title: Brain connectivity in late-life depression and aging revealed by network analysis.
abstract: OBJECTIVE
  To use novel methods to examine age associations across an integrated brain network in healthy older adults (HOA) and individuals with late-life depression (LLD). Graph theory metrics describe the organizational configuration of both the global network and specified brain regions.
  
  
  METHODS
  Cross-sectional data were acquired. Graph theory was used to explore diffusion tensor imaging-derived white matter networks. Forty-eight HOA and 28 adults with LLD were recruited from the community. Global and local metrics in prefrontal, cingulate, and temporal regions were calculated. Group differences and associations with age were explored.
  
  
  RESULTS
  Group differences were noted in local metrics of the right prefrontal and temporal regions, but no significant differences were observed on global metrics. Local (not global) metrics were associated with age differently across groups. For HOA, local metrics across all regions correlated with age, whereas in adults with LLD, correlations were only observed within temporal regions. In keeping with hypothesized regions impacted by LLD, stronger hubs in right temporal regions were observed among HOA, whereas LLD individuals were characterized by robust hubs in frontal regions.
  
  
  CONCLUSIONS
  We demonstrate widespread age-related changes in local network properties among HOA with different and more restricted local changes in LLD. Although a preliminary analysis, different patterns of correlations in local networks coupled with equivalent global metrics may reflect altered local structural brain networks in patients with LLD.
authors.affiliation: Department of Psychiatry, University of Illinois at Chicago, Chicago, IL; Department of Psychology, Goldsmiths University of London, London, United Kingdom. Electronic address: r.charlton@gold.ac.uk.
authors.forename: Rebecca A
authors.initials: RA
authors.lastname: Charlton
authors.affiliation: Department of Psychiatry, University of Illinois at Chicago, Chicago, IL; Community Psychiatry Associates, Sacramento, CA.
authors.forename: Alex
authors.initials: A
authors.lastname: Leow
authors.affiliation: Department of Bioengineering, University of Illinois at Chicago, Chicago, IL.
authors.forename: Johnson
authors.initials: J
authors.lastname: GadElkarim
authors.affiliation: Department of Psychiatry, University of Illinois at Chicago, Chicago, IL.
authors.forename: Aifeng
authors.initials: A
authors.lastname: Zhang
authors.affiliation: Department of Psychiatry, University of Illinois at Chicago, Chicago, IL.
authors.forename: Olusola
authors.initials: O
authors.lastname: Ajilore
authors.affiliation: Department of Psychiatry, University of Illinois at Chicago, Chicago, IL; Department of Bioengineering, University of Illinois at Chicago, Chicago, IL; Department of Radiology, University of Illinois at Chicago, Chicago, IL.
authors.forename: Shaolin
authors.initials: S
authors.lastname: Yang
authors.affiliation: Department of Psychiatry, University of Illinois at Chicago, Chicago, IL.
authors.forename: Melissa
authors.initials: M
authors.lastname: Lamar
authors.affiliation: Department of Psychiatry, University of Illinois at Chicago, Chicago, IL.
authors.forename: Anand
authors.initials: A
authors.lastname: Kumar
mesh_terms: D000367:Age Factors; D000368:Aged; D000375:Aging / Q000502:physiology*; D002540:Cerebral Cortex / Q000502:physiology / Q000503:physiopathology*; D063132:Connectome / Q000379:methods*; D003430:Cross-Sectional Studies; D003865:Major Depressive Disorder / Q000503:physiopathology*; D056324:Diffusion Tensor Imaging / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009415:Nerve Net / Q000502:physiology / Q000503:physiopathology*
keywords: Late-life depression; age effects; diffusion tensor imaging; graph theory; network analysis