Disrupted Small World Topology and Modular Organisation of Functional Networks in Late-life Depression with and Without Amnestic Mild Cognitive Impairment

Overview

Journal J Neurol Neurosurg Psychiatry

Publisher BMJ Publishing Group

Specialties Neurology
Neurosurgery
Psychiatry

Date 2014 Nov 30

PMID 25433036

Citations 30

Authors

Wenjun Li

B Douglas Ward

Xiaolin Liu

Gang Chen

Jennifer L Jones

Piero G Antuono

Shi-Jiang Li

Joseph S Goveas

Affiliations

Soon will be listed here.

Abstract

Background: The topological architecture of the whole-brain functional networks in those with and without late-life depression (LLD) and amnestic mild cognitive impairment (aMCI) are unknown.

Aims: To investigate the differences in the small-world measures and the modular community structure of the functional networks between patients with LLD and aMCI when occurring alone or in combination and cognitively healthy non-depressed controls.

Methods: 79 elderly participants (LLD (n=23), aMCI (n=18), comorbid LLD and aMCI (n=13), and controls (n=25)) completed neuropsychiatric assessments. Graph theoretical methods were employed on resting-state functional connectivity MRI data.

Results: LLD and aMCI comorbidity was associated with the greatest disruptions in functional integration measures (decreased global efficiency and increased path length); both LLD groups showed abnormal functional segregation (reduced local efficiency). The modular network organisation was most variable in the comorbid group, followed by patients with LLD-only. Decreased mean global, local and nodal efficiency metrics were associated with greater depressive symptom severity but not memory performance.

Conclusions: Considering the whole brain as a complex network may provide unique insights on the neurobiological underpinnings of LLD with and without cognitive impairment.

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References

Van der Mussele S, Fransen E, Struyfs H, Luyckx J, Marien P, Saerens J . Depression in mild cognitive impairment is associated with progression to Alzheimer's disease: a longitudinal study. J Alzheimers Dis. 2014; 42(4):1239-50. DOI: 10.3233/JAD-140405. View

Sheline Y, Raichle M . Resting state functional connectivity in preclinical Alzheimer's disease. Biol Psychiatry. 2013; 74(5):340-7. PMC: 3537262. DOI: 10.1016/j.biopsych.2012.11.028. View

Ajilore O, Lamar M, Kumar A . Association of brain network efficiency with aging, depression, and cognition. Am J Geriatr Psychiatry. 2013; 22(2):102-10. PMC: 3947188. DOI: 10.1016/j.jagp.2013.10.004. View

Shi F, Liu B, Zhou Y, Yu C, Jiang T . Hippocampal volume and asymmetry in mild cognitive impairment and Alzheimer's disease: Meta-analyses of MRI studies. Hippocampus. 2009; 19(11):1055-64. DOI: 10.1002/hipo.20573. View

Brier M, Thomas J, Fagan A, Hassenstab J, Holtzman D, Benzinger T . Functional connectivity and graph theory in preclinical Alzheimer's disease. Neurobiol Aging. 2013; 35(4):757-68. PMC: 3880636. DOI: 10.1016/j.neurobiolaging.2013.10.081. View

Biswal B, Mennes M, Zuo X, Gohel S, Kelly C, Smith S . Toward discovery science of human brain function. Proc Natl Acad Sci U S A. 2010; 107(10):4734-9. PMC: 2842060. DOI: 10.1073/pnas.0911855107. View

Wang L, Zang Y, He Y, Liang M, Zhang X, Tian L . Changes in hippocampal connectivity in the early stages of Alzheimer's disease: evidence from resting state fMRI. Neuroimage. 2006; 31(2):496-504. DOI: 10.1016/j.neuroimage.2005.12.033. View

Modrego P, Ferrandez J . Depression in patients with mild cognitive impairment increases the risk of developing dementia of Alzheimer type: a prospective cohort study. Arch Neurol. 2004; 61(8):1290-3. DOI: 10.1001/archneur.61.8.1290. View

Li W, Tugan Muftuler L, Chen G, Ward B, Budde M, Jones J . Effects of the coexistence of late-life depression and mild cognitive impairment on white matter microstructure. J Neurol Sci. 2014; 338(1-2):46-56. PMC: 4428544. DOI: 10.1016/j.jns.2013.12.016. View

10.

Power J, Barnes K, Snyder A, Schlaggar B, Petersen S . Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. Neuroimage. 2011; 59(3):2142-54. PMC: 3254728. DOI: 10.1016/j.neuroimage.2011.10.018. View

11.

Wang J, Zuo X, Gohel S, Milham M, Biswal B, He Y . Graph theoretical analysis of functional brain networks: test-retest evaluation on short- and long-term resting-state functional MRI data. PLoS One. 2011; 6(7):e21976. PMC: 3139595. DOI: 10.1371/journal.pone.0021976. View

12.

Aizenstein H, Butters M, Figurski J, Stenger V, Reynolds 3rd C, Carter C . Prefrontal and striatal activation during sequence learning in geriatric depression. Biol Psychiatry. 2005; 58(4):290-6. DOI: 10.1016/j.biopsych.2005.04.023. View

13.

Ajilore O, Lamar M, Leow A, Zhang A, Yang S, Kumar A . Graph theory analysis of cortical-subcortical networks in late-life depression. Am J Geriatr Psychiatry. 2013; 22(2):195-206. PMC: 3858393. DOI: 10.1016/j.jagp.2013.03.005. View

14.

Power J, Cohen A, Nelson S, Wig G, Barnes K, Church J . Functional network organization of the human brain. Neuron. 2011; 72(4):665-78. PMC: 3222858. DOI: 10.1016/j.neuron.2011.09.006. View

15.

Alexopoulos G, Hoptman M, Kanellopoulos D, Murphy C, Lim K, Gunning F . Functional connectivity in the cognitive control network and the default mode network in late-life depression. J Affect Disord. 2012; 139(1):56-65. PMC: 3340472. DOI: 10.1016/j.jad.2011.12.002. View

16.

Wang J, Zuo X, Dai Z, Xia M, Zhao Z, Zhao X . Disrupted functional brain connectome in individuals at risk for Alzheimer's disease. Biol Psychiatry. 2012; 73(5):472-81. DOI: 10.1016/j.biopsych.2012.03.026. View

17.

Annweiler C, Beauchet O, Bartha R, Wells J, Borrie M, Hachinski V . Motor cortex and gait in mild cognitive impairment: a magnetic resonance spectroscopy and volumetric imaging study. Brain. 2013; 136(Pt 3):859-71. DOI: 10.1093/brain/aws373. View

18.

Bullmore E, Sporns O . Complex brain networks: graph theoretical analysis of structural and functional systems. Nat Rev Neurosci. 2009; 10(3):186-98. DOI: 10.1038/nrn2575. View

19.

Bracht T, Federspiel A, Schnell S, Horn H, Hofle O, Wiest R . Cortico-cortical white matter motor pathway microstructure is related to psychomotor retardation in major depressive disorder. PLoS One. 2013; 7(12):e52238. PMC: 3527384. DOI: 10.1371/journal.pone.0052238. View

20.

Rubinov M, Sporns O . Complex network measures of brain connectivity: uses and interpretations. Neuroimage. 2009; 52(3):1059-69. DOI: 10.1016/j.neuroimage.2009.10.003. View