Abstract
Bipolar II disorder (BD-II) major depression episode is highly associated with suicidality, and objective neural biomarkers could be key elements to assist in early prevention and intervention. This study aimed to integrate altered brain functionality in the frontolimbic system and machine learning techniques to classify suicidal BD-II patients and predict suicidality risk at the individual level. A cohort of 169 participants were enrolled, including 43 BD-II depression patients with at least one suicide attempt during a current depressive episode (SA), 62 BD-II depression patients without a history of attempted suicide (NSA), and 64 demographically matched healthy controls (HCs). We compared resting-state functional connectivity (rsFC) in the frontolimbic system among the three groups and explored the correlation between abnormal rsFCs and the level of suicide risk (assessed using the Nurses' Global Assessment of Suicide Risk, NGASR) in SA patients. Then, we applied support vector machines (SVMs) to classify SA vs. NSA in BD-II patients and predicted the risk of suicidality. SA patients showed significantly decreased frontolimbic rsFCs compared to NSA patients. The left amygdala-right middle frontal gyrus (orbital part) rsFC was negatively correlated with NGASR in the SA group, but not the severity of depressive or anxiety symptoms. Using frontolimbic rsFCs as features, the SVMs obtained an overall 84% classification accuracy in distinguishing SA and NSA. A significant correlation was observed between the SVMs-predicted NGASR and clinical assessed NGASR (r = 0.51, p = 0.001). Our results demonstrated that decreased rsFCs in the frontolimbic system might be critical objective features of suicidality in BD-II patients, and could be useful for objective prediction of suicidality risk in individuals.
Highlights
Bipolar II disorder (BD-II), characterized by at least one episode of hypomania, one episode of major depression, and no history of a full manic episode, constitutes one of the major causes of suicide attempts (SA), especially during major depressive episodes [1, 2]
For comparisons between the SA and NSA groups, we did not observe any significant differences in years of education, duration of disease, age of BD onset, family history of mental disorder, the polarity of the first episode, HAMD-17, HAMD-16, Hamilton Anxiety Rating Scale (HAMA), combination with a somatic disorder, psychotic characteristics, number of previous episodes of depression and hypomania, occupation status, and rapid cycling
We contributed to the identification of neuroimaging biomarkers for suicide attempts in patients with BD-II depression
Summary
Bipolar II disorder (BD-II), characterized by at least one episode of hypomania, one episode of major depression, and no history of a full manic episode, constitutes one of the major causes of suicide attempts (SA), especially during major depressive episodes [1, 2]. Numerous studies have reported clinical features, including a family history of suicide, presence of hopelessness, loss of interest or pleasure, prior suicide attempts, and others, were associated with high suicide risk in individuals with bipolar disorder and might help identify at-risk patients [8, 9]. Clinical assessments such as the Nurses’ Global Assessment of Suicide Risk (NGASR) [10] remain the cornerstone of suicide risk assessment for psychosis patients. It is challenging to accurately assess the risk of suicidality in patients with BD-II during depressive episodes in clinical practice, highlighting the need to identify reliable and accurate biomarkers for suicidality
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