Shared and distinct resting functional connectivity in children and adults with attention-deficit/hyperactivity disorder

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 ADHD adult . Many studies have questioned the stability in diagnosing of ADHD from childhood to adulthood, and the shared and distinct aberrant functional connectivities (FCs) between ADHD child and ADHD adult remain unidentified. We aim to explore shared and distinct FC patterns in ADHD child and ADHD adult , 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 ADHD child , 28 HCs) and adult (112 ADHD adult ,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 ADHD child , 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.

The stress–Wnt-signaling axis: a hypothesis for attention-deficit hyperactivity disorder and therapy approaches

“…Alterations in brain structure, connectivity, and maturation processes in patients with ADHD have been reported [18][19][20][21][22] . Particularly, a delay in cerebral cortex maturation predominantly in the frontal cortex has been noted in ADHD patients 18 .…”

Linking ADHD and Behavioral Assessment Through Identification of Shared Diagnostic Task-Based Functional Connections

“…It has been argued more recently (Michelini et al, 2019) that atypical task-based functional connectivity in individuals with childhood ADHD may persist into adulthood. Taken together, these findings suggest that a neural signature of ADHD may be found within taskbased functional connectivity from the go/no-go task, even from young adults, advancing this approach as a potential detector of biomarkers that may address the poor stability of ADHD diagnosis (Guo et al, 2020).…”

“…The difference in classification performance between our study and these earlier studies suggests that, though summary metrics quantifying connectivity motifs in core functional networks are predictive of ADHD, information about specific connections provides a great deal of additional diagnostic information. Guo et al (2020) demonstrated that SVM classifiers were able to identify ADHD male adults from rs-fMRI connectivity measured among ADHD children with 76% accuracy, after first selecting the top 2% of diagnostic features from alternative modelssimilar to the feature reduction step employed in the present study. The authors argue that, though the predictive features may vary somewhat across cohort, the reasonable cross-cohort performance suggests that resting state functional connectivity may be a developmentally stable biomarker of ADHD.…”

Assessing Fine-Granularity Structural and Functional Connectivity in Children With Attention Deficit Hyperactivity Disorder

“…Functional and structural abnormalities of the precentral gyrus are common in ADHD studies. In a recent resting-state functional connectivity study of ADHD, Guo also used whole-brain functional connectivity to classify features for machine learning and found that two of the four features with the best discriminability were related to the precentral gyrus, namely the precentral gyrus-prefrontal lobe and the precentral gyrus-superior temporal gyrus (Guo et al, 2020). In a young adult with ADHD, Krista found that the cerebral cortex thickness of the precentral and postcentral gyrus was the only brain regions associated with the persistence of ADHD, and the cluster in the precentral gyrus was close to that of DICCCOL 175 (Lisdahl et al, 2016).…”