Kaylita Chantiluke

Subcortical brain volume differences in participants with attention deficit hyperactivity disorder in children and adults: a cross-sectional mega-analysis

BACKGROUND Neuroimaging studies have shown structural alterations in several brain regions in children and adults with attention deficit hyperactivity disorder (ADHD). Through the formation of the international ENIGMA ADHD Working Group, we aimed to address weaknesses of previous imaging studies and meta-analyses, namely inadequate sample size and methodological heterogeneity. We aimed to investigate whether there are structural differences in children and adults with ADHD compared with those without this diagnosis. METHODS In this cross-sectional mega-analysis, we used the data from the international ENIGMA Working Group collaboration, which in the present analysis was frozen at Feb 8, 2015. Individual sites analysed structural T1-weighted MRI brain scans with harmonised protocols of individuals with ADHD compared with those who do not have this diagnosis. Our primary outcome was to assess case-control differences in subcortical structures and intracranial volume through pooling of all individual data from all cohorts in this collaboration. For this analysis, p values were significant at the false discovery rate corrected threshold of p=0·0156. FINDINGS Our sample comprised 1713 participants with ADHD and 1529 controls from 23 sites with a median age of 14 years (range 4-63 years). The volumes of the accumbens (Cohens d=-0·15), amygdala (d=-0·19), caudate (d=-0·11), hippocampus (d=-0·11), putamen (d=-0·14), and intracranial volume (d=-0·10) were smaller in individuals with ADHD compared with controls in the mega-analysis. There was no difference in volume size in the pallidum (p=0·95) and thalamus (p=0·39) between people with ADHD and controls. Exploratory lifespan modelling suggested a delay of maturation and a delay of degeneration, as effect sizes were highest in most subgroups of children (<15 years) versus adults (>21 years): in the accumbens (Cohens d=-0·19 vs -0·10), amygdala (d=-0·18 vs -0·14), caudate (d=-0·13 vs -0·07), hippocampus (d=-0·12 vs -0·06), putamen (d=-0·18 vs -0·08), and intracranial volume (d=-0·14 vs 0·01). There was no difference between children and adults for the pallidum (p=0·79) or thalamus (p=0·89). Case-control differences in adults were non-significant (all p>0·03). Psychostimulant medication use (all p>0·15) or symptom scores (all p>0·02) did not influence results, nor did the presence of comorbid psychiatric disorders (all p>0·5). INTERPRETATION With the largest dataset to date, we add new knowledge about bilateral amygdala, accumbens, and hippocampus reductions in ADHD. We extend the brain maturation delay theory for ADHD to include subcortical structures and refute medication effects on brain volume suggested by earlier meta-analyses. Lifespan analyses suggest that, in the absence of well powered longitudinal studies, the ENIGMA cross-sectional sample across six decades of ages provides a means to generate hypotheses about lifespan trajectories in brain phenotypes. FUNDING National Institutes of Health.

Disorder-specific functional abnormalities during sustained attention in youth with Attention Deficit Hyperactivity Disorder (ADHD) and with Autism

Attention Deficit Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD) are often comorbid and share behavioural-cognitive abnormalities in sustained attention. A key question is whether this shared cognitive phenotype is based on common or different underlying pathophysiologies. To elucidate this question, we compared 20 boys with ADHD to 20 age and IQ matched ASD and 20 healthy boys using functional magnetic resonance imaging (fMRI) during a parametrically modulated vigilance task with a progressively increasing load of sustained attention. ADHD and ASD boys had significantly reduced activation relative to controls in bilateral striato–thalamic regions, left dorsolateral prefrontal cortex (DLPFC) and superior parietal cortex. Both groups also displayed significantly increased precuneus activation relative to controls. Precuneus was negatively correlated with the DLPFC activation, and progressively more deactivated with increasing attention load in controls, but not patients, suggesting problems with deactivation of a task-related default mode network in both disorders. However, left DLPFC underactivation was significantly more pronounced in ADHD relative to ASD boys, which furthermore was associated with sustained performance measures that were only impaired in ADHD patients. ASD boys, on the other hand, had disorder-specific enhanced cerebellar activation relative to both ADHD and control boys, presumably reflecting compensation. The findings show that ADHD and ASD boys have both shared and disorder-specific abnormalities in brain function during sustained attention. Shared deficits were in fronto–striato–parietal activation and default mode suppression. Differences were a more severe DLPFC dysfunction in ADHD and a disorder-specific fronto–striato–cerebellar dysregulation in ASD.

Pattern classification of response inhibition in ADHD: toward the development of neurobiological markers for ADHD.

The diagnosis of Attention Deficit Hyperactivity Disorder (ADHD) is based on subjective measures despite evidence for multisystemic structural and functional deficits. ADHD patients have consistent neurofunctional deficits in motor response inhibition. The aim of this study was to apply pattern classification to task‐based functional magnetic resonance imaging (fMRI) of inhibition, to accurately predict the diagnostic status of ADHD. Thirty adolescent ADHD and thirty age‐matched healthy boys underwent fMRI while performing a Stop task. fMRI data were analyzed with Gaussian process classifiers (GPC), a machine learning approach, to predict individual ADHD diagnosis based on task‐based activation patterns. Traditional univariate case‐control analyses were also performed to replicate previous findings in a relatively large dataset. The pattern of brain activation correctly classified up to 90% of patients and 63% of controls, achieving an overall classification accuracy of 77%. The regions of the discriminative network most predictive of controls included later developing lateral prefrontal, striatal, and temporo‐parietal areas that mediate inhibition, while regions most predictive of ADHD were in earlier developing ventromedial fronto‐limbic regions, which furthermore correlated with symptom severity. Univariate analysis showed reduced activation in ADHD in bilateral ventrolateral prefrontal, striatal, and temporo‐parietal regions that overlapped with areas predictive of controls, suggesting the latter are dysfunctional areas in ADHD. We show that significant individual classification of ADHD patients of 77% can be achieved using whole brain pattern analysis of task‐based fMRI inhibition data, suggesting that multivariate pattern recognition analyses of inhibition networks can provide objective diagnostic neuroimaging biomarkers of ADHD. Hum Brain Mapp 35:3083–3094, 2014.

Disorder-Specific Predictive Classification of Adolescents with Attention Deficit Hyperactivity Disorder (ADHD) Relative to Autism Using Structural Magnetic Resonance Imaging

Objective Attention Deficit Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder, but diagnosed by subjective clinical and rating measures. The study’s aim was to apply Gaussian process classification (GPC) to grey matter (GM) volumetric data, to assess whether individual ADHD adolescents can be accurately differentiated from healthy controls based on objective, brain structure measures and whether this is disorder-specific relative to autism spectrum disorder (ASD). Method Twenty-nine adolescent ADHD boys and 29 age-matched healthy and 19 boys with ASD were scanned. GPC was applied to make disorder-specific predictions of ADHD diagnostic status based on individual brain structure patterns. In addition, voxel-based morphometry (VBM) analysis tested for traditional univariate group level differences in GM. Results The pattern of GM correctly classified 75.9% of patients and 82.8% of controls, achieving an overall classification accuracy of 79.3%. Furthermore, classification was disorder-specific relative to ASD. The discriminating GM patterns showed higher classification weights for ADHD in earlier developing ventrolateral/premotor fronto-temporo-limbic and stronger classification weights for healthy controls in later developing dorsolateral fronto-striato-parieto-cerebellar networks. Several regions were also decreased in GM in ADHD relative to healthy controls in the univariate VBM analysis, suggesting they are GM deficit areas. Conclusions The study provides evidence that pattern recognition analysis can provide significant individual diagnostic classification of ADHD patients and healthy controls based on distributed GM patterns with 79.3% accuracy and that this is disorder-specific relative to ASD. Findings are a promising first step towards finding an objective differential diagnostic tool based on brain imaging measures to aid with the subjective clinical diagnosis of ADHD.

Fronto-Striato-Cerebellar Dysregulation in Adolescents with Depression During Motivated Attention

BACKGROUND Pediatric major depressive disorder (MDD) is associated with deficits in sustained attention, thought to be related to underlying motivation deficits. This hypothesis, however, has never directly been tested using functional magnetic resonance imaging. In this study, we investigated the neurofunctional correlates of the interplay between attention and motivation in medication-naive pediatric MDD using a rewarded sustained attention task. METHODS Functional magnetic resonance imaging was used to compare brain activation between 20 medication-naïve, noncomorbid, first-episode adolescents with MDD aged 13 to 18 years and 21 gender-, age-, and IQ-matched healthy adolescents. Participants performed a sustained attention task with and without a monetary reward to assess the impact of reward on sustained attention networks. RESULTS During nonrewarded sustained attention, adolescents with MDD showed reduced activation compared with healthy control subjects in occipital cortex. When sustained attention was rewarded, however, the underactivation in adolescents with MDD was in an extensive right hemispheric network of inferior fronto-striato-thalamic attention and limbic hippocampus-anterior cingulate reward processing areas. Major depressive disorder patients showed increased activation in cerebellum, which correlated with reduced frontal activation and depressive symptoms, suggesting compensatory response. Further analysis showed that reward upregulated fronto-striatal and hippocampal/temporal activation in control subjects but deactivated these regions in MDD, with opposite effects in the cerebellum. CONCLUSIONS Medication-naïve MDD adolescents show abnormalities in the regulation in fronto-striato-cerebellar brain regions involved in attention and reward during motivated but not unmotivated attention. This suggests a dysfunctional interplay between motivation and cognition in pediatric MDD, where motivation appears less capable of upregulating attention networks relative to healthy youths.

Disorder-specific functional abnormalities during temporal discounting in youth with Attention Deficit Hyperactivity Disorder (ADHD), Autism and comorbid ADHD and Autism

Attention Deficit Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD) are often comorbid and share cognitive abnormalities in temporal foresight. A key question is whether shared cognitive phenotypes are based on common or different underlying pathophysiologies and whether comorbid patients have additive neurofunctional deficits, resemble one of the disorders or have a different pathophysiology. We compared age- and IQ-matched boys with non-comorbid ADHD (18), non-comorbid ASD (15), comorbid ADHD and ASD (13) and healthy controls (18) using functional magnetic resonance imaging (fMRI) during a temporal discounting task. Only the ASD and the comorbid groups discounted delayed rewards more steeply. The fMRI data showed both shared and disorder-specific abnormalities in the three groups relative to controls in their brain-behaviour associations. The comorbid group showed both unique and more severe brain-discounting associations than controls and the non-comorbid patient groups in temporal discounting areas of ventromedial and lateral prefrontal cortex, ventral striatum and anterior cingulate, suggesting that comorbidity is neither an endophenocopy of the two pure disorders nor an additive pathology.

Pattern classification of response inhibition in ADHD

The diagnosis of Attention Deficit Hyperactivity Disorder (ADHD) is based on subjective measures despite evidence for multisystemic structural and functional deficits. ADHD patients have consistent neurofunctional deficits in motor response inhibition. The aim of this study was to apply pattern classification to task‐based functional magnetic resonance imaging (fMRI) of inhibition, to accurately predict the diagnostic status of ADHD. Thirty adolescent ADHD and thirty age‐matched healthy boys underwent fMRI while performing a Stop task. fMRI data were analyzed with Gaussian process classifiers (GPC), a machine learning approach, to predict individual ADHD diagnosis based on task‐based activation patterns. Traditional univariate case‐control analyses were also performed to replicate previous findings in a relatively large dataset. The pattern of brain activation correctly classified up to 90% of patients and 63% of controls, achieving an overall classification accuracy of 77%. The regions of the discriminative network most predictive of controls included later developing lateral prefrontal, striatal, and temporo‐parietal areas that mediate inhibition, while regions most predictive of ADHD were in earlier developing ventromedial fronto‐limbic regions, which furthermore correlated with symptom severity. Univariate analysis showed reduced activation in ADHD in bilateral ventrolateral prefrontal, striatal, and temporo‐parietal regions that overlapped with areas predictive of controls, suggesting the latter are dysfunctional areas in ADHD. We show that significant individual classification of ADHD patients of 77% can be achieved using whole brain pattern analysis of task‐based fMRI inhibition data, suggesting that multivariate pattern recognition analyses of inhibition networks can provide objective diagnostic neuroimaging biomarkers of ADHD. Hum Brain Mapp 35:3083–3094, 2014.

Inverse Effect of Fluoxetine on Medial Prefrontal Cortex Activation During Reward Reversal in ADHD and Autism

Attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) share brain function abnormalities during cognitive flexibility. Serotonin is involved in both disorders, and selective serotonin reuptake inhibitors (SSRIs) can modulate cognitive flexibility and improve behavior in both disorders. Thus, this study investigates shared and disorder-specific brain dysfunctions in these 2 disorders during reward reversal, and the acute effects of an SSRI on these. Age-matched boys with ADHD (15), ASD (18), and controls (21) were compared with functional magnetic resonance imaging (fMRI) during a reversal task. Patients were scanned twice, under either an acute dose of Fluoxetine or placebo in a double-blind, placebo-controlled randomized design. Repeated-measures analyses within patients assessed drug effects. Patients under each drug condition were compared with controls to assess normalization effects. fMRI data showed that, under placebo, ASD boys underactivated medial prefrontal cortex (mPFC), compared with control and ADHD boys. Both patient groups shared decreased precuneus activation. Under Fluoxetine, mPFC activation was up-regulated and normalized in ASD boys relative to controls, but down-regulated in ADHD boys relative to placebo, which was concomitant with worse task performance in ADHD. Fluoxetine therefore has inverse effects on mPFC activation in ASD and ADHD during reversal learning, suggesting dissociated underlying serotonin abnormalities.

Inverse fluoxetine effects on inhibitory brain activation in non-comorbid boys with ADHD and with ASD

RationaleAttention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are often comorbid and have both performance and brain dysfunctions during motor response inhibition. Serotonin agonists modulate motor response inhibition and have shown positive behavioural effects in both disorders.AimsWe therefore used functional magnetic resonance imaging (fMRI) to investigate the so far unknown shared and disorder-specific inhibitory brain dysfunctions in these two disorders, as well as the effects of a single dose of the selective serotonin reuptake inhibitor fluoxetine.MethodsAge-matched boys with ADHD (18), ASD (19) and healthy controls (25) were compared with fMRI during a stop task measuring motor inhibition. Patients were scanned twice, under either an acute dose of fluoxetine or placebo in a double-blind, placebo-controlled randomised design. Repeated measures analyses within patients assessed drug effects. To test for potential normalisation effects of brain dysfunctions, patients under each drug condition were compared to controls.ResultsUnder placebo, relative to controls, ASD boys showed overactivation in left and right inferior frontal cortex (IFC), while ADHD boys showed disorder-specific underactivation in orbitofrontal cortex (OFC) and basal ganglia. Under fluoxetine, the prefrontal dysfunctions were no longer observed, due to inverse effects of fluoxetine on these activations: fluoxetine downregulated IFC and OFC activation in ASD but upregulated them in ADHD.ConclusionsThe findings show that fluoxetine normalises frontal lobe dysfunctions in both disorders via inverse effects, downregulating abnormally increased frontal activation in ASD and upregulating abnormally decreased frontal activation in ADHD, potentially reflecting inverse baseline serotonin levels in both disorders.

Disorder-specific grey matter deficits in attention deficit hyperactivity disorder relative to autism spectrum disorder

Background. Attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are two common childhood disorders that exhibit genetic and behavioural overlap and have abnormalities in similar brain systems, in particular in frontal and cerebellar regions. This study compared the two neurodevelopmental disorders to investigate shared and disorder-specific structural brain abnormalities. Method. Forty-four predominantly medication-naïve male adolescents with ADHD, 19 medication-naïve male adolescents with ASD and 33 age-matched healthy male controls were scanned using high-resolution T1-weighted volumetric imaging in a 3-T magnetic resonance imaging (MRI) scanner. Voxel-based morphometry (VBM) was used to test for group-level differences in structural grey matter (GM) and white matter (WM) volumes. Results. There was a significant group difference in the GM of the right posterior cerebellum and left middle/superior temporal gyrus (MTG/STG). Post-hoc analyses revealed that this was due to ADHD boys having a significantly smaller right posterior cerebellar GM volume compared to healthy controls and ASD boys, who did not differ from each other. ASD boys had a larger left MTG/STG GM volume relative to healthy controls and at a more lenient threshold relative to ADHD boys. Conclusions. The study shows for the first time that the GM reduction in the cerebellum in ADHD is disorder specific relative to ASD whereas GM enlargement in the MTG/STG in ASD may be disorder specific relative to ADHD. This study is a first step towards elucidating disorder-specific structural biomarkers for these two related childhood disorders.