SUMMARY Balanced chromosomal abnormalities (BCAs) represent a reservoir of single gene disruptions in neurodevelopmental disorders (NDD). We sequenced BCAs in autism and related NDDs, revealing disruption of 33 loci in four general categories: 1) genes associated with abnormal neurodevelopment (e.g., AUTS2, FOXP1, CDKL5), 2) single gene contributors to microdeletion syndromes (MBD5, SATB2, EHMT1, SNURF-SNRPN), 3) novel risk loci (e.g., CHD8, KIRREL3, ZNF507), and 4) genes associated with later onset psychiatric disorders (e.g., TCF4, ZNF804A, PDE10A, GRIN2B, ANK3). We also discovered profoundly increased burden of copy number variants among 19,556 neurodevelopmental cases compared to 13,991 controls (p = 2.07×10−47) and enrichment of polygenic risk alleles from autism and schizophrenia genome-wide association studies (p = 0.0018 and 0.0009, respectively). Our findings suggest a polygenic risk model of autism incorporating loci of strong effect and indicate that some neurodevelopmental genes are sensitive to perturbation by multiple mutational mechanisms, leading to variable phenotypic outcomes that manifest at different life stages.

Truncating mutations of chromodomain helicase DNA-binding protein 8 (CHD8), and of many other genes with diverse functions, are strong-effect risk factors for autism spectrum disorder (ASD), suggesting multiple mechanisms of pathogenesis. We explored the transcriptional networks that CHD8 regulates in neural progenitor cells (NPCs) by reducing its expression and then integrating transcriptome sequencing (RNA sequencing) with genome-wide CHD8 binding (ChIP sequencing). Suppressing CHD8 to levels comparable with the loss of a single allele caused altered expression of 1,756 genes, 64.9% of which were up-regulated. CHD8 showed widespread binding to chromatin, with 7,324 replicated sites that marked 5,658 genes. Integration of these data suggests that a limited array of direct regulatory effects of CHD8 produced a much larger network of secondary expression changes. Genes indirectly down-regulated (i.e., without CHD8-binding sites) reflect pathways involved in brain development, including synapse formation, neuron differentiation, cell adhesion, and axon guidance, whereas CHD8-bound genes are strongly associated with chromatin modification and transcriptional regulation. Genes associated with ASD were strongly enriched among indirectly down-regulated loci (P < 10 −8) and CHD8-bound genes (P = 0.0043), which align with previously identified coexpression modules during fetal development. We also find an intriguing enrichment of cancer-related gene sets among CHD8-bound genes (P < 10 −10). In vivo suppression of chd8 in zebrafish produced macrocephaly comparable to that of humans with inactivating mutations. These data indicate that heterozygous disruption of CHD8 precipitates a network of gene-expression changes involved in neurodevelopmental pathways in which many ASD-associated genes may converge on shared mechanisms of pathogenesis.he genetic architecture of autism spectrum disorder (ASD) is complex and heterogeneous. A wave of recent discoveries has identified individual genes that contribute to ASD when they suffer heterozygous inactivation by coding mutation, copy number variation, or balanced chromosomal abnormalities (1-7). Many of these genes fit neatly into current biological models of ASD involving altered synaptic structure and glutamatergic neurotransmission, but others have been surprising, with a less ready biological interpretation, including genes involved in chromatin modification, DNA methylation, cell adhesion, and global transcriptional regulation. This diversity of genes predisposing to ASD suggests either that there are many pathways that independently can result in the autism phenotype or that functionally distinct ASD-risk genes can trigger consequences that converge on a limited number of shared pathways of ASD pathogenesis. Because now experimental tools are available to reduce gene expression specifically in human neural progenitor cells (NPCs), which can mimic the impact of functional hemizygosity, we have explored this question by investigating the functional genomic consequences of suppr...

Autism is an etiologically and clinically heterogeneous group of disorders, diagnosed solely by the complex behavioral phenotype. On the basis of the high-heritability index, geneticists are confident that autism will be the first behavioral disorder for which the genetic basis can be well established. Although it was initially assumed that major genome-wide and candidate gene association studies would lead most directly to common autism genes, progress has been slow. Rather, most discoveries have come from studies of known genetic disorders associated with the behavioral phenotype. New technology, especially array chromosomal genomic hybridization, has both increased the identification of putative autism genes and raised to approximately 25%, the percentage of children for whom an autism-related genetic change can be identified. Incorporating clinical geneticists into the diagnostic and autism research arenas is vital to the field. Interpreting this new technology and deciphering autism's genetic montage require the skill set of the clinical geneticist including knowing how to acquire and interpret family pedigrees, how to analyze complex morphologic, neurologic, and medical phenotypes, sorting out heterogeneity, developing rational genetic models, and designing studies. The current emphasis on deciphering autism spectrum disorders has accelerated the field of neuroscience and demonstrated the necessity of multidisciplinary research that must include clinical geneticists both in the clinics and in the design and implementation of basic, clinical, and translational research.

Context Clinical best estimate diagnoses of specific autism spectrum disorders (autistic disorder, pervasive developmental disorder-not otherwise specified, Asperger’s disorder) have been used as the diagnostic gold standard, even when information from standardized instruments is available. Objective To determine if the relationships between behavioral phenotypes and clinical diagnoses of different autism spectrum disorders vary across 12 university-based sites. Design Multi-site observational study collecting clinical phenotype data (diagnostic, developmental and demographic) for genetic research. Classification trees were employed to identify characteristics that predicted diagnosis across and within sites. Setting Participants were recruited through 12 university-based autism service providers into a genetic study of autism. Participants 2102 probands (1814 males) between 4 and 18 years of age (M age=8.93, SD=3.5 years) who met autism spectrum criteria on the Autism Diagnostic Interview–Revised and Autism Diagnostic Observation Schedule and had a clinical diagnosis of an autism spectrum disorder. Main Outcome Measures Best estimate clinical diagnoses predicted by standardized scores from diagnostic, cognitive, and behavioral measures. Results Though distributions of scores on standardized measures were similar across sites, significant site differences emerged in best estimate clinical diagnoses of specific autism spectrum disorders. Relationships between clinical diagnoses and standardized scores, particularly verbal IQ, language level and core diagnostic features, varied across sites in weighting of information and cut-offs. Conclusions Clinical distinctions among categorical diagnostic subtypes of autism spectrum disorders were not reliable even across sites with well-documented fidelity using standardized diagnostic instruments. Results support the move from existing sub-groupings of autism spectrum disorders to dimensional descriptions of core features of social affect and fixated, repetitive behaviors, together with characteristics such as language level and cognitive function.

Heterogeneity within the autism diagnosis obscures the genetic basis of the disorder and impedes our ability to develop effective treatments. We found that by using two readily available tests, autism can be divided into two subgroups, "essential autism" and "complex autism," with different outcomes and recurrence risks. Complex autism consists of individuals in whom there is evidence of some abnormality of early morphogenesis, manifested by either significant dysmorphology or microcephaly. The remainder have "essential autism." From 1995 to 2001, 260 individuals who met DSM-IV criteria for autistic disorder were examined. Five percent (13/260) were microcephalic and 16% (41/260) had significant physical anomalies. Individually, each trait predicted a poorer outcome. Together they define the "complex autism" subgroup, comprising 20% (46/233) of the total autism population. Individuals with complex autism have lower IQs (P=0.006), more seizures (P=0.0008), more abnormal EEGs (46% vs. 30%), more brain abnormalities by MRI (28% vs. 13%). Everyone with an identifiable syndrome was in the complex group. Essential autism defines the more heritable group with higher sib recurrence (4% vs. 0%), more relatives with autism (20% vs. 9%), and higher male to female ratio (6.5:1 vs. 3.2:1). Their outcome was better with higher IQs (P=0.02) and fewer seizures (P=0.0008). They were more apt to develop autism with a regressive onset (43% vs. 23%, P=0.02). Analysis of the features predictive of poor outcome (IQ<55, functionally non-verbal) showed that microcephaly was 100% specific but only 14% sensitive; the presence of physical anomalies was 86% specific and 34% sensitive. The two tests combined yielded 87% specificity, 47% sensitivity, and an odds ratio of 4.8:1 for poor outcome. Separating essential from complex autism should be the first diagnostic step for children with autism spectrum disorders as it allows better prognostication and counseling. Definition of more homogeneous populations should increase power of research analyses.

Computerized binocular infrared pupillography was used to measure the transient pupillary light reflex (PLR) in both children with autism spectrum disorders (ASDs) and children with typical development. We found that participants with ASDs showed significantly longer PLR latency, smaller constriction amplitude and lower constriction velocity than children with typical development. The PLR latency alone can be used to discriminate the ASD group from the control group with a cross-validated success rate of 89.6%. By adding the constriction amplitude, the percentage of correct classification can be further improved to 92.5%. In addition, the right-lateralization of contraction anisocoria that was observed in participants with typical development was not observed in those with ASDs. Further studies are necessary to understand the origin and implications of these observations. It is anticipated that as potential biomarkers, these pupillary light reflex measurements will advance our understanding of neurodevelopmental differences in the autism brain.

Taken together, the present findings indicate that ASD is associated with impairments in some, but not all, aspects of inhibitory control. Individuals with ASD appear to have difficulty ignoring distracting visual information, but prepotent response inhibition and resistance to proactive interference are relatively intact. The current findings also provide support for a multitype model of inhibitory control.

We investigated pupillary light reflex (PLR) in 152 children with ASD, 116 typically developing (TD) children, and 36 children with non-ASD neurodevelopmental disorders (NDDs). Heart rate variability (HRV) was measured simultaneously to study potential impairments in the autonomic nervous system (ANS) associated with ASD. The results showed that the ASD group had significantly longer PLR latency, reduced relative constriction amplitude, and shorter constriction/redilation time than those of the TD group. Similar atypical PLR parameters were observed in the NDD group. A significant age effect on PLR latency was observed in children younger than 9 years in the TD group, but not in the ASD and NDD groups. Atypical HRV parameters were observed in the ASD and NDD groups. A significant negative correlation existed between the PLR constriction amplitude and average heart rate in children with an ASD, but not in children with typical development.