What is it about?

To understand the onset of heavy drinking habits and develop prevention strategies, we need to characterize predisposition profiles at early ages. This longitudinal work provides important evidence by showing how adolescents at risk for engaging in alcohol behaviors showed resting-state functional connectivity and gray matter differences years before. The combination of these metrics allows us to establish predictive models of future alcohol episodes. In addition, differences in functional connectivity showed a positive relationship with behavioral variables such as lower executive functions and higher sensation seeking. These predisposition traits may rely on divergent neurodevelopmental pathways and deeper neurobiological abnormalities, such as dysfunctions of inhibitory neurotransmission and/or a genetic background of vulnerability.

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Why is it important?

These results highlight the presence of alterations prior to consumption, possibly related to different neuromaturative trajectories. On the other hand, the identification of risk profiles represents an advance in the knowledge of the causes behind these behaviours and the first step in the development of possible prevention strategies.

Perspectives

The use of alcohol as a form of entertainment is becoming increasingly normalised among the adolescent population. Consumption typically starts at the age of 14 and escalates to heavy episodic drinking around the age of 16. This pattern of use is associated with the development of alterations in brain structure and function. However, numerous research studies indicate that some of these differences can be found in stages prior to consumption. For this reason, we ask the question: Can we predict earlier drinking from neuroimaging data?

Alberto del Cerro León
Universidad Complutense de Madrid

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This page is a summary of: Adolescent alcohol consumption predicted by differences in electrophysiological functional connectivity and neuroanatomy, Proceedings of the National Academy of Sciences, October 2024, Proceedings of the National Academy of Sciences,
DOI: 10.1073/pnas.2320805121.
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