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Graph theory analysis of whole brain functional connectivity to assess disturbances associated with suicide attempts in bipolar disorder.

ABSTRACT: Brain targets to lower the high risk of suicide in Bipolar Disorder (BD) are needed. Neuroimaging studies employing analyses dependent on regional assumptions could miss hubs of dysfunction critical to the pathophysiology of suicide behaviors and their prevention. This study applied intrinsic connectivity distribution (ICD), a whole brain graph-theoretical approach, to identify hubs of functional connectivity (FC) disturbances associated with suicide attempts in BD. ICD, from functional magnetic resonance imaging data acquired while performing a task involving implicit emotion regulation processes important in BD and suicide behaviors, was compared across 40 adults with BD with prior suicide attempts (SAs), 49 with BD with no prior attempts (NSAs) and 51 healthy volunteers (HVs). Areas of significant group differences were used as seeds to identify regional FC differences and explore associations with suicide risk-related measures. ICD was significantly lower in SAs than in NSAs and HVs in bilateral ventromedial prefrontal cortex (vmPFC) and right anterior insula (RaIns). Seed connectivity revealed altered FC from vmPFC to bilateral anteromedial orbitofrontal cortex, left ventrolateral PFC (vlPFC) and cerebellum, and from RaIns to right vlPFC and temporopolar cortices. VmPFC and RaIns ICD were negatively associated with suicidal ideation severity, and vmPFC ICD with hopelessness and attempt lethality severity. The findings suggest that SAs with BD have vmPFC and RaIns hubs of dysfunction associated with altered FC to other ventral frontal, temporopolar and cerebellar cortices, and with suicidal ideation, hopelessness, and attempt lethality. These hubs may be targets for novel therapeutics to reduce suicide risk in BD.

SUBMITTER: Sankar A

PROVIDER: S-EPMC8748935 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:We conducted a retrospective investigation of potential clinical, demographic, and neuropsychological risk factors for suicide attempts in patients diagnosed with bipolar disorder.Participants included 67 adult inpatients and outpatients aged 18-60 years meeting DSM-IV criteria for bipolar disorder (bipolar I and II disorders, bipolar disorder not otherwise specified). We assessed demographic factors, mood symptoms, psychosis, trauma history, trait impulsivity, trait aggression, and reasons for living. The primary outcome measures were the Barratt Impulsiveness Scale-version II, Aggression Questionnaire, and 10 cognitive outcome variables. The cognitive outcome variables assessed cognitive performance across several domains, including processing speed, attention, verbal learning, and executive function. Another aspect of cognitive function, decision making, was assessed using the Iowa Gambling Task. The study was conducted from July 2007-July 2009.We found that nonattempters reported significantly higher trait impulsivity scores on the Barratt Impulsiveness Scale compared to attempters (t(57) = 2.2, P = .03) and that, among attempters, lower trait impulsivity score was associated with higher scores of lethality of prior attempts (r(25) = -0.53, P = .01). Analyses revealed no other group differences on demographic, clinical, or neurocognitive variables when comparing attempters versus nonattempters. Regression models failed to identify any significant predictors of past suicide attempt.The largely negative results of our study are particularly important in highlighting the clinical dilemma faced by many clinicians when trying to predict which patients will make serious suicide attempts and which patients are at a lower risk for acting on suicidal thoughts. A limitation of our work is that we examined stable trait measures of impulsivity among a euthymic sample rather than mood state or the impact of mood state on traits. Overall, we conclude that suicidal behavior is extremely difficult to predict, even when comprehensive clinical and neurocognitive information is available.

Project description:Bipolar disorder is often misdiagnosed as major depressive disorder, which leads to inadequate treatment. Depressed individuals versus healthy control subjects, show increased expectation of negative outcomes. Due to increased impulsivity and risk for mania, however, depressed individuals with bipolar disorder may differ from those with major depressive disorder in neural mechanisms underlying anticipation processes. Graph theory methods for neuroimaging data analysis allow the identification of connectivity between multiple brain regions without prior model specification, and may help to identify neurobiological markers differentiating these disorders, thereby facilitating development of better therapeutic interventions. This study aimed to compare brain connectivity among regions involved in win/loss anticipation in depressed individuals with bipolar disorder (BDD) versus depressed individuals with major depressive disorder (MDD) versus healthy control subjects using graph theory methods. The study was conducted at the University of Pittsburgh Medical Center and included 31 BDD, 39 MDD, and 36 healthy control subjects. Participants were scanned while performing a number guessing reward task that included the periods of win and loss anticipation. We first identified the anticipatory network across all 106 participants by contrasting brain activation during all anticipation periods (win anticipation + loss anticipation) versus baseline, and win anticipation versus loss anticipation. Brain connectivity within the identified network was determined using the Independent Multiple sample Greedy Equivalence Search (IMaGES) and Linear non-Gaussian Orientation, Fixed Structure (LOFS) algorithms. Density of connections (the number of connections in the network), path length, and the global connectivity direction ('top-down' versus 'bottom-up') were compared across groups (BDD/MDD/healthy control subjects) and conditions (win/loss anticipation). These analyses showed that loss anticipation was characterized by denser top-down fronto-striatal and fronto-parietal connectivity in healthy control subjects, by bottom-up striatal-frontal connectivity in MDD, and by sparse connectivity lacking fronto-striatal connections in BDD. Win anticipation was characterized by dense connectivity of medial frontal with striatal and lateral frontal cortical regions in BDD, by sparser bottom-up striatum-medial frontal cortex connectivity in MDD, and by sparse connectivity in healthy control subjects. In summary, this is the first study to demonstrate that BDD and MDD with comparable levels of current depression differed from each other and healthy control subjects in density of connections, connectivity path length, and connectivity direction as a function of win or loss anticipation. These findings suggest that different neurobiological mechanisms may underlie aberrant anticipation processes in BDD and MDD, and that distinct therapeutic strategies may be required for these individuals to improve coping strategies during expectation of positive and negative outcomes.

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Graph theory analysis of whole brain functional connectivity to assess disturbances associated with suicide attempts in bipolar disorder.

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