Characteristics of Temporal Dynamics of Intrinsic Brain Activity in Unmedicated Bipolar II Disorder with Suicidality

Abstract

Background: Bipolar disorder (BD) is associated with a high risk of suicide. Routine neuroimaging examination exhibited that BD with suicidality was associated with brain structural and functional changes. However, the alterations of brain dynamics are still unknown. Purpose: To investigate the alterations of brain dynamics in unmedicated BD II depression with suicidality and to predict the severity of suicidality. Materials and Methods: The prospective study included 106 BD II participants (20 with suicidal attempt (SA), 35 with suicidal ideation (SI), 51 without SI (NSI)) and 50 healthy controls (HCs) who underwent resting-state functional magnetic resonance imaging (rs-fMRI) between February 2016 and December 2017. We first used sliding window analysis to evaluate the dynamic amplitude of low-frequency fluctuations (dALFF). Then we predicted the severity of suicidality using a multivariate regression model. Results: One-Way ANOVA analyses revealed that the dALFF in the right temporal pole (TP), inferior temporal gyrus (ITG), superior temporal gyrus (STG), and the bilateral precuneus/posterior cingulate cortex (PCC) was significantly different among the 4 groups. Post hoc comparisons revealed all BD groups showed decreased dALFF in the bilateral precuneus/PCC compared with HCs. Increased dALFF was found in the right STG and ITG in the SA group compared with the others, and in the right TP in the SA group compared with SI and HCs groups. Importantly, these temporal variabilities could be used to predict the severity of suicidality (r = 0.330, p = 0.036), whereas static ALFF couldn't (r = -0.050, p = 0.532). Conclusion: Our findings suggest that alterations of temporal variability in the precuneus/PCC is a common feature of BD participants, the right temporal lobe involved in impulsivity, social and emotional processing are associated with suicidality in BD II depression participants. This predictive model using the dynamics of intrinsic brain activity may be helpful for clinical applications. Funding: The study was supported by grants from the National Natural Science Foundation of China (81971597, 81671670, and 81501456); Project in Basic Research and Applied Basic Research in General Colleges and Universities of Guangdong, China (2018KZDXM009); Planned Science and Technology Project of Guangzhou, China (20160402007 and 201604020184). Declaration of Interest: The authors declare no other competing interests. Ethical Approval: This retrospective study was approved by the Ethics Committee of the First Affiliated Hospital of Jinan University, Guangzhou, China.