Neural function associated with substance use resilience among vulnerable youth Meghan E. Martz, PhD, Robert A. Zucker, PhD, Mary M. Heitzeg, PhD Department of Psychiatry, University of Michigan INTRODUCTION Figure 1. Hierarchical logistic regression analyses CONCLUSIONS Model 1 Early adolescence 1. Reactive control 2. Externalizing behaviors Model 2 Late adolescence Model 3 Early adulthood 1. Inhibitory control 2. Reward responsivity Transition to adulthood Resilient (low binge drinking/marijuana use) vs. Risk (high binge drinking/marijuana use) Youth with a family history of substance use disorder (SUD; FH+) are vulnerable to develop drug and alcohol use problems, in part, through a risk phenotype characterized by behavioral undercontrol/disinhibition (Zucker et al., 2011). Yet, a resilient subgroup of FH+ youth are not heavy substance users (Chassin et al., 2002). Few studies have examined both psychosocial and neural mechanisms protective against heavy substance use. The present study addresses this gap by examining the extent to which neural function involved in disinhibition predicts resilience among FH+ youth over and above psychosocial measures of behavioral control. This work is important, because neuroimaging assessments may be able to uncover unique identifiers of resilience that psychosocial measures are unable to detect. Greater activation in the right DLPFC related to inhibitory control may be a protective factor among resilient youth, over and above psychosocial measures of early adolescent reactive control and late adolescent externalizing behaviors. Testing VS activation during reward anticipation and feedback contrasts did not result in significant differences between resilient and risk groups. Thus, a greater level of inhibitory control may be an indicator of resilience among FH+ youth who are predisposed to disrupted reward responsivity. Given that the DLPFC is involved in top-down cognitive control processes (Garavan et al., 2002; MacDonald et al., 2000) and shares connections with brain regions associated with reward responsivity, resilient FH+ youth may have a greater capacity for inhibitory control over reward-driven impulses. Control measures Sex Number of parents with SUD RESULTS Resilient youth (N=21) were in the low binge drinking and low marijuana use trajectory groups and had no occasions of weekly binge drinking or monthly marijuana use (Figure 2). Risk youth (N=36) were in the chronic high or late-onset binge drinking and/or chronic high marijuana use trajectory groups and reported at least 2 occasions of weekly binge drinking and/or marijuana use (Figure 2). Figure 2. Best fitting trajectory models among full MLS sample METHODS CLINICAL IMPLICATIONS Marijuana Use Trajectory Groups Binge Drinking Trajectory Groups Pre- and post-test neuroimaging assessments can provide a baseline measure of inhibitory control that could be tested again after completion of interventions aimed at boosting self-regulation skills among FH+ youth. Neuroimaging techniques, such as fMRI, may be useful to prospectively identify neural markers of resilience among vulnerable populations. Sample 57 FH+ youth (28% female) from the neuroimaging subsample of the Michigan Longitudinal Study (MLS), an ongoing, prospective study of youth from families with high levels of SUD (Zucker et al., 2000) Measures Substance use: Past year binge drinking and marijuana use (ages 17-26) Psychosocial measures: Reactive control and externalizing behaviors (ages 12-14; ages 17-18) Neural measures: Go/No-Go Task; Monetary Incentive Delay Task (MIDT) (age 20) Control measures: Sex and number of parents with SUD Analytic Plan Step 1: Form resilient and risk groups using growth mixture modeling (GMM) and empirically-based cut points Step 2: Identify regions of interest (ROIs) showing significant whole-brain task activation from Go/No-Go Task and MIDT during fMRI Step 3: Test hierarchical logistic regression models (Figure 1) Chronic high 18.2% Chronic high 3.5% Moderate 10.9% Late onset 11.2% Low/non-use 70.9% Low/non-use 85.3% Ages 17-18 Ages 19-20 Ages 21-22 Ages 23-24 Ages 25-26 Ages 17-18 Ages 19-20 Ages 21-22 Ages 23-24 Ages 25-26 BIC=5691.71, Entropy=0.97, LMR=155.28, p<0.01 BIC=15242.77, Entropy=0.95, LMR=158.41, p<0.001 Greater activation in the right dorsolateral prefrontal cortex (DLPFC) during correct inhibition, over and above greater reactive control in early adolescence and lower externalizing behaviors in late adolescence, was a significant predictor of resilience (Figure 3). No other ROIs from the Go/No-Go Task (right inferior orbitofrontal gyrus, left middle frontal gyrus) or MIDT (left and right ventral striatum (VS)) were significant neural predictors of resilience in Model 3. Corresponding author: Meghan E. Martz, PhD mmartz@umich.edu Figure 3. Hierarchical logistic regression results Resilient vs. Risk Group Model 1 Model 2 Model 3 OR 95% CI Male 0.74 (0.13, 4.31) 0.45 (0.06, 3.44) 0.96 (0.09, 10.36) Parents with SUD 0.86 (0.18, 4.20) 0.88 (0.14, 5.61) 0.09 (0.00, 2.01) Reactive control (ages 12-14) 1.61 (0.83, 3.12) 1.72 (0.80, 3.72) 3.28* (1.07, 10.08) Externalizing (ages 12-14) 0.93 (0.82, 1.05) 0.97 (0.85, 1.12) 1.01 (0.87, 1.17) Reactive control (ages 17-18) 1.28 (0.45, 3.63) 0.83 (0.24, 2.82) Externalizing (ages 17-18) 0.78* (0.62, 0.98) 0.70* (0.51, 0.96) Right DLPFC (Go/No-Go Task) 1.88* (1.03, 3.44) *p<0.05, **p<0.01 Nagelkerke R2=0.22, Model χ2=6.78, p=ns Nagelkerke R2=0.40, Model χ2=13.48, p<0.05 Nagelkerke R2=0.55, Model χ2=20.11, p<0.01 NIAAA: R01 AA12217 and R01 AA07065 to R. Zucker and M. Heitzeg, T32 AA07477 to F. Blow; NIDA: R01 DA027261 to M. Heitzeg and R. Zucker