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Critical region within 22q11.2 linked to higher rate of autism spectrum disorder.

ABSTRACT: BACKGROUND:Previous studies have reported no clear critical region for medical comorbidities in children with deletions or duplications of 22q11.2. The purpose of this study was to evaluate whether individuals with small nested deletions or duplications of the LCR-A to B region of 22q11.2 show an elevated rate of autism spectrum disorder (ASD) compared to individuals with deletions or duplications that do not include this region. METHODS:We recruited 46 patients with nested deletions (n = 33) or duplications (n = 13) of 22q11.2, including LCR-A to B (ndel = 11), LCR-A to C (ndel = 4), LCR-B to D (ndel = 14; ndup = 8), LCR-C to D (ndel = 4; ndup = 2), and smaller nested regions (n = 3). Parent questionnaire, record review, and, for a subset, in-person evaluation were used for ASD diagnostic classification. Rates of ASD in individuals with involvement of LCR-B to LCR-D were compared with Fisher's exact test to LCR-A to LCR-B for deletions, and to a previously published sample of LCR-A to LCR-D for duplications. The rates of medical comorbidities and psychiatric diagnoses were determined from questionnaires and chart review. We also report group mean differences on psychiatric questionnaires. RESULTS:Individuals with deletions involving LCR-A to B showed a 39-44% rate of ASD compared to 0% in individuals whose deletions did not involve LCR-A to B. We observed similar rates of medical comorbidities in individuals with involvement of LCR-A to B and LCR-B to D for both duplications and deletions, consistent with prior studies. CONCLUSIONS:Children with nested deletions of 22q11.2 may be at greater risk for autism spectrum disorder if the region includes LCR-A to LCR-B. Replication is needed.

SUBMITTER: Clements CC

PROVIDER: S-EPMC5658953 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background and aimChildren with Developmental Language Disorder (DLD) are at an increased risk to develop behaviors associated with Autism Spectrum Disorder (ASD). The relationship between early language difficulties and the occurrence of ASD-related behaviors in DLD is poorly understood. One factor that may hinder progress in understanding this relationship is the etiological heterogeneity of DLD. We therefore study this relationship in an etiologically homogeneous group of children, who share phenotypic characteristics with children with DLD: children with the 22q11.2 Deletion Syndrome (22q11DS). We compare children with 22q11DS, to children with DLD and age-matched typically developing children (TD).Method44 children with 22q11DS, 65 children with DLD and 81 TD children, between 3.0-6.5 years old, participated in a longitudinal cohort study that included a baseline measure and a follow-up measure with a 1-year interval. A parental questionnaire (SRS-2) was used to measure the incidence of behaviors in two key behavioral domains associated with ASD: Social Communication and Interaction and Restricted Repetitive Behaviors and Interests. At baseline, we assessed children's expressive and receptive language abilities as well as their intellectual functioning with standardized tests. We compared the distribution of ASD-related behaviors between the three groups. We used regression analyses to investigate whether language abilities at baseline predict ASD-related behavior at follow-up, accounting for ASD-related behavior at baseline, demographic variables and intellectual functioning.ResultsBoth the children with 22q11DS and the children with DLD displayed significantly more ASD-related behaviors than the TD children. Over 30% of children in both clinical groups had scores exceeding the subclinical threshold for ASD in both behavioral domains. Both in 22q11DS and DLD, baseline receptive language scores were negatively correlated with ASD-related behaviors 1 year later, when controlling for baseline SRS-scores. However, this association was statistically significant only in children with 22q11DS, even when controlled for IQ-scores, and it was significantly stronger as than in the TD group. The strength of the association did not differ significantly between 22q11DS and DLD.ConclusionBoth children with 22q11DS and children with DLD present with elevated rates of ASD-related behaviors at a preschool-age. Only in children with 22q11DS we observed that weaker receptive language skills were related to increased behavioral problems in the domain of social communication and interaction one year later.ImplicationsOur findings indicate that relations between early language impairment and other behavioral phenotypes may be more feasible to detect in a subgroup of children with a homogeneous etiology, than in a group of children with a heterogeneous etiology (such as children with DLD). Our results in 22q11DS reveal that receptive language is especially important in predicting the occurrence of ASD-related behaviors. Future research is needed to determine to what extent receptive language predicts the occurrence of ASD-related behaviors in children with DLD, especially among those children with DLD with the weakest receptive language. Clinically, screening for ASD-related behaviors in children with developmental language difficulties is recommended from a young age, especially among children with receptive language difficulties.

Project description:22q11.2 Deletion Syndrome (22q11DS) represents one of the most common known genetic risk factors for the development of psychotic illness, and is also associated with high rates of autistic spectrum disorders (ASD) in childhood. We performed integrated genomic analyses of 22q11DS to identify genes and pathways related to specific phenotypes. Eighty percent of 22q11DS individuals (n=37) carried the typical 3 Mb deletion, with significant variability in the deletion characteristics in the remainder of the sample (n=9). Both analysis of differential expression and weighted gene coexpression network analysis (WGCNA) identified peripheral changes in gene expression related to psychotic symptom expression in patients, including a module of co-expressed genes which was associated with psychosis in 22q11DS and involved in pathways associated with transcriptional regulation. Remarkably, this 22q11DS psychosis module was significantly enriched for brain-expressed genes, was not related to antipsychotic medication use, and showed significant overlap with transcriptional changes occurring in idiopathic schizophrenia in an independent dataset. In those with 22q11DS-ASD, both differential expression and WGCNA analyses pointed towards dysregulation of immune response pathways. The ASD-associated module showed overlap with a neuronal module enriched for known autism susceptibility genes identified in brain transcriptome data from individuals with idiopathic autism. These findings further support the use of peripheral tissue in the study of major mutational models of diseases affecting the brain, and point towards specific pathways dysregulated in 22q11DS carriers with psychosis and ASD, warranting their further investigation in idiopathic illness. Participants. Forty-six patients with a molecularly confirmed diagnosis of a 22q11.2 deletion and 66 controls (24 unrelated controls and 42 first-degree relatives of 22q11DS patients) were recruited from an ongoing longitudinal study. Comparative Genomic Hybridization Arrays. To characterize the boundaries of the 22q11.2 deletion, we designed a custom NimbleGen 12*135 HX12 array. Microarray-based gene expression analysis. Whole-genome transcriptional profiling was performed using Illumina Human HT-12 microarrays.Gene ontology annotation was performed using DAVID (http://david.abcc.ncifcrf.gov/) and pathway analysis was performed by using the Functional Analysis Annotation tool in the Ingenuity Pathways Analysis (IPA) software (Ingenuity Systems, www.ingenuity.com). Because the healthy control group included parents of 22q11DS patients, there were significant age differences between groups (Table 1, p<.001); thus, we corrected for age in all analyses.Weighted Gene Co-expression Network Analysis (WGCNA). We conducted WGCNA, a systems biology approach used to identify networks of co-expressed genes in relation to phenotypic data, using the R package. Phenotypic traits examined within the 22q11DS group included: categorical and dimensional indicators of psychosis (i.e. psychosis diagnosis and SIPS psychotic symptom severity score), ASD, and gender. For modules that showed a statistically significant relationship with any phenotypic trait (p<.05), GO analyses and IPA were conducted. Validation with published datasets. In order to validate our gene expression and WGCNA results, we overlapped gene lists obtained from microarray differential expression analysis for 22q11DS vs. Controls,

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Critical region within 22q11.2 linked to higher rate of autism spectrum disorder.

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