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Psychiatry"],"abstract":"<jats:sec><jats:title>Introduction<\/jats:title><jats:p>The externalizing disorders of attention deficit hyperactivity disorder (ADHD), oppositional defiant disorder (ODD), and conduct disorder (CD) are common in adolescence and are strong predictors of adult psychopathology. While treatable, substantial diagnostic overlap complicates intervention planning. Understanding which factors predict the onset of each disorder and disambiguating their different predictors is of substantial translational interest.<\/jats:p><\/jats:sec><jats:sec><jats:title>Materials and methods<\/jats:title><jats:p>We analyzed 5,777 multimodal candidate predictors from children aged 9\u201310 years and their parents in the ABCD cohort to predict the future onset of ADHD, ODD, and CD at 2-year follow-up. We used deep learning optimized with an innovative AI algorithm to jointly optimize model training, perform automated feature selection, and construct individual-level predictions of illness onset and all prevailing cases at 11\u201312 years and examined relative predictive performance when candidate predictors were restricted to only neural metrics.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Multimodal models achieved ~86\u201397% accuracy, 0.919\u20130.996 AUROC, and ~82\u201397% precision and recall in testing in held-out, unseen data. In neural-only models, predictive performance dropped substantially but nonetheless achieved accuracy and AUROC of ~80%. Parent aggressive and externalizing traits uniquely differentiated the onset of ODD, while structural MRI metrics in the limbic system were specific to CD. Psychosocial measures of sleep disorders, parent mental health and behavioral traits, and school performance proved valuable across all disorders. In neural-only models, structural and functional MRI metrics in subcortical regions and cortical-subcortical connectivity were emphasized. Overall, we identified a strong correlation between accuracy and final predictor importance.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Deep learning optimized with AI can generate highly accurate individual-level predictions of the onset of early adolescent externalizing disorders using multimodal features. While externalizing disorders are frequently co-morbid in adolescents, certain predictors were specific to the onset of ODD or CD vs. ADHD. To our knowledge, this is the first machine learning study to predict the onset of all three major adolescent externalizing disorders with the same design and participant cohort to enable direct comparisons, analyze &amp;gt;200 multimodal features, and include many types of neuroimaging metrics. Future study to test our observations in external validation data will help further test the generalizability of these findings.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fpsyt.2023.1280326","type":"journal-article","created":{"date-parts":[[2023,12,8]],"date-time":"2023-12-08T12:31:05Z","timestamp":1702038665000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":13,"title":["Selectively predicting the onset of ADHD, oppositional defiant disorder, and conduct disorder in early adolescence with high accuracy"],"prefix":"10.3389","volume":"14","author":[{"given":"Nina","family":"de Lacy","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael J.","family":"Ramshaw","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2023,12,8]]},"reference":[{"key":"B1","first-page":"85","article-title":"Children with externalizing behavior problems","volume-title":"The Power of Positive Parenting: Transforming the Lives of Children, Parents, and Communities Using the Triple P System","author":"Mazzucchelli","year":"2018"},{"key":"B2","doi-asserted-by":"publisher","first-page":"500","DOI":"10.1007\/s10578-020-01027-z","article-title":"Community-based prevalence of externalizing and internalizing disorders among school-aged children and adolescents in four geographically dispersed school districts in the United States","volume":"52","author":"Danielson","year":"2021","journal-title":"Child Psychiatry Hum Dev."},{"key":"B3","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1080\/15374416.2017.1417860","article-title":"Prevalence of parent-reported ADHD diagnosis and associated treatment among U.S. children and adolescents, 2016","volume":"47","author":"Danielson","year":"2018","journal-title":"J Clin Child Adolesc Psychol"},{"key":"B4","doi-asserted-by":"publisher","first-page":"716","DOI":"10.1176\/ajp.2006.163.4.716","article-title":"The prevalence and correlates of adult ADHD in the United States: results from the National Comorbidity Survey Replication","volume":"163","author":"Kessler","year":"2006","journal-title":"Am J Psychiatry."},{"key":"B5","article-title":"Prevalence of Oppositional Defiant Disorder and Conduct Disorder","volume-title":"Mental Disorders and Disabilities Among Low-Income Children 13.","author":"Boat","year":"2015"},{"key":"B6","doi-asserted-by":"publisher","first-page":"1","DOI":"10.15585\/mmwr.su7102a1","article-title":"Mental health surveillance among children - United States, 2013-2019","volume":"71","author":"Bitsko","year":"2022","journal-title":"MMWR Suppl."},{"key":"B7","first-page":"1","article-title":"Mental health surveillance among children\u2013United States, 2005-2011","volume":"62","author":"Perou","year":"2013","journal-title":"MMWR Suppl."},{"key":"B8","doi-asserted-by":"publisher","first-page":"703","DOI":"10.1111\/j.1469-7610.2007.01733.x","article-title":"Lifetime prevalence, correlates, and persistence of oppositional defiant disorder: results from the National Comorbidity Survey Replication","volume":"48","author":"Nock","year":"2007","journal-title":"J Child Psychol Psychiatry."},{"key":"B9","doi-asserted-by":"publisher","first-page":"510","DOI":"10.1037\/h0079567","article-title":"Antisocial disorders in hyperactive subjects from childhood to adulthood: predictive factors and characterization of subgroups","volume":"64","author":"Herrero","year":"1994","journal-title":"Am J Orthopsychiatry."},{"key":"B10","doi-asserted-by":"publisher","first-page":"1120","DOI":"10.1001\/archpsyc.1988.01800360068010","article-title":"Estimates of the prevalence of childhood maladjustment in a community survey in Puerto Rico. 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