Reliable Multimodal Brain Signatures Predict Mental Health Outcomes in Children.

Abstract

Background: Interindividual brain differences likely precede the emergence of mood and anxiety disorders; however, the specific brain alterations remain unclear. While many studies focus on a single imaging modality in isolation, recent advances in multimodal image analysis allow for a more comprehensive understanding of the complex neurobiology that underlies mental health.

Methods: In a large population-based cohort of children from the ABCD (Adolescent Brain Cognitive Development) Study (N > 10,000), we applied data-driven linked independent component analysis to identify linked variations in cortical structure and white matter microstructure that together predict longitudinal behavioral and mental health symptoms. Brain differences were examined in a subsample of twins depending on the presence of at-risk behaviors.

Results: Two multimodal brain signatures at ages 9 to 10 years predicted longitudinal mental health symptoms from 9 to 12 years, with small effect sizes. Cortical variations in association, limbic, and default mode regions linked with peripheral white matter microstructure together predicted higher depression and anxiety symptoms across 2 independent split-halves. The brain signature differed between depression and anxiety symptom trajectories and related to emotion regulation network functional connectivity. Linked variations of subcortical structures and projection tract microstructure variably predicted behavioral inhibition, sensation seeking, and psychosis symptom severity over time in male participants. These brain patterns were significantly different between pairs of twins discordant for self-injurious behavior.

Conclusions: Our results demonstrate reliable, multimodal brain patterns in childhood, before mood and anxiety disorders tend to emerge, that lay the foundation for long-term mental health outcomes and offer targets for early identification of children at risk.