The influence of comorbid oppositional defiant disorder on white matter microstructure in attention-deficit/hyperactivity disorder

Ewijk, Hanneke van; Noordermeer, Siri D. S.; Heslenfeld, Dirk J.; Luman, Marjolein; Hartman, Catharina A.; Hoekstra, Pieter J.; Faraone, Stephen V.; Franke, Barbara; Buitelaar, Jan K.; Oosterlaan, Jaap

doi:10.1007/s00787-015-0784-3

Cited by 13 publications

(5 citation statements)

References 41 publications

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“…ADHD with frequent comorbidity on ODD was associated with alterations in GMV of orbitofrontal cortex, the superior frontal gyrus, middle frontal gyrus, and the inferior parietal gyrus (64) and FA of inferior fronto-occipital fasciculus, corticospinal tract, forceps minor, and internal capsule (65). In addition, ADHD is closely related to the dysfunction of frontal-striatalcerebellar circuits (66).…”

Section: More Sensitive Brain Age-based Analysesmentioning

confidence: 99%

Multidimensional brain-age prediction reveals altered brain developmental trajectory in psychiatric disorders

et al. 2022

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Brain-age prediction has emerged as a novel approach for studying brain development. However, brain regions change in different ways and at different rates. Unitary brain-age indices represent developmental status averaged across the whole brain and therefore do not capture the divergent developmental trajectories of various brain structures. This staggered developmental unfolding, determined by genetics and postnatal experience, is implicated in the progression of psychiatric and neurological disorders. We propose a multidimensional brain-age index (MBAI) that provides regional age predictions. Using a database of 556 individuals, we identified clusters of imaging features with distinct developmental trajectories and built machine learning models to obtain brain-age predictions from each of the clusters. Our results show that the MBAI provides a flexible analysis of region-specific brain-age changes that are invisible to unidimensional brain-age. Importantly, brain-ages computed from region-specific feature clusters contain complementary information and demonstrate differential ability to distinguish disorder groups (e.g., depression and oppositional defiant disorder) from healthy controls. In summary, we show that MBAI is sensitive to alterations in brain structures and captures distinct regional change patterns that may serve as biomarkers that contribute to our understanding of healthy and pathological brain development and the characterization and diagnosis of psychiatric disorders.

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Section: More Sensitive Brain Age-based Analysesmentioning

confidence: 99%

Multidimensional brain-age prediction reveals altered brain developmental trajectory in psychiatric disorders

et al. 2022

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“…The ratio of psychiatric comorbidity in our ASD group (Supplementary Table 1) is largely compatible with the previous literature 91 . Nonetheless, this caveat regarding inclusion criteria may influence the present results, as ADHD is also highly associated with impaired self-regulation 92,93 . Furthermore, the concurrent use of methylphenidate might also have effects on the WM microstructure 94 .…”

Section: Discussionmentioning

confidence: 84%

Association of self-regulation with white matter correlates in boys with and without autism spectrum disorder

Lin

Tseng

et al. 2020

Sci Rep

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previous studies demonstrated distinct neural correlates underpinning impaired self-regulation (dysregulation) between individuals with autism spectrum disorder (ASD) and typically developing controls (TDC). However, the impacts of dysregulation on white matter (WM) microstructural property in ASD and TDC remain unclear. Diffusion spectrum imaging was acquired in 59 ASD and 62 TDC boys. We investigated the relationship between participants' dysregulation levels and microstructural property of 76 WM tracts in a multivariate analysis (canonical correlation analysis), across diagnostic groups. A single mode of brain-behavior co-variation was identified: participants were spread along a single axis linking diagnosis, dysregulation, diagnosis-by-dysregulation interaction, and intelligence to a specific WM property pattern. This mode corresponds to diagnosis-distinct correlates underpinning dysregulation, which showed higher generalized fractional anisotropy (GFA) associated with less dysregulation in ASD but greater dysregulation in TDC, in the tracts connecting limbic and emotion regulation systems. Moreover, higher GFA of the tracts implicated in memory, attention, sensorimotor processing, and perception associated with less dysregulation in TDC but worse dysregulation in ASD. No shared WM correlates of dysregulation between ASD and TDC were identified. Corresponding to previous studies, we demonstrated that ASD and TDC have broad distinct white matter microstructural property underpinning self-regulation. Autism spectrum disorder (ASD) is a neurodevelopmental disorder that encompasses the impairments in social interaction and communication and restricted, repetitive patterns of behaviors 1. Besides the core symptoms, impaired self-regulation (namely dysregulation) in ASD is also common 2,3. Generally, individuals' optimal selfregulation can facilitate flexible modification of their interoceptive state and modulation of response to exteroceptive stimuli 4. Suboptimal self-regulation is associated with heightened risk for affective psychopathology 5 and maladaptive behaviors 6-8. Dysregulation in ASD also links to higher use of psychiatric services, more social impairment, lower family quality of life, and more depressive and anxiety symptoms 9-13. Dysregulation associated with ASD may be explained by co-occurring psychiatric disorders, maladaptive strategies, less-frequent use of cognitive reappraisal, and inherent autistic psychopathology 2,14,15. Self-regulation is a theoretically complex construct, which involves the affective, behavioral, and cognitive control 16. Specifically, emotion regulation involves dual processes, which initiate regulation contingent on explicit and implicit goals as supported by controlled and automatic processes, repsectively 17. Cognitive control interacts with motivation and may be treated as a domain of reward-based decision making 18. Behavioral regulation is theoretically associated with belief salience measures, past behavior/habit, perceived behavioral control, selfefficacy, mora...

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“…Although only a few small studies distinguished ADHD CD+ from ADHD ODD+ , most of them still revealed a significant difference between ADHD CD+ and ADHD ODD+ . For example, van Ewijk et al found that comorbid ODD is associated with altered WM microstructure, and there was an interaction between ODD and (subclinical) CD, which indicated that ODD and CD should be treated as separate constructs [ 40 ]. This again illustrates that comorbid ODD and comorbid CD are different in children with ADHD.…”

Section: Discussionmentioning

confidence: 99%

The potential shared brain functional alterations between adults with ADHD and children with ADHD co-occurred with disruptive behaviors

Liu

Jia

et al. 2022

Child Adolesc Psychiatry Ment Health

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Background Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder. Many previous studies have shown that the comorbid status of disruptive behaviour disorders (DBD) was a predictor for ADHD persistence into adulthood. However, the brain mechanisms underlying such a relationship remain unclear. Thus, we aim to investigate whether the brain functional alteration in adults with ADHD could also be detected in children with ADHD co-occurring with disruptive behaviours from both quantitative and categorical dimensions. Methods A total of 172 children with ADHD (cADHD), 98 adults with ADHD (aADHD), 77 healthy control children (cHC) and 40 healthy control adults (aHC) were recruited. The whole-brain spontaneous fluctuations in brain activity of each participant were recorded using functional near-infrared spectroscopy (fNIRS), and the functional connectivities (FCs) were calculated. We first compared the FC differences between aADHD and aHC. Then, for the regions with significantly abnormal FCs in aADHD, we further compared these features between cADHD and cHC. In addition, the correlation between these FCs and the conduct disorder (CD)/oppositional defiant disorder (ODD) symptoms were analysed in cADHD. Moreover, to render the results readily interpretable, we compared the FC differences among ADHDCD−, subthreshold ADHDCD+ and cHC groups, and among ADHDODD−, ADHDODD+ and cHC groups. Finally, we repeated the above analysis after controlling for other comorbidities and core symptoms to diminish the potential confounding effects. Results We found that compared with aHC, aADHD showed significantly increased FCs in the VN, DMN, SMN, and DAN. The aforementioned abnormal FCs were also detected in cADHD, however, in an opposite orientation. Notably, these abnormal FCs were positively correlated with CD symptoms. Finally, the subthreshold ADHDCD+ group even exhibited a tendency of adult-like increased FCs compared with the cHC. The results held after controlling for other comorbidities and core symptoms. Conclusion This study provides functional neuroimaging evidence that CD might be a risk factor for ADHD persistence into adulthood. Our work highlights the importance of differentiating ADHDCD+ from ADHD and inspiring further understanding of brain development in ADHD.

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The influence of comorbid oppositional defiant disorder on white matter microstructure in attention-deficit/hyperactivity disorder

Cited by 13 publications

References 41 publications

Multidimensional brain-age prediction reveals altered brain developmental trajectory in psychiatric disorders

Multidimensional brain-age prediction reveals altered brain developmental trajectory in psychiatric disorders

Association of self-regulation with white matter correlates in boys with and without autism spectrum disorder

The potential shared brain functional alterations between adults with ADHD and children with ADHD co-occurred with disruptive behaviors

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