Autism Spectrum Disorder: From Genes to Circuits to Behavior

Abstracts

Updating and Defining the Genetic Landscape
Stephan Sanders, MD, Yale University School of Medicine

Autism is a severe disorder that affects 1 in 88 children in the USA. Since autism is highly heritable identifying the specific genes responsible offers a promising route to understanding the etiology and, ultimately, developing effective treatments. Progress in identifying the genes responsible has been slow, however recent advances in technology have allowed scientists to examine the genome in unprecedented detail. Three types of genetic variation have been convincingly associated with autism: De novo (new variations in DNA seen in a child, but not seen in either parent) copy number variants (large regions of DNA that are deleted or duplicated); de novo loss of function mutations (small changes in DNA that stop one copy of a gene working); and inherited homozygous loss of function variants (i.e. gene knockouts). In this talk Dr. Sanders will review the evidence linking these variants with autism, the specific genes involved and the implications for understanding the cause of autism.
 

Defining the Behavioral Repertoire in Mice with ASD Construct Validity
Laurence Tecott, MD, PhD, University of California, San Francisco

The introduction of genes conferring susceptibility to autism spectrum disorders (ASD) into mice provides valuable opportunities for determining how genes implicated in ASD impact brain function and behavior. The utility of these models depends to a substantial extent on the quality of rodent behavioral assessment methods, and most are subject to limitations relating to circadian factors, animal handling, interpretation, and throughput. To enhance the extent to which the behavioral impact of genetic factors may be determined, we have developed a novel bioinformatics-based approach that probes high-resolution behavioral datasets to reveal patterns that comprise mouse "lifestyles." We are now applying this approach to examine the impact of genes associated with ASD on the behavioral repertoire of the mouse. The presentation will address the foundations of this technology, its application to an ASD-relevant mouse model, and strategies for developing hardware and software to further enhance its utility for quantitative assessment of ASD-related behaviors.
 

A New Angle on Angelman Syndrome Therapeutics
Ben Philpot, PhD, University of North Carolina, Chapel Hill

Angelman syndrome (AS) is a debilitating autism spectrum disorder for which no effective treatment or cure currently exists. AS is caused by maternal deletions or mutations of a single gene, the E3 ubiquitin ligase UBE3A. The UBE3A gene is expressed monoallelically in neurons due to epigenetic silencing of the paternal allele, so losing function of the maternal allele eliminates UBE3A protein. Motivated by this biology, we hypothesized that neural and behavioral dysfunctions associated with AS could be treated by unsilencing the intact paternal UBE3A. Towards this goal, we developed the first-ever screen to identify small molecule compounds that can unsilence an imprinted gene. This seminar will discuss the assay development, drug screen, target identification, and pre-clinical testing of potential AS therapeutics that arose through our novel drug discovery approach.
 

Update on MEG Imaging and Potential Biomarkers for ASD
Tim Roberts, PhD, The Children's Hospital of Philadelphia

Background: Brain level traits, or endophenotypes, of ASD may serve as diagnostic or prognostic biomarkers. MEG provides a neurally-sensitive imaging modality combining spatial and high temporal resolution. Perhaps more importantly, such brain measures may identify neural systems that lend themselves (1) to patient stratification and thus improve group homogeneity (stratification biomarkers), (2) to measuring therapeutic response, and (3) in translation to the preclinical environment where behavioral analogy is an important, but limited tool.
 
Objective: To draw together MEG imaging results from multiple imaging modalities in a large cohort of children with ASD and both typically developing and clinical controls.
 
Methods: Approximately 200 children (6–15yrs) with ASD and age/IQ-matched typically developing (TD) subjects were administered tests of auditory processing while whole-head MEG data were collected. Diagnosis was confirmed via ADOS and ADI-R and/or SCQ. Language impairment was quantified using the Core Language Index (CLI) of the CELF-4. An additional cohort of children with specific language impairment (SLI; language impairment in the absence of ASD) were also recruited. Whole-head biomagnetometer data (Omega, 275-channel, VSMMedTech Inc.) were obtained during presentation of isolated sinusoidal tones (500 and 1000 Hz) as well as oddball mismatch tone and vowel paradigms. Dependent variables were left and right auditory cortex latencies for M50, M100 and the mismatch field (MMF). Evoked gamma-band power and phase synchrony were assessed by time-frequency transformation. MRI (Siemens 3T Verio™) was performed for anatomic registration and for estimation of regional white matter integrity using diffusion tensor imaging (DTI; 30 directions, b=1000s/mm²). In a subset of the subjects, levels of GABA and Glutamate in auditory cortex were obtained using the MEGAPRESS MRS sequence (TE=68ms).
 
Results: Examining pure tones, M50 and M100 latency were delayed in ASD versus TD. The latency prolongation in ASD persisted even after measures of language impairment (CLI of the CELF-4) and IQ (FSIQ or PRI) were added as covariates. Diminished gamma-band phase synchrony was observed in ASD. No latency prolongation was observed in the cohort of children with SLI. MMF latency was prolonged in ASD, especially in the subset of children with ASD with language impairment (i.e. CELF CLI < 85). MMF latency was similarly prolonged in children with SLI. DTI of the acoustic radiations was lower in ASD and exhibited a flatter developmental trajectory than observed in typical development. DTI of the left superior longitudinal fasciculus (SLF) was abnormal in ASD, specifically exhibiting elevated mean diffusivity (MD), especially in the subset of children with ASD with language impairment. Although mean diffusivity was also elevated in children with SLI, the most pronounced elevation was observed in the cohort with ASD and language impairment. A 2×2 ANOVA (with factors of ASD/noASD and LI/noLI) with PRI and age as covariates revealed significant main effects (p<0.05) of both ASD and LI. GABA levels in superior temporal gyrus (STG; including auditory cortex) were significantly lower (p<0.05) in ASD than TD.
 
Discussion: There is considerable emerging physiologic evidence for brain abnormalities in ASD. Some of these abnormalities appear to be proportional to clinical severity (in the domain of interest: language). Converging evidence from multiple modalities supports neurobiological interpretation of developmental anomalies that are both general to ASD and also specific to the language impairment aspect of the phenotype.
 

Fragile X Syndrome: Genes to Circuits to Clinical Trials
Paul Wang, MD, Seaside Therapeutics

In the 20 years since the genetic etiology of Fragile X syndrome (FXS) was first described, advances in molecular biology and neuroscience have led to the illumination of the pathophysiology of FXS. Genetic and pharmacologic rescue experiments in animal models of FXS have provided a rational foundation on which to develop potential therapies for patients with FXS. While the clinical translation of basic research advances will be enormously challenging, trials of mGluR5 and GABA-B agents are now underway in children and adults with FXS. Research also suggests that many cases of autism spectrum disorder (ASD) share aspects of their pathophysiology with FXS, motivating trials of the same agents in the broader ASD population.