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Structural Covariance Network Properties Predictive of Early Adolescent Alcohol Initiation
H Byrne1, R Visontay1, E K Devine1
1The Matilda Centre for Research in Substance Use and Mental Health, The University of Sydney.
Importance:
Early alcohol initiation (before age 15) is associated with adverse outcomes. Understanding mechanisms behind early alcohol initiation is essential for informing prevention efforts.
Objective:
To examine whether structural covariance network properties at ages 9-10 years predict early alcohol initiation.
Design:
Case-control, population-based study design.
Setting:
Data from the Adolescent Brain Cognitive Development study were used. Baseline structural brain imaging data (ages 9-10) were used for generation and comparison of structural covariance networks. Data from baseline to 4-year follow-up (≤age 15) assessments were used to determine alcohol initiation.
Participants:
Participants were excluded if they reported consuming a full drink of alcohol at baseline, or did not meet imaging inclusion criteria. Controls were excluded if they had not yet been assessed or were missing substance use data at 4-year follow-up. In total, 3,878 participants met study criteria, of which 182 participants initiated alcohol. Structural covariance network properties were compared between the full sample and a 1:1 propensity-matched sample based on age, sex, race, ethnicity, religion, parental education, prenatal alcohol exposure, and baseline alcohol sipping.
Main Outcomes And Measures:
Structural covariance networks were estimated using regional cortical thickness and volume measurements. Measures of network segregation (modularity, clustering coefficient), integration (characteristic path length, global efficiency), and resilience (degree assortativity) were compared between groups. Early alcohol initiation was defined as consuming a full drink between baseline and 4-year follow-up.
Results:
Alcohol initiators (n=182, median[IQR] age, 10.3[9.9-10.8]; 101 female[55.5%]) demonstrated lower network segregation (modularity: area-under-the-curve[AUC] difference[95%CI]=-0.017[-0.017,-0.007], p=0.030; clustering coefficient: AUC[95%CI]=-0.026[-0.027,-0.012], p=0.0495) and higher network integration (characteristic path length: AUC[95%CI]=-0.106[-0.099,-0.046], p=0.020; global efficiency: AUC[95%CI]=0.011[0.005,0.011], p=0.010), compared to non-initiators (n=3,696, median[IQR] age, 9.9[9.4-10.4]; 1750 female[47.4%]) when controlling for age, sex, and mean cortical thickness. Within the matched sample, only differences in network integration were preserved (characteristic path length: AUC[95%CI]=-0.044[-0.032,0.035], p=0.010; global efficiency: AUC[95%CI]=0.003[-0.003,0.003], p=0.040). There were no differences between full or matched samples when comparing cortical volume structural covariance networks.
Conclusions And Relevance:
Differences in cortical thickness structural covariance network properties at ages 9-10 predicted alcohol initiation before age 15. These findings suggest cortical thickness network topology may reflect a neuroanatomical risk marker for early alcohol initiation.
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