Literature DB >> 31597581

Using resting-state intrinsic network connectivity to identify suicide risk in mood disorders.

Jonathan P Stange1, Lisanne M Jenkins2, Stephanie Pocius3, Kayla Kreutzer1, Katie L Bessette1, Sophie R DelDonno1, Leah R Kling1, Runa Bhaumik1, Robert C Welsh3, John G Keilp4, K Luan Phan5, Scott A Langenecker3.   

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.

Entities:  

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

Year:  2019        PMID: 31597581      PMCID: PMC7368462          DOI: 10.1017/S0033291719002356

Source DB:  PubMed          Journal:  Psychol Med        ISSN: 0033-2917            Impact factor:   7.723


  86 in total

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7.  Cognitive Risk and Protective Factors for Suicidal Ideation: A Two Year Longitudinal Study in Adolescence.

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8.  The impact of global signal regression on resting state correlations: are anti-correlated networks introduced?

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10.  Biological risk factors for suicidal behaviors: a meta-analysis.

Authors:  B P Chang; J C Franklin; J D Ribeiro; K R Fox; K H Bentley; E M Kleiman; M K Nock
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2.  Spontaneous transient states of fronto-temporal and default-mode networks altered by suicide attempt in major depressive disorder.

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Journal:  Front Neurol       Date:  2022-09-01       Impact factor: 4.086

4.  Using Network Parcels and Resting-State Networks to Estimate Correlates of Mood Disorder and Related Research Domain Criteria Constructs of Reward Responsiveness and Inhibitory Control.

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Journal:  Biol Psychiatry Cogn Neurosci Neuroimaging       Date:  2021-07-13
  4 in total

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