title: Anomalous gray matter structural networks in major depressive disorder.
abstract: BACKGROUND
  Major depressive disorder (MDD) is characterized by abnormalities in structure, function, and connectivity in several brain regions. Few studies have examined how these regions are organized in the brain or investigated network-level structural aberrations that might be associated with depression.
  
  
  METHODS
  We used graph analysis to examine the gray matter structural networks of individuals diagnosed with MDD (n = 93) and a demographically similar healthy comparison group (n = 151) with no history of psychopathology. The efficiency of structural networks for processing information was determined by quantifying local interconnectivity (clustering) and global integration (path length). We also compared the groups on the contributions of high-degree nodes (i.e., hubs) and regional network measures, including degree (number of connections in a node) and betweenness (fraction of short path connections in a node).
  
  
  RESULTS
  Depressed participants had significantly decreased clustering in their brain networks across a range of network densities. Compared with control subjects, depressed participants had fewer hubs primarily in medial frontal and medial temporal areas, had higher degree in the left supramarginal gyrus and right gyrus rectus, and had higher betweenness in the right amygdala and left medial orbitofrontal gyrus.
  
  
  CONCLUSIONS
  Networks of depressed individuals are characterized by a less efficient organization involving decreased regional connectivity compared with control subjects. Regional connections in the amygdala and medial prefrontal cortex may play a role in maintaining or adapting to depressive pathology. This is the first report of anomalous large-scale gray matter structural networks in MDD and provides new insights concerning the neurobiological mechanisms associated with this disorder.
authors.affiliation: Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California. Electronic address: mksingh@stanford.edu.
authors.forename: Manpreet K
authors.initials: MK
authors.lastname: Singh
authors.forename: Shelli R
authors.initials: SR
authors.lastname: Kesler
authors.forename: S M
authors.initials: SM
authors.lastname: Hadi Hosseini
authors.forename: Ryan G
authors.initials: RG
authors.lastname: Kelley
authors.forename: Debha
authors.initials: D
authors.lastname: Amatya
authors.forename: J Paul
authors.initials: JP
authors.lastname: Hamilton
authors.forename: Michael C
authors.initials: MC
authors.lastname: Chen
authors.forename: Ian H
authors.initials: IH
authors.lastname: Gotlib
mesh_terms: D000328:Adult; D001921:Brain / Q000473:pathology*; D003865:Major Depressive Disorder / Q000473:pathology*; D005260:Female; D006801:Humans; D008297:Male; D008959:Models, Neurological; D009415:Nerve Net / Q000473:pathology*
keywords: Connectivity; depression; graph analysis; gray matter; small world; structural network