Variant-specific vulnerability in metabolic connectivity and resting-state networks in behavioural variant of frontotemporal dementia. (November 2019)

• Record Type: Journal Article
• Authors: Malpetti, Maura; Carli, Giulia; Sala, Arianna; Cerami, Chiara; Marcone, Alessandra; Iannaccone, Sandro; Magnani, Giuseppe; Perani, Daniela
• Is Part Of: Cortex. Volume 120(2019)
• Page Start: 483
• Page End: 497
• Publication Date: 2019-11
• Subjects: Fluorine-18-flourodeoxiglucose -- Positron emission tomography -- Brain metabolic connectivity -- Behavioural variant of frontotemporal dementia; Neuropsychology -- Periodicals; Nervous system -- Periodicals; Neurology -- Periodicals; Psychophysiology -- Periodicals; Behavior -- Periodicals; Neurology -- Periodicals; 612.825
• DOI: 10.1016/j.cortex.2019.07.018
• Languages: English
• ISSNs: 0010-9452

Abstract

Abstract: Brain connectivity measures represent candidate biomarkers of neuronal dysfunction in neurodegenerative diseases. Previous findings suggest that the behavioural variant of frontotemporal dementia (bvFTD) and its variants (i.e., frontal and temporo-limbic) may be related to the vulnerability of distinct functional connectivity networks. In this study, 82 bvFTD patients were included, and two patient groups were identified as frontal and temporo-limbic bvFTD variants. Two advanced multivariate analytical approaches were applied to FDG-PET data, i.e., sparse inverse covariance estimation (SICE) method and seed-based interregional correlation analysis (IRCA). These advanced methods allowed the assessment of (i) the whole-brain metabolic connectivity, without any a priori assumption, and (ii) the main brain resting-state networks of crucial relevance for cognitive and behavioural functions. In the whole bvFTD group, we found dysfunctional connectivity patterns in frontal and limbic regions and in all major brain resting-state networks as compared to healthy controls (HC N = 82). In the two bvFTD variants, SICE and IRCA analyses identified variant-specific reconfigurations of whole-brain connectivity and resting-state networks. Specifically, the frontal bvFTD variant was characterised by metabolic connectivity alterations in orbitofrontal regions and anterior resting-state networks, while the temporo-limbic bvFTD variant was characterised by connectivity alterations in the limbic and salience networks. These results highlight different neural vulnerabilities in the two bvFTD variants, as shown by the dysfunctional connectivity patterns, with relevance for the different neuropsychological profiles. This new evidence provides further insight in the variability of bvFTD and may contribute to a more accurate classification of these patients.