Considerable interest has arisen concerning the relationship between hereditary connective tissue disorders such as the Ehlers-Danlos syndromes (EDS)/hypermobility spectrum disorders (HSD) and autism, both in terms of their comorbidity as well as co-occurrence within the same families. This paper reviews our current state of knowledge, as well as highlighting unanswered questions concerning this remarkable patient group, which we hope will attract further scientific interest in coming years. In particular, patients themselves are demanding more research into this growing area of interest, although science has been slow to answer that call. Here, we address the overlap between these two spectrum conditions, including neurobehavioral, psychiatric, and neurological commonalities, shared peripheral neuropathies and neuropathologies, and similar autonomic and immune dysregulation. Together, these data highlight the potential relatedness of these two conditions and suggest that EDS/HSD may represent a subtype of autism.

This review is aimed at exploring the usefulness of measuring event-related potential (ERP) in cognitive tests and discusses several applications of the ERP technique. Analysis of ERP components is one of the most informative dynamic methods of investigation and monitoring of information processing stages in the human brain. Amplitude and latency of ERP components at specified topographies reflect early sensory perception processes and higher level processing including attention, cortical inhibition, memory update, error monitoring, and other cognitive activities. ERPs provide a method of studying cognitive processes in typical subjects, as well as a sensitive instrument to assess differences in individuals with neuro- and psychopathologies. Despite significant advances in functional neuroimaging, the ERP measure still represents an important tool for brain research in psychiatry, as many psychiatric diseases correlate with certain altered patterns of ERPs. Such ERP alterations can serve as valid biological markers for functional diagnostic or for better understanding of the cognitive functions which are disturbed in psychiatric disorders. Application of ERPs in psychiatric treatment research is an approach aimed at validation of specific ERP measures as sensitive functional outcomes of experimental neuromodulation interventions such as rTMS and neurofeedback. Also discussed are additional aspects of ERP usefulness in psychiatry research and treatment.

Intellectual disability (ID), autism, and epilepsy share frequent yet variable comorbidities with one another. In order to better understand potential genetic divergence underlying this variable risk, we studied genes responsible for monogenic IDs, grouped according to their autism and epilepsy comorbidities. Utilizing 465 different forms of ID with known molecular origins, we accessed available genetic databases in conjunction with gene ontology (GO) to determine whether the genetics underlying ID diverge according to its comorbidities with autism and epilepsy and if genes highly penetrant for autism or epilepsy share distinctive features that set them apart from genes that confer comparatively variable or no apparent risk. The genetics of ID with autism are relatively enriched in terms associated with nervous system-specific processes and structural morphogenesis. In contrast, we find that ID with highly comorbid epilepsy (HCE) is modestly associated with lipid metabolic processes while ID without autism or epilepsy comorbidity (ID only) is enriched at the Golgi membrane. Highly comorbid autism (HCA) genes, on the other hand, are strongly enriched within the nucleus, are typically involved in regulation of gene expression, and, along with IDs with more variable autism, share strong ties with a core protein-protein interaction (PPI) network integral to basic patterning of the CNS. According to GO terminology, autism-related gene products are integral to neural development. While it is difficult to draw firm conclusions regarding IDs unassociated with autism, it is clear that the majority of HCA genes are tightly linked with general dysregulation of gene expression, suggesting that disturbances to the chronology of neural maturation and patterning may be key in conferring susceptibility to autism spectrum conditions.

Postmortem neuropathological studies of autism consistently reveal distinctive types of malformations, including cortical dysplasias, heterotopias, and various neuronomorphometric abnormalities. In keeping with these observations, we review here that 88% of high-risk genes for autism influence neural induction and early maturation of the neuroblast. In addition, 80% of these same genes influence later stages of differentiation, including neurite and synapse development, suggesting that these gene products exhibit long-lasting developmental effects on cell development as well as extensive functional redundancy in processes of neural proliferation, growth, and maturation. We also address the putative genetic overlap of autism with conditions like epilepsy and schizophrenia, with implications to shared and divergent etiologies. This review imports the necessity of a frameshift in our understanding of the neurodevelopmental basis of autism to include all stages of neuronal maturation, ranging from neural induction to synaptogenesis.

Background: Linking genotype to phenotype is a major aim of genetics research, yet the underlying biochemical mechanisms of many complex conditions continue to remain elusive. Recent research provides evidence that relevant gene-phenotype associations are discoverable in the study of intellectual disability (ID). Here we expand on that work, identifying distinctive gene interaction modules with unique enrichment patterns reflective of associated clinical features in ID. Methods: Two hundred twelve forms of monogenic ID were curated according to comorbidities with autism and epilepsy. These groups were further subdivided according to secondary clinical manifestations of complex vs. simple facial dysmorphia and neurodegenerative-like features due to their clinical prominence, modest symptom overlap, and probable etiological divergence. An aggregate gene interaction ID network for these phenotype subgroups was discovered via a public database of known gene interactions: protein-protein, genetic, and mRNA coexpression. Additional annotation resources (Gene Ontology, Human Phenotype Ontology, TRANSFAC/JASPAR, and KEGG/WikiPathways) were utilized to assess functional and phenotypic enrichment patterns within subgroups. Results: Phenotypic analysis revealed high rates of complex facial dysmorphia in ID with comorbid autism. In contrast, neurodegenerative-like features were overrepresented in ID with epilepsy. Network analysis subsequently showed that gene groups divided according to clinical features of interest resulted in distinctive interaction clusters, with unique functional enrichments according to gene set. Conclusions: These data suggest that specific comorbid and secondary clinical features in ID are predictive of underlying genotype. In summary, ID form unique clusters, which are comprised of individual conditions with remarkable genotypic and phenotypic overlap.