Citation

Stange JP, Jenkins LM, Pocius S, Kreutzer K, Bessette KL, DelDonno SR, Kling LR, Bhaumik R, Welsh RC, Keilp JG, Phan KL, Langenecker SA. Psychol. Med. 2019; ePub(ePub): ePub.

Affiliation

University of Utah, Salt Lake City, UT, USA.

Copyright

(Copyright © 2019, Cambridge University Press)

DOI

10.1017/S0033291719002356

PMID

31597581

Abstract

BACKGROUND: Little is known about the neural substrates of suicide risk in mood disorders. Improving the identification of biomarkers of suicide risk, as indicated by a history of suicide-related behavior (SB), could lead to more targeted treatments to reduce risk.

METHODS: Participants were 18 young adults with a mood disorder with a history of SB (as indicated by endorsing a past suicide attempt), 60 with a mood disorder with a history of suicidal ideation (SI) but not SB, 52 with a mood disorder with no history of SI or SB (MD), and 82 healthy comparison participants (HC). Resting-state functional connectivity within and between intrinsic neural networks, including cognitive control network (CCN), salience and emotion network (SEN), and default mode network (DMN), was compared between groups.

RESULTS: Several fronto-parietal regions (k > 57, p < 0.005) were identified in which individuals with SB demonstrated distinct patterns of connectivity within (in the CCN) and across networks (CCN-SEN and CCN-DMN). Connectivity with some of these same regions also distinguished the SB group when participants were re-scanned after 1-4 months. Extracted data defined SB group membership with good accuracy, sensitivity, and specificity (79-88%).

CONCLUSIONS: These results suggest that individuals with a history of SB in the context of mood disorders may show reliably distinct patterns of intrinsic network connectivity, even when compared to those with mood disorders without SB. Resting-state fMRI is a promising tool for identifying subtypes of patients with mood disorders who may be at risk for suicidal behavior.

Language: en

Keywords

Depression; fMRI; intrinsic networks; mood disorders; neural networks; neuroimaging; resting-state connectivity; suicide