Schizophrenia occurs in about one in four individuals with 22q11.2 deletion syndrome (22q11.2DS). The aim of this International Brain and Behavior 22q11.2DS Consortium (IBBC) study was to identify genetic factors that contribute to schizophrenia, in addition to the ~20-fold increased risk conveyed by the 22q11.2 deletion. Using whole-genome sequencing data from 519 unrelated individuals with 22q11.2DS, we conducted genome-wide comparisons of common and rare variants between those with schizophrenia and those with no psychotic disorder at age ≥25 years. Available microarray data enabled direct comparison of polygenic risk for schizophrenia between 22q11.2DS and independent population samples with no 22q11.2 deletion, with and without schizophrenia (total n=35,182). Polygenic risk for schizophrenia within 22q11.2DS was significantly greater for those with schizophrenia (p adj =6.73x10-6). Novel reciprocal case-control comparisons between the 22q11.2DS and population-based cohorts showed that polygenic risk score was significantly greater in individuals with psychotic illness, regardless of the presence of the 22q11.2 deletion. Within the 22q11.2DS cohort, results of gene-set analyses showed some support for rare variants affecting synaptic genes. No common or rare variants within the 22q11.2 deletion region were significantly associated with schizophrenia. These findings suggest that in addition to conferring a greatly increased risk to schizophrenia, the risk is higher when the 22q11.2 deletion and common polygenic risk factors that contribute to schizophrenia in the general population are both present.
Atypical cortical organization and reduced integrity of the gray–white matter boundary have been reported by postmortem studies in individuals with autism spectrum disorder (ASD). However, there are no in vivo studies that examine these particular features of cortical organization in ASD. Hence, we used structural magnetic resonance imaging to examine differences in tissue contrast between gray and white matter in 98 adults with ASD and 98 typically developing controls, to test the hypothesis that individuals with ASD have significantly reduced tissue contrast. More specifically, we examined contrast as a percentage between gray and white matter tissue signal intensities (GWPC) sampled at the gray–white matter boundary, and across different cortical layers. We found that individuals with ASD had significantly reduced GWPC in several clusters throughout the cortex (cluster, P < 0.05). As expected, these reductions were greatest when tissue intensities were sampled close to gray–white matter interface, which indicates a less distinct gray–white matter boundary in ASD. Our in vivo findings of reduced GWPC in ASD are therefore consistent with prior postmortem findings of a less well-defined gray–white matter boundary in ASD. Taken together, these results indicate that GWPC might be utilized as an in vivo proxy measure of atypical cortical microstructural organization in future studies.
These findings highlight the need for considering normative sex-related phenotypic diversity when determining an individual's risk for ASD and provide important novel insights into the neurobiological mechanisms mediating sex differences in ASD prevalence.
Autism spectrum disorder (ASD) is a lifelong neurodevelopmental condition that is accompanied by an atypical development of brain maturation. So far, brain development has mainly been studied during early childhood in ASD, and using measures of total or lobular brain volume. However, cortical volumetric measures are a product of two distinct biological neuroanatomical features, cortical thickness, and surface area, which most likely also have different neurodevelopmental trajectories in ASD. Here, we therefore examined age-related differences in cortical thickness and surface area in a cross-sectional sample of 77 male individuals with ASD ranging from 7 to 25 years of age, and 77 male neurotypical controls matched for age and FSIQ. Surface-based measures were analyzed using a general linear model (GLM) including linear, quadratic, and cubic age terms, as well as their interactions with the main effect of group. When controlling for the effects of age, individuals with ASD had spatially distributed reductions in cortical thickness relative to controls, particularly in fronto-temporal regions, and also showed significantly reduced surface area in the prefrontal cortex and the anterior temporal lobe. We also observed significant group × age interactions for both measures. However, while cortical thickness was best predicted by a quadratic age term, the neurodevelopmental trajectory for measures of surface area was mostly linear. Our findings suggest that ASD is accompanied by age-related and region-specific reductions in cortical thickness and surface area during childhood and early adulthood. Thus, differences in the neurodevelopmental trajectory of maturation for both measures need to be taken into account when interpreting between-group differences overall.
Stereotyped, repetitive behaviours in autism may reflect deficits in serotonin-modulated inhibitory control. Daly et al. use fMRI to compare the effects of acute tryptophan depletion in adult males with autism and controls performing the Go/No-Go task. Opposite effects are seen in the two groups, consistent with altered inhibition in autism.
It is generally agreed that the human brain is responsive to environmental influences, and that the male brain may be particularly sensitive to early adversity. However, this is largely based on retrospective studies of older children and adolescents exposed to extreme environments in childhood. Less is understood about how normative variations in parent–child interactions are associated with the development of the infant brain in typical settings. To address this, we used magnetic resonance imaging to investigate the relationship between observational measures of mother–infant interactions and regional brain volumes in a community sample of 3- to 6-month-old infants (N = 39). In addition, we examined whether this relationship differed in male and female infants. We found that lower maternal sensitivity was correlated with smaller subcortical grey matter volumes in the whole sample, and that this was similar in both sexes. However, male infants who showed greater levels of positive communication and engagement during early interactions had smaller cerebellar volumes. These preliminary findings suggest that variations in mother–infant interaction dimensions are associated with differences in infant brain development. Although the study is cross-sectional and causation cannot be inferred, the findings reveal a dynamic interaction between brain and environment that may be important when considering interventions to optimize infant outcomes.
The 22q11.2 deletion syndrome (22q11.2DS) is a neurodevelopmental disorder associated with a number of volumetric brain abnormalities. The syndrome is also associated with an increased risk for neuropsychiatric disorders including schizophrenia and autism spectrum disorder. An earlier meta-analysis showed reduced grey and white matter volumes in individuals with 22q11.2DS. Since this analysis was conducted, the number of studies has increased markedly, permitting more precise estimates of effects and more regions to be examined. Although 22q11.2DS is clinically heterogeneous, it is not known to what extent this heterogeneity is mirrored in neuroanatomy. The aim of this study was thus to investigate differences in mean brain volume and structural variability within regions, between 22q11.2DS and typically developing controls. We examined studies that reported measures of brain volume using MRI in PubMed, Web of Science, Scopus and PsycINFO from inception to 1 May 2019. Data were extracted from studies in order to calculate effect sizes representing case-control difference in mean volume, and in the variability of volume (as measured using the log variability ratio (lnVR) and coefficient of variation ratio (CVR)). We found significant overall decreases in mean volume in 22q11.2DS compared with control for: total brain (g = −0.96; p < 0.001); total grey matter (g = −0.81, p < 0.001); and total white matter (g = −0.81; p < 0.001). There was also a significant overall reduction of mean volume in 22q11.2DS subjects compared with controls in frontal lobe (g = −0.47; p < 0.001), temporal lobe (g = −0.84; p < 0.001), parietal lobe (g = −0.73; p = 0.053), cerebellum (g = −1.25; p < 0.001) and hippocampus (g = −0.90; p < 0.001). Significantly increased variability in 22q11.2DS individuals compared with controls was found only for the hippocampus (VR, 1.14; p = 0.036; CVR, 1.30; p < 0.001), and lateral ventricles (VR, 1.56; p = 0.004). The results support the notion that structural abnormalities in 22q11.2DS and schizophrenia are convergent, and also to some degree with findings in autism spectrum disorder. Finally, the increased variability seen in the hippocampus in 22q11.2DS may underlie some of the heterogeneity observed in the neuropsychiatric phenotype.
22q11.2 Deletion Syndrome (22q11.2DS) is a genetic condition associated with a high prevalence of neuropsychiatric conditions that include autism spectrum disorder (ASD). While evidence suggests that clinical phenotypes represent distinct neurodevelopmental outcomes, it remains unknown whether this translates to the level of neurobiology. To fractionate the 22q11.2DS phenotype on the level of neuroanatomy, we examined differences in vertex-wise estimates of cortical volume, surface area, and cortical thickness between 1) individuals with 22q11.2DS (n = 62) and neurotypical controls (n = 57) and 2) 22q11.2DS individuals with ASD symptomatology (n = 30) and those without (n = 25). We firstly observed significant differences in surface anatomy between 22q11.2DS individuals and controls for all 3 neuroanatomical features, predominantly in parietotemporal regions, cingulate and dorsolateral prefrontal cortices. We also established that 22q11.2DS individuals with ASD symptomatology were neuroanatomically distinct from 22q11.2DS individuals without ASD symptoms, particularly in brain regions that have previously been linked to ASD (e.g., dorsolateral prefrontal cortices and the entorhinal cortex). Our findings indicate that different clinical 22q11.2DS phenotypes, including those with ASD symptomatology, may represent different neurobiological subgroups. The spatially distributed patterns of neuroanatomical differences associated with ASD symptomatology in 22q11.2DS may thus provide useful information for patient stratification and the prediction of clinical outcomes.
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