Decreased between-hemisphere connectivity strength and network efficiency in geriatric depression.

Published

Journal Article

White matter (WM) lesions have been recognized as a key etiological factor in geriatric depression. However, little is known about the topological pattern changes of WM in geriatric depression in the remitted state (RGD) and its relationship to depressive episodes. To address these questions, we acquired diffusion tensor images in 24 RGD and 24 healthy participants. Among them, 10 patients and 19 healthy controls completed a 1-year follow up. Between-hemisphere connectivity and graph theoretical methods were used to analyze the data. We found significantly reduced WM connectivity between the left and right hemisphere in the RGD group compared with the control group. Those with multiple depression episodes had greater reduction in between-hemisphere connectivity strength than those with fewer episodes. In addition, the RGD group had a reduced global clustering coefficient, global efficiency, and network strength, and an increased shortest path length compared with the controls. A lower clustering coefficient was correlated with poorer memory function. The reduction of nodal clustering coefficient, global efficiency, and network strength in several regions were associated with slower information processing speed. At 1-year follow up, the network properties in the RGD subjects were significantly changed suggesting instability of WM network properties of depressed patients. Together, our study provides direct evidence of reduced between-hemisphere WM connectivity with greater depressive episodes, and of alterations of network properties with cognitive dysfunction in geriatric depression. Hum Brain Mapp 38:53-67, 2017. © 2016 Wiley Periodicals, Inc.

Full Text

Duke Authors

Cited Authors

  • Li, X; Steffens, DC; Potter, GG; Guo, H; Song, S; Wang, L

Published Date

  • January 2017

Published In

Volume / Issue

  • 38 / 1

Start / End Page

  • 53 - 67

PubMed ID

  • 27503772

Pubmed Central ID

  • 27503772

Electronic International Standard Serial Number (EISSN)

  • 1097-0193

Digital Object Identifier (DOI)

  • 10.1002/hbm.23343

Language

  • eng

Conference Location

  • United States