behavioral variant frontotemporal dementia (bvFTD) and semantic variant primary progressive aphasia (svPPA) at a group level, and has been linked to salience (SN) and semantic-appraisal (SAN) network atrophy. However, clinical observations of individual patients show much greater heterogeneity, thus measuring this clinical variability and identifying the underlying neurologic mechanisms is a critical step for understanding the symptom profile of any one patie ...[more]

PMID: 30836325

Similar Datasets

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.

Project description:BACKGROUND:Diagnosing frontotemporal dementia may be challenging. New methods for analysis of regional brain atrophy patterns on magnetic resonance imaging (MRI) could add to the diagnostic assessment. Therefore, we aimed to develop automated imaging biomarkers for differentiating frontotemporal dementia subtypes from other diagnostic groups, and from one another. METHODS:In this retrospective multicenter cohort study, we included 1213 patients (age 67 ± 9, 48% females) from two memory clinic cohorts: 116 frontotemporal dementia, 341 Alzheimer's disease, 66 Dementia with Lewy bodies, 40 vascular dementia, 104 other dementias, 229 mild cognitive impairment, and 317 subjective cognitive decline. Three MRI atrophy biomarkers were derived from the normalized volumes of automatically segmented cortical regions: 1) the anterior vs. posterior index, 2) the asymmetry index, and 3) the temporal pole left index. We used the following performance metrics: area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. To account for the low prevalence of frontotemporal dementia we pursued a high specificity of 95%. Cross-validation was used in assessing the performance. The generalizability was assessed in an independent cohort (n = 200). RESULTS:The anterior vs. posterior index performed with an AUC of 83% for differentiation of frontotemporal dementia from all other diagnostic groups (Sensitivity = 59%, Specificity = 95%, positive likelihood ratio = 11.8, negative likelihood ratio = 0.4). The asymmetry index showed highest performance for separation of primary progressive aphasia and behavioral variant frontotemporal dementia (AUC = 85%, Sensitivity = 79%, Specificity = 92%, positive likelihood ratio = 9.9, negative likelihood ratio = 0.2), whereas the temporal pole left index was specific for detection of semantic variant primary progressive aphasia (AUC = 85%, Sensitivity = 82%, Specificity = 80%, positive likelihood ratio = 4.1, negative likelihood ratio = 0.2). The validation cohort provided corresponding results for the anterior vs. posterior index and temporal pole left index. CONCLUSION:This study presents three quantitative MRI biomarkers, which could provide additional information to the diagnostic assessment and assist clinicians in diagnosing frontotemporal dementia.

Dataset Information

Divergent patterns of loss of interpersonal warmth in frontotemporal dementia syndromes are predicted by altered intrinsic network connectivity.

Publications

Divergent patterns of loss of interpersonal warmth in frontotemporal dementia syndromes are predicted by altered intrinsic network connectivity.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets