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Abstract
Attention-deficit/hyperactivity disorder (ADHD) often persists into adulthood, with a shift of symptoms including less hyperactivity/impulsivity and more co-morbidity of affective disorders in ADHDadult. Many studies have questioned the stability in diagnosing of ADHD from childhood to adulthood, and the shared and distinct aberrant functional connectivities (FCs) between ADHDchild and ADHDadult remain unidentified. We aim to explore shared and distinct FC patterns in ADHDchild and ADHDadult, and further investigated the cross-cohort predictability using the identified FCs. After investigating the ADHD-discriminative FCs from healthy controls (HCs) in both child (34 ADHDchild, 28 HCs) and adult (112 ADHDadult,77 HCs) cohorts, we identified both shared and distinct aberrant FC patterns between cohorts and their association with clinical symptoms. Moreover, the cross-cohort predictability using the identified FCs were tested. The ADHD-HC classification accuracies were 84.4% and 81.0% for children and male adults, respectively. The ADHD-discriminative FCs shared in children and adults lie in the intra-network within default mode network (DMN) and the inter-network between DMN and ventral attention network, positively correlated with total scores of ADHD symptoms. Particularly, inter-network FC between somatomotor network and dorsal attention network was uniquely impaired in ADHDchild, positively correlated with hyperactivity index; whereas the aberrant inter-network FC between DMN and limbic network exhibited more adult-specific ADHD dysfunction. And their cross-cohort predictions were 70.4% and 75.6% between each other. This work provided imaging evidence for symptomatic changes and pathophysiological continuity in ADHD from childhood to adulthood, suggesting that FCs may serve as potential biomarkers for ADHD diagnosis.
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1 Peking University Sixth Hospital/Institute of Mental Health, Beijing, China (GRID:grid.11135.37) (ISNI:0000 0001 2256 9319); Ministry of Health (Peking University), National Clinical Research Center for Mental Disorders & Key Laboratory of Mental Health, Beijing, China (GRID:grid.453135.5) (ISNI:0000 0004 1769 3691)
2 Chinese Academy of Sciences, Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Beijing, China (GRID:grid.9227.e) (ISNI:0000000119573309); University of Chinese Academy of Sciences, Beijing, China (GRID:grid.410726.6) (ISNI:0000 0004 1797 8419)
3 Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) [Georgia State University, Georgia Institute of Technology, Emory University], Atlanta, USA (GRID:grid.453135.5)
4 University of Wollongong, Brain & Behaviour Research Institute, School of Psychology, Wollongong, Australia (GRID:grid.1007.6) (ISNI:0000 0004 0486 528X)
5 Chinese Academy of Sciences, Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Beijing, China (GRID:grid.9227.e) (ISNI:0000000119573309); Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) [Georgia State University, Georgia Institute of Technology, Emory University], Atlanta, USA (GRID:grid.9227.e); Chinese Academy of Sciences, CAS Center for Excellence in Brain Science, Institute of Automation, Beijing, China (GRID:grid.9227.e) (ISNI:0000000119573309)