One hallmark of several autism spectrum disorders (ASDs) is altered protein synthesis in the brain, which results in synaptic dysfunction and disease pathology. Genetic variations in PTEN, TSC1, TSC2, FMR1, SHANK3 and NLGN3, and microdeletions at 16p11.2 have all been linked to ASDs, and mouse models of these mutations exhibit alterations in a form of synaptic plasticity called metabotropic glutamate receptor-induced long-term depression (mGluR-LTD). Many studies support a role for mGluR-LTD in learning, with alterations in mGluR-LTD linked to a variety of neurological disease states, including ASDs. These studies have also demonstrated that the proper functioning of mGluR-LTD relies on rapid synthesis of proteins, leading to the suggestion that aberrations in mRNA translation may contribute to disease pathology. However, it remains unclear what particular mRNAs are involved in this process.

Technological advances in whole-genome sequencing (WGS) to study complex genetic disorders have outpaced innovations in the analysis of large genetic datasets. An ever-increasing amount of genetic data is being acquired, at a higher resolution, from patient populations numbering in the thousands. While this has led to the identification of many genes and genetic variants associated with increased risk for disorders, such as autism spectrum disorder (ASD), novel biological insight from these datasets has lagged behind.

Genetics plays a central role in autism spectrum disorder (ASD), yet much remains unknown about how DNA sequence variation predisposes individuals to ASD. Rare mutations have emerged as critical in ASD, and there is great hope that whole-genome sequencing will reveal many more causal mutations and lead to a better understanding of genetics and pathogenesis in ASD. This presumes that we will be able to identify which DNA mutations predispose individuals to ASD against the background of the millions of benign or unrelated DNA mutations present in every human genome. For mutations that disrupt proteins, such causal relationships have been successfully demonstrated, leading to significant new insights into the etiology of ASD. However, the majority of the human genome does not code for proteins, and predicting which mutations are pathogenic in noncoding regions is much more challenging. Enhancers — regulatory DNA sequences within our genomes that control when genes are activated — have emerged as critically important to human health and development. It is likely that noncoding mutations that disrupt enhancers also contribute to the pathogenesis of ASD.

Amniotic fluid (AF) and cerebrospinal fluid (CSF) are routinely sampled for biomarkers of diseases, including autism spectrum disorder (ASD). The cerebral cortex, which governs higher cognitive functions, initially develops from neural stem cells that interface with CSF-filled ventricles. Surprisingly little is known about how fluid-borne signals are distributed across the developing brain, or about the mechanisms by which changes in fluid composition actively instruct brain development.

Autism spectrum disorders (ASD) are frequently associated with immune dysregulation. Peripheral immune responses and microglial function have been the major focus in the field. However, recent studies have suggested that neurons are also able to use their own innate immune receptors, including toll-like receptors (TLRs), to detect the danger signals derived from both endogenous cells and pathogens.

Chromosomal copy number variations (CNVs) are common genetic abnormalities in autism spectrum disorder (ASD) and have been identified in approximately 10 percent of individuals with ASD. Currently, there is a knowledge gap in the understanding of the molecular and synaptic mechanisms underlying CNV-associated ASD.

Williams syndrome (WS) is a neurodevelopmental disorder caused by deletions in the 7q11.23 chromosomal region. Individuals with WS show developmental delays, learning disabilities and excessively social behavior. Interestingly, individuals with duplications of this same chromosomal region display a symmetrically opposite phenotype with regard to social behavior. This genomic segment therefore offers a unique opportunity to understand the molecular underpinnings of social behaviors.