Aberrant brain network topology in youth with a familial risk for bipolar disorder: a task‐based fMRI connectome study

• Published in: Journal of child psychology and psychiatry Vol. 65; no. 8; pp. 1072 - 1086
• Main Authors: Pan, Nanfang, Qin, Kun, Patino, Luis R., Tallman, Maxwell J., Lei, Du, Lu, Lu, Li, Wenbin, Blom, Thomas J., Bruns, Kaitlyn M., Welge, Jeffrey A., Strawn, Jeffrey R., Gong, Qiyong, Sweeney, John A., Singh, Manpreet K., DelBello, Melissa P.
• Format: Journal Article
• Language: English
• Published: England Blackwell Publishing Ltd 01.08.2024
• Subjects: Adolescent; Age; Antidepressants; At risk populations; Biological markers; Biomarkers; Bipolar disorder; Bipolar Disorder - diagnostic imaging; Bipolar Disorder - physiopathology; Brain; Child; Clustering; Connectome; Default Mode Network - diagnostic imaging; Default Mode Network - physiopathology; Emotional disorders; Familial factors; familial risk; Female; fMRI; functional connectome; Functional magnetic resonance imaging; Genetic Predisposition to Disease; graph theory; Group Dynamics; Hippocampus; Humans; Magnetic Resonance Imaging; Male; Nerve Net - diagnostic imaging; Nerve Net - physiopathology; Networks; Neuroimaging; Physiological psychology; psychoradiology; Risk; Segregation; Side effects; Youth; fMRI; Bipolar disorder; psychoradiology; graph theory; functional connectome; familial risk
• ISSN: 0021-9630; 1469-7610; 1469-7610
• DOI: 10.1111/jcpp.13946

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.