Literature DB >> 27673479

DTI-based connectome analysis of adolescents with major depressive disorder reveals hypoconnectivity of the right caudate.

Olga Tymofiyeva1, Colm G Connolly2, Tiffany C Ho3, Matthew D Sacchet3, Eva Henje Blom4, Kaja Z LeWinn2, Duan Xu5, Tony T Yang2.   

Abstract

BACKGROUND: Adolescence is a vulnerable period for the onset of major depressive disorder (MDD). While some studies have shown white matter alterations in adolescent MDD, there is still a gap in understanding how the brain is affected at a network level.
METHODS: We compared diffusion tensor imaging (DTI)-based brain networks in a cohort of 57 adolescents with MDD and 41 well-matched healthy controls who completed self-reports of depression symptoms and stressful life events. Using atlas-based brain regions as network nodes and tractography streamline count or mean fractional anisotropy (FA) as edge weights, we examined weighted local and global network properties and performed Network-Based Statistic (NBS) analysis.
RESULTS: While there were no significant group differences in the global network properties, the FA-weighted node strength of the right caudate was significantly lower in depressed adolescents and correlated positively with age across both groups. The NBS analysis revealed a cluster of lower FA-based connectivity in depressed subjects centered on the right caudate, including connections to frontal gyri, insula, and anterior cingulate. Within this cluster, the most robust difference between groups was the connection between the right caudate and middle frontal gyrus. This connection showed a significant diagnosis by stress interaction and a negative correlation with total stress in depressed adolescents. LIMITATIONS: Use of DTI-based tractography, one atlas-based parcellation, and FA values to characterize brain networks represent this study's limitations.
CONCLUSIONS: Our results allowed us to suggest caudate-centric models of dysfunctional processes underlying adolescent depression, which might guide future studies and help better understand and treat this disorder.
Copyright © 2016 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Adolescence; Brain; Caudate; Connectomics; Depression; Diffusion; Graph theory; MRI; Neural network; Tractography

Mesh:

Year:  2016        PMID: 27673479      PMCID: PMC5107159          DOI: 10.1016/j.jad.2016.09.013

Source DB:  PubMed          Journal:  J Affect Disord        ISSN: 0165-0327            Impact factor:   4.839


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