Structural And Functional Network Imaging Study Of Suicide Attempts Behavior In Bipolar Disorder Patients With A Current Major Depressive Episode

Objective: Bipolar disorder(BD)is the most closely associated with a high risk of suicidality,especially during major depressive episodes.However,the clinical assessment of suicide cannot meet the needs of clinical practice to date,and the early identification and intervention of BD patients with suicide behaviors are still one of the major challenges in clinic.Most previous studies only were focused on the characteristics of neural networks in a single mode of neuroimaging,and structural and functional connectivity alterations have been previously reported in BD with suicide attempts.Little is known how abnormal structural and functional connectivity relates to each other,and studies with a single mode might be insufficient to depict the pathological changes.Whether the internal consistency of structural and functional modal neural networks could better understand the pathological mechanism of suicide behaviors and assist in clinical prediction of suicidal risk in BD remains to be explored.Here,we hypothesize: 1.structure connectivity constrains functional connectivity;2.the structural–functional coupling index,an important parameter to quantitatively evaluate the internal consistency of structural and functional networks,might be a more sensitive biomarker to detect subtle brain abnormalities than any single modality in BD patients with a current major depressive episode who had suicide attempts.Methods: A total of 191 BD patients aged from 18 to 55 with a current major depressive episode,and 113 healthy controls(HC)were recruited.Among them,fifteen BD patients and one healthy control participants were excluded due to excessive head movements and poor image quality.In the final analyses,176 BD patients and 112 healthy subjects were included.There were 75 individuals with at least one suicide attempt during the recent depressive episode(SA group)and 101 with no suicide attempt history during the present or in previous depressive episodes(NSA group).Firstly,we investigated structural and resting-state f MRI connectivity neural circuits using a network-based statistic(NBS)and identified the abnormal SC and FC network between the SA group,NSA group and HC group.Secondly a cross-modality analysis was conducted,in which we evaluated the SC in the altered FC network and the FC in the altered SC network,to investigate the relationship between SC network and FC network.as well as their coupling among the three groups.Finally,the SC-FC coupling index of SA and NSA was compared,and the correlation analyses were performed with the risk of suicide(assessed using the Nurses’ Global Assessment of Suicide Risk,NGASR)in BD patients.Result: Firstly,we found that the SA group,compared to the NSA group,showed significantly decreased central-temporal structural connectivity and increased frontal–temporal functional connectivity.In addition,there were no single SC or FC abnormality was associated with the risk of suicide(assessed by NGASR)in BD patients.Secondly,we confirmed that the altered structural connectivity network predicted the abnormal functional connectivity network profile.Finally,compared NSA,SA showed decreased structural–functional coupling in a frontal-centraltemporal network,and the structural–functional coupling was significantly correlated with suicide risk but not with depression or anxiety severity.Conclusion: Our findings suggest that the structural networks is the key determinant of brain dysfunction,and structural–functional coupling could serve as a valuable traitlike biomarker for BD suicidal predication over and above the intramodality network connectivity.Such a measure could have clinical implications for early identification of suicide attempters with BD depression and inform strategies for prevention.