Structural and functional connectivity in the default mode network in 22q11.2 deletion syndrome

Maria Carmela Padula, Marie Schaer, Maude Schneider, Dimitri Nestor Alice Van De Ville
BioMed Central, 2015
Journal paper

Abstract

Background: The neural endophenotype associated with 22q11.2 deletion syndrome (22q11DS) includes deviant cortical development and alterations in brain connectivity. Resting-state functional magnetic resonance imaging (fMRI) findings also reported disconnectivity within the default mode network (DMN). In this study, we explored the relationship between functional and structural DMN connectivity and their changes with age in patients with 22q11DS in comparison to control participants. Given previous evidence of an association between DMN disconnectivity and the manifestation of psychotic symptoms, we further investigated this relationship in our group of patients with 22q11DS. Methods: T1-weighted, diffusion, and resting-state fMRI scans were acquired from 41 patients with 22q11DS and 43 control participants aged 6 to 28 years. A data-driven approach based on independent component analysis (ICA) was used to identify the DMN and to define regions of interest for the structural and functional connectivity analysis. Prodromal psychotic symptoms were assessed in adolescents and adults using the positive symptom scores of the Structured Interview of Prodromal Syndromes (SIPS). Connectivity measures were compared between groups and correlated with age. Repeating the between-group analysis in three different age bins further assessed the presence of age-related alterations in DMN connectivity. Structural and functional connectivity measures were then correlated with the SIPS scores. Results: A simultaneous reduction of functional and structural connectivity between core medial nodes of the DMN was observed. Furthermore, structural connectivity measures significantly increased with age in the control group but not in patients with 22q11DS, suggesting the presence of an age-related alteration of the DMN structural connections. No correlations were found between the DMN disconnectivity and expression of prodromal symptoms in 22q11DS. Conclusions: These findings indicate the presence of functional and structural DMN disconnectivity in 22q11DS and that patients with 22q11DS fail to develop normal structural connections between medial DMN nodes. This suggests the presence of altered neurodevelopmental trajectories in 22q11DS.

Official source

https://infoscience.epfl.ch/record/212112?ln=en

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Related concepts

Related publications

Maria Carmela Padula, Marie Schaer, Maude Schneider, Dimitri Nestor Alice Van De Ville
BioMed Central, 2015
Journal paper

Abstract

Official source

https://infoscience.epfl.ch/record/212112?ln=en

About this result

Related concepts (14)

Related concepts

Related publications (10)

Related publications

Related publications (10)

Resting-state networks in adolescents with 22q11.2 deletion syndrome: Associations with prodromal symptoms and executive functions

Maude Schneider, Dimitri Nestor Alice Van De Ville

Atypical functional connectivity in the maturing brains of 22q11.2 deletion syndrome (22q11DS) may contribute to the expression of early psychotic symptoms commonly reported by these youths. This study's objective was to examine functional connectivity in cerebral networks at rest (Resting-State Networks; RSNs) and their relationship to symptomatic and neuropsychological characteristics putting them at very high risk factor for developing psychosis. Twenty-seven adolescents with 22q11DS and 33 typically developing control adolescents matched for age, gender and handedness underwent an 8-minute resting state functional MRI session. RSNs identification procedure employed Independent Component Analysis (ICA). We tested for potential group differences in functional connectivity within-networks. Then, we examined relationships between network connectivity and symptomatic/neuropsychological characteristics in the 22q11DS group. A total of nine resting-state networks were identified. Between-group differences suggested both increased and decreased functional connectivity in the 22q11DS group, involving the default-mode, sensorimotor, visuo-spatial, and high level visual networks. Finally, atypical connectivity in the default-mode network, specifically within the left superior frontal gyrus region, correlated with prodromal symptom intensity and neuropsychological performances in the 22q11DS group. The results suggest that atypical functional connectivity may sustain both increased vulnerability to psychosis and characteristic cognitive impairments in 22q11DS. (C) 2012 Elsevier B.V. All rights reserved.

Elsevier2012

Principal components of functional connectivity: A new approach to study dynamic brain connectivity during rest

Nora Leonardi, Jonas Richiardi, Dimitri Nestor Alice Van De Ville

Functional connectivity (FC) as measured by correlation between NM BOLD time courses of distinct brain regions has revealed meaningful organization of spontaneous fluctuations in the resting brain. However, an increasing amount of evidence points to non-stationarity of FC; i.e., FC dynamically changes over time reflecting additional and rich information about brain organization, but representing new challenges for analysis and interpretation. Here, we propose a data-driven approach based on principal component analysis (PCA) to reveal hidden patterns of coherent FC dynamics across multiple subjects. We demonstrate the feasibility and relevance of this new approach by examining the differences in dynamic FC between 13 healthy control subjects and 15 minimally disabled relapse-remitting multiple sclerosis patients. We estimated whole-brain dynamic FC of regionally-averaged BOLD activity using sliding time windows. We then used PCA to identify FC patterns, termed "eigenconnectivities", that reflect meaningful patterns in FC fluctuations. We then assessed the contributions of these patterns to the dynamic FC at any given time point and identified a network of connections centered on the default-mode network with altered contribution in patients. Our results complement traditional stationary analyses, and reveal novel insights into brain connectivity dynamics and their modulation in a neurodegenerative disease. (C) 2013 Elsevier Inc. All rights reserved.

Elsevier2013

, , ,

The clinical picture associated with 22q11.2 deletion syndrome (22q11DS) includes mild mental retardation and an increased risk of schizophrenia. While the clinical phenotype has been related to structural brain network alterations, there is only scarce information about functional connectivity in 22q11DS. However, such studies could lead to a better comprehension of the disease and reveal potential biomarkers for psychosis. A connectivity decoding approach was used to discriminate between 42 patients with 22q11DS and 41 controls using resting-state connectivity. The same method was then applied within the 22q11DS group to identify brain connectivity patterns specifically related to the presence of psychotic symptoms. An accuracy of 84 % was achieved in differentiating patients with 22q11DS from controls. The discriminative connections were widespread, but predominantly located in the bilateral frontal and right temporal lobes, and were significantly correlated to IQ. An 88 % accuracy was obtained for identification of existing psychotic symptoms within the patients group. The regions containing most discriminative connections included the anterior cingulate cortex (ACC), the left superior temporal and the right inferior frontal gyri. Functional connectivity alterations in 22q11DS affect mostly frontal and right temporal lobes and are related to the syndrome's mild mental retardation. These results also provide evidence that resting-state connectivity can potentially become a biomarker for psychosis and that ACC plays an important role in the development of psychotic symptoms.

Springer Verlag2014