In this study, we used computational methods to examine key midline regions that may be affected by early malformations of cortical development resulting from a chromosome 22q11.2 deletion. Cortical thickness maps and gyral complexity analyses provided a detailed characterization of areas of anomalous cortical development in this syndrome, revealing 3 main findings. First, we detected discrete regions of reduced cortical thickness in bilateral ventromedial occipital–temporal cortex, as well as the anterior cingulate, medial frontal, and subgenual prefrontal cortex. Second, fractal dimension (complexity) measures of the human cerebral neocortex in 3D revealed that children with 22q11.2DS had significantly increased gyral complexity specifically in the occipital cortex. Third, variation in gray matter volume, particularly in the frontal cortex, was strongly correlated with measures of cognitive ability, suggesting that, within 22q11.2DS, regionally specific neuroanatomic alterations may underlie cognitive and behavioral differences.
Here we visualized for the first time the profile of cortical thickness deficits across the medial hemispheric surface associated with the 22q11.2 chromosomal deletion. Decreases in cortical thickness were most pronounced (by 10–15%) in the ventromedial occipital–temporal cortex. Functional neuroimaging studies have shown that this region is critical for visuospatial navigation and directing spatial attention (Galati et al. 2001
), cognitive areas of disproportionate deficit in patients with 22q11.2DS (Simon et al. 2002
; Simon, Bearden, et al. 2005
). Cortical thinning in this region of the brain may underlie the prominent mathematical difficulties characteristic of this syndrome (Barnea-Goraly et al. 2005
; De Smedt et al. 2007
), as numerical–spatial interactions are believed to arise from common parietal circuits for attention to external space and internal representations of numbers (Hubbard et al. 2005
). Using a large battery of mathematical tests (De Smedt et al. 2007
) found that children with 22q11.2DS had specific difficulty with the semantic manipulation of quantities, a cognitive function which depends on a bilateral inferior parietal network (Dehaene et al. 1999
Although prior volumetric studies have primarily detected deficits in posterior brain regions, with relative preservation of frontal lobe regions, we also identified localized decreases in cortical thickness in frontal regions, particularly within the subgenual prefrontal cortex and anterior cingulate. Both functional neuroimaging and lesion studies in human and nonhuman primates have demonstrated that these brain regions are critical for emotional modulation, motivation and attention (Goldman et al. 1974
; Pardo et al. 1990
; Devinsky et al. 1995
; Drevets et al. 1998
), functions which are consistently reported to be significantly affected in both children and adults with 22q11.2DS (Swillen, Vandeputte, et al. 1999
; Arnold et al. 2001
). Structural and functional abnormalities in these brain regions are also frequently reported in children with attention deficit hyperactivity disorder (see Durston 2003
for a review), a diagnosis received by 30–50% of children and adolescents with 22q11.2 deletions (Papolos et al. 1996
; Feinstein et al. 2002
; Antshel et al. 2005
). Additionally, a recent functional MRI study identified hypoactivation in the dorsolateral prefrontal cortex and anterior cingulate in children with 22q11.2 deletions during performance on a verbal working memory task, which was not attributable to performance decrements, suggesting that the frontal component of the distributed network subserving executive function and working memory may be disrupted in youth with this syndrome (Kates et al. 2007
Increased Gyral Complexity in 22q11.2DS
Despite the pronounced cortical thinning observed in posterior brain regions in children with 22q11.2DS, we found concomitant increases in gyral complexity in these regions. These findings may be related, as it may be that in order to fit more GM into the same surface, the cortex must become more gyrified in those regions (Toro and Burnod 2005
). According to the radial unit model of cortical evolution (Rakic 1988b
), an increase in cerebral convolutions results in a net increase in cortical surface due to the addition of radial units, or minicolumns (Rakic 2004
). Thus, in disorders involving a larger than normal number of convolutions (i.e., PMG), the affected cortex is thinner, but is nevertheless associated with an increase in total cortical surface, suggesting that—in the extreme—increased gyral complexity is associated with cortical thinning. However, the lack of direct correlation between gyral complexity and thickness suggests that there is not a straightforward, linear relationship between surface geometry (e.g., gyrification measures) and regional tissue concentration (e.g., cortical thickness and GM volume). Only one other study, to our knowledge, has examined gyral complexity in 22q11.2DS (Schaer et al. 2006
). Using a semiautomated method for calculating a GI, this study observed decreased gyrification in the frontal and parietal lobes. Methodological differences are the most likely explanation for these contrasting findings. In particular, because gyrification indices are known to be affected by the orientation of slicing the brain (Thompson et al. 2005
), the derivation of the GI from coronal sections may have obscured differences that would be easier to detect in other planes.
Notably, a similar pattern of increased gyral complexity in posterior cortex has been observed in Williams Syndrome (WS), a genetic deletion syndrome with a characteristic cognitive profile—involving relative strengths in verbal memory, in contrast to marked deficits in visuospatial memory—that bears striking similarity to that seen in 22q11.2DS (Bearden et al. 2002
). A recent study using similar methods to analyze gyrification with excellent spatial resolution revealed increased gyrification bilaterally in occipital regions and over the cuneus in WS subjects (Gaser et al. 2006
). Thus, it is tempting to speculate that a similar neuroanatomic substrate may underlie the visuospatial impairments observed in patients with Williams Syndrome and 22q11.2DS, by affecting the flow of information through distributed neural systems; this hypothesis awaits further testing using multimodal imaging approaches.
Associations with Cognitive Abilities
Perhaps surprisingly, there was not a significant correlation of IQ with overall cortical thickness in children with 22q11.2DS. The thickness of the cortex, ranging between 1.5 and 4.5 mm across cortical regions, reflects cytoarchitectural characteristics of the neuropil including the density and arrangement of neurons, neuroglia, and nerve fibers (Armstrong et al. 1995
). As such, we might expect measures of cortical thickness to more closely link with cognitive abilities than volumetric measures. However, only a few studies have examined the relationship between intelligence and cortical thickness, with mixed results. Shaw et al. (2006)
examined the trajectory of change in cortical thickness from childhood to young adulthood, and found that relationships between IQ and cortical thickness were not significant in early childhood,
but that these relationships shifted toward positive correlations (predominantly in frontal cortical regions) in older subjects, suggesting that the correlation is highly age dependent and may be zero or even negative in younger individuals. Using stepwise multiple regression analyses, a prior study of healthy adults found gray matter to be the best predictor of variation in IQ, when including overall intracranial, gray, and white matter volumes in the model (Narr et al. 2007
). Although this study also found significant associations between FSIQ and cortical thickness in prefrontal (BA 10/11 and 47) and temporal (BA 37 and 36) cortical regions, the sample consisted of a large group of healthy young adults (N
= 65), so differences across studies may be either a function of sample size, and/or developmental differences.
Nevertheless, we did find that gray matter volume deficits in frontal and parietal regions were significantly linked to IQ scores in 22q11.2DS, with the strongest associations found between frontal gray matter and verbal and visuo-constructive abilities. The same GM deficits were also less strongly linked with academic abilities in reading and arithmetic. This pattern is highly consistent with 2 studies examining the relationship between gray matter density and IQ in normal adults (Haier et al. 2004
) and normal twin pairs (Thompson, Cannon, et al. 2001
), both of which found the strongest linkage between gray matter in frontal regions and measures of intelligence. Additionally, functional brain imaging studies support the notion that activation within the frontal lobes is the primary source of differences in performance on tasks of “general intelligence” (g
) (Duncan et al. 2000
). Interestingly, the correlations identified here in patients with 22q11.2DS are markedly higher than those generally reported in healthy populations, as a recent meta-analysis of the relationship between in vivo brain volume and intelligence in normal individuals, involving 37 studies and a total of 1530 people, estimated the population correlation to be 0.33 (McDaniel 2005
). This difference may be partially attributable to the greater variability in cognitive function in 22q11.2DS, although this possibility requires confirmation in a larger sample of patients. In any case, these findings clearly demonstrate that the observed neuroanatomic alterations have functional significance in patients with this syndrome.
Although this study was not designed to examine the developmental trajectory of cortical thickness alterations in 22q11.2DS, our data provide preliminary evidence for differences in the pattern of age-associated cortical thinning in this syndrome. In healthy control subjects, localized cortical thinning, primarily in superior parietal and cingulate cortices, was associated with increasing age. This pattern is fairly consistent with the trajectory of cortical thickness seen in healthy comparison subjects in a recent longitudinal study of child onset schizophrenia (Vidal et al. 2006
). However, children with 22q11.2DS showed a more posterior and more widespread pattern of age-related cortical thinning, particularly in ventromedial occipital–temporal regions. The time course of the observed differences will be assessed in the future in a prospective longitudinal design, in order to establish when in the course of development these differences emerge, and how they change over time within individual patients with 22q11.2DS.
Cortical thinning over the course of normal development likely reflects synaptic pruning, a process which is generally associated with increased cognitive efficiency (Johnson and Munakata 2005
). However, excessive pruning may indicate a pathological process, as suggested by the pattern of gray matter loss seen in adolescents with childhood-onset schizophrenia, in which early gray matter deficits in the parietal cortex progressed anteriorly into the temporal lobes and engulfed sensorimotor and dorsolateral prefrontal cortices, resulting in dramatic gray matter loss over a 5-year period (Thompson, Vidal, et al. 2001
; Vidal et al. 2006
Although little is known regarding longitudinal brain development in children with 22q11.2DS, the first longitudinal study to examine the developmental trajectory of brain volume in 22q11.2DS was recently completed (Gothelf et al. 2005
). Children and adolescents with 22q11.2DS who were rescanned, on average, 5 years later, showed a greater longitudinal increase in white matter, and superior temporal gyrus and caudate nucleus volumes compared with typically developing controls, as well as a more robust decrease in amygdala volume. The trajectory of change in the candidate brain regions examined in this study did not distinguish between psychotic and nonpsychotic adolescents with 22q11.2DS, although this may have been the result of limited power to examine subgroup differences.
Pathogenesis of Cortical Malformations in 22q11.2DS
The human neocortex is organized into functionally unique subdivisions that are distinguished by differences in cytoarchitecture, input and output connections, and gene expression patterns (O'Leary and Nakagawa 2002
; Rash and Grove 2006
). In adults, borders between neocortical areas can be sharply defined by differences in cytoarchitecture and neuronal connections, as well as differences in gene expression. These properties determine the functional specializations of particular cortical subregions.
The term “cortical arealization” refers to the process of regional and areal differentiation of the developing mammalian neocortex (Mallamaci and Stoykova 2006
). This process involves an interplay between intrinsic genetic mechanisms and extrinsic information relayed to the cortex by thalamocortical input. Several transcription factors, with varying expression across the embryonic cortical axes, are now known to determine the size and position of particular cortical areas (O'Leary et al. 2007
). Members of the fibroblast growth factor (Fgf
) family of genes, for example, are implicated in the control of neocortical regionalization. Using a set of gene expression markers to distinguish subdivisions of the newborn mouse frontal cortex (Cholfin and Rubenstein 2007
) found that loss of a particular fibroblast growth factor gene, Fgf17
, selectively reduces the size of the dorsal frontal cortex, whereas the ventral and orbital frontal cortical regions maintained normal appearance. These changes were complemented by a rostromedial shift of sensory cortical areas in Fgf17
mutant mice. Thus, in addition to an overall effect on patterning the neocortical map, Fgf17
showed an unexpectedly selective role in regulating dorsal frontal cortical development. Genetic manipulations during embryonic development that result in fairly subtle decreases or increases in the sizes of somatosensory and motor areas in adults can result in significant deficiencies at tactile and motor behaviors, suggesting that these areas have an optimal size for maximum behavioral performance (see O'Leary et al. 2007
for a review). Our findings of highly robust relationships between neuroanatomic variation in specific brain regions and phenotypic variation in patients with 22q11.2 deletions are in line with this view.
According to the radial unit hypothesis, the embryonic cerebral ventricle contains proliferative units that provide a “proto-map” of prospective cytoarchitectonic areas (Rakic 1988b
). Neurons proliferate in the germinal zones, within the walls of the lateral ventricles, then migrate along various pathways to the appropriate layers of distinct cytoarchitectonic areas in the developing cortex, where they disengage from the guide cell and begin to extend neurites and establish synaptic connections (Guerrini et al. 2008
). This model thus offers a framework for understanding genetic and epigenetic regulation of the division of cytoarchitectonic regions, as well as the pathogenesis of particular disorders of cortical development (Rakic 2004
). As our data suggest that a specific genetic mutation may affect the generation and migration of cortical neurons that are destined for particular regions of the cortex, our findings provide additional, albeit indirect, support for the protomap hypothesis.
Candidate Genes for Cortical Alterations
Over the past several years, genetic studies of cerebral cortical development in mice and in humans have identified several genes that, when mutated, can disrupt each of the main stages of cell proliferation and specification, neuronal migration and late cortical organization, resulting in disorders of neuronal migration and cerebral cortical development (Barkovich et al. 2005
; Guerrini et al. 2008
). It is likely that the cortical dysmorphology observed here is shaped primarily by genetically programmed anomalous neurodevelopment that disrupts midline cortical development. Moreover, findings of increased gyrification in posterior cortical regions suggest that one or more genes in the 22q11.2 region is involved in cortical development during the critical period when cortical folding occurs. Several genes that direct early cell differentiation and are highly expressed in the brain, including Tbx1
, goosecoid-like, ZNF74 zinc finger gene, GNB1L, which is widely expressed in the mouse forebrain, midbrain and hindbrain, and proline dehydrogenase, which regulates glutamate and γ-aminobutyrate neurotransmission (Paterlini et al. 2005
), are located in the deleted region (Maynard et al. 2003
). The expression of several zinc finger proteins has been shown to be critical for normal development of the cerebral cortex (Aruga et al. 1998
; Chen, Schaevitz, et al. 2005
; Chen, Rasin, et al. 2005
). Four zinc finger genes map to 22q11.2 within the DiGeorge syndrome region, suggesting that these may be potential candidate genes for the developmental malformations associated with this syndrome (Aubry et al. 1992
). The Zinc finger gene 312 (Zfp312, also known as Fez1) has also been demonstrated to play a critical role in the patterning of cortical axonal projections and the dendritic development of pyramidal neurons, the largest cellular elements in cortex (Chen, Rasin, et al. 2005
Several studies in mice have found Tbx1
to be the critical cause of the cardiac defects characteristic of the 22q11.2 phenotype (e.g., Vitelli et al. 2002
), and may also be involved in some of the behavioral and psychiatric symptoms associated with the syndrome (Paylor et al. 2006
). Another T-box transcription factor, T-box-brain2, leads to microcephaly with PMG and callosal agenesis (Baala et al. 2007
), all of which have been reported in rare cases in individuals with 22q11.2DS (Cramer et al. 1996
; Kraynack et al. 1999
; Robin et al. 2006
). In this regard, it is also interesting that another PMG syndrome, frontoparietal PMG, has been mapped to chromosome 16q12.2–21 (Piao et al. 2002
), and subsequently associated with mutations of a gene in the G-protein-coupled receptor family, the Gpr56
gene (Piao et al. 2004
). Thus, the gene expression patterns seen in a mouse Gpr56
mutant, as well as the pattern of cortical abnormalities seen in patients with homozygous Gpr56
mutations, offer convincing evidence that this gene regulates cortical patterning (Piao et al. 2004
). Although it is not yet clear precisely what gene(s) in the 22q11.2 region may be critically implicated in the identified cortical malformations, it is intriguing that—consistent with our findings of predominantly right-lateralized cortical thinning in ventromedial cortex—Robin et al. (2006)
observed a striking tendency toward right hemisphere PMG in a series of 22q11.2DS patients, suggesting that the relevant genes may be asymmetrically expressed in the brain.
Finally, the catechol-O
-methyl transferase (COMT) gene, located within this region, has a major role in dopamine metabolism, particularly in the prefrontal cortex (Tunbridge et al. 2006
). Several lines of evidence point to a role of COMT in both executive cognition and susceptibility to psychosis (Egan et al. 2001
), leading to speculation that COMT haploinsufficiency is responsible for the behavioral and cognitive abnormalities in 22q11.2DS. Although there is some evidence that genetic variation in COMT may influence working memory and executive cognition, both in individuals with 22q11.2DS and in the general population (Bearden et al. 2004a
; Gothelf et al. 2005
; Shashi et al. 2006
), evidence for its involvement in psychosis susceptibility remains equivocal (Murphy and Owen 2001
; Bassett et al. 2007
In addition, other neurobiological mechanisms occurring downstream of the genetic lesion are likely to also be involved in the observed neuroanatomic alterations; for example, abnormal mechanical constraints may arise from inappropriately targeted or missing neural connections. Lesion studies in nonhuman primates have shown that disruption of afferent pathways, when occurring very early in development, can lead to the emergence of abnormal sulcal and gyral patterning (Goldman and Galkin 1978
; Rakic 1988a
). Although cortical architecture in 22q11.2DS is highly likely to be affected by haploinsufficiency for particular genes in the deleted region, epigenetic and environmental influences are likely contributors as well. As such, direct causality cannot be determined from this study, in which we correlate a genetic mutation with neuroanatomic alteration. Longitudinal studies are clearly warranted in order to begin to disentangle the complex genetic and nongenetic influences that contribute to the neuroanatomic and cognitive abnormalities in this syndrome.
Because comparison subjects were not IQ-matched to the 22q11.2DS patients, IQ significantly differed between groups. Because IQ is inextricably correlated with diagnosis, we did not control for IQ in our analyses, as doing so would incorrectly eliminate some disease-specific effects. In developmentally delayed populations the issue of appropriately matched comparison subjects is complex, as individuals with comparable IQ to those with 22q11.2 deletions are likely to have intellectual disability of heterogeneous etiology, such as undetected chromosomal abnormalities or unknown environmental exposures (e.g., lead exposure, birth complications), which are likely to lead to a variety of cortical anomalies that are not well characterized. Moreover, including children with familial low IQ and/or environmental exposures would likely lead to systematic unmatching on other demographic variables, such as parental education. Thus, we adopted this more straightforward approach for this investigation, but clearly an optimal design for future studies would include both normal as well as IQ-matched comparison groups, possibly involving another discrete genetic etiology in order to minimize heterogeneity.
These findings offer novel information regarding patterns of neuroanatomic alteration and their relationship to cognitive abilities in children with 22q11.2 deletions. The fact that the neuroanatomic abnormalities in this syndrome are localized to particular brain regions adds to the growing body of evidence from both human and experimental animal studies that specific cytoarchitectonic areas can be a selective target for gene mutations. Aberrant parieto-occipital brain development, as evidenced by both increased complexity and cortical thinning in these regions, suggests a compelling neuroanatomic substrate for the deficits in visuospatial and numerical understanding in 22q11.2DS. In addition, significant cortical thinning in medial frontal and cingulate regions may contribute to the emotional and attentional difficulties characteristic of this syndrome. These observations suggest new hypotheses regarding the effects of haploinsufficiency for genes in the 22q11.2 region, the investigation of which will result in a more complete elucidation of the associations between genes, brain, cognition and behavior, both in 22q11.2DS and in the broader population.