Multimodal neural correlates of childhood psychopathology
- McGill University, Canada
- University of Geneva, Switzerland
- National University of Singapore, Singapore
- Geneva University Hospitals, Switzerland
Abstract
Complex structural and functional changes occurring in typical and atypical development necessitate multidimensional approaches to better understand the risk of developing psychopathology. Here, we simultaneously examined structural and functional brain network patterns in relation to dimensions of psychopathology in the Adolescent Brain Cognitive Development dataset. Several components were identified, recapitulating the psychopathology hierarchy, with the general psychopathology (p) factor explaining most covariance with multimodal imaging features, while the internalizing, externalizing, and neurodevelopmental dimensions were each associated with distinct morphological and functional connectivity signatures. Connectivity signatures associated with the p factor and neurodevelopmental dimensions followed the sensory-to-transmodal axis of cortical organization, which is related to the emergence of complex cognition and risk for psychopathology. Results were consistent in two separate data subsamples and robust to variations in analytical parameters. Although model parameters yielded statistically significant brain-behavior associations in unseen data, generalizability of the model was rather limited for all three latent components (r change from within- to out-of-sample statistics: LC1within=0.36, LC1out=0.03; LC2within=0.34, LC2out=0.05; LC3within=0.35, LC3out=0.07). Our findings help in better understanding biological mechanisms underpinning dimensions of psychopathology, and could provide brain-based vulnerability markers.
Data availability
The ABCD data are publicly available via the NIMH Data Archive (https://nda.nih.gov/abcd/).The preprocessing pipeline can be found at https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/preprocessing/CBIG_fMRI_Preproc2016.Preprocessing code specific to this study can be found here: https://github.com/ThomasYeoLab/ABCD_scripts.The code for analyses can be found here: (https://github.com/valkebets/multimodal_psychopathology_components).
Article and author information
Author details
Funding
NUS Yong Loo Lin School of Medicine (NUHSRO/2020/124/TMR/LOA)
- BT Thomas Yeo
Singapore National Medical Research Council (OFLCG19May-0035; CTGIIT23jan-0001; OFIRG24jan-0030; STaR20nov-0003)
- BT Thomas Yeo
Singapore Ministry of Health (CG21APR1009)
- BT Thomas Yeo
Temasek Foundation (TF2223-IMH-01)
- BT Thomas Yeo
National Institutes of Health (R01MH133334)
- BT Thomas Yeo
Natural Sciences and Engineering Research Council of Canada (NSERC Discovery-1304413)
- Boris C Bernhardt
Canadian Institutes of Health Research (FDN-154298; PJT-174995)
- Boris C Bernhardt
Sick Kids Foundation (NI17-039)
- Boris C Bernhardt
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Human subjects: Ethical review and approval of the protocol was obtained from the Institutional Review Board (IRB) at the University of California, San Diego, as well as from local IRB (Auchter et al., 2018; https://doi.org/10.1016/j.dcn.2018.04.003). Parents/guardians and children provided written assent (Clark et al., 2018; https://doi.org/10.1016/j.dcn.2017.06.005).
Copyright
© 2024, Royer et al.
This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.
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Multimodal neural correlates of childhood psychopathology
eLife 13:e87992.
https://doi.org/10.7554/eLife.87992
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