Multisystem Environmental Factors Elucidate Shared and Distinct Associations With Brain and Behavior in Adolescents - 20/11/25

Doi : 10.1016/j.jaac.2025.10.008

Jivesh Ramduny, PhD ^a,^⁎ , Samuel Paskewitz, PhD ^a, Inti A. Brazil, PhD ^b, Arielle Baskin-Sommers, PhD ^a
^a Yale University, New Haven, Connecticut
^b Radboud University, Nijmegen, the Netherlands

^∗Correspondence to Jivesh Ramduny, PhD, Yale University, 100 College Street, New Haven, CT 06520-8047100 College StreetNew HavenCT06520-8047

Sous presse. Épreuves corrigées par l'auteur. Disponible en ligne depuis le Thursday 20 November 2025

Abstract

Objective

Environmental factors have long been shown to influence brain structure and adolescent psychopathology. However, almost no research has included environmental factors spanning micro-to-macro-systems, brain structure, and psychopathology in an integrated framework. Here, we assessed the ways and degree to which multisystem environmental factors during late childhood are associated with subcortical volume and psychopathology during early adolescence.

Method

We used baseline, 2-year follow-up, and 3-year follow-up data from the Adolescent Brain Cognitive Development℠ Study (n = 2,766). A Bayesian latent profile analysis was applied to obtain distinct multisystem environmental profiles during late childhood. The profiles were used in a path analysis to derive their direct and indirect effects on subcortical volume and psychopathology during early adolescence.

Results

Bayesian latent profile analysis revealed 9 environmental profiles. Two distinct profiles were directly associated with greater externalizing psychopathology in adolescents: (1) adversity across family, school, and neighborhood systems, and (2) family conflict and low school involvement. In contrast, a profile of family and neighborhood affluence was directly associated with lower externalizing psychopathology. Furthermore, family/neighborhood affluence was associated with higher subcortical volume, which in turn was associated with lower externalizing and internalizing psychopathology; conversely, a family economic and neighborhood adversity profile was associated with lower subcortical volume, which in turn was associated with higher externalizing and internalizing psychopathology.

Conclusion

We identified environmental and brain-related equifinal pathways associated with externalizing and internalizing psychopathology. This work highlights the importance of considering the role of multiple systems and factors in the conceptualization and treatment of adolescent psychopathology.

Diversity & Inclusion Statement

One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented racial and/or ethnic groups in science. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented sexual and/or gender groups in science. One or more of the authors of this paper received support from a program designed to increase minority representation in science. We actively worked to promote sex and gender balance in our author group. We actively worked to promote inclusion of historically underrepresented racial and/or ethnic groups in science in our author group. While citing references scientifically relevant for this work, we also actively worked to promote sex and gender balance in our reference list. While citing references scientifically relevant for this work, we also actively worked to promote inclusion of historically underrepresented racial and/or ethnic groups in science in our reference list. The author list of this paper includes contributors from the location and/or community where the research was conducted who participated in the data collection, design, analysis, and/or interpretation of the work.

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Key words : adolescence, environment, subcortical brain volume, psychopathology, externalizing

Plan

	Additional support for this work was made possible from the National Institute of Environmental Health Sciences (NIEHS) R01-ES032295, R01-ES031074, and R21DA057592. This work also obtained support from the Yale Kavli Institute for Neuroscience and the Wu Tsai Institute at Yale University.
	This work has been previously posted on a preprint server: 2024.12.17.628982v1
	Data Sharing: Data used in the preparation of this article were obtained from the ABCD Study® (abcdstudy.org/), held in the NIMH Data Archive (NDA). This is a multisite, longitudinal study designed to recruit more than 10,000 children aged 9-10 and follow them over 10 years into early adulthood. The ABCD Study is supported by the National Institutes of Health (NIH) and additional federal partners under award numbers: U01DA041048, U01DA050989, U01DA051016, U01DA041022, U01DA051018, U01DA051037, U01DA050987, U01DA041174, U01DA041106, U01DA041117, U01DA041028, U01DA041134, U01DA050988, U01DA051039, U01DA041156, U01DA041025, U01DA041120, U01DA051038, U01DA041148, U01DA041093, U01DA041089, U24DA041123, U24DA041147. The full list of federal supporters is available at federal-partners.html. The complete lists of participating sites and study investigators can be found at consortium_members/. The ABCD Consortium investigators designed and implemented the study and/or provided the data but did not necessarily participate in the 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.
	Code Availability: The analysis code for the Bayesian LPA framework can be found at dpm.lpa. The analysis code for the integrated approach can be found at embeddedbrain.
	Samuel Paskewitz, PhD, served as the statistical expert for this research.
	We thank the Yale Center for Research Computing for guidance and use of the research computing infrastructure.
	Disclosure: Jivesh Ramduny, Samuel Paskewitz, Inti A. Brazil, and Arielle Baskin-Sommers have reported no biomedical financial interests or potential conflicts of interest.