Neuroanatomical correlates of attention-deficit–hyperactivity disorder accounting for comorbid oppositional defiant disorder and conduct disorder

Authors


Daimei Sasayama, MD, Department of Psychiatry, Shinshu University School of Medicine, 3-1-1 Asahi, Matsumoto, Nagano 390-8621, Japan. Email: sasayama@shinshu-u.ac.jp

Abstract

Aim:  An increasing number of neuroimaging studies have been conducted to uncover the pathophysiology of attention-deficit–hyperactivity disorder (ADHD). The findings are inconsistent, however, at least partially due to methodological differences. In the present study voxel-based morphometry (VBM) was used to evaluate brain morphology in ADHD subjects after taking into account the confounding effect of oppositional defiant disorder (ODD) and conduct disorder (CD) comorbidity.

Methods:  Eighteen children with ADHD and 17 age- and gender-matched typically developing subjects underwent high-spatial resolution magnetic resonance imaging. The regional gray matter volume differences between the children with ADHD and controls were examined with and without accounting for comorbid ODD and CD in a voxel-by-voxel manner throughout the entire brain.

Results:  The VBM indicated significantly smaller regional gray matter volume in regions including the bilateral temporal polar and occipital cortices and the left amygdala in subjects with ADHD compared with controls. Significantly smaller regional gray matter volumes were demonstrated in more extensive regions including the bilateral temporal polar cortices, bilateral amygdala, right occipital cortex, right superior temporal sulcus, and left middle frontal gyrus after controlling for the confounding effect of comorbid ODD and CD. 

Conclusion:  Morphological abnormalities in ADHD were seen not only in the regions associated with executive functioning but also in the regions associated with social cognition. When the effect of comorbid CD and ODD was taken into account, there were more extensive regions with significantly smaller volume in ADHD compared to controls.

ATTENTION-DEFICIT–HYPERACTIVITY DISORDER (ADHD) is a neurobehavioral disorder characterized by pervasive inattention and/or hyperactivity–impulsivity resulting in significant functional impairment. The pathophysiology is presumed to be linked to dysfunction of frontal–striatal–cerebellar circuits, although the exact mechanism has not yet been elucidated. Recently, an increasing number of neuroimaging studies using magnetic resonance imaging (MRI) or functional MRI have been conducted to uncover the pathophysiology of ADHD. Such studies have demonstrated functional as well as structural abnormalities associated with ADHD in the corpus callosum, prefrontal cortex, caudate nucleus, putamen, globus pallidus, anterior temporal lobe, and cerebellum.1,2 The findings are inconsistent, however, at least partially due to different methodologies and subject selection among studies.

Although the majority of previous structural MRI studies of ADHD have used the regions of interest (ROI) method,3–10 which could be applied only to a selected set of brain structures, several recent studies have used relatively newer neuroimaging analysis techniques such as voxel-based morphometry (VBM)11–14 and surface-based computational image analysis.15,16 While most previous morphological analyses with MRI using the ROI method have focused on the frontal lobe,4,9,10 basal ganglia,3,4,7,10 and cerebellum,3,6 VBM allows identification of regional differences even with no a priori region of interest, enabling an objective analysis of the whole brain. Accordingly, studies using newer neuroimaging analysis techniques have identified other abnormal regions such as the temporal or parietal lobes in patients with ADHD.11,13

Disruptive behavioral disorders (DBD), which include oppositional defiant disorder (ODD) and conduct disorder (CD), are common comorbidities of ADHD reported across cultures. Epidemiological studies indicate that the diagnoses of DBD are present in 40–70% of children with ADHD, and the prevalence of comorbid DBD in the clinical population is probably even higher than in community samples.17,18 A substantial proportion of ADHD children with comorbid DBD are known to develop antisocial personality disorder in adulthood.19 Harpold et al. reported that adults with ADHD with a childhood history of ODD also have increased risk for multiple anxiety disorders, bipolar disorder, and substance use disorders.20 Despite the high prevalence and the serious consequences of ODD and CD in ADHD patients, only a few previous neuroimaging studies have considered the presence of ODD and CD. Three previous VBM studies examining ADHD subjects with ODD or CD have found smaller gray matter volume in several regions, such as in the limbic structures,21,22 the basal ganglia,13 and the cerebellum.13

We used VBM to identify the morphological abnormalities in a voxel-by-voxel manner throughout the entire brain in ADHD subjects compared with the typically developing subjects. Subjects were grouped into those with and without comorbid ODD or CD to account for the effects of comorbidity on brain morphology.

METHODS

Subjects

Eighteen right-handed (determined using the Edinburgh Inventory23) inpatients and outpatients with ADHD were recruited from the Mental Health Clinic for Children, Shinshu University Hospital, Japan. Of these, eight were diagnosed with ADHD alone (boys/girls: 6/2), while 10 were diagnosed with comorbid ODD or CD (boys/girls: 7/3; six with ODD and four with CD). ADHD subjects were diagnosed with ADHD combined type (n = 10), inattentive type (n = 6), or hyperactive type (n = 2) according to DSM-IV-TR criteria.24 Subjects did not meet criteria for any other disorder, including pervasive developmental disorder (PDD), tic, or other affective illness. The Japanese edition of ADHD Rating Scale-IV (ADHD-RS)25 was used to evaluate the severity of ADHD symptoms. As the original version, the Japanese version has been shown to have adequate reliability and validity.26 The severity of oppositional defiant behaviors was measured on the Oppositional Defiant Behavior Inventory (ODBI).27 The ODBI is composed of 18 items describing oppositional behaviors. Each item is rated on a 4-point scale ranging from 0 to 3, with a higher score indicating more oppositional behaviors. The children's IQ scores were assessed using the Wechsler Intelligence Scale for Children, third edition.28 Seventeen right-handed, age- and gender-matched typically developing subjects were recruited for comparison. The typically developing control group had no history of treatment for psychiatric illness, and they were interviewed by experienced child psychiatrists to rule out any psychiatric disorder.

The exclusion criteria for both groups were mental retardation (IQ < 70), learning disability, neurological illness, traumatic brain injury with any known cognitive consequences or loss of consciousness for >5 min, and substance abuse or addiction. The ethics committee of Shinshu University Hospital approved the study. All the subjects gave their written informed consent after a complete explanation of the study.

Table 1 lists the demographic characteristics of the subjects. No significant difference was found in age, gender, parental socioeconomic status, or handedness index among the three diagnostic groups (controls/ADHD alone/ADHD with comorbid ODD or CD). No significant difference in IQ and ADHD-RS between subjects with ADHD alone and those with ADHD comorbid with ODD or CD was found. In contrast, ADHD subjects with comorbid ODD or CD had a significantly more severe ODBI than subjects with ADHD alone (P = 0.004). Compared to the control group, ADHD-RS and ODBI were significantly higher in subjects with ADHD alone (ADHD-RS, P < 0.001; ODBI, P = 0.001) and in those with ADHD comorbid with ODD or CD (ADHD-RS, P < 0.001; ODBI, P < 0.001).

Table 1.  Subject characteristics and test scores
VariableADHD patients (n = 18)Control subjects (n = 17)F-tests
ADHD alone (n = 8)Comorbid with ODD or CD (n = 10)
MeanSDMeanSDMeanSDFP
  • Determined using Edinburgh Inventory.23: scores >0 indicate right-handedness. A score of 100 indicates strong right-handedness.

  • Because the homogeneity of variance was violated according to the Levine's test, Welch F tests were performed.

  • ADHD, attention-deficit–hyperactivity disorder; ADHD-RS, ADHD Rating Scale; CD, conduct disorder; FIQ, full IQ; ODBI, Oppositional Defiant Behavior Inventory; ODD, oppositional defiant disorder; SES, socioeconomic status, assessed using the Hollingshead scale. Higher scores indicate lower status.

Age (years) (range)8.9 (6–12)2.411.9 (6–16)3.410.0 (6–14)2.42.90.07
Gender (boys/girls)6/27/312/5χ2 = 0.10.9
Parental SES3.00.53.00.82.50.62.80.08
Handedness (range)93.8 (50–100)17.791.2 (58–100)16.3100 (100–100)01.90.17
FIQ (range)90.9 (78–104)10.789.2 (73–112)13.9  T = 0.260.8
ADHD-RS (family, total)21.17.722.715.40.060.226.5<0.001
ODBI (family)16.18.236.916.01.12.730.4<0.001
Hyperactive subtype2 0     
Inattentive subtype2 4     
Combined subtype4 6     

MRI acquisition and image processing for VBM

All MRI was performed with a 1.5-T clinical imager (Magnetom Symphony; Siemens, Erlangen, Germany), using magnetization prepared rapid gradient echo (TR/TE = 3000/3.48 ms; flip angle 15°, 1.0-mm slice thickness, field of view 25.6 cm, and a matrix 512 × 512). Image processing for VBM, a fully automatic technique for computational analysis of differences in regional brain volume throughout the entire brain, was conducted using SPM2 (Institute of Neurology, London, UK). The method for image processing was the same as that used in previous studies.29,30 Briefly, this method involves the following steps: (i) spatial normalization of all images to a standardized anatomical space; (ii) extraction of gray and white matter from the normalized images; and (iii) analysis of differences in regional gray and white matter volume across the whole brain. The spatial normalization to standard anatomical space was performed in a two-stage process. In the first step, each image was registered to the International Consortium for Brain Mapping template (Montreal Neurological Institute, Montreal, Canada). The normalized images of all participants were averaged and smoothed with an 8-mm Gaussian kernel and then used as a new scanner- and population-specific template. In the second normalization step, each image of the entire group was deformed to the study-specific template using a non-linear spatial transformation. Finally, using a modified mixture model cluster analysis, normalized images were corrected for non-uniformities in signal intensity and partitioned using a study-specific customized prior probability map into gray and white matter, cerebrospinal fluid, and background. In an intensity-modulation step, voxel values of the segmented images were multiplied by the measure of warped and unwarped structures derived from the non-linear step of the spatial normalization. This step converts relative regional gray matter density to absolute gray matter density expressed as the amount of gray matter per unit volume of brain tissue prior to spatial normalization. The resulting modulated gray and white matter images were smoothed with a 12-mm Gaussian kernel.

Statistical analysis

Subject demographic characteristics were compared among the three diagnostic groups using one-way analysis of variance and χ2 test. The IQ scores were compared using unpaired t-test between subjects with ADHD alone and those with ADHD comorbid with ODD or CD. P < 0.05 was considered as statistically significant.

Statistical analyses of VBM were performed using an analysis of covariance model.31 To account for global anatomical variations, the statistical analysis treated the intracranial volume (ICV) and age as confounding covariates and the ADHD diagnosis as condition. To detect the neuroanatomical correlates of ADHD diagnosis accounting for comorbid ODD or CD, a diagnostic variable (1, no comorbidities; 2, ODD or CD) was used together with ICV and age as confounding covariates in the additional statistical analysis. We also conducted analysis using the ODBI score instead of the diagnostic variable as a confounding covariate to take into account the subthreshold conduct problems. To test the hypotheses with respect to regionally specific association with the ADHD diagnosis, the estimates were compared using two linear contrasts. The resulting set of voxel values for each contrast constituted a statistical parametric map of the t-statistic [SPM(t)]. The SPM(t) were displayed at an uncorrected threshold of P < 0.001 for graphical reporting. The statistics in the tables were transformed to a Z-score to make them more intuitive. The significance of each region was corrected for multiple comparisons using the false discovery rate (FDR).32 The statistical significance level was set at the FDR-corrected P < 0.05.

RESULTS

Group differences in regional brain volume

Table 2 lists the regions that showed smaller gray matter volumes in subjects with ADHD. No significant white matter volume difference between the groups was found. The VBM indicated significantly smaller regional gray matter volumes of regions including the bilateral temporal polar and occipital cortices and the left amygdala in subjects with ADHD compared with controls. In contrast, after controlling for the confounding effect of comorbid ODD and CD, significantly smaller regional gray matter volumes were demonstrated in the extensive brain regions including the bilateral temporal polar cortices, bilateral amygdala, right occipital cortex, right superior temporal sulcus, and left middle frontal gyrus in subjects with ADHD (FDR-corrected P < 0.05), as shown in Fig. 1. To account for the subthreshold conduct problems, we next treated the ODBI score instead of the diagnostic variable as the confounding covariate. The statistical significance level was also set at FDR-corrected P < 0.05 using the small volume correction with significant clusters, which were derived from the analysis using the diagnostic variable as the covariate, as searched volume. Accounting for the subthreshold conduct problems did not substantially change the statistical conclusion, because the statistical significance was preserved after adopting the ODBI score as a covariate (FDR-corrected P < 0.05; right temporal pole, [46 12 −34], Z = 4.2, [34 16 −32], Z = 4.02; right anterior ventral temporal cortex, [44 −8 −46], Z = 3.78; right orbitofrontal cortices, [22 18 −20], Z = 3.53; left amygdala, [−18 0 −32], Z = 3.23; left anterior ventral temporal, and left orbitofrontal cortices, [−22 16 −22], Z = 3.11; right superior temporal sulcus, [52 −36 −4], Z = 3.36; right occipital cortex, [34 −80 10], Z = 3.24; left parietal cortex, [−48 −70 44], Z = 3.32). The direct comparison between ADHD subjects with and without ODD or CD showed no significant gray matter volume difference between these diagnostic subgroups throughout the entire brain (FDR-corrected P > 0.08).

Table 2.  Regions with smaller gray matter volumes in ADHD subjects
Brain regions included within significant clusterPeak coordinateZ scoreFDR-corrected PCluster Size (k) (Voxel threshold: P < 0.001)
xyz
  1. ADHD, attention-deficit–hyperactivity disorder; CD, conduct disorder; FDR, false discovery rate; ODD, oppositional defiant disorder.

Not accounting for the comorbid ODD or CD      
 Right temporal pole and anterior ventral temporal cortex4412−345.210.0011932
 Bilateral occipital cortices0−7463.720.015671
 Left amygdala−26−4−303.310.03747
 Left occipital cortex−2−92−103.270.04126
 Left anterior ventral temporal cortex−42−10−463.230.04311
 Left temporal pole−306−463.210.0456
Controlling for the confounding effect of comorbid ODD or CD diagnosis
 Right amygdala, temporal pole, anterior ventral temporal and orbitofrontal cortices3416−325.090.0032027
 Left amygdala, temporal pole, anterior ventral temporal and orbitofrontal cortices−24−2−264.690.0031743
 Right occipital cortex44−84204.110.005404
 Right superior temporal sulcus50−40−23.620.01218
 Left parietal cortex−50−68443.440.01884
 Left middle frontal gyrus−3440163.420.0185
 Left temporal pole−524−383.360.0225
 Left occipital cortex−12−78103.310.02351
 Left occipital cortex−18−72−83.210.0276
 Right rectal gyrus1034−263.210.02815
 Right rectal gyrus618−163.130.0313
 Left parahippocampal gyrus22−28−203.130.0323
 Left parahippocampal gyrus24−26−223.10.0331
 Right rectal gyrus1254−223.10.0341
Figure 1.

Regions with smaller gray matter volumes in subjects with attention-deficit–hyperactivity disorder (ADHD). (a,d,g) Right temporal pole (area 1); (b,e,h) left amygdala (area 2); (c,f,i) left middle frontal gyrus (area 3). The gray matter regions with significantly smaller volumes in subjects with ADHD compared with controls are rendered onto the averaged image of the whole study sample (n = 35; voxel threshold: uncorrected P < 0.001).

DISCUSSION

The present VBM study investigating structural brain differences between ADHD subjects and the control subjects showed that controlling for the confounding effect of comorbid ODD and CD resulted in more extensive regions with significantly smaller volume in ADHD compared to controls. Treating ODD or CD diagnosis as the confounding covariate, significantly smaller volumes were found in the bilateral temporal polar cortices, bilateral amygdala, right occipital cortex, right superior temporal sulcus, and left middle frontal gyrus in subjects with ADHD compared with controls.

Children with ADHD have poor performance in executive function tasks.33,34 This may be partly due to abnormalities in the dorsolateral prefrontal cortex (DLPFC),35 which lies in the middle frontal gyrus and is responsible for executive functioning.36 In the present study the volume of the left middle frontal gyrus was significantly smaller in subjects with ADHD when the confounding effect of comorbid ODD and CD was accounted for. A number of previous studies of ADHD using the ROI method,3,6–8,10,37 VBM,12–14,38 or surface-based computational morphometry16 have similarly reported smaller volumes of the DLPFC regions. Functional imaging studies using positron emission tomography or functional MRI have also reported an association of DLPFC with ADHD symptoms.39,40

The present study found smaller volumes of the anterior temporal region, which plays an important role in social and emotional processing,41 in subjects with ADHD. A study using surface-based computational morphometry and a VBM study in twins have similarly reported abnormalities of anterior temporal regions in ADHD subjects.16,38 A study using functional MRI reported decreased metabolism in the same region.39 The amygdala is one of the most critical structures in the anterior temporal region, playing a crucial role in emotional and social behavior.42 A few studies including one meta-analysis have reported significantly smaller volumes of the amygdala in subjects with ADHD.2,3,7 These findings may be associated with social–cognitive impairment observed in ADHD children.43–45 The literature suggests that a region of the right superior temporal sulcus, which was found to have a significantly smaller volume in the present study, is also involved in social perception, specifically in analyzing the intentions of other people's actions.46

Previous reports have been inconsistent regarding the volume of the occipital lobes in subjects with ADHD. Some report smaller volumes in ADHD subjects,4,6,11,13,15 while others report no significant volume differences.5,37 Cerebellar and basal ganglia volume deficits have also been reported in a number of studies,12–14 but the present results indicated no significant volume changes in these regions.

The high rate of coexisting conditions with ADHD is often conceived as the result of ADHD being not a single entity.47 Of the many different comorbid configurations of ADHD, comorbidity of ADHD and CD has the most data substantiating its consideration as a distinct subtype. Children with this comorbidity differ from other children with ADHD in several associated features such as family history, longitudinal course, and neurochemical function.48–50 Although it remains unresolved as to whether children with ADHD and comorbid conduct problems represent a distinct subtype or a more virulent presentation of ADHD, it seems imprudent to neglect the confounding effects of such comorbidities when studying ADHD.

Only a few neuroimaging studies of ADHD subjects have considered the presence of ODD and CD. A VBM study that accounted for ODD and CD comorbidities reported that volume deficits of the cerebellum and the right globus pallidus were significantly greater compared to controls in children with ADHD plus comorbid ODD or CD, but not in those with ADHD alone.13 Another VBM study reported that CD symptoms were correlated with smaller gray matter volumes in limbic brain structures while hyperactive/impulsive symptoms were associated with smaller volumes in the frontoparietal and temporal cortices.22 A VBM study by Sterzer et al. examined 12 male adolescents with CD, seven of whom fulfilled the diagnostic criteria for ADHD.21 They reported smaller gray matter volumes in the bilateral anterior insula and the left amygdala in the clinical sample compared to healthy controls. Contrary to these findings, a recent study by De Brito et al. reported greater gray matter volumes of various regions including frontal, parietal, and temporal lobes in boys with conduct problems.51 They had selected only boys with callous–unemotional conduct problems and used hyperactivity inattention symptoms as a covariate. Their study showed that the gray matter is larger in a certain type of conduct disorders. These previous studies suggest that consideration of the confounding effects of the comorbid conduct problems may affect the results of neuroimaging studies of ADHD, and the inconsistent results among the other previous neuroimaging studies of ADHD may be partly due to the inadequate consideration of comorbid conditions.

In the present study, controlling for the effect of CD/ODD resulted in more extensive regions with significantly smaller volume in ADHD compared to controls, suggesting that the diagnosis of comorbid CD/ODD tends to be associated with an increase in the gray matter volume. Given that a positive correlation has been observed in a recent study between callous–unemotional traits and hyperactivity symptoms,52 the present results agree with those reported by De Brito et al.51 Although, in the present study, no significant gray matter volume difference was seen on direct comparison of ADHD subjects with and without ODD or CD, further studies with an increased number of subjects may allow statistically significant results to be obtained.

There were several limitations to the present study. First, the present sample size did not allow for further examination of the potential differential effects of ADHD subtype and sex. A more detailed analysis in homogeneous groups of patients should be performed in future studies. Second, the average age was greater, although not statistically significant, in the ADHD subjects with comorbid ODD or CD compared with the ADHD-alone group, which may have contributed to the difference in focal volume changes. Third, the effect of medication was not considered, although a recent study by Shaw et al. found no evidence of association between psychostimulant medication and differences in the development of the cerebral cortex.53 Fourth, the present study did not examine subjects with ODD or CD without comorbid ADHD. Inclusion of subjects with pure ODD or CD should yield a better understanding of the effects of comorbidities. Fifth, the degree of social dysfunction was not quantitatively assessed in the present study. The difference in social dysfunction between children with ADHD and controls could not be examined in the present study. Whether the regional brain volumes are associated with social–cognitive impairment in ADHD subjects needs further investigation.

In conclusion, morphological analysis of ADHD subjects using VBM indicated smaller volumes of the regions associated with social cognition (i.e. anterior temporal region and superior temporal sulcus) as well as in the regions responsible for executive functioning (i.e. DLPFC). When the effect of comorbid CD and ODD was taken into account, there were more extensive regions with significantly smaller volume in ADHD compared to controls. The inconsistency among previous neuroimaging studies of ADHD may reflect inadequate consideration of ADHD subtypes or comorbidities and differences in image analysis and sample selection. Consideration of the clinical heterogeneity of the ADHD diagnosis and the development of better neuroimaging analysis methods in future studies should result in more precise findings.

ACKNOWLEDGMENTS

This study was supported by a Grant-in-Aid for Scientific Research (C) (2) 14570915 ‘Research about the limbic system volume in the Oppositional Defiant Disorder comorbid with Attention Deficit Hyperactivity Disorder’ from the Japanese Ministry of Education, Culture, Sports, Science and Technology. The authors are grateful to those children (and their parents) who participated in the present study. We would like to express special thanks to Mrs Akiko Ryokawa for her help in recruiting the control subjects.

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