Multi-level predictors of depression symptoms in the Adolescent Brain Cognitive Development (ABCD) study

J Child Psychol Psychiatry. 2022 Dec;63(12):1523-1533. doi: 10.1111/jcpp.13608. Epub 2022 Mar 21.

Abstract

Background: While identifying risk factors for adolescent depression is critical for early prevention and intervention, most studies have sought to understand the role of isolated factors rather than across a broad set of factors. Here, we sought to examine multi-level factors that maximize the prediction of depression symptoms in US children participating in the Adolescent Brain and Cognitive Development (ABCD) study.

Methods: A total of 7,995 participants from ABCD (version 3.0 release) provided complete data at baseline and 1-year follow-up data. Depression symptoms were measured with the Child Behavior Checklist. Predictive features included child demographic, environmental, and structural and resting-state fMRI variables, parental depression history and demographic characteristics. We used linear (elastic net regression, EN) and non-linear (gradient-boosted trees, GBT) predictive models to identify which set of features maximized prediction of depression symptoms at baseline and, separately, at 1-year follow-up.

Results: Both linear and non-linear models achieved comparable results for predicting baseline (EN: MAE = 3.757; R2 = 0.156; GBT: MAE = 3.761; R2 = 0.147) and 1-year follow-up (EN: MAE = 4.255; R2 = 0.103; GBT: MAE = 4.262; R2 = 0.089) depression. Parental history of depression, greater family conflict, and shorter child sleep duration were among the top predictors of concurrent and future child depression symptoms across both models. Although resting-state fMRI features were relatively weaker predictors, functional connectivity of the caudate was consistently the strongest neural feature associated with depression symptoms at both timepoints.

Conclusions: Consistent with prior research, parental mental health, family environment, and child sleep quality are important risk factors for youth depression. Functional connectivity of the caudate is a relatively weaker predictor of depression symptoms but may represent a biomarker for depression risk.

Keywords: ABCD Study; Adolescence; depression; functional MRI (fMRI); sleep.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Adolescent
  • Brain / diagnostic imaging
  • Child
  • Cognition
  • Depression* / psychology
  • Family Conflict
  • Humans
  • Magnetic Resonance Imaging* / methods

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