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dc.contributor.authorVettore, Martina
dc.contributor.authorDe Marco, Matteo
dc.contributor.authorPallucca, Claudia
dc.contributor.authorBendini, Matteo
dc.contributor.authorGallucci, Maurizio
dc.contributor.authorVenneri, Annalena
dc.date.accessioned2021-10-21T07:31:16Z
dc.date.available2021-10-21T07:31:16Z
dc.date.issued2021
dc.date.submitted2021-07-06
dc.identifier.issn1663-4365
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/329702
dc.description.abstract"Mild cognitive impairment" (MCI) is a diagnosis characterised by deficits in episodic memory (aMCI) or in other non-memory domains (naMCI). Although the definition of subtypes is helpful in clinical classification, it provides little insight on the variability of neurofunctional mechanisms (i.e., resting-state brain networks) at the basis of symptoms. In particular, it is unknown whether the presence of a high load of white-matter hyperintensities (WMHs) has a comparable effect on these functional networks in aMCI and naMCI patients. This question was addressed in a cohort of 123 MCI patients who had completed an MRI protocol inclusive of T1-weighted, fluid-attenuated inversion recovery (FLAIR) and resting-state fMRI sequences. T1-weighted and FLAIR images were processed with the Lesion Segmentation Toolbox to quantify whole-brain WMH volumes. The CONN toolbox was used to preprocess all fMRI images and to run an independent component analysis for the identification of four large-scale haemodynamic networks of cognitive relevance (i.e., default-mode, salience, left frontoparietal, and right frontoparietal networks) and one control network (i.e., visual network). Patients were classified based on MCI subtype (i.e., aMCI vs. naMCI) and WMH burden (i.e., low vs. high). Maps of large-scale networks were then modelled as a function of the MCI subtype-by-WMH burden interaction. Beyond the main effects of MCI subtype and WMH burden, a significant interaction was found in the salience and left frontoparietal networks. Having a low WMH burden was significantly more associated with stronger salience-network connectivity in aMCI (than in naMCI) in the right insula, and with stronger left frontoparietal-network connectivity in the right frontoinsular cortex. Vice versa, having a low WMH burden was significantly more associated with left-frontoparietal network connectivity in naMCI (than in aMCI) in the left mediotemporal lobe. The association between WMH burden and strength of connectivity of resting-state functional networks differs between aMCI and naMCI patients. Although exploratory in nature, these findings indicate that clinical profiles reflect mechanistic interactions that may play a central role in the definition of diagnostic and prognostic statuses.
dc.languageen
dc.publisherFrontiers Media SA
dc.subjectNeuroscience
dc.subjectdementia
dc.subjectAlzheimer’s disease
dc.subjecthaemodynamic
dc.subjectsmall vessel disease
dc.subjectindependent component analysis
dc.titleWhite-Matter Hyperintensity Load and Differences in Resting-State Network Connectivity Based on Mild Cognitive Impairment Subtype.
dc.typeArticle
dc.date.updated2021-10-21T07:31:15Z
prism.publicationNameFront Aging Neurosci
prism.volume13
dc.identifier.doi10.17863/CAM.77148
dcterms.dateAccepted2021-09-09
rioxxterms.versionofrecord10.3389/fnagi.2021.737359
rioxxterms.versionVoR
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by/4.0/
dc.identifier.eissn1663-4365
cam.issuedOnline2021-10-07


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