(PS3-40) Predictors and Structural Brain Differences Associated With Depressive Symptoms in Adolescents

Depression is a prevalent mental health disorder that affects adolescents across diverse backgrounds. This study examines how demographic characteristics, family psychiatric history, and screen time relate to depressive symptoms in adolescents. Exploratory analyses investigated the relationship between depressive symptoms and global brain structure, focusing on cortical thickness and surface area.
Data were analyzed from the Adolescent Brain Cognitive Development (ABCD) Study. Participants were ages 9-10 at baseline and we examined longitudinal data across five years total. Depressive symptoms were measured using the DSM5-oriented-depressive problems score from the Child Behavior Checklist (CBCL). A linear mixed model (LMM) was used to assess relationships between depressive symptoms and sex, race, socioeconomic status (parental education, total household income), screen time, and family psychiatric history. Final LMM sample sizes per year were as follows: baseline (n = 8439), year 1 (n = 7982), year 2 (n = 7786), year 3 (n = 7248), and year 4 (n = 3306).
Exploratory analyses were conducted separately using linear models to investigate the relationship between baseline depressive symptoms and mean cortical thickness as well as total cortical surface area, controlling for sex and race (N = 9086).
Significant associations were found between depressive symptoms and sex, race, income, screen time, and family psychiatric history. Females had significantly higher depressive symptoms than males (p < 0.001). White adolescents had higher depressive symptoms than Black adolescents (p < 0.001). Lower household income was associated with higher depressive symptoms (p < 0.001), while parental education was not related. Higher screen time was associated with greater depressive symptoms (p < 0.001). Of the family history factors, parental depression history had the strongest association to depressive symptoms (p < 0.001), with maternal depression having a greater association than paternal. Family histories of bipolar, antisocial traits, and anxiety were positively associated with greater depressive symptoms (p < 0.001). Family history of substance use and psychotic disorders were not associated.
The exploratory analyses revealed that depressive symptoms were negatively associated with total cortical surface area (p < 0.001) but unrelated to mean cortical thickness (p=0.20). Females showed greater association between depressive symptoms and cortical surface area relative to males.
Our findings reinforce the idea that depression is influenced by a combination of demographic, environmental, and familial factors. The exploratory findings also support that surface area may be a more sensitive marker of depression-related brain differences. Additionally, the sex-specific results highlight the need for further investigation on sex differences in adolescent depression.
These results may inform early interventions or prevention strategies in higher-risk populations. Future research should explore causal mechanisms linking these factors to depression and longitudinal changes in brain structure associated with depressive symptoms.