ADHD and autism symptoms in youth: a network analysis.

BACKGROUND: Previous research investigating the overlap between attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (henceforth, autism) symptoms in population samples have relied on latent variable modeling in which averaged scores representing dimensions were derived from observed symptoms. There are no studies evaluating how ADHD and autism symptoms interact at the level of individual symptom items. METHODS: We aimed to address this gap by performing a network analysis on data from a school survey of children aged 6-17 years old (N = 7,405). ADHD and autism symptoms were measured via parent-report on the Swanson, Nolan, Pelham-IV questionnaire and the Childhood Autism Spectrum test, respectively. RESULTS: A relatively low interconnectivity between ADHD and autism symptoms was found with only 10.06% of possible connections (edges) between one ADHD and one autism symptoms different than zero. Associations between ADHD and autism symptoms were significantly weaker than those between two symptoms pertaining to the same construct. Select ADHD symptoms, particularly those presenting in social contexts (e.g. 'talks excessively', 'does not wait turn'), showed moderate-to-strong associations with autism symptoms, but some were considered redundant to autism symptoms. CONCLUSIONS: The present findings indicate that individual ADHD and autism symptoms are largely segregated in accordance with diagnostic boundaries corresponding to these conditions in children and adolescents from the community. These findings could improve our clinical conceptualization of ADHD and autism and guide advancements in diagnosis and treatment.

Putative contributions of the sex chromosome proteins SOX3 and SRY to neurodevelopmental disorders.

The male-biased prevalence of certain neurodevelopmental disorders and the sex-biased outcomes associated with stress exposure during gestation have been previously described. Here, we hypothesized that genes distinctively targeted by only one or both homologous proteins highly conserved across therian mammals, SOX3 and SRY, could induce sexual adaptive changes that result in a differential risk for neurodevelopmental disorders. ChIP-seq/chip data showed that SOX3/SRY gene targets were expressed in different brain cell types in mice. We used orthologous human genes in rodent genomes to extend the number of SOX3/SRY set (1,721). These genes were later found to be enriched in five modules of coexpressed genes during the early and mid-gestation periods (FDR < 0.05), independent of sexual hormones. Genes with differential expression (24, p < 0.0001) and methylation (40, p < 0.047) between sexes were overrepresented in this set. Exclusive SOX3 or SRY target genes were more associated with the late gestational and postnatal periods. Using autism as a model sex-biased disorder, the SOX3/SRY set was enriched in autism gene databases (FDR ≤ 0.05), and there were more de novo variations from the male autism spectrum disorder (ASD) samples under the SRY peaks compared to the random peaks (p < 0.024). The comparison of coexpressed networks of SOX3/SRY target genes between male autism and control samples revealed low preservation in gene modules related to stress response (99 genes) and neurogenesis (78 genes). This study provides evidence that while SOX3 is a regulatory mechanism for both sexes, the male-exclusive SRY also plays a role in gene regulation, suggesting a potential mechanism for sex bias in ASD.

Sex differences in gene regulatory networks during mid-gestational brain development.

Neurodevelopmental disorders differ considerably between males and females, and fetal brain development is one of the most critical periods to determine risk for these disorders. Transcriptomic studies comparing male and female fetal brain have demonstrated that the highest difference in gene expression occurs in sex chromosomes, but several autossomal genes also demonstrate a slight difference that has not been yet explored. In order to investigate biological pathways underlying fetal brain sex differences, we applied medicine network principles using integrative methods such as co-expression networks (CEMiTool) and regulatory networks (netZoo). The pattern of gene expression from genes in the same pathway tend to reflect biologically relevant phenomena. In this study, network analysis of fetal brain expression reveals regulatory differences between males and females. Integrating two different bioinformatics tools, our results suggest that biological processes such as cell cycle, cell differentiation, energy metabolism and extracellular matrix organization are consistently sex-biased. MSET analysis demonstrates that these differences are relevant to neurodevelopmental disorders, including autism.