The Autism Simplex Collection: an international, expertly phenotyped autism sample for genetic and phenotypic analyses

ANKS1B encoded AIDA-1 regulates social behaviors by controlling oligodendrocyte function

Heterozygous deletions in the ANKS1B gene cause ANKS1B neurodevelopmental syndrome (ANDS), a rare genetic disease characterized by autism spectrum disorder (ASD), attention deficit/hyperactivity disorder, and speech and motor deficits. The ANKS1B gene encodes for AIDA-1, a protein that is enriched at neuronal synapses and regulates synaptic plasticity. Here we report an unexpected role for oligodendroglial deficits in ANDS pathophysiology. We show that Anks1b-deficient mouse models display deficits in oligodendrocyte maturation, myelination, and Rac1 function, and recapitulate white matter abnormalities observed in ANDS patients. Selective loss of Anks1b from the oligodendrocyte lineage, but not from neuronal populations, leads to deficits in social preference and sensory reactivity previously observed in a brain-wide Anks1b haploinsufficiency model. Furthermore, we find that clemastine, an antihistamine shown to increase oligodendrocyte precursor cell maturation and central nervous system myelination, rescues deficits in social preference in 7-month-old Anks1b-deficient mice. Our work shows that deficits in social behaviors present in ANDS may originate from abnormal Rac1 activity within oligodendrocytes.

Comparing synaptic proteomes across five mouse models for autism reveals converging molecular similarities including deficits in oxidative phosphorylation and Rho GTPase signaling

Specific and effective treatments for autism spectrum disorder (ASD) are lacking due to a poor understanding of disease mechanisms. Here we test the idea that similarities between diverse ASD mouse models are caused by deficits in common molecular pathways at neuronal synapses. To do this, we leverage the availability of multiple genetic models of ASD that exhibit shared synaptic and behavioral deficits and use quantitative mass spectrometry with isobaric tandem mass tagging (TMT) to compare their hippocampal synaptic proteomes. Comparative analyses of mouse models for Fragile X syndrome (Fmr1 knockout), cortical dysplasia focal epilepsy syndrome (Cntnap2 knockout), PTEN hamartoma tumor syndrome (Pten haploinsufficiency), ANKS1B syndrome (Anks1b haploinsufficiency), and idiopathic autism (BTBR+) revealed several common altered cellular and molecular pathways at the synapse, including changes in oxidative phosphorylation, and Rho family small GTPase signaling. Functional validation of one of these aberrant pathways, Rac1 signaling, confirms that the ANKS1B model displays altered Rac1 activity counter to that observed in other models, as predicted by the bioinformatic analyses. Overall similarity analyses reveal clusters of synaptic profiles, which may form the basis for molecular subtypes that explain genetic heterogeneity in ASD despite a common clinical diagnosis. Our results suggest that ASD-linked susceptibility genes ultimately converge on common signaling pathways regulating synaptic function and propose that these points of convergence are key to understanding the pathogenesis of this disorder.

Estimating the Prevalence of De Novo Monogenic Neurodevelopmental Disorders from Large Cohort Studies

Rare diseases impact up to 400 million individuals globally. Of the thousands of known rare diseases, many are rare neurodevelopmental disorders (RNDDs) impacting children. RNDDs have proven to be difficult to assess epidemiologically for several reasons. The rarity of them makes it difficult to observe them in the population, there is clinical overlap among many disorders, making it difficult to assess the prevalence without genetic testing, and data have yet to be available to have accurate counts of cases. Here, we utilized large sequencing cohorts of individuals with rare, de novo monogenic disorders to estimate the prevalence of variation in over 11,000 genes among cohorts with developmental delay, autism spectrum disorder, and/or epilepsy. We found that the prevalence of many RNDDs is positively correlated to the previously estimated incidence. We identified the most often mutated genes among neurodevelopmental disorders broadly, as well as developmental delay and autism spectrum disorder independently. Finally, we assessed if social media group member numbers may be a valuable way to estimate prevalence. These data are critical for individuals and families impacted by these RNDDs, clinicians and geneticists in their understanding of how common diseases are, and for researchers to potentially prioritize research into particular genes or gene sets.

Brief Report: The Broad Autism Phenotype in Swedish Parents of Children With and Without Autism Spectrum Conditions

The broad autism phenotype (BAP) is a set of characteristics often observed in typically developing people with a genetic load for autism, such as parents of autistic children. The Broad Autism Phenotypic Questionnaire (BAPQ) is a 36-item questionnaire developed to identify the BAP in first-degree relatives of autistic people. We translated the BAPQ into Swedish and examined its psychometric properties in a Swedish sample consisting of 45 parents of children with ASC and 74 parents of non-autistic children. We found support for the original 3-factor structure (aloof, pragmatic language and rigid), good internal consistency and convergent validity with the Autism Quotient. Thus, the Swedish BAPQ exhibits acceptable psychometric properties and may be useful for assessing the BAP in non-clinical populations.

Developmental Variability in Autism Across 17 000 Autistic Individuals and 4000 Siblings Without an Autism Diagnosis: Comparisons by Cohort, Intellectual Disability, Genetic Etiology, and Age at Diagnosis

Importance

Presence of developmental delays in autism is well established, yet few studies have characterized variability in developmental milestone attainment in this population.

Objective

To characterize variability in the age at which autistic individuals attain key developmental milestones based on co-occurring intellectual disability (ID), presence of a rare disruptive genetic variant associated with neurodevelopmental disorders (NDD), age at autism diagnosis, and research cohort membership.

Design

The study team harmonized data from 4 cross-sectional autism cohorts: the Autism Genetics Research Exchange (n = 3284; 1997-2015), The Autism Simplex Collection (n = 694; 2008-2011), the Simons Simplex Collection (n = 2753; 2008-2011), and the Simons Foundation Powering Autism Research for Knowledge (n = 10 367; 2016-present). The last sample further included 4145 siblings without an autism diagnosis or ID.

Participants

Convenience sample of 21 243 autistic individuals or their siblings without an autism diagnosis aged 4 to 17 years.

Main Outcomes and Measures

Parents reported ages at which participants attained key milestones including smiling, sitting upright, crawling, walking, spoon-feeding self, speaking words, speaking phrases, and acquiring bladder and bowel control. A total of 5295 autistic individuals, and their biological parents, were genetically characterized to identify de novo variants in NDD-associated genes. The study team conducted time-to-event analyses to estimate and compare percentiles in time with milestone attainment across autistic individuals, subgroups of autistic individuals, and the sibling sample.

Results

Seventeen thousand ninety-eight autistic individuals (mean age, 9.15 years; 80.8% male) compared with 4145 siblings without autism or ID (mean age, 10.2 years; 50.2% female) showed delays in milestone attainment, with median (IQR) delays ranging from 0.7 (0.3-1.6) to 19.7 (11.4-32.2) months. More severe and more variable delays in autism were associated with the presence of co-occurring ID, carrying an NDD-associated rare genetic variant, and being diagnosed with autism by age 5 years. More severe and more variable delays were also associated with membership in earlier study cohorts, consistent with autism's diagnostic and ascertainment expansion over the last 30 years.

Conclusions and Relevance

As the largest summary to date of developmental milestone attainment in autism, to our knowledge, this study demonstrates substantial developmental variability across different conditions and provides important context for understanding the phenotypic and etiological heterogeneity of autism.

Recent ultra-rare inherited variants implicate new autism candidate risk genes

Autism is a highly heritable complex disorder in which de novo mutation (DNM) variation contributes significantly to risk. Using whole-genome sequencing data from 3,474 families, we investigate another source of large-effect risk variation, ultra-rare variants. We report and replicate a transmission disequilibrium of private, likely gene-disruptive (LGD) variants in probands but find that 95% of this burden resides outside of known DNM-enriched genes. This variant class more strongly affects multiplex family probands and supports a multi-hit model for autism. Candidate genes with private LGD variants preferentially transmitted to probands converge on the E3 ubiquitin-protein ligase complex, intracellular transport and Erb signaling protein networks. We estimate that these variants are approximately 2.5 generations old and significantly younger than other variants of similar type and frequency in siblings. Overall, private LGD variants are under strong purifying selection and appear to act on a distinct set of genes not yet associated with autism.

Association Between DCC Polymorphisms and Susceptibility to Autism Spectrum Disorder

Autism spectrum disorder (ASD) represents a group of childhood-onset lifelong neuro-developmental disorders. However, the association between single nucleotide polymorphisms (SNPs) in the deleted in colorectal carcinoma (DCC) gene and ASD susceptibility remains unclear. We investigated the association between ASD susceptibility and seven SNPs in DCC on the basis of a case-control study (231 ASD cases and 242 controls) in Chinese Han. We found that there was no association between ASD susceptibility and the seven SNPs in DCC; however, T-A haplotype (rs2229082-rs2270954), T-A-T-C haplotype (rs2229082-rs2270954-rs2292043-rs2292044), C-G-T-C-T haplotype (rs934345-rs17753970-rs2229082-rs2270954-rs2292043), C-G-T-C-T-G haplotype (rs934345-rs17753970-rs2229082-rs2270954-rs2292043-rs2292044), and G-G-T-C-C-C-C haplotype (rs934345-rs17753970-rs2229082-rs2270954-rs2292043-rs2292044-rs16956878) were associated with ASD susceptibility. Our results indicate that the haplotypes formed on the basis of the seven SNPs in DCC may be implicated in ASD.

Big data approaches to develop a comprehensive and accurate tool aimed at improving autism spectrum disorder diagnosis and subtype stratification

Purpose

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder that is difficult to diagnose accurately due to its heterogeneous clinical manifestations. Comprehensive models combining different big data approaches (e.g. neuroimaging, genetics, eye tracking, etc.) may offer the opportunity to characterize ASD from multiple distinct perspectives. This paper aims to provide an overview of a novel diagnostic approach for ASD classification and stratification based on these big data approaches.

Design/methodology/approach

Multiple types of data were collected and recorded for three consecutive years, including clinical assessment, neuroimaging, gene mutation and expression and response signal data. The authors propose to establish a classification model for predicting ASD clinical diagnostic status by integrating the various data types. Furthermore, the authors suggest a data-driven approach to stratify ASD into subtypes based on genetic and genomic data.

Findings

By utilizing complementary information from different types of ASD patient data, the proposed integration model has the potential to achieve better prediction performance than models focusing on only one data type. The use of unsupervised clustering for the gene-based data-driven stratification will enable identification of more homogeneous subtypes. The authors anticipate that such stratification will facilitate a more consistent and personalized ASD diagnostic tool.

Originality/value

This study aims to utilize a more comprehensive investigation of ASD-related data types than prior investigations, including proposing longitudinal data collection and a storage scheme covering diverse populations. Furthermore, this study offers two novel diagnostic models that focus on case-control status prediction and ASD subtype stratification, which have been under-explored in the prior literature.

Dysregulation of Circadian Rhythms in Autism Spectrum Disorders

Background:

The alterations in neurological and neuroendocrine functions observed in the autism spectrum disorder (ASD) involves environmentally dependent dysregulation of neurodevelopment, in interaction with multiple coding gene defects. Disturbed sleep-wake patterns, as well as abnormal melatonin and glucocorticoid secretion, show the relevance of an underlying impairment of the circadian timing system to the behavioral phenotype of ASD. Thus, understanding the mechanisms involved in the circadian dysregulation in ASD could help to identify early biomarkers to improve the diagnosis and therapeutics as well as providing a significant impact on the lifelong prognosis.

Objective:

In this review, we discuss the organization of the circadian timing system and explore the connection between neuroanatomic, molecular, and neuroendocrine responses of ASD and its clinical manifestations. Here we propose interconnections between circadian dysregulation, inflammatory baseline and behavioral changes in ASD. Taking into account, the high relevancy of melatonin in orchestrating both circadian timing and the maintenance of physiological immune quiescence, we raise the hypothesis that melatonin or analogs should be considered as a pharmacological approach to suppress inflammation and circadian misalignment in ASD patients.

Strategy:

This review provides a comprehensive update on the state-of-art of studies related to inflammatory states and ASD with a special focus on the relationship with melatonin and clock genes. The hypothesis raised above was analyzed according to the published data.

Conclusion:

Current evidence supports the existence of associations between ASD to circadian dysregulation, behavior problems, increased inflammatory levels of cytokines, sleep disorders, as well as reduced circadian neuroendocrine responses. Indeed, major effects may be related to a low melatonin rhythm. We propose that maintaining the proper rhythm of the circadian timing system may be helpful to improve the health and to cope with several behavioral changes observed in ASD subjects.

Bio-collections in autism research

Autism spectrum disorder (ASD) is a group of complex neurodevelopmental disorders with diverse clinical manifestations and symptoms. In the last 10 years, there have been significant advances in understanding the genetic basis for ASD, critically supported through the establishment of ASD bio-collections and application in research. Here, we summarise a selection of major ASD bio-collections and their associated findings. Collectively, these include mapping ASD candidate genes, assessing the nature and frequency of gene mutations and their association with ASD clinical subgroups, insights into related molecular pathways such as the synapses, chromatin remodelling, transcription and ASD-related brain regions. We also briefly review emerging studies on the use of induced pluripotent stem cells (iPSCs) to potentially model ASD in culture. These provide deeper insight into ASD progression during development and could generate human cell models for drug screening. Finally, we provide perspectives concerning the utilities of ASD bio-collections and limitations, and highlight considerations in setting up a new bio-collection for ASD research.

The impact of genetics on future drug discovery in schizophrenia

INTRODUCTION

Failures of investigational new drugs (INDs) for schizophrenia have left huge unmet medical needs for patients. Given the recent lackluster results, it is imperative that new drug discovery approaches (and resultant drug candidates) target pathophysiological alterations that are shared in specific, stratified patient populations that are selected based on pre-identified biological signatures. One path to implementing this paradigm is achievable by leveraging recent advances in genetic information and technologies. Genome-wide exome sequencing and meta-analysis of single nucleotide polymorphism (SNP)-based association studies have already revealed rare deleterious variants and SNPs in patient populations. Areas covered: Herein, the authors review the impact that genetics have on the future of schizophrenia drug discovery. The high polygenicity of schizophrenia strongly indicates that this disease is biologically heterogeneous so the identification of unique subgroups (by patient stratification) is becoming increasingly necessary for future investigational new drugs. Expert opinion: The authors propose a pathophysiology-based stratification of genetically-defined subgroups that share deficits in particular biological pathways. Existing tools, including lower-cost genomic sequencing and advanced gene-editing technology render this strategy ever more feasible. Genetically complex psychiatric disorders such as schizophrenia may also benefit from synergistic research with simpler monogenic disorders that share perturbations in similar biological pathways.

De novo unbalanced translocation (4p duplication/8p deletion) in a patient with autism, OCD, and overgrowth syndrome

Chromosomal abnormalities, such as unbalanced translocations and copy number variants (CNVs), are found in autism spectrum disorders (ASDs) [Sanders et al. (2011) Neuron 70: 863-885]. Many chromosomal abnormalities, including sub microscopic genomic deletions and duplications, are missed by G-banded karyotyping or Fragile X screening alone and are picked up by chromosomal microarrays [Shen et al. (2010) Pediatrics 125: e727-735]. Translocations involving chromosomes 4 and 8 are possibly the second most frequent translocation in humans and are often undetected in routine cytogenetics [Giglio et al. (2002) Circulation 102: 432-437]. Deletions of 4p16 have been associated with Wolf-Hirschhorn syndrome while 4p16 duplications have been associated with an overgrowth syndrome and mild to moderate mental retardation [Partington et al. (1997) Journal of Medical Genetics 34: 719-728]. The 8p23.3 region contains the autism candidate gene DLGAP2, which can contribute to autism when disrupted [Marshall et al. (2008) The American Journal of Human Genetics 82: 477-488] . There has been a case report of a family with autism spectrum disorder (ASD), prominent obsessional behavior, and overgrowth in patients with der (8) t (4;8) p (16;23) [Partington et al. (1997)]. This is an independent report of a male patient with autism, obsessive compulsive disorder (OCD), attention-deficit hyperactivity disorder (ADHD), and an overgrowth syndrome, whose de novo unbalanced translocation der (8) t (4;8) p (16.1→ter; 23.1→ter) was initially missed by routine cytogenetics but detected with SNP microarray, allowing higher resolution of translocation breakpoints.

Targeted sequencing identifies 91 neurodevelopmental-disorder risk genes with autism and developmental-disability biases

Gene-disruptive mutations contribute to the biology of neurodevelopmental disorders (NDDs), but most of the related pathogenic genes are not known. We sequenced 208 candidate genes from >11,730 cases and >2,867 controls. We identified 91 genes, including 38 new NDD genes, with an excess of de novo mutations or private disruptive mutations in 5.7% of cases. Drosophila functional assays revealed a subset with increased involvement in NDDs. We identified 25 genes showing a bias for autism versus intellectual disability and highlighted a network associated with high-functioning autism (full-scale IQ >100). Clinical follow-up for NAA15, KMT5B, and ASH1L highlighted new syndromic and nonsyndromic forms of disease.

The evolution and population diversity of human-specific segmental duplications

Segmental duplications contribute to human evolution, adaptation and genomic instability but are often poorly characterized. We investigate the evolution, genetic variation and coding potential of human-specific segmental duplications (HSDs). We identify 218 HSDs based on analysis of 322 deeply sequenced archaic and contemporary hominid genomes. We sequence 550 human and nonhuman primate genomic clones to reconstruct the evolution of the largest, most complex regions with protein-coding potential (n=80 genes/33 gene families). We show that HSDs are non-randomly organized, associate preferentially with ancestral ape duplications termed “core duplicons”, and evolved primarily in an interspersed inverted orientation. In addition to Homo sapiens-specific gene expansions (e.g., TCAF1/2), we highlight ten gene families (e.g., ARHGAP11B and SRGAP2C) where copy number never returns to the ancestral state, there is evidence of mRNA splicing, and no common gene-disruptive mutations are observed in the general population. Such duplicates are candidates for the evolution of human-specific adaptive traits.

A Subset of Autism-Associated Genes Regulate the Structural Stability of Neurons

Autism spectrum disorder (ASD) comprises a range of neurological conditions that affect individuals’ ability to communicate and interact with others. People with ASD often exhibit marked qualitative difficulties in social interaction, communication, and behavior. Alterations in neurite arborization and dendritic spine morphology, including size, shape, and number, are hallmarks of almost all neurological conditions, including ASD. As experimental evidence emerges in recent years, it becomes clear that although there is broad heterogeneity of identified autism risk genes, many of them converge into similar cellular pathways, including those regulating neurite outgrowth, synapse formation and spine stability, and synaptic plasticity. These mechanisms together regulate the structural stability of neurons and are vulnerable targets in ASD. In this review, we discuss the current understanding of those autism risk genes that affect the structural connectivity of neurons. We sub-categorize them into (1) cytoskeletal regulators, e.g., motors and small RhoGTPase regulators; (2) adhesion molecules, e.g., cadherins, NCAM, and neurexin superfamily; (3) cell surface receptors, e.g., glutamatergic receptors and receptor tyrosine kinases; (4) signaling molecules, e.g., protein kinases and phosphatases; and (5) synaptic proteins, e.g., vesicle and scaffolding proteins. Although the roles of some of these genes in maintaining neuronal structural stability are well studied, how mutations contribute to the autism phenotype is still largely unknown. Investigating whether and how the neuronal structure and function are affected when these genes are mutated will provide insights toward developing effective interventions aimed at improving the lives of people with autism and their families.

Phenotyping, Etiological Factors, and Biomarkers: Toward Precision Medicine in Autism Spectrum Disorders

Despite the progress made in understanding the biology of autism spectrum disorder (ASD), effective biological interventions for the core symptoms remain elusive. Because of the etiological heterogeneity of ASD, identification of a "one-size-fits-all" treatment approach will likely continue to be challenging. A meeting was convened at the University of Missouri and the Thompson Center to discuss strategies for stratifying patients with ASD for the purpose of moving toward precision medicine. The "white paper" presented here articulates the challenges involved and provides suggestions for future solutions.

A randomized placebo-controlled pilot study of N-acetylcysteine in youth with autism spectrum disorder

BACKGROUND

Social impairment is a defining feature of autism spectrum disorder (ASD) with no demonstrated effective pharmacologic treatments. The goal of this study was to evaluate efficacy, safety, and tolerability of oral N-acetylcysteine (NAC), an antioxidant whose function overlaps with proposed mechanisms of ASD pathophysiology, targeting core social impairment in youth with ASD.

METHODS

This study was a 12-week randomized, double-blind, placebo-controlled trial of oral NAC in youth with ASD. Study participants were medically healthy youth age 4 to 12 years with ASD, weighing ≥15 kg, and judged to be moderately ill based on the Clinical Global Impressions Severity scale. The participants were randomized via computer to active drug or placebo in a 1:1 ratio, with the target dose of NAC being 60 mg/kg/day in three divided doses. The primary outcome measure of efficacy was the Clinical Global Impressions Improvement (CGI-I) scale anchored to core social impairment. To investigate the impact of NAC on oxidative stress markers in peripheral blood, venous blood samples were collected at screen and week 12.

RESULTS

Thirty-one patients were enrolled (NAC = 16, placebo = 15). Three participants were lost to follow-up, and three left the trial due to adverse effects. The average daily dose of NAC at week 12 was 56.2 mg/kg (SD = 9.7) with dose ranging from 33.6 to 64.3 mg/kg. The frequency of adverse events was so low that comparisons between groups could not be conducted. At week 12, there was no statistically significant difference between the NAC and placebo groups on the CGI-I (p > 0.69) but the glutathione (GSH) level in blood was significantly higher in the NAC group (p < 0.05). The oxidative glutathione disulfide (GSSG) level increased in the NAC group, however only at a trend level of significance (p = 0.09). There was no significant difference between the NAC and placebo groups in the GSH/GSSG ratio, DNA strand break and oxidative damage, and blood homocysteine levels at week 12 (ps > 0.16).

CONCLUSIONS

The results of this trial indicate that NAC treatment was well tolerated, had the expected effect of boosting GSH production, but had no significant impact on social impairment in youth with ASD.

TRIAL REGISTRATION

Clinicaltrials.gov NCT00453180.

Disruption of POGZ Is Associated with Intellectual Disability and Autism Spectrum Disorders

Intellectual disability (ID) and autism spectrum disorders (ASD) are genetically heterogeneous, and a significant number of genes have been associated with both conditions. A few mutations in POGZ have been reported in recent exome studies; however, these studies do not provide detailed clinical information. We collected the clinical and molecular data of 25 individuals with disruptive mutations in POGZ by diagnostic whole-exome, whole-genome, or targeted sequencing of 5,223 individuals with neurodevelopmental disorders (ID primarily) or by targeted resequencing of this locus in 12,041 individuals with ASD and/or ID. The rarity of disruptive mutations among unaffected individuals (2/49,401) highlights the significance (p = 4.19 × 10(-13); odds ratio = 35.8) and penetrance (65.9%) of this genetic subtype with respect to ASD and ID. By studying the entire cohort, we defined common phenotypic features of POGZ individuals, including variable levels of developmental delay (DD) and more severe speech and language delay in comparison to the severity of motor delay and coordination issues. We also identified significant associations with vision problems, microcephaly, hyperactivity, a tendency to obesity, and feeding difficulties. Some features might be explained by the high expression of POGZ, particularly in the cerebellum and pituitary, early in fetal brain development. We conducted parallel studies in Drosophila by inducing conditional knockdown of the POGZ ortholog row, further confirming that dosage of POGZ, specifically in neurons, is essential for normal learning in a habituation paradigm. Combined, the data underscore the pathogenicity of loss-of-function mutations in POGZ and define a POGZ-related phenotype enriched in specific features.

Translating Research to Practice for Children With Autism Spectrum Disorder: Part I: Definition, Associated Behaviors, Prevalence, Diagnostic Process, and Interventions

INTRODUCTION

The number of children with autism spectrum disorder (ASD) is rising, along with the potential for challenging behaviors during health care encounters.

METHOD

We present an overview of the emerging science related to ASD diagnosis and interventions for children with ASD.

RESULTS

Emerging science on ASD reveals common associated challenging behaviors, increasing prevalence, emphasis on early diagnosis at 18 to 24 months of age, changes in the diagnostic process with criteria from the Diagnostic and Statistical Manual of Mental Disorders, 5th edition, and interventions with medication, education, and behavior management.

DISCUSSION

Family and health care provider preparation strategies facilitate care of children with ASD and their families. Early diagnosis at 18 to 24 months of age and evidence-based interventions contribute to best outcomes for children and families. Health care providers must be aware of the state of the science for diagnosis and best practices to provide family-centered care for this growing population.

Recurrent de novo mutations implicate novel genes underlying simplex autism risk

Autism spectrum disorder (ASD) has a strong but complex genetic component. Here we report on the resequencing of 64 candidate neurodevelopmental disorder risk genes in 5,979 individuals: 3,486 probands and 2,493 unaffected siblings. We find a strong burden of de novo point mutations for these genes and specifically implicate nine genes. These include CHD2 and SYNGAP1, genes previously reported in related disorders, and novel genes TRIP12 and PAX5. We also show that mutation carriers generally have lower IQs and enrichment for seizures. These data begin to distinguish genetically distinct subtypes of autism important for etiological classification and future therapeutics.

Analysis of rare, exonic variation amongst subjects with autism spectrum disorders and population controls

We report on results from whole-exome sequencing (WES) of 1,039 subjects diagnosed with autism spectrum disorders (ASD) and 870 controls selected from the NIMH repository to be of similar ancestry to cases. The WES data came from two centers using different methods to produce sequence and to call variants from it. Therefore, an initial goal was to ensure the distribution of rare variation was similar for data from different centers. This proved straightforward by filtering called variants by fraction of missing data, read depth, and balance of alternative to reference reads. Results were evaluated using seven samples sequenced at both centers and by results from the association study. Next we addressed how the data and/or results from the centers should be combined. Gene-based analyses of association was an obvious choice, but should statistics for association be combined across centers (meta-analysis) or should data be combined and then analyzed (mega-analysis)? Because of the nature of many gene-based tests, we showed by theory and simulations that mega-analysis has better power than meta-analysis. Finally, before analyzing the data for association, we explored the impact of population structure on rare variant analysis in these data. Like other recent studies, we found evidence that population structure can confound case-control studies by the clustering of rare variants in ancestry space; yet, unlike some recent studies, for these data we found that principal component-based analyses were sufficient to control for ancestry and produce test statistics with appropriate distributions. After using a variety of gene-based tests and both meta- and mega-analysis, we found no new risk genes for ASD in this sample. Our results suggest that standard gene-based tests will require much larger samples of cases and controls before being effective for gene discovery, even for a disorder like ASD.

This study evaluates association of rare variants and autism spectrum disorders (ASD) in case and control samples sequenced by two centers. Before doing association analyses, we studied how to combine information across studies. We first harmonized the whole-exome sequence (WES) data, across centers, in terms of the distribution of rare variation. Key features included filtering called variants by fraction of missing data, read depth, and balance of alternative to reference reads. After filtering, the vast majority of variants calls from seven samples sequenced at both centers matched. We also evaluated whether one should combine summary statistics from data from each center (meta-analysis) or combine data and analyze it together (mega-analysis). For many gene-based tests, we showed that mega-analysis yields more power. After quality control of data from 1,039 ASD cases and 870 controls and a range of analyses, no gene showed exome-wide evidence of significant association. Our results comport with recent results demonstrating that hundreds of genes affect risk for ASD; they suggest that rare risk variants are scattered across these many genes, and thus larger samples will be required to identify those genes.