A prospective investigation of youth alcohol experimentation and reward responsivity in the ABCD study - PubMed (original) (raw)
A prospective investigation of youth alcohol experimentation and reward responsivity in the ABCD study
April C May et al. Front Psychiatry. 2022.
Abstract
Rationale: Greater risk-taking behaviors, such as alcohol experimentation, are associated with different patterns of brain functioning in regions implicated in reward (nucleus accumbens, NA) and cognitive control (inferior frontal gyrus, IFG). These neural features have been observed in youth with greater risk-taking tendencies prior to substance use initiation, suggesting NA-IFG disruption may serve as an early marker for subsequent substance use disorders. Prospective studies are needed to determine if NA-IFG neural disruption predicts future substance use in school-age children, including those with minimal use of alcohol (e.g., sipping). The present large-sample prospective study sought to use machine learning to: (1) examine alcohol sipping at ages 9, 10 as a potential behavioral indicator of concurrent underlying altered neural responsivity to reward, and (2) determine if alcohol sipping and NA-IFG activation at ages 9, 10 can be used to predict which youth reported increased alcohol use at ages 11, 12. Additionally, low-level alcohol use and brain functioning at ages 9, 10 were examined as predictors of substance use and brain functioning at ages 11, 12.
Design and methods: This project used data from the baseline (Time 1) and two-year follow-up (Time 2) assessments of the Adolescent Brain Cognitive Development (ABCD) Study (Release 3.0). Support Vector Machine (SVM) learning determined if: (1) NA-IFG neural activity could correctly identify youth who reported alcohol sipping at Time 1 (n = 7409, mean age = 119.34 months, SD = 7.53; 50.27% female), and (2) NA-IFG and alcohol sipping frequency at Time 1 could correctly identify youth who reported drinking alcohol at Time 2 (n = 4000, mean age = 143.25 months, SD = 7.63; 47.53% female). Linear regression was also used to examine the relationship between alcohol sipping and NA-IFG activity at Time 1 and substance use and NA-IFG activity at Time 2. Data were also examined to characterize the environmental context in which youth first tried sips of alcohol (e.g., with or without parental permission, as part of a religious experience).
Results: Approximately 24% of the sample reported having tried sips of alcohol by ages 9, 10. On average, youth reported trying sips of alcohol 4.87 times (SD = 23.19) with age of first sip occurring at 7.36 years old (SD = 1.91). The first SVM model classified youth according to alcohol sipping status at Time 1 no better than chance with an accuracy of 0.35 (balanced accuracy = 0.52, sensitivity = 0.24, specificity = 0.80). The second SVM model classified youth according to alcohol drinking status at Time 2 with an accuracy of 0.76 (balanced accuracy = 0.56, sensitivity = 0.21, specificity = 0.91). Linear regression demonstrated that frequency of alcohol sipping at Time 1 predicted frequency of alcohol use at Time 2 (p < 0.001, adjusted _R_ 2 = 0.075). Alcohol sipping at Time 1 was not linearly associated with NA or IFG activity at Time 2 (all _p_s > 0.05), and NA activity at Time 1 and Time 2 were not related (all _p_s > 0.05). Activity in the three subsections of the IFG at Time 1 predicted activity in those same regions at Time 2 (all _p_s < 0.02).
Conclusions and implications: Early sips of alcohol appear to predict alcohol use in early adolescence. Findings do not provide strong evidence for minimal early alcohol use (sipping) as a behavioral marker of underlying alterations in NA-IFG neural responsivity to reward. Improving our understanding of the neural and behavioral factors that indicate a greater propensity for future substance use is crucial for identifying at-risk youth and potential targets for preventative efforts.
Keywords: alcohol experimentation; alcohol sipping; inferior frontal gyrus; machine learning; nucleus accumbens; support vector machine; youth.
Copyright © 2022 May, Jacobus, Simmons and Tapert.
Conflict of interest statement
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Figures
FIGURE 1
Monetary Incentive Delay Task used in the Adolescent Brain and Cognitive Development (ABCD) Study (53). Adapted from Knutson et al. (50).
FIGURE 2
Depiction of location of ROIs used in analyzes including bilateral pars opercularis (red), pars triangularis (green), pars orbitalis (yellow), and nucleus accumbens (aqua).
FIGURE 3
Data cleaning steps for Hypothesis 1 resulting in a subsample of n = 7409.
FIGURE 4
Support Vector Machine (SVM) results for Hypothesis 1. (A) Graph depicting accuracy vs. cost for model selection. (B) Receiver Operating Characteristic (ROC) Curve. (C) Importance scores for each feature.
FIGURE 5
Support Vector Machine (SVM) results for Hypothesis 3. (A) Graph depicting accuracy vs. cost for model selection. (B) Receiver Operating Characteristic (ROC) Curve. (C) Importance scores for each feature.
References
- Johnston LD, Miech RA, O’Malley PM, Bachman JG, Schulenberg JE, Patrick ME. Monitoring the Future National Survey Results on Drug use 1975-2018: Overview, key Findings on Adolescent Drug Use. Ann Arbor, MI: Institute for Social Research; (2019).
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