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Background: Suicide among youth is a major public health challenge, attracting increasing attention. However, the neurobiological mechanisms and the pathophysiology underlying suicidal behavior in depressed youths are still unclear. The fMRI enables a better understanding of functional changes in the brains of young suicide attempters with depressive disorder through detecting spontaneous neural activity. The purpose of this study was to identify the relationship between abnormalities involving local brain function and suicidal attempts in depressed youths using resting-state fMRI (RS-fMRI).Method: Thirty-five depressed youths aged between 15 and 29 years with a history of suicidal attempts (SU group), 18 patients without suicidal attempts (NSU group) and 47 gender-, age- and education-matched healthy controls (HC) underwent psychological assessment and R-fMRI. The differences in fractional amplitude of low-frequency fluctuation (ALFF) among the three groups were compared. The clinical factors correlated with z-score ALFF in the regions displaying significant group differences were investigated. The ROC method was used to evaluate these clusters as markers to screen patients with suicidal behavior.Results: Compared with the NSU and HC groups, the SU group showed increased zALFF in the right superior temporal gyrus (r-STG), left middle temporal gyrus (L-MTG) and left middle occipital gyrus (L-MOG). Additionally, significantly decreased zALFF values in the L-SFG and L-MFG were found in the SU group compared with the NSU group, which were negatively correlated with BIS scores in the SU group. Further ROC analysis revealed that the mean zALFF values in these two regions (sensitivity=83.3% and specificity=71.4%) served as markers to differentiate the two patient subtypes.Conclusion: The SU group had abnormal spontaneous neural activity during the resting state, and decreased activity in L-SFG and L-MFG was associated with increased impulsivity in SU group. Our results suggested that abnormal neural activity in these brain regions may represent a potential neurobiological diathesis or predisposition to suicidal behavior in youth depression. [ABSTRACT FROM AUTHOR]

Background: Suicidal behavior is a major concern for patients who suffer from major depressive disorder (MDD), especially among adolescents and young adults. Machine learning models with the capability of suicide risk identification at an individual level could improve suicide prevention among high-risk patient population.Methods: A cross-sectional assessment was conducted on a sample of 66 adolescents/young adults diagnosed with MDD. The structural T1-weighted MRI scan of each subject was processed using the FreeSurfer software. The classification model was conducted using the Support Vector Machine - Recursive Feature Elimination (SVM-RFE) algorithm to distinguish suicide attempters and patients with suicidal ideation but without attempts.Results: The SVM model was able to correctly identify suicide attempters and patients with suicidal ideation but without attempts with a cross-validated prediction balanced accuracy of 78.59%, the sensitivity was 73.17% and the specificity was 84.0%. The positive predictive value of suicide attempt was 88.24%, and the negative predictive value was 65.63%. Right lateral orbitofrontal thickness, left caudal anterior cingulate thickness, left fusiform thickness, left temporal pole volume, right rostral anterior cingulate volume, left lateral orbitofrontal thickness, left posterior cingulate thickness, right pars orbitalis thickness, right posterior cingulate thickness, and left medial orbitofrontal thickness were the 10 top-ranked classifiers for suicide attempt.Conclusions: The findings indicated that structural MRI data can be useful for the classification of suicide risk. The algorithm developed in current study may lead to identify suicide attempt risk among MDD patients. [ABSTRACT FROM AUTHOR]

Internet addiction (IA) is common among young students. This study aimed to examine the influence and mechanisms of IA and susceptible personality traits on the impact of suicidal ideation in adolescent students in China. This cross-sectional study (09/2012–09/2015) used stratified cluster sampling with "school type" for stratification; 136,266 students from 63 schools completed the questionnaire. Logistic regression analysis was performed to estimate the effect of IA (Young's Internet Addiction Test) and susceptible personality (Barratt impulsiveness scale, Buss & Perry Aggression Questionnaire; and Eysenck Personality Questionnaire-R Short Scale) on suicidal ideation (Scale of Suicidal Ideation). Suicidal ideation was observed in 20,218 (14.77%) of the students, and IA was detected in 28,836 (21.16%) subjects. Compared with those without IA, students with IA had a higher prevalence of suicidal ideation (P < 0.0001). No planning impulsiveness had a predictive effect on suicidal ideation in the impulsive personality trait, while in the aggressive personality trait, hostility and self-aggression had a predictive effect on suicidal ideation (all P < 0.0001). High psychoticism and neuroticism were impact factors for suicidal ideation, but extroversion was a protective factor (all P < 0.0001). These results highlight the importance of assessing personality traits and reducing IA as a possible means of lessening suicidal ideation. Susceptible personality (such as high psychoticism, high neuroticism, and low extroversion) play a prominent role in influencing the probability of having suicidal behavior among those recently exposed to IA. IA and susceptible personality traits were significantly correlated with suicidal and self-harm ideation among adolescent students. [ABSTRACT FROM AUTHOR]

• 76 major depressive disorder (MDD) patients with and without suicide behavior history young adults (aged 18–24 years) were recruited. • There were significant differences in functional connectivity in the subregions of ACC-superior frontal gyrus, left insula and right caudate between the two groups. • The suicidal ideation score has been linked to ACC-frontal gyrus functional connectivity. • This experiment is the first, to our knowledge, focused on the ACC functional connectivity role of young adults suicidal-MDD. Functional alterations in the subregions of the anterior cingulate cortex (ACC) have been observed in patients with major depressive disorder (MDD). Studies have shown that higher depressive symptoms are associated with altered functional connectivity (FC) in different ACC sub-regions. Suicide is highly prevalent in patients with MDD; however, it is unclear whether suicidal behavior is associated with the FC alterations in the subregions of the ACC in these indibiduals. Seventy-six patients with MDD (41 with and 35 without a history of suicidal behavior) underwent functional magnetic resonance imaging (fMRI) and were assessed using the Hamilton Rating Scale for Depression (HAMD), the Scale for Suicide Ideation (SSI), and the Columbia Scale for Rating of Suicide Severity. We investigated the FC between the ACC subregions and other brain regions in young MDD patients with and without a history of suicidal behavior. The FC in the subregions of the ACC-superior frontal gyrus differed significantly between the two groups. Additionally, the anterior sgACC-right caudate FC and the pgACC-left insula FC were found to be abnormal in the suicidal MDD group. Interestingly, the suicidal ideation score positively correlated with decreased FC in the pgACC-superior frontal gyrus in both groups, but it negatively correlated with increased FC in the anterior sgACC-superior frontal gyrus in the non-suicidal MDD group. Our findings indicate that altered connections of subregions in the ACC may be involved in the neurological mechanisms underlying suicide in young adults with MDD. [ABSTRACT FROM AUTHOR]

• Dissociable intrinsic connected networks and altered intra- and inter-network connectivity among DMN, CEN, SN were identified. • SU displayed reduced internetwork connectivity of aDMN-SN and aDMN-rFPN, but enhanced SN-rFPN connectivity. • Opposite patterns of functional network connectivity between DMN and SN with CEN in youth suicidal depressed patients. • The functional network connectivity between aDMN and R-FPN was negatively correlated with BHS scores. The purpose of this study was to investigate the changes in resting-state brain functional network connectivity (FNC) in young depressed patients with and without suicidal behavior, and the relationship between FNC and suicidal attempts in depressed youths using resting-state fMRI (RS-fMRI). We conducted independent component analysis (ICA) to identify intrinsically connected neural networks and analyze the alterations of intra- and inter-network connectivity using FNC analysis in 35 depressed youth with suicidal attempts (SU group), 18 patients without suicidal attempts (NSU group) and 47 healthy controls (HC), and investigate brain-behavior associations between the FNC coefficients and clinical behavior in the SU group. SU group showed significantly decreased internetwork connectivity between anterior default mode network (aDMN) and salience network (SN), as well as the right frontal-parietal network (rFPN). However, the internetwork connectivity between the SN and rFPN in SU group was higher than that in NSU group. Moreover, decreased aDMN-rFPN connectivity was negatively correlated with BHS scores, and the differences in SN-rFPN and aDMN-pDMN connectivity were negatively associated with the HAMD score in the SU group. Our findings may provide new insights into the patterns of functional organization in the brain of suicidal depressed patients. [ABSTRACT FROM AUTHOR]