Multi-level Predictors of Depression Symptoms in the Adolescent Brain Cognitive Development (ABCD) Study

Ho, T-C.; Shah, Raj; Mishra, Jyoti; Ac, May; Sf, Tapert

doi:10.1101/2021.02.11.21251432

Cited by 2 publications

(1 citation statement)

References 55 publications

(67 reference statements)

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“…Thus, these data are attractive to use in research on adolescent depression, and are popular. The number of publications based on the ABCD data are growing every year (https://abcdstudy.org/publications/), as are the studies that specifically address depression (for example, [Ho et al, 2022, Lee et al, 2022, Klein et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Validation of CBCL depression scores of adolescents in three independent datasets

Zelenina¹,

Pine²,

Stringaris³

et al. 2023

Preprint

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The Adolescent Brain Cognitive Development dataset (ABCD) is a popular source of data for research on children and adolescents, aged 9-11 at baseline. Depression is frequently first diagnosed in adolescents, is prevalent and carries heavy burden, thus ABCD provides an attractive opportunity to research depression in adolescents. The only continuous measure of depression provided in ABCD is the parent-report Child Behavior Checklist’s DSM-5-Oriented Affective Problems scale (CBCL-Aff). It is important for depression research in the ABCD dataset that the CBCL-Aff is a valid measure of depression in this age group. We, therefore, tested the sensitivity and specificity of the CBCL-Aff for depression in the ABCD data. CBCL-Aff agreed with parent-report of children’s symptoms but disagreed with child self-report. To resolve this disagreement, we further confirmed our results in two independent datasets, aged 9-12: the Healthy Brain Network (HBN) and the Brazilian High Risk Cohort Study (BHRC). Both datasets provided clinician-report depression diagnoses, which we used as a gold standard. CBCL-Aff successfully predicted clinician-report diagnoses, supporting its validity as a continuous measure of depression. As parents and children disagreed on the child’s symptoms, we discuss implications of using a parent-report only measure of child depression.

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Section: Introductionmentioning

confidence: 99%

Validation of CBCL depression scores of adolescents in three independent datasets

Zelenina¹,

Pine²,

Stringaris³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

Predicting depression risk in early adolescence via multimodal brain imaging

Barbeau

Xia

Chai

2023

Preprint

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Depression is an incapacitating psychiatric disorder with high prevalence in adolescent populations that is influenced by many risk factors, including family history of depression. The ability to predict who may develop depression before adolescence, when rates of depression increase markedly, is important for early intervention and prevention. Using a large longitudinal sample from the Adolescent Brain Cognitive Development (ABCD) Study (2658 participants after imaging quality control, between 9-10 years at baseline), we applied machine learning methods on a set of comprehensive multimodal neuroimaging features to predict depression risk at the two-year follow-up from the baseline visit. Features include derivatives from structural MRI, diffusion tensor imaging, and task and rest functional MRI. A rigorous cross-validation method of leave-one-site-out was used. Additionally, we tested the prediction models in a high-risk group of participants with parental history of depression (N=625). The results showed all brain features had prediction scores significantly better than expected by chance. When predicting depression onset in the high-risk group, brain features from resting-state functional connectomes showed the best classification performance, outperforming other brain features based on structural MRI and task-based fMRI. Results demonstrate that the functional connectivity of the brain can predict the risk of depression in early adolescence better than other univariate neuroimaging derivatives, highlighting the key role of the interacting elements of the connectome capturing more individual variability in psychopathology compared to measures of single brain regions.

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Multi-level Predictors of Depression Symptoms in the Adolescent Brain Cognitive Development (ABCD) Study

Cited by 2 publications

References 55 publications

Validation of CBCL depression scores of adolescents in three independent datasets

Validation of CBCL depression scores of adolescents in three independent datasets

Predicting depression risk in early adolescence via multimodal brain imaging

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