Tam T. Nguyen-Louie

Neural Predictors of Initiating Alcohol Use During Adolescence

OBJECTIVE Underage drinking is widely recognized as a leading public health and social problem for adolescents in the United States. Being able to identify at-risk adolescents before they initiate heavy alcohol use could have important clinical and public health implications; however, few investigations have explored individual-level precursors of adolescent substance use. This prospective investigation used machine learning with demographic, neurocognitive, and neuroimaging data in substance-naive adolescents to identify predictors of alcohol use initiation by age 18. METHOD Participants (N=137) were healthy substance-naive adolescents (ages 12-14) who underwent neuropsychological testing and structural and functional magnetic resonance imaging (sMRI and fMRI), and then were followed annually. By age 18, 70 youths (51%) initiated moderate to heavy alcohol use, and 67 remained nonusers. Random forest classification models identified the most important predictors of alcohol use from a large set of demographic, neuropsychological, sMRI, and fMRI variables. RESULTS Random forest models identified 34 predictors contributing to alcohol use by age 18, including several demographic and behavioral factors (being male, higher socioeconomic status, early dating, more externalizing behaviors, positive alcohol expectancies), worse executive functioning, and thinner cortices and less brain activation in diffusely distributed regions of the brain. CONCLUSIONS Incorporating a mix of demographic, behavioral, neuropsychological, and neuroimaging data may be the best strategy for identifying youths at risk for initiating alcohol use during adolescence. The identified risk factors will be useful for alcohol prevention efforts and in research to address brain mechanisms that may contribute to early drinking.

Neural predictors of alcohol use and psychopathology symptoms in adolescents

Adolescence is a period marked by increases in risk taking, sensation seeking, and emotion dysregulation. Neurobiological models of adolescent development propose that lagging development in brain regions associated with affect and behavior control compared to regions associated with reward and emotion processing may underlie these behavioral manifestations. Cross-sectional studies have identified several functional brain networks that may contribute to risk for substance use and psychopathology in adolescents. Determining brain structure measures that prospectively predict substance use and psychopathology could refine our understanding of the mechanisms that contribute to these problems, and lead to improved prevention efforts. Participants (N = 265) were healthy substance-naïve adolescents (ages 12-14) who underwent magnetic resonance imaging and then were followed annually for up to 13 years. Cortical thickness and surface area measures for three prefrontal regions (dorsolateral prefrontal cortex, inferior frontal gyrus, and orbitofrontal cortex) and three cortical regions from identified functional networks (anterior cingulate cortex, insular cortex, and parietal cortex) were used to predict subsequent binge drinking, externalizing symptoms, and internalizing symptoms. Thinner dorsolateral prefrontal cortex and inferior frontal cortex in early adolescence predicted more binge drinking and externalizing symptoms, respectively, in late adolescence (ps < .05). Having a family history of alcohol use disorder predicted more subsequent binge drinking and externalizing symptoms. Thinner parietal cortex, but not family history, predicted more subsequent internalizing symptoms (p < .05). This study emphasizes the temporal association between maturation of the salience, inhibition, and executive control networks in early adolescence and late adolescent behavior outcomes. Our findings indicate that developmental variations in these brain regions predate behavioral outcomes of substance use and psychopathology, and may therefore serve as prospective biomarkers of vulnerability.

Effects of sleep on substance use in adolescents: a longitudinal perspective

Substance use (SU) and sleep problems appear interrelated, but few studies have examined the influence of adolescent sleep patterns on development of SU disorders. This study prospectively examined the influence of sleep habits on subsequent SU in youth who later transitioned into heavy drinking. At time 1 (T1), participants (n = 95) were substance‐naive 12‐ to 14‐year‐olds. Path‐analytic models examined whether the effects of T1 risk factors (familial SU disorder, inhibition control, and externalizing and internalizing traits) on time 3 (M = 19.8 years old) tobacco, alcohol, and cannabis were mediated by time 2 (M = 15.1 years old) sleep chronotype, daytime sleepiness, and erratic sleep/wake behaviors. Significant direct path effects of T1 risk factors and time 2 sleep behaviors on time 3 SU were found, Ps < 0.05. In models that examined the effect of each individual sleep behavior separately on SU, more erratic sleep/wake and greater daytime sleepiness predicted higher lifetime use events for all substances (Ps < 0.01). Higher evening chronotype tendencies predicted lower tobacco and higher alcohol and cannabis lifetime use events (Ps < 0.01). Erratic sleep/wake behaviors mediated the effect of inhibitory control on subsequent SU; less erratic sleep/wake behaviors predicted better inhibition control ( β̂ = −0.20, P < 0.05). Early‐mid adolescent psychiatric health and sleep behaviors prior to drinking onset predicted greater SU 5 years later. Participants were substance‐naïve at baseline, allowing for the examination of temporal order in the relationship between sleep problems and alcohol use. Early adolescent sleep problems may be an important risk factor for SU in later life.

Approaching Adolescent Substance Abuse Treatment through Neuroscience

Although the human brain reaches 90 percent of its full size by age six (Reiss et al., 1996), structures continue to develop throughout adolescence and into adulthood. During this crucial developmental period, cortical and subcortical structures are refined and reorganized as changes in gray and white matter take place. Subcortical gray matter, including the hippocampus and limbic system structures, increase in volume linearly with age. At the same time, cortical gray matter follows an inverted-U-shaped pattern of development, in which an initial increase in volume is followed by a period of decrease before reaching full maturation (Giedd, 2004). Evidence suggests that the increased volume reflects active synaptogenesis and dendritic arborization, rather than the creation of new neurons (Shaw et al., 2006). After structures reach their peak sizes, unnecessary and unused connections are selectively eliminated (Tamnes et al., 2010). This suggests that adolescent neurodevelopment is not a passive, predetermined process. Neuronal proliferation and pruning may be intricately linked to environmental factors in which new synapses are created to accommodate learned materials. Importantly, environmental factors and experiences likely play a critical role in determining which circuits are retained (Greenough et al., 1987).