Dataset Information

Integrated analysis of gray and white matter alterations in attention-deficit/hyperactivity disorder.

ABSTRACT:

Background

Magnetic resonance imaging (MRI) is able to provide detailed insights into the structural organization of the brain, e.g., by means of mapping brain anatomy and white matter microstructure. Understanding interrelations between MRI modalities, rather than mapping modalities in isolation, will contribute to unraveling the complex neural mechanisms associated with neuropsychiatric disorders as deficits detected across modalities suggest common underlying mechanisms. Here, we conduct a multimodal analysis of structural MRI modalities in the context of attention-deficit/hyperactivity disorder (ADHD).

Methods

Gray matter volume, cortical thickness, surface areal expansion estimates, and white matter diffusion indices of 129 participants with ADHD and 204 participants without ADHD were entered into a linked independent component analysis. This data-driven analysis decomposes the data into multimodal independent components reflecting common inter-subject variation across imaging modalities.

Results

ADHD severity was related to two multimodal components. The first component revealed smaller prefrontal volumes in participants with more symptoms, co-occurring with abnormal white matter indices in prefrontal cortex. The second component demonstrated decreased orbitofrontal volume as well as abnormalities in insula, occipital, and somato-sensory areas in participants with more ADHD symptoms.

Conclusions

Our results replicate and extend previous unimodal structural MRI findings by demonstrating that prefrontal, parietal, and occipital areas, as well as fronto-striatal and fronto-limbic systems are implicated in ADHD. By including multiple modalities, sensitivity for between-participant effects is increased, as shared variance across modalities is modeled. The convergence of modality-specific findings in our results suggests that different aspects of brain structure share underlying pathophysiology and brings us closer to a biological characterization of ADHD.

SUBMITTER: Francx W

PROVIDER: S-EPMC4893015 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Publications

Integrated analysis of gray and white matter alterations in attention-deficit/hyperactivity disorder.

Francx Winke W Llera Alberto A Mennes Maarten M Zwiers Marcel P MP Faraone Stephen V SV Oosterlaan Jaap J Heslenfeld Dirk D Hoekstra Pieter J PJ Hartman Catharina A CA Franke Barbara B Buitelaar Jan K JK Beckmann Christian F CF

NeuroImage. Clinical 20160304

<h4>Background</h4>Magnetic resonance imaging (MRI) is able to provide detailed insights into the structural organization of the brain, e.g., by means of mapping brain anatomy and white matter microstructure. Understanding interrelations between MRI modalities, rather than mapping modalities in isolation, will contribute to unraveling the complex neural mechanisms associated with neuropsychiatric disorders as deficits detected across modalities suggest common underlying mechanisms. Here, we cond ...[more]

PMID: 27298764

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Project description:Attention-deficit/hyperactivity disorder has been identified to involve the impairment of large-scale functional networks within grey matter, and recent studies have suggested that white matter, which also encodes neural activity, can manifest intrinsic functional organization similar to that of grey matter. However, the alterations in white matter functional networks in attention-deficit/hyperactivity disorder remain unknown. We recruited a total of 99 children, including 66 drug-naive patients and 33 typically developing controls aged from 6 to 14, to characterize the alterations in functional networks within white matter in drug-naive children with attention-deficit/hyperactivity disorder. Using clustering analysis, resting-state functional MRI data in the white matter were parsed into different networks. Intrinsic activity within each network and connectivity between networks and the associations between network activity strength and clinical symptoms were assessed. We identified eight distinct white matter functional networks: the default mode network, the somatomotor network, the dorsal attention network, the ventral attention network, the visual network, the deep frontoparietal network, the deep frontal network and the inferior corticospinal-posterior cerebellum network. The default mode, somatomotor, dorsal attention and ventral attention networks showed lower spontaneous neural activity in patients. In particular, the default mode network and the somatomotor network largely showed higher connectivity with other networks, which correlated with more severe hyperactive behaviour, while the dorsal and ventral attention networks mainly had lower connectivity with other networks, which correlated with poor attention performance. In conclusion, there are two distinct patterns of white matter functional networks in children with attention-deficit/hyperactivity disorder, with one being the hyperactivity-related hot networks including default mode network and somatomotor network and the other being inattention-related cold networks including dorsal attention and ventral attention network. These results extended upon our understanding of brain functional networks in attention-deficit/hyperactivity disorder from the perspective of white matter dysfunction.

Project description:ImportanceClinical overlap between autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) is increasingly appreciated, but the underlying brain mechanisms remain unknown to date.ObjectiveTo examine associations between white matter organization and 2 commonly co-occurring neurodevelopmental conditions, ASD and ADHD, through both categorical and dimensional approaches.Design, setting, and participantsThis investigation was a cross-sectional diffusion tensor imaging (DTI) study at an outpatient academic clinical and research center, the Department of Child and Adolescent Psychiatry at New York University Langone Medical Center. Participants were children with ASD, children with ADHD, or typically developing children. Data collection was ongoing from December 2008 to October 2015.Main outcomes and measuresThe primary measure was voxelwise fractional anisotropy (FA) analyzed via tract-based spatial statistics. Additional voxelwise DTI metrics included radial diffusivity (RD), mean diffusivity (MD), axial diffusivity (AD), and mode of anisotropy (MA).ResultsThis cross-sectional DTI study analyzed data from 174 children (age range, 6.0-12.9 years), selected from a larger sample after quality assurance to be group matched on age and sex. After quality control, the study analyzed data from 69 children with ASD (mean [SD] age, 8.9 [1.7] years; 62 male), 55 children with ADHD (mean [SD] age, 9.5 [1.5] years; 41 male), and 50 typically developing children (mean [SD] age, 9.4 [1.5] years; 38 male). Categorical analyses revealed a significant influence of ASD diagnosis on several DTI metrics (FA, MD, RD, and AD), primarily in the corpus callosum. For example, FA analyses identified a cluster of 4179 voxels (TFCE FEW corrected P < .05) in posterior portions of the corpus callosum. Dimensional analyses revealed associations between ASD severity and FA, RD, and MD in more extended portions of the corpus callosum and beyond (eg, corona radiata and inferior longitudinal fasciculus) across all individuals, regardless of diagnosis. For example, FA analyses revealed clusters overall encompassing 12121 voxels (TFCE FWE corrected P < .05) with a significant association with parent ratings in the social responsiveness scale. Similar results were evident using an independent measure of ASD traits (ie, children communication checklist, second edition). Total severity of ADHD-traits was not significantly related to DTI metrics but inattention scores were related to AD in corpus callosum in a cluster sized 716 voxels. All these findings were robust to algorithmic correction of motion artifacts with the DTIPrep software.Conclusions and relevanceDimensional analyses provided a more complete picture of associations between ASD traits and inattention and indexes of white matter organization, particularly in the corpus callosum. This transdiagnostic approach can reveal dimensional relationships linking white matter structure to neurodevelopmental symptoms.

Dataset Information

Integrated analysis of gray and white matter alterations in attention-deficit/hyperactivity disorder.

Background

Methods

Results

Conclusions

Publications

Integrated analysis of gray and white matter alterations in attention-deficit/hyperactivity disorder.

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