Study Reveals That Brain Development in Teens Could Predict Drinking Behavior

A man drinking alcohol

During adolescence, adolescent brains are rapidly creating new connections. Networks associated with reward and inhibition, two systems that typically develop differently in males and females, are two of the systems that undergo rewiring during this phase of development.
In a study that has recently been published in JAMA Psychiatry, Sarah W. Yip and her colleagues, Sarah D. Lichenstein and Qinghao Liang examined an extensive MRI dataset of adolescent brains to determine if they could predict drinking behaviour in teenagers by looking at how these two systems reorganise during development.

Introduction to the Study:

According to the study, how inhibitory and rewarding pathways- which generally control “brake” and “go” behaviour—develop can predict how likely those teenagers will be to drink extensively in the future. According to Sarah W. Yip, PhD, associate professor of psychiatry and in the Yale Child Study Centre, “mapping adolescent brain networks can aid in the prediction of both present and future risky drinking behaviour”.

Aiming to identify these sex differences in the brain, Yip and her associates—including major contributors Sarah D. Lichenstein, PhD, assistant professor of psychiatry; Godfrey Pearlson, MBBS, MA, professor of psychiatry and of neuroscience; and Qinghao Liang, PhD candidate—wanted to test their hypothesis. “We were aware that there might be sex-related differences in how alcohol use develops. Therefore, we were interested in seeing if there were any differences in brain networks between men’s and women’s alcohol usage” they added.

Data Collection:

The Alcohol Use Disorder Identification Test (AUDIT) was used to determine whole-brain functional organisation patterns related to current and future alcohol use risk. Longitudinal multisite functional magnetic resonance imaging (fMRI) data were gathered at ages 14 and 19.
The IMAGEN consortium, a European multisite research of adolescent neurodevelopment, gathered primary data. Using information from a single-site research of collegiate alcohol use conducted in the US, the model’s generalizability was further examined.
The main sample was a developmental cohort of 1359 teenagers with information on alcohol use, phenotyping, and neuroimaging. A different cohort of 114 people was used to evaluate the generalizability of the model in more detail.

Data Findings:

The study’s 1359 participants had an average age of 14.42 (0.40) years, with 729 of them (or 54%) being female. The data-driven, whole-brain connectivity approach identified networks linked to vulnerability for current and future AUDIT-defined alcohol use risk (primary outcomes, as stated above, future: 0.22; P .001 and present: 0.27; P .001).

The accuracy of brain-behaviour models was also found to differ by gender, with female-only models regularly outperforming male-only models. Specifically, utilising data collected during both reward and inhibitory fMRI tasks, female-only models identified networks conferring sensitivity for present and future severity. However, utilising data collected during the inhibitory control—but not the rewarding—task, male-only models were successful in correctly identifying networks, revealing the domain specificity of alcohol use risk networks in male adolescents.

Implications for Targeted Intervention Strategies:

These findings indicate that while interventions targeting inhibitory control processes may be successful in reducing alcohol use risk in male adolescents, it is probable that both inhibitory and reward-related processes are relevant to alcohol use behaviours in adolescents who are female. They also uncover brand-new networks of youth alcohol consumption risk that could be utilised to spot at-risk teenagers and guide intervention efforts. Male and female students experienced the same systems and sex differences as expected, so “the same networks predicted risky drinking behaviour even when the contexts and nations were different,” according to Yip.

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