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Large-scale functional brain networks of maladaptive childhood aggression identified by connectome-based predictive modeling

Molecular Psychiatry volume 27, pages 985–999 (2022)Cite this article

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Abstract

Disruptions in frontoparietal networks supporting emotion regulation have been long implicated in maladaptive childhood aggression. However, the association of connectivity between large-scale functional networks with aggressive behavior has not been tested. The present study examined whether the functional organization of the connectome predicts severity of aggression in children. This cross-sectional study included a transdiagnostic sample of 100 children with aggressive behavior (27 females) and 29 healthy controls without aggression or psychiatric disorders (13 females). Severity of aggression was indexed by the total score on the parent-rated Reactive-Proactive Aggression Questionnaire. During fMRI, participants completed a face emotion perception task of fearful and calm faces. Connectome-based predictive modeling with internal cross-validation was conducted to identify brain networks that predicted aggression severity. The replication and generalizability of the aggression predictive model was then tested in an independent sample of children from the Adolescent Brain Cognitive Development (ABCD) study. Connectivity predictive of aggression was identified within and between networks implicated in cognitive control (medial-frontal, frontoparietal), social functioning (default mode, salience), and emotion processing (subcortical, sensorimotor) (r = 0.31, RMSE = 9.05, p = 0.005). Out-of-sample replication (p < 0.002) and generalization (p = 0.007) of findings predicting aggression from the functional connectome was demonstrated in an independent sample of children from the ABCD study (n = 1791; n = 1701). Individual differences in large-scale functional networks contribute to variability in maladaptive aggression in children with psychiatric disorders. Linking these individual differences in the connectome to variation in behavioral phenotypes will advance identification of neural biomarkers of maladaptive childhood aggression to inform targeted treatments.

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Fig. 1: Brain-wide functional connectivity predicts severity of aggressive behavior.
Fig. 2: Networks predicting aggression summarized by connectivity between macroscale brain regions and networks.
Fig. 3: Follow-up analyses for high-degree nodes contributing to the connectome model in the discovery sample of 129 children.
Fig. 4: Dorsolateral prefrontal cortex connectivity predicts aggressive behavior.
Fig. 5: Replication of findings using CPM prediction of aggression in an out-of-sample dataset.
Fig. 6: Network model of aggression.

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Data availability

To promote data transparency, anonymized data that support the findings of this study are available from the corresponding authors upon reasonable request. Data from the studies reported in this paper (transdiagnostic sample from Yale and ABCD) have also been shared on the National Institute of Mental Health Data Archive (NDA; https://nda.nih.gov/).

Code availability

CPM code is available at https://github.com/YaleMRRC/CPM.

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Acknowledgements

This work was supported by NIMH grant R01MH101514 (DGS). KI is a fellow on NCATS grant KL2 TR001862, TL1 TR001864, and the Translational Developmental Neuroscience Training Program (T32 MH18268) directed by MJC. We thank Sonia Rowley and Julia Zhong for their assistance with reviewing the final version of the manuscript, Iciar Iturmendi for her assistance with formatting Figs. 3 and 6, Dr Megan Tudor for subject characterization assessments, and Emilie Bertschinger, Tess Gladstone, and Carolyn Marsh for study coordination. A portion of the data used in the preparation of this article were obtained from the Adolescent Brain Cognitive Development (ABCD) study (https://abcdstudy.org), held in the NIMH Data Archive (NDA). This is a multisite, longitudinal study designed to recruit more than 10,000 children age 9–10 and follow them over 10 years into early adulthood. The ABCD study is supported by the National Institutes of Health and additional federal partners under award numbers U01DA041022, U01DA041028, U01DA041048, U01DA041089, U01DA041106, U01DA041117, U01DA041120, U01DA041134, U01DA041148, U01DA041156, U01DA041174, U24DA041123, U24DA041147, U01DA041093, and U01DA041025. A full list of supporters is available at https://abcdstudy.org/federal-partners.html. A listing of participating sites and a complete listing of the study investigators can be found at https://abcdstudy.org/scientists/workgroups/. ABCD consortium investigators designed and implemented the study and/or provided data but did not necessarily participate in analysis or writing of this report. This manuscript reflects the views of the authors and may not reflect the opinions or views of the NIH or ABCD consortium investigators.

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A version of this manuscript was posted as a preprint on Research Square. The authors retain full copyright. https://doi.org/10.21203/rs.3.rs-356217/v1.

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Authors and Affiliations

  1. Child Study Center, Yale University School of Medicine, New Haven, CT, USA

    Karim Ibrahim, Michael J. Crowley, Dustin Scheinost & Denis G. Sukhodolsky

  2. Department of Diagnostic Radiology, Yale University School of Medicine, New Haven, CT, USA

    Stephanie Noble, Cheryl Lacadie & Dustin Scheinost

  3. Department of Psychology, Yale University, New Haven, CT, USA

    George He & Gregory McCarthy

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  1. Karim Ibrahim
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  2. Stephanie Noble
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  3. George He
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  8. Denis G. Sukhodolsky
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Contributions

Conception: KI, DGS, DS, GM; design of the work: KI, DGS, DS, GM; acquisition, analysis, interpretation of data: KI, DGS, DS, SN, CL, GH; manuscript writing and revising: KI, DGS, DS, MJC, GM, SN, CL, GH.

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Correspondence to Karim Ibrahim or Denis G. Sukhodolsky.

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Competing interests

DGS receives royalties from Guilford Press for a treatment manual on CBT for anger and aggression in children. KI, SN, GH, CL, MJC, GM, and DS have no competing interests or potential conflicts of interest to declare related to this study.

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Ibrahim, K., Noble, S., He, G. et al. Large-scale functional brain networks of maladaptive childhood aggression identified by connectome-based predictive modeling. Mol Psychiatry 27, 985–999 (2022). https://doi.org/10.1038/s41380-021-01317-5

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