Brain structural covariance network features are robust markers of early heavy alcohol use.

ABSTRACT:

Background and aims

Recently, we demonstrated that a distinct pattern of structural covariance networks (SCN) from magnetic resonance imaging (MRI)-derived measurements of brain cortical thickness characterized young adults with alcohol use disorder (AUD) and predicted current and future problematic drinking in adolescents relative to controls. Here, we establish the robustness and value of SCN for identifying heavy alcohol users in three additional independent studies.

Design and setting

Cross-sectional and longitudinal studies using data from the Pediatric Imaging, Neurocognition and Genetics (PING) study (n = 400, age range = 14-22 years), the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) (n = 272, age range = 17-22 years) and the Human Conne

SUBMITTER: Ottino-Gonzalez J 

PROVIDER: S-EPMC10872365 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature