DRD3 gene and striatum in autism spectrum disorder.

A single-nucleotide polymorphism (SNP) of the DRD3 gene (rs167771) was recently associated with autism spectrum disorders (ASD). Different polymorphisms of rs167771 corresponded to varying degrees of stereotyped behaviour. As DRD3 receptors are relatively overexpressed in the striatum, we investigated whether striatal volume was related to these polymorphisms in autism. We assessed volumes of caudate nucleus and putamen in 86 participants with ASD (mean age 15.3 years). MANCOVA showed an association between alleles of the rs167771 SNP and the volume of striatal structures. Furthermore, greater caudate nucleus volume correlated with stereotyped behaviour. These findings support a relationship between DRD3 gene SNPs, striatum and stereotyped behaviour in ASD.

Unique developmental trajectories of cortical thickness and surface area.

There is evidence that the timing of developmental changes in cortical volume and thickness varies across the brain, although the processes behind these differences are not well understood. In contrast to volume and thickness, the regional developmental trajectories of cortical surface area have not yet been described. The present study used a combined cross-sectional and longitudinal design with 201 MRI-scans (acquired at 1.5-T) from 135 typically developing children and adolescents. Scans were processed using FreeSurfer software and the Desikan-Killiany atlas. Developmental trajectories were estimated using mixed model regression analysis. Within most regions, cortical thickness showed linear decreases with age, whereas both cortical volume and surface area showed curvilinear trajectories. On average, maximum surface area occurred later in development than maximum volume. Global gender differences were more pronounced in cortical volume and surface area than in average thickness. Our findings suggest that developmental trajectories of surface area and thickness differ across the brain, both in their pattern and their timing, and that they also differ from the developmental trajectory of global cortical volume. Taken together, these findings indicate that the development of surface area and thickness is driven by different processes, at least in part.

Typical development of basal ganglia, hippocampus, amygdala and cerebellum from age 7 to 24.

Developmental imaging studies show that cortical grey matter decreases in volume during childhood and adolescence. However, considerably less research has addressed the development of subcortical regions (caudate, putamen, pallidum, accumbens, thalamus, amygdala, hippocampus and the cerebellar cortex), in particular not in longitudinal designs. We used the automatic labeling procedure in FreeSurfer to estimate the developmental trajectories of the volume of these subcortical structures in 147 participants (age 7.0-24.3years old, 94 males; 53 females) of whom 53 participants were scanned twice or more. A total of 223 magnetic resonance imaging (MRI) scans (acquired at 1.5-T) were analyzed. Substantial diversity in the developmental trajectories was observed between the different subcortical gray matter structures: the volume of caudate, putamen and nucleus accumbens decreased with age, whereas the volume of hippocampus, amygdala, pallidum and cerebellum showed an inverted U-shaped developmental trajectory. The thalamus showed an initial small increase in volume followed by a slight decrease. All structures had a larger volume in males than females over the whole age range, except for the cerebellum that had a sexually dimorphic developmental trajectory. Thus, subcortical structures appear to not yet be fully developed in childhood, similar to the cerebral cortex, and continue to show maturational changes into adolescence. In addition, there is substantial heterogeneity between the developmental trajectories of these structures.

Caudate nucleus is enlarged in high-functioning medication-naive subjects with autism.

BACKGROUND: Autism is defined by three symptom clusters, including repetitive and stereotyped behavior. Previous studies have implicated basal ganglia in these behaviors. Earlier studies investigating basal ganglia in autism have included subjects on neuroleptics known to affect basal ganglia volumes. Therefore, we investigated these structures in medication-naive subjects with autism. METHODS: Volumetric magnetic resonance measures of caudate, putamen, and nucleus accumbens were compared in two independent samples of medication-naive, high-functioning subjects with autism or Asperger syndrome: 1) 21 affected children and adolescents and 21 matched control subjects; and 2) 21 affected adolescents and young adults and 21 matched control subjects. RESULTS: Caudate nucleus was enlarged in both samples. This result remained significant after correction for total brain volume. CONCLUSIONS: These results implicate caudate nucleus in autism, as an enlargement of this structure was disproportional to an increase in total brain volume in two independent samples of medication-naive subjects with autism.

Gray and white matter volume abnormalities in monozygotic and same-gender dizygotic twins discordant for schizophrenia.

BACKGROUND: Whole brain tissue volume decreases in schizophrenia have been related to both genetic risk factors and disease-related (possibly nongenetic) factors; however, whether genetic and environmental risk factors in the brains of patients with schizophrenia are differentially reflected in gray or white matter volume change is not known. METHODS: Magnetic resonance imaging (1.5 T) brain scans of 11 monozygotic and 11 same-gender dizygotic twin pairs discordant for schizophrenia were acquired and compared with 11 monozygotic and 11 same-gender dizygotic healthy control twin pairs. RESULTS: Repeated-measures volume analysis of covariance revealed decreased whole brain volume in the patients with schizophrenia as compared with their co-twins and with healthy twin pairs. Decreased white matter volume was found in discordant twin pairs compared with healthy twin pairs, particularly in the monozygotic twin pairs. A decrease in gray matter was found in the patients compared with their co-twins and compared with the healthy twins. CONCLUSIONS: The results suggest that the decreases in white matter volume reflect the increased genetic risk to develop schizophrenia, whereas the decreases in gray matter volume are related to environmental risk factors. Study of genes involved in the (maintenance) of white matter structures may be particularly fruitful in schizophrenia.

Changes in the development of striatum are involved in repetitive behavior in autism.

BACKGROUND: Repetitive behavior is a core feature of autism and has been linked to differences in striatum. In addition, the brain changes associated with autism appear to vary with age. However, most studies investigating striatal differences in autism are cross-sectional, limiting inferences on development. In this study, we set out to 1) investigate striatal development in autism, using a longitudinal design; and 2) examine the relationship between striatal development and repetitive behavior. METHODS: We acquired longitudinal structural magnetic resonance imaging scans from 86 individuals (49 children with autism, 37 matched control subjects). Each individual was scanned twice, with a mean scan interval time of 2.4 years. Mean age was 9.9 years at time 1 and 12.3 years at time 2. Striatal structures were traced manually with high reliability. Multivariate analyses of variance were used to investigate differences in brain development between diagnostic groups. To examine the relationship with behavior, correlations between changes in brain volumes and clinical measures were calculated. RESULTS: Our results showed an increase in the growth rate of striatal structures for individuals with autism compared with control subjects. The effect was specific to caudate nucleus, where growth rate was doubled. Second, faster striatal growth was correlated with more severe repetitive behavior (insistence on sameness) at the preschool age. CONCLUSIONS: This longitudinal study of brain development in autism confirms the involvement of striatum in repetitive behavior. Furthermore, it underscores the significance of brain development in autism, as the severity of repetitive behavior was related to striatal growth, rather than volume per se.

Fronto-striatal circuitry and inhibitory control in autism: findings from diffusion tensor imaging tractography.

INTRODUCTION: Repetitive behaviour and inhibitory control deficits are core features of autism; and it has been suggested that they result from differences in the anatomy of striatum; and/or the 'connectivity' of subcortical regions to frontal cortex. There are few studies, however, that have measured the micro-structural organisation of white matter tracts connecting striatum and frontal cortex. AIMS: To investigate differences in bulk volume of striatum and micro-structural organisation of fronto-striatal white matter in people with autism; and their association with repetitive behaviour and inhibitory control. METHODS: We compared the bulk volume of striatum (caudate nucleus, putamen and nucleus accumbens) and white matter organisation of fronto-striatal tracts using (respectively) structural magnetic resonance imaging (sMRI) and tract specific diffusion tensor imaging (DTI) measures in 21 adults with autism and 22 controls. We also assessed performance on a cognitive inhibition (go/nogo) task. RESULTS: Bulk volume of striatal structures did not differ between groups. However, adults with autism had a significantly smaller total brain white matter volume, lower fractional anisotropy of white matter tracts connecting putamen to frontal cortical areas, higher mean diffusivity of white matter tracts connecting accumbens to frontal cortex and worse performance on the go/nogo task. Also, performance on the go/nogo task was significantly related to anatomical variation when both groups were combined; but not within the autism group alone. CONCLUSIONS: These data suggest that autism may be associated with differences in the anatomy of fronto-striatal white matter tracts.

Differential brain development with low and high IQ in attention-deficit/hyperactivity disorder.

Attention-Deficit/Hyperactivity Disorder (ADHD) and intelligence (IQ) are both heritable phenotypes. Overlapping genetic effects have been suggested to influence both, with neuroimaging work suggesting similar overlap in terms of morphometric properties of the brain. Together, this evidence suggests that the brain changes characteristic of ADHD may vary as a function of IQ. This study investigated this hypothesis in a sample of 108 children with ADHD and 106 typically developing controls, who participated in a cross-sectional anatomical MRI study. A subgroup of 64 children also participated in a diffusion tensor imaging scan. Brain volumes, local cortical thickness and average cerebral white matter microstructure were analyzed in relation to diagnostic group and IQ. Dimensional analyses investigated possible group differences in the relationship between anatomical measures and IQ. Second, the groups were split into above and below median IQ subgroups to investigate possible differences in the trajectories of cortical development. Dimensionally, cerebral gray matter volume and cerebral white matter microstructure were positively associated with IQ for controls, but not for ADHD. In the analyses of the below and above median IQ subgroups, we found no differences from controls in cerebral gray matter volume in ADHD with below-median IQ, but a delay of cortical development in a number of regions, including prefrontal areas. Conversely, in ADHD with above-median IQ, there were significant reductions from controls in cerebral gray matter volume, but no local differences in the trajectories of cortical development.In conclusion, the basic relationship between IQ and neuroanatomy appears to be altered in ADHD. Our results suggest that there may be multiple brain phenotypes associated with ADHD, where ADHD combined with above median IQ is characterized by small, more global reductions in brain volume that are stable over development, whereas ADHD with below median IQ is associated more with a delay of cortical development.

The neurobiology of repetitive behavior: and men.

In young, typically developing children, repetitive behavior similar to that in certain neuropsychiatric syndromes is common. Whereas this behavior is adaptive in typical development, in many disorders it forms a core component of symptoms and causes prominent impairment in the daily life of affected individuals. Understanding the neurobiological mechanisms involved repetitive behavior will improve our understanding of the pathogenesis of developmental neuropsychiatric disorders, stimulating novel approaches to these conditions. However, studies on the neurobiology of human repetitive behavior have often been limited to distinct conditions and generalization has been hindered by inconsistent terminology. In this paper, we synthesize the 'disorder-driven' literature, building on findings from fundamental animal research and translational models. These findings suggest a model for classifying repetitive behavior by its neuroanatomical correlates.

The neurobiology of repetitive behavior: of mice .

Repetitive and stereotyped behavior is a prominent element of both animal and human behavior. Similar behavior is seen across species, in diverse neuropsychiatric disorders and in key phases of typical development. This raises the question whether these similar classes of behavior are caused by similar neurobiological mechanisms or whether they are neurobiologically unique? In this paper we discuss fundamental animal research and translational models. Imbalances in corticostriatal function often result in repetitive behavior, where different classes of behavior appear to be supported by similar neural mechanisms. Although the exact nature of these imbalances are not yet fully understood, synthesizing the literature in this area provides a framework for studying the neurobiological systems involved in repetitive behavior.

Changes in the developmental trajectories of striatum in autism.

BACKGROUND: Repetitive and stereotyped behavior has been associated with striatum in various neuropsychiatric disorders. However, striatal involvement has not yet been shown conclusively in autism. Issues include the use of neuroleptic medication and differences in mean age between samples, where conflicting results may reflect differences in developmental stage between samples. The objective was to examine brain development in a homogeneous sample of subjects with high-functioning autism. METHODS: Magnetic resonance measures of brain structure of 188 individuals (99 subjects with high-functioning autism and 89 typically developing, matched control subjects) aged between 6 years and 25 years were compared. Measurements included the volume of brain structures, including striatum, as well as voxel-based assessment of gray matter density. RESULTS: Developmental trajectories of the caudate nucleus, putamen, and nucleus accumbens differed between subjects with autism and control subjects. Results were not accounted for by overall changes in brain volume or neuroleptic medication. The development of the caudate nucleus differed from typical most, as its volume increased with age in autism, while it decreased for control subjects. Voxel-based analysis showed that changes in striatum localized to the head of the caudate nucleus. Overall, caudate nucleus volume was associated with repetitive behavior in autism. CONCLUSIONS: We report changes in striatal development in autism, while caudate volume is associated with repetitive behaviors. This emphasizes the importance of striatum in the etiology of autism, in particular in the development of repetitive behavior that characterizes the disorder.