Literature DB >> 29995357

Modes of Resting Functional Brain Organization Differentiate Suicidal Thoughts and Actions: A Preliminary Study.

Ricardo Cáceda1,2, Keith Bush3, G Andrew James3, Zachary N Stowe4, Clint D Kilts3.   

Abstract

OBJECTIVE: A major target in suicide prevention is interrupting the progression from suicidal thoughts to action. Use of complex algorithms in large samples has identified individuals at very high risk for suicide. We tested the ability of data-driven pattern classification analysis of brain functional connectivity to differentiate recent suicide attempters from patients with suicidal ideation.
METHODS: We performed a cross-sectional study using resting-state functional magnetic resonance imaging in depressed inpatients and outpatients of both sexes recruited from a university hospital between March 2014 and June 2016: recent suicide Attempters within 3 days of an attempt (n = 10), Suicidal Ideators (n = 9), Depressed Non-Suicidal Controls (n = 17), and Healthy Controls (n = 18). All depressed patients fulfilled DSM-IV-TR criteria for major depressive episode and either major depressive disorder, bipolar disorder, or depression not otherwise specified. A subset of suicide attempters (n = 7) were rescanned within 7 days. We used a support vector machine data-driven neural pattern classification analysis of resting-state functional connectivity to characterize recent suicide attempters and then tested the classifier's specificity.
RESULTS: A binary classifier trained to discriminate patterns of resting-state functional connectivity robustly differentiated Suicide Attempters from Suicidal Ideators (mean accuracy = 0.788, signed rank test: P = .002; null hypothesis: area under the curve = 0.5), with distinct functional connectivity between the default mode and the limbic, salience, and central executive networks. The classifier did not discriminate stable Suicide Attempters from Suicidal Ideators (mean accuracy = 0.58, P = .33) or presence from absence of lifetime suicidal behavior (mean accuracy = 0.543, P = .348) and was not improved by modeling clinical variables (mean accuracy = 0.736, P = .002).
CONCLUSIONS: Measures of intrinsic brain organization may have practical value as objective measures of suicide risk and its underlying mechanisms. Further incorporation of serum or cognitive markers and use of a prospective study design are needed to validate and refine the clinical relevance of this candidate biomarker of suicide risk. © Copyright 2018 Physicians Postgraduate Press, Inc.

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Mesh:

Year:  2018        PMID: 29995357      PMCID: PMC9227961          DOI: 10.4088/JCP.17m11901

Source DB:  PubMed          Journal:  J Clin Psychiatry        ISSN: 0160-6689            Impact factor:   5.906


  54 in total

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Authors:  Ricardo Cáceda; Dante Durand; Edmi Cortes; Stefania Prendes-Alvarez; Tori Moskovciak; Philip D Harvey; Charles B Nemeroff
Journal:  Psychosom Med       Date:  2014 Jul-Aug       Impact factor: 4.312

2.  Abnormal baseline brain activity in suicidal and non-suicidal patients with major depressive disorder.

Authors:  Tingting Fan; Xia Wu; Li Yao; Jie Dong
Journal:  Neurosci Lett       Date:  2012-11-29       Impact factor: 3.046

3.  Differential patterns of activity and functional connectivity in emotion processing neural circuitry to angry and happy faces in adolescents with and without suicide attempt.

Authors:  L A Pan; S Hassel; A M Segreti; S A Nau; D A Brent; M L Phillips
Journal:  Psychol Med       Date:  2013-01-09       Impact factor: 7.723

4.  Decreased resting state metabolic activity in frontopolar and parietal brain regions is associated with suicide plans in depressed individuals.

Authors:  Kees van Heeringen; Guo-Rong Wu; Myriam Vervaet; Marie-Anne Vanderhasselt; Chris Baeken
Journal:  J Psychiatr Res       Date:  2016-10-19       Impact factor: 4.791

5.  Heroin addicts have higher discount rates for delayed rewards than non-drug-using controls.

Authors:  K N Kirby; N M Petry; W K Bickel
Journal:  J Exp Psychol Gen       Date:  1999-03

6.  Organization of intrinsic functional brain connectivity predicts decisions to reciprocate social behavior.

Authors:  Ricardo Cáceda; G Andrew James; David A Gutman; Clinton D Kilts
Journal:  Behav Brain Res       Date:  2015-07-09       Impact factor: 3.332

7.  Response to unfairness across the suicide risk spectrum.

Authors:  Jessica M Carbajal; Jorge L Gamboa; Jordan Moore; Favrin Smith; Lou Ann Eads; Jeffrey L Clothier; Ricardo Cáceda
Journal:  Psychiatry Res       Date:  2017-08-26       Impact factor: 3.222

8.  Functional domains as correlates of suicidality among psychiatric inpatients.

Authors:  Zimri S Yaseen; Igor I Galynker; Jessica Briggs; Rachel D Freed; Vilma Gabbay
Journal:  J Affect Disord       Date:  2016-05-30       Impact factor: 4.839

9.  Predicting suicides after outpatient mental health visits in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS).

Authors:  R C Kessler; M B Stein; M V Petukhova; P Bliese; R M Bossarte; E J Bromet; C S Fullerton; S E Gilman; C Ivany; L Lewandowski-Romps; A Millikan Bell; J A Naifeh; M K Nock; B Y Reis; A J Rosellini; N A Sampson; A M Zaslavsky; R J Ursano
Journal:  Mol Psychiatry       Date:  2016-07-19       Impact factor: 15.992

10.  Opposite effective connectivity in the posterior cingulate and medial prefrontal cortex between first-episode schizophrenic patients with suicide risk and healthy controls.

Authors:  Huiran Zhang; Xiaomei Wei; Haojuan Tao; Tumbwene E Mwansisya; Weidan Pu; Zhong He; Aimin Hu; Lin Xu; Zhening Liu; Baoci Shan; Zhimin Xue
Journal:  PLoS One       Date:  2013-05-21       Impact factor: 3.240

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  7 in total

1.  Longitudinal decreases in suicidal ideation are associated with increases in salience network coherence in depressed adolescents.

Authors:  Jaclyn Schwartz; Sarah J Ordaz; Tiffany C Ho; Ian H Gotlib
Journal:  J Affect Disord       Date:  2018-11-03       Impact factor: 4.839

2.  Electrophysiological Changes Between Patients With Suicidal Ideation and Suicide Attempts: An Event-Related Potential Study.

Authors:  Sung Hoon Yoon; Se-Hoon Shim; Ji Sun Kim
Journal:  Front Psychiatry       Date:  2022-05-20       Impact factor: 5.435

3.  Slower perception of time in depressed and suicidal patients.

Authors:  Ricardo Cáceda; Jessica M Carbajal; Ronald M Salomon; Jordan E Moore; Greg Perlman; Prasad R Padala; Abdullah Hasan; Pedro L Delgado
Journal:  Eur Neuropsychopharmacol       Date:  2020-09-29       Impact factor: 4.600

Review 4.  Machine learning as the new approach in understanding biomarkers of suicidal behavior.

Authors:  Alja Videtič Paska; Katarina Kouter
Journal:  Bosn J Basic Med Sci       Date:  2021-08-01       Impact factor: 3.363

5.  Examination of structural brain changes in recent suicidal behavior.

Authors:  Diane J Kim; Elizabeth A Bartlett; Christine DeLorenzo; Ramin V Parsey; Clinton Kilts; Ricardo Cáceda
Journal:  Psychiatry Res Neuroimaging       Date:  2020-10-24       Impact factor: 2.493

6.  Promising Neuroimaging Biomarkers in Depression.

Authors:  Chien-Han Lai
Journal:  Psychiatry Investig       Date:  2019-09-23       Impact factor: 2.505

7.  Functional network alterations differently associated with suicidal ideas and acts in depressed patients: an indirect support to the transition model.

Authors:  Gerd Wagner; Meng Li; Matthew D Sacchet; Stéphane Richard-Devantoy; Gustavo Turecki; Karl-Jürgen Bär; Ian H Gotlib; Martin Walter; Fabrice Jollant
Journal:  Transl Psychiatry       Date:  2021-02-04       Impact factor: 6.222

  7 in total

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