Search

Background: Youth with a family history of bipolar disorder (BD) may be at increased risk for mood disorders and for developing side effects after antidepressant exposure. The neurobiological basis of these risks remains poorly understood. We aimed to identify biomarkers underlying risk by characterizing abnormalities in the brain connectome of symptomatic youth at familial risk for BD. Methods: Depressed and/or anxious youth (n = 119, age = 14.9 ± 1.6 years) with a family history of BD but no prior antidepressant exposure and typically developing controls (n = 57, age = 14.8 ± 1.7 years) received functional magnetic resonance imaging (fMRI) during an emotional continuous performance task. A generalized psychophysiological interaction (gPPI) analysis was performed to compare their brain connectome patterns, followed by machine learning of topological metrics. Results: High‐risk youth showed weaker connectivity patterns that were mainly located in the default mode network (DMN) (network weight = 50.1%) relative to controls, and connectivity patterns derived from the visual network (VN) constituted the largest proportion of aberrant stronger pairs (network weight = 54.9%). Global local efficiency (Elocal, p =.022) and clustering coefficient (Cp, p =.029) and nodal metrics of the right superior frontal gyrus (SFG) (Elocal: p <.001; Cp: p =.001) in the high‐risk group were significantly higher than those in healthy subjects, and similar patterns were also found in the left insula (degree: p =.004; betweenness: p =.005; age‐by‐group interaction, p =.038) and right hippocampus (degree: p =.003; betweenness: p =.003). The case–control classifier achieved a cross‐validation accuracy of 78.4%. Conclusions: Our findings of abnormal connectome organization in the DMN and VN may advance mechanistic understanding of risk for BD. Neuroimaging biomarkers of increased network segregation in the SFG and altered topological centrality in the insula and hippocampus in broader limbic systems may be used to target interventions tailored to mitigate the underlying risk of brain abnormalities in these at‐risk youth. [ABSTRACT FROM AUTHOR]

Background: Mindfulness‐based cognitive therapy for children (MBCT‐C), as a psychotherapeutic intervention, has been shown to be effective for treating mood dysregulation (MD). While previous neuroimaging studies of MD have reported both pre‐treatment structural and functional alterations, the effects of MBCT‐C on brain morphological network organisation has not been investigated. Methods: We investigated brain morphological network organisation in 10 mood‐dysregulated youth with familial risk for bipolar disorder and 15 matched healthy comparison youth (HC). Effects of 12 weeks of MBCT‐C were examined in the mood‐dysregulated youth. Topological properties of brain networks used for analyses were constructed based on morphological similarities in regional grey matter using a graph‐theory approach using MRI data. Results: At baseline, compared with the HC group, the mood‐dysregulated group exhibited increased global efficiency (Eglob), decreased path length (Lp), and abnormal nodal properties, mainly in the limbic system. Right temporal pole alterations at baseline predicted change in Child and Adolescent Mindfulness Measure scores after treatment. The mood‐dysregulated group showed significant decreases in both the Eglob and Lp metrics after MBCT‐C, suggesting an improved capacity for optimal information processing. Changes in Lp were correlated with changes in Emotion Regulation Checklist scores. Our results show significant topological alterations in the mood‐dysregulated group as compared to controls at baseline. After MBCT‐C, disrupted topological properties in the mood‐dysregulated group were significantly reduced. Conclusion: MBCT‐C may facilitate clinically meaningful changes in the brain structural network in mood‐dysregulated individuals. [ABSTRACT FROM AUTHOR]