Abstract

BackgroundChildhood exposure to social risk has the potential to disrupt brain development and increase vulnerability to adverse mental health outcomes. Here, we examine the effect of adversity on brain structure and psychopathology in the Adolescent Brain and Cognitive Development (ABCD) study, a US population-based sample of 10 year-olds.MethodsPersonal, caregiver, family and neighborhood characteristics were considered in 9299 unrelated children [age: mean (sd)=9.9 y (0.6); 53% males]. Hidden Markov Models were used identify clusters of participants based on their psychosocial exposure. The identified clusters were compared in terms of current psychopathology, lifetime psychiatric diagnosis, intelligence and brain structure.ResultsABCD participants clustered in to a “disadvantaged” group (N=4205) with multiple adverse exposures, and an “enriched” group (N= 5094) with limited exposure to adversity and multiple protective factors. Compared to the enriched group, the disadvantaged group had higher levels of all types of psychopathology and lifetime psychiatric diagnoses; lower scores on fluid and crystallized intelligence; smaller subcortical volumes; thinner sensorimotor cortices and thicker cortex in frontal regions; smaller surface area in temporal regions and larger surface area in the posterior cingulate cortices (all p<0.05 following Bonferroni correction for multiple testing).ConclusionsSocial adversity has significant and wide-ranging consequences for brain development and psychopathology, that shows little specificity for types of symptoms.DisclosureNo significant relationships.

Highlights

  • Childhood exposure to social risk has the potential to disrupt brain development and increase vulnerability to adverse mental health outcomes

  • A focus on individual symptoms would, result in a more precise assessment of treatment efficacy and has potential in improving our understanding of the working mechanisms of treatment. Such an approach may help in improving the identification of patients who are -based on their pretreatment symptomatology- the most likely to benefit from a particular treatment

  • To show the potential of network estimation techniques in a) unraveling the diverse symptom-specific responses to various depression treatments and b) improving the identification of patients who are the most likely to benefit from these treatments

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Summary

Introduction

Childhood exposure to social risk has the potential to disrupt brain development and increase vulnerability to adverse mental health outcomes. Symptom-specific assessment of treatment efficacy: The potential of network estimation techniques A focus on individual symptoms would, result in a more precise assessment of treatment efficacy and has potential in improving our understanding of the working mechanisms of treatment.

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