Attention-deficit/hyperactivity disorder without comorbidity is associated with distinct atypical patterns of cerebral microstructural development

Abstract

Differential core symptoms and treatment responses are associated with the pure versus comorbid forms of attention-deficit/hyperactivity disorder (ADHD). However, comorbidity has largely been unaccounted for in neuroimaging studies of ADHD. We used diffusional kurtosis imaging to investigate gray matter (GM) and white matter (WM) microstructure of children and adolescents with ADHD (n = 22) compared to typically developing controls (TDC, n = 27) and examined whether differing developmental patterns are related to comorbidity. The ADHD group (ADHD-mixed) consisted of subgroups with and without comorbidity (ADHD-comorbid, n = 11; ADHD-pure, n = 11, respectively). Age-related changes and group differences in cerebral microstructure of the ADHD-mixed group and each ADHD subgroup were compared to TDC. Whole-brain voxel-based analyses with mean kurtosis (MK) and mean diffusivity (MD) metrics were conducted to probe GM and WM. Tract-based spatial statistics analyses of WM were performed with MK, MD, fractional anisotropy, and directional (axial, radial) kurtosis and diffusivity metrics. ADHD-pure patients lacked significant age-related changes in GM and WM microstructure that were observed globally in TDC and had significantly greater WM microstructural complexity than TDC in bilateral frontal and parietal lobes, insula, corpus callosum, and right external and internal capsules. Including ADHD patients with diverse comorbidities in analyses masked these findings. A distinct atypical age-related trajectory and aberrant regional differences in brain microstructure were detected in ADHD without comorbidity. Our results suggest that different phenotypic manifestations of ADHD, defined by the presence or absence of comorbidity, differ in cerebral microstructural markers.

Keywords: ADHD; DKI; cerebral microstructure; comorbidity; development; diffusion MRI.

Figure 1

Age‐related increases in GM and WM microstructure indexed by increasing MK. Whole‐brain VBA of MK regression with age were conducted within the TDC group (left‐most column), ADHD‐mixed group (second column from left), ADHD‐pure subgroup (third column), and ADHD‐comorbid subgroup (fourth column). Voxel‐level FDR correction was applied to correct for multiple comparisons (p < 0.05). Only significant clusters are displayed on axial slices (red–yellow corresponding to low–high significance). For the TDC, ADHD‐mixed groups and the ADHD‐comorbid subgroup, MK was found to be significantly increasing with increasing age whereas the ADHD‐pure subgroup displayed no significant age‐related changes except when the significance threshold was lowered by removing the FDR correction (right‐most column: uncorrected p < 0.001). All images are in radiological convention (R‐right = L‐left) and normalized into 1 × 1 × 1 mm³ MNI152 standard space. For the ADHD‐comorbid subgroup, there were 0.15% of significant voxels with t‐values above the displayed range of 0–10. For visual efficiency, these voxels were displayed as having the maximum value within the range.

Figure 2

Age‐related increases in GM and WM microstructure indexed by increasing MK: effect sizes. Whole‐brain VBA of MK regression with age were conducted within the TDC group (left‐most column), ADHD‐mixed group (second column from left), ADHD‐pure subgroup (third column), and ADHD‐comorbid subgroup (fourth column). Voxel‐level FDR correction was applied to correct for multiple comparisons (p < 0.05). Only significant clusters are displayed on axial slices (blue–red corresponding to low–high effect sizes: correlation coefficient r‐values). For the TDC, ADHD‐mixed groups, and the ADHD‐comorbid subgroup, MK was found to be significantly increasing with increasing age whereas the ADHD‐pure subgroup displayed no significant age‐related changes except when the significance threshold was lowered by removing the FDR correction (right‐most column: uncorrected, p < 0.001). All images are in radiological convention (R‐right = L‐left) and normalized into 1 × 1 × 1 mm³ MNI152 standard space.

Figure 3

Percent of WM voxels with significant age‐related changes in microstructure. WM TBSS analyses of metric regression with age were conducted within the (A) TDC group, (C) ADHD‐mixed group, (B) ADHD‐pure subgroup, and (D) ADHD‐comorbid subgroup. For each group and subgroup, MK, K _||, K _⊥, MD, D _||, D _⊥, and FA metrics were tested for significant increases or decreases with increasing age. Voxel‐level TFCE correction for familywise error was applied with 2,000 permutations to correct for multiple comparisons (p < 0.05). The percent of significant voxels within the WM skeleton mask is displayed for each metric within each group and subgroup.

Figure 4

Dissociable patterns of greater WM microstructure in ADHD cohorts. TBSS analyses of group means within the WM skeleton mask (green voxels) detected (A) significantly higher kurtosis metrics in the ADHD cohorts; first left column: ADHD‐mixed > TDC in MK (orange and maroon clusters) and K _|| (blue and maroon clusters), second column: ADHD‐pure > TDC in K _|| (blue clusters), third column: ADHD‐comorbid > TDC in MK (orange clusters). (B) Significantly lower MD in the ADHD cohorts were also detected; first left column: ADHD‐mixed < TDC in MD (magenta clusters), second column: ADHD‐pure < TDC in MD (magenta clusters). Student's t‐tests were conducted and voxel‐level TFCE correction for familywise error was applied with 2,000 permutations to correct for multiple comparisons (p < 0.05). All images are in radiological convention (R‐right = L‐left), normalized into 1 × 1 × 1 mm³ MNI152 standard space and significant clusters have been thickened using the FMRIB Software Library “tbss_fill” tool for visualization.