Triple Interactions Between the Environment, Brain, and Behavior in Children: An ABCD Study

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Abstract Submission 

Dongmei Zhi¹, Rongtao Jiang², Godfrey Pearlson², Zening Fu³, Shile Qi⁴, Weizheng Yan⁵, Aichen Feng⁶, Ming Xu⁶, Vince Calhoun⁷, Jing Sui⁸

¹Beijing Normal University, Beijing, Select a State, ²Yale School of Medicine, New Haven, CT, ³Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) Georgi, Atlanta, GA, ⁴Nanjing University of Aeronautics and Astronautics, Nanjing, Jiang Su, ⁵Emory University, Atlanta, GA, ⁶Institute of Automation, Chinese Academy of Sciences, Beijing, Select a State, ⁷GSU/GATech/Emory, Decatur, GA, ⁸Beijing Normal University, Beijing, China

Dongmei Zhi  
Beijing Normal University
Beijing, Select a State

Rongtao Jiang  
Yale School of Medicine
New Haven, CT

Godfrey Pearlson  
Yale School of Medicine
New Haven, CT

Zening Fu  
Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) Georgi
Atlanta, GA

Shile Qi  
Nanjing University of Aeronautics and Astronautics
Nanjing, Jiang Su

Weizheng Yan  
Emory University
Atlanta, GA

Aichen Feng  
Institute of Automation, Chinese Academy of Sciences
Beijing, Select a State

Ming Xu  
Institute of Automation, Chinese Academy of Sciences
Beijing, Select a State

Vince Calhoun  
GSU/GATech/Emory
Decatur, GA

Jing Sui  
Beijing Normal University
Beijing, China

Despite the well-known fact that environmental exposures play a critical role in influencing behaviors [1], we have limited understanding of how these exposures interact with the brain and in turn shape our behaviors, especially during adolescence with rapid development of brain and behaviors [2].

In this work, we investigated the comprehensive environment-brain-behavior triple interactions among whole-brain functional network connectivity (FNC) derived from a spatially constrained single-subject ICA method [3], 41 environmental exposures (spanning perinatal, family, school, neighborhood and individual lifestyle), and 23 behaviors related to cognitive ability and mental health in 7655 children selected from the ABCD study at both baseline and longitudinally (Fig. 1) [4, 5]. Linear mixed-effect models were adopted to examine the associations between 41 environmental exposures and 1378 whole-brain FNC pairs, 10 cognitive abilities, and 13 mental health measures at both baseline and longitudinally, while adjusting for multiple confounders. Furthermore, we used partial least squares regression to identify key predictive FNC signatures and environmental exposures that support individual-level prediction of behaviors at both baseline and longitudinally. Most importantly, mediation analysis was used to examine whether and to what extent the 'predictome' FNC signatures mediated the significant environment-behavior associations.

We found family and neighborhood exposures such as family income and area deprivation index were common critical environmental influencers on cognitive ability and mental health at both baseline and longitudinally (Fig. 2A). Healthy perinatal development was unique protective factor for evolving better cognitive ability, whereas sleep problems, family conflicts and adverse school environments specifically increase risk of mental health. As illustrated in Fig. 2B, family income and caregiver education are the top 2 ranked exposures influencing most FNCs, which manifest as similar network architectures, especially the cross-module connections. Subcortical network stands out with the highest vulnerability to environment, mainly in domains of family, perinatal and neighborhood exposures, where the thalamus was the most susceptible to environmental influences (Fig. 2C, D, E).
Moreover, FNC demonstrated more predictive power for cognitive abilities than mental health, where thalamus and hippocampus play important roles in longitudinal prediction, while environmental exposures demonstrated more predictive power than FNC in both baseline and longitudinal prediction of all behaviors, especially for mental health (r = 0.31~0.63) (Fig. 2F). Results highlighted FNCs within subcortical (SCN) and cognitive control (CCN) networks, and between SCN-SMN as the most contributing networks to predict mental problems, and within CCN, default mode networks (DMN), and between DMN-CCN for predicting cognitive abilities (Fig. 2G). Notably, these predictions remained significant even controlling for multiple covariates, and site harmonization via ComBat (Fig. 2H). Most importantly, we successfully validated the FNC-based prediction of fluid intelligence using independent UK Biobank data (N = 20,852, Fig. 2I). Finally, the identified predictive FNCs can also mediate the environment-behavior associations significantly, implicating the plastic and flexible environment-brain-behavior interactive loops.

Collectively, this work investigated the environment-brain-behavior triple interactions in children comprehensively based on ABCD data at both baseline and longitudinally, identified CCN, DMN, and SCN as the most predictive functional networks for a wide repertoire of behaviors, and underscored the long-lasting impact of critical environmental exposures on childhood development, especially the attainable targets with family conflict, sleep quality, school and neighborhood environments to promote the healthy development of adolescents.

Early life, Adolescence, Aging ¹

Multivariate Approaches ²

Cognition

Development

FUNCTIONAL MRI

Machine Learning

Statistical Methods

Other - Environmental exposure, mental health, functional network connectivity, individualized prediction, mediation analysis.