Publication

A new publication from Dr. Matthias H. Schmidt and Dr. Chris V. Bowen!

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Abstract

Background: Most psychiatric disorders emerge in the second decade of life. In the present study, we examined whether environmental adversity, developmental antecedents, major depressive disorder, and functional impairment correlate with deviation from normative brain development in adolescence.

Methods: We trained a brain age prediction model using 189 structural magnetic resonance imaging brain features in 1299 typically developing adolescents (age range 9-19 years, mean = 13.5, SD = 3.04), validated the model in a holdout set of 322 adolescents (mean = 13.5, SD = 3.07), and used it to predict age in an independent risk-enriched cohort of 150 adolescents (mean = 13.6, SD = 2.82). We tested associations between the brain age gap and adversity, early antecedents, depression, and functional impairment.

Results: We accurately predicted chronological age in typically developing adolescents (mean absolute error = 1.53 years). The model generalized to the validation set (mean absolute error = 1.55 years, 1.98 bias adjusted) and to the independent at-risk sample (mean absolute error = 1.49 years, 1.86 bias adjusted). The brain age estimate was reliable in repeated scans (intraclass correlation = 0.94). Experience of environmental adversity (β = 0.18; 95% CI, 0.04 to 0.31; p = .02), diagnosis of major depressive disorder (β = 0.61; 95% CI, 0.23 to 0.99; p = .01), and functional impairment (β = 0.16; 95% CI, 0.05 to 0.27; p = .01) were associated with a positive brain age gap.

Conclusions: Risk factors, diagnosis, and impact of mental illness are associated with an older-appearing brain during development.

Keywords: Brain age gap; Machine learning; Maturation; Neurodevelopment; Neuroimaging; Psychiatric disorders.