Impact of Childhood Trauma on Executive Function in Adolescence-Mediating Functional Brain Networks and Prediction of High-Risk Drinking - PubMed
Impact of Childhood Trauma on Executive Function in Adolescence-Mediating Functional Brain Networks and Prediction of High-Risk Drinking
Sarita Silveira et al. Biol Psychiatry Cogn Neurosci Neuroimaging. 2020 May.
Abstract
Background: Childhood trauma is known to impart risk for several adverse life outcomes. Yet, its impact during adolescent development is not well understood. We aimed to investigate the relationships among childhood trauma, functional brain connectivity, executive dysfunction (ED), and the development of high-risk drinking in adolescence.
Methods: Data from the National Consortium on Alcohol and Neurodevelopment in Adolescence (sample size = 392, 55% female) cohort were used. This included resting-state functional magnetic resonance imaging at baseline, childhood trauma and ED self-reports, and detailed interviews on alcohol and substance use collected at baseline and at 4 annual follow-ups. We used longitudinal regression analyses to confirm the relationship between childhood trauma and ED, identified the mediating functional brain network hubs, and used these linkages to predict future high-risk drinking in adolescence.
Results: Childhood trauma severity was significantly related to ED in all years. At baseline, distributed functional connectivity from hub regions in the bilateral dorsal anterior cingulate cortex, right anterior insula, right intraparietal sulcus, and bilateral pre- and postcentral gyri mediated the relationship between childhood trauma and ED. Furthermore, high-risk drinking in follow-up years 1-4 could be predicted with high accuracy from the trauma-affected functional brain networks that mediated ED at baseline, together with age, childhood trauma severity, and extent of ED.
Discussion: Functional brain networks, particularly from hub regions important for cognitive and sensorimotor control, explain the relationship between childhood trauma and ED and are important for predicting future high-risk drinking. These findings are relevant for the prognosis of alcohol use disorders.
Keywords: Adolescence; Binge drinking; Brain networks; Childhood trauma; Development; Executive function.
Copyright © 2020 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.
Conflict of interest statement
DISCLOSURES
The authors report no biomedical financial interests or potential conflicts of interest.
Figures

Association between indices of the Childhood Trauma Questionnaire and the Behavior Rating Inventory of Executive Function (BRIEF) at baseline (BL) and at 1- (Y1), 2- (Y2), 3- (Y3), and 4-year (Y4) follow-ups.

(A) Functional region-to-region connections that mediate the Childhood Trauma Questionnaire–Behavior Rating Inventory of Executive Function relationship. Hub nodes were defined based on the sum total of significant connections from that region that fulfill criteria for mediation. Hubs with >3, >4, and >5 sum total mediating connections surpassing p < .05, p < .005, p < .0005 bootstrap thresholds for multiple comparisons are shown in cyan, blue, and yellow, respectively. (B) Sum total of independently significant mediating connections from each of the 236 regions of interest. Mediating hubs (i.e., regions of interest for which the total sum of mediating connections surpasses the bootstrap threshold for multiple comparisons) are labeled and correspond to the 11 hubs pictured in (A). Suffixes (1) and (2) refer to distinct mediating hubs in the same cortical region (see Table 2). aI, anterior insula; dACC, dorsal anterior cingulate cortex; IPS, intraparietal sulcus; l, left; post-CG, postcentral gyrus; pre-CG, precentral gyrus; r, right.

(A) Predictive model of future high-risk drinking in years 1–4 using baseline data. (B) Cumulative sensitivity and specificity of predicting high-risk drinkers in follow-up years 1–4 based on demographic, behavioral, and functional connectivity data at study baseline, with synthetic minority oversampling technique applied. Results of logistic regression (LR), support-vector machine (SVM), gradient boost (GB), AdaBoost (AB), and random forest (RF) algorithms are compared. For LR, results without any synthetic minority class over-sampling are also shown (LR SM–) to exemplify the poor sensitivity obtained without applying this technique. Model predictions are displayed against the 95% confidence interval = 44%–56% (blue region) for 50% chance level prediction (black line). (C) Relative feature importance for prediction of high-risk versus low-risk drinkers in follow-up years 1–4 using the random forest ensemble learning algorithm, which was most predictive (i.e., with combined highest sensitivity and specificity) among the tested models (B). Means and SDs of feature importance are shown across five folds of cross-validation. Suffixes (1) and (2) refer to distinct hubs in the same cortical region that mediate the childhood trauma → executive dysfunction relationship (see Table 2). aI, anterior insula; AUD, alcohol use disorder; Bl, baseline; dACC, dorsal anterior cingulate cortex; IPS, intraparietal sulcus; l, left; MDD, major depressive disorder; post-CG, postcentral gyrus; pre-CG, precentral gyrus; r, right.
Comment in
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Predicting Trajectories of Risk or Resilience in Traumatized Youth.
Barzilay R. Barzilay R. Biol Psychiatry Cogn Neurosci Neuroimaging. 2020 May;5(5):473-475. doi: 10.1016/j.bpsc.2020.03.002. Biol Psychiatry Cogn Neurosci Neuroimaging. 2020. PMID: 32386685 Free PMC article. No abstract available.
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References
-
- Felitti VJ, Anda RF, Nordenberg D, Williamson DF, Spitz AM, Edwards V, et al. (1998): Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults: The adverse childhoos experiences (ACE) study. Am J Prev Med 14:245–258. - PubMed
-
- Dube SR, Anda RF, Felitti VJ, Edwards VJ, Croft JB (2002): Adverse childhood experiences and personal alcohol abuse as an adult. Addict Behav 27:713–725. - PubMed
-
- Fuller-Thomson E, Roane JL, Brennenstuhl S (2016): Three types of adverse childhood experiences, and alcohol and drug dependence among adults: An investigation using population-based data. Subst Use Misuse 51:1451–1461. - PubMed