The segregated connectome of late-life depression: a combined cortical thickness and structural covariance analysis

Late-life depression (LLD) has been associated with both generalized and focal neuroanatomical changes including gray matter atrophy and white matter abnormalities. However, previous literature has not been consistent and, in particular, its impact on the topology organization of brain networks rema...

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Main Authors:	Mak, Elijah, Colloby, Sean J., Thomas, Alan, O'Brien, John T.
Format:	Online
Language:	English
Published:	Elsevier 2016
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5096887/

id	pubmed-5096887
recordtype	oai_dc
spelling	pubmed-50968872016-12-01 The segregated connectome of late-life depression: a combined cortical thickness and structural covariance analysis Mak, Elijah Colloby, Sean J. Thomas, Alan O'Brien, John T. Regular Article Late-life depression (LLD) has been associated with both generalized and focal neuroanatomical changes including gray matter atrophy and white matter abnormalities. However, previous literature has not been consistent and, in particular, its impact on the topology organization of brain networks remains to be established. In this multimodal study, we first examined cortical thickness, and applied graph theory to investigate structural covariance networks in LLD. Thirty-three subjects with LLD and 25 controls underwent T1-weighted, fluid-attenuated inversion recovery and clinical assessments. Freesurfer was used to perform vertex-wise comparisons of cortical thickness, whereas the Graph Analysis Toolbox (GAT) was implemented to construct and analyze the structural covariance networks. LLD showed a trend of lower thickness in the left insular region (p < 0.001 uncorrected). In addition, the structural network of LLD was characterized by greater segregation, particularly showing higher transitivity (i.e., measure of clustering) and modularity (i.e., tendency for a network to be organized into subnetworks). It was also less robust against random failure and targeted attacks. Despite relative cortical preservation, the topology of the LLD network showed significant changes particularly in segregation. These findings demonstrate the potential for graph theoretical approaches to complement conventional structural imaging analyses and provide novel insights into the heterogeneous etiology and pathogenesis of LLD. Elsevier 2016-12 /pmc/articles/PMC5096887/ /pubmed/27721203 http://dx.doi.org/10.1016/j.neurobiolaging.2016.08.013 Text en © 2016 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	Mak, Elijah Colloby, Sean J. Thomas, Alan O'Brien, John T.
spellingShingle	Mak, Elijah Colloby, Sean J. Thomas, Alan O'Brien, John T. The segregated connectome of late-life depression: a combined cortical thickness and structural covariance analysis
author_facet	Mak, Elijah Colloby, Sean J. Thomas, Alan O'Brien, John T.
author_sort	Mak, Elijah
title	The segregated connectome of late-life depression: a combined cortical thickness and structural covariance analysis
title_short	The segregated connectome of late-life depression: a combined cortical thickness and structural covariance analysis
title_full	The segregated connectome of late-life depression: a combined cortical thickness and structural covariance analysis
title_fullStr	The segregated connectome of late-life depression: a combined cortical thickness and structural covariance analysis
title_full_unstemmed	The segregated connectome of late-life depression: a combined cortical thickness and structural covariance analysis
title_sort	segregated connectome of late-life depression: a combined cortical thickness and structural covariance analysis
description	Late-life depression (LLD) has been associated with both generalized and focal neuroanatomical changes including gray matter atrophy and white matter abnormalities. However, previous literature has not been consistent and, in particular, its impact on the topology organization of brain networks remains to be established. In this multimodal study, we first examined cortical thickness, and applied graph theory to investigate structural covariance networks in LLD. Thirty-three subjects with LLD and 25 controls underwent T1-weighted, fluid-attenuated inversion recovery and clinical assessments. Freesurfer was used to perform vertex-wise comparisons of cortical thickness, whereas the Graph Analysis Toolbox (GAT) was implemented to construct and analyze the structural covariance networks. LLD showed a trend of lower thickness in the left insular region (p < 0.001 uncorrected). In addition, the structural network of LLD was characterized by greater segregation, particularly showing higher transitivity (i.e., measure of clustering) and modularity (i.e., tendency for a network to be organized into subnetworks). It was also less robust against random failure and targeted attacks. Despite relative cortical preservation, the topology of the LLD network showed significant changes particularly in segregation. These findings demonstrate the potential for graph theoretical approaches to complement conventional structural imaging analyses and provide novel insights into the heterogeneous etiology and pathogenesis of LLD.
publisher	Elsevier
publishDate	2016
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5096887/
_version_	1613714508041158656

The segregated connectome of late-life depression: a combined cortical thickness and structural covariance analysis

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