Recent genome-wide association studies (GWAS) have implicated a range of genes from discrete biological pathways in the aetiology of autism. However, despite the strong influence of genetic factors, association studies have yet to identify statistically robust, replicated major effect genes or SNPs. We apply the principle of the SNP ratio test methodology described by O'Dushlaine et al to over 2100 families from the Autism Genome Project (AGP). Using a two-stage design we examine association enrichment in 5955 unique gene-ontology classifications across four groupings based on two phenotypic and two ancestral classifications. Based on estimates from simulation we identify excess of association enrichment across all analyses. We observe enrichment in association for sets of genes involved in diverse biological processes, including pyruvate metabolism, transcription factor activation, cell-signalling and cell-cycle regulation. Both genes and processes that show enrichment have previously been examined in autistic disorders and offer biologically plausibility to these findings.
autism; genome-wide association analysis; pathway analysis; family-based association test; gene ontology
Brain development follows a different trajectory in children with Autism Spectrum Disorders (ASD) than in typically developing children. A proxy for neurodevelopment could be head circumference (HC), but studies assessing HC and its clinical correlates in ASD have been inconsistent. This study investigates HC and clinical correlates in the Simons Simplex Collection cohort.
We used a mixed linear model to estimate effects of covariates and the deviation from the expected HC given parental HC (genetic deviation). After excluding individuals with incomplete data, 7225 individuals in 1891 families remained for analysis. We examined the relationship between HC/genetic deviation of HC and clinical parameters.
Gender, age, height, weight, genetic ancestry and ASD status were significant predictors of HC (estimate of the ASD effect=0.2cm). HC was approximately normally distributed in probands and unaffected relatives, with only a few outliers. Genetic deviation of HC was also normally distributed, consistent with a random sampling of parental genes. Whereas larger HC than expected was associated with ASD symptom severity and regression, IQ decreased with the absolute value of the genetic deviation of HC.
Measured against expected values derived from covariates of ASD subjects, statistical outliers for HC were uncommon. HC is a strongly heritable trait and population norms for HC would be far more accurate if covariates including genetic ancestry, height and age were taken into account. The association of diminishing IQ with absolute deviation from predicted HC values suggests HC could reflect subtle underlying brain development and warrants further investigation.
head circumference; body metrics; genetic ancestry; IQ; autism spectrum disorder; ASD
Two common sources of DNA for whole exome sequencing (WES) are whole blood (WB) and immortalized lymphoblastoid cell line (LCL). However, it is possible that LCLs have a substantially higher rate of mutation than WB, causing concern for their use in sequencing studies. We compared results from paired WB and LCL DNA samples for 16 subjects, using LCLs of low passage number (<5). Using a standard analysis pipeline we detected a large number of discordant genotype calls (approximately 50 per subject) that we segregated into categories of “confidence” based on read-level quality metrics. From these categories and validation by Sanger sequencing, we estimate that the vast majority of the candidate differences were false positives and that our categories were effective in predicting valid sequence differences, including LCLs with putative mosaicism for the non-reference allele (3–4 per exome). These results validate the use of DNA from LCLs of low passage number for exome sequencing.
graphical diagnostics; lymphoblastoid cell line; mosaicism; sequence variant call; strand bias; somatic mutation
Insecticide-treated bed nets (ITNs), used extensively to reduce human exposure to malaria, work through physical and chemical means to block or deter host-seeking mosquitoes. Despite the importance of ITNs, very little is known about how host-seeking mosquitoes behave around occupied bed nets. As a result, evidence-based evaluations of the effects of physical damage on bed net effectiveness are not possible and there is a dearth of knowledge on which to base ITN design.
The dispersion of colony-raised female Anopheles gambiae and Anopheles albimanus was observed in 2-hr laboratory experiments in which up to 200 mosquitoes were released inside a mosquito-proof 3 m × 3 m tent housing a bed net arrayed with 18 30 cm × 30 cm sticky screen squares on the sides, ends and roof. Numbers of mosquitoes caught on the sticky squares were interpreted as the ‘mosquito pressure’ on that part of the net.
Presence of a human subject in the bed net significantly increased total mosquito pressure on the net for both species and significantly re-oriented An. gambiae to the roof of the net. Anopheles albimanus pressure was greatest on the bed net roof in both host-present and no-host conditions. The effects of different human subjects in the bed net, of different ambient conditions (dry, cool conditions vs warm, humid conditions) and of bed net treatment (deltamethrin-treated or no insecticide) on mosquito pressure patterns were tested for both species. Species-specific pressure patterns did not vary greatly as a result of any of these factors though some differences were noted that may be due the size of the different human subjects.
As a result of the interaction between host-seeking responses and the convective plume from the net occupant, species-specific mosquito pressure patterns manifest more or less predictably on the bed net. This has implications for bed net design and suggests that current methods of assessing damaged bed nets, which do not take damage location into account, should be modified.
Anopheles; Host-seeking; Bed nets; Durability; ITNs; LLINs
De novo genetic variation is an important class of risk factors for autism spectrum disorder (ASD). Recently, whole exome sequencing of ASD families has identified a novel de novo missense mutation in the human dopamine (DA) transporter (hDAT) gene, which results in a Thr to Met substitution at site 356 (hDAT T356M). The dopamine transporter (DAT) is a presynaptic membrane protein that regulates dopaminergic tone in the central nervous system by mediating the high-affinity re-uptake of synaptically released DA, making it a crucial regulator of DA homeostasis. Here, we report the first functional, structural, and behavioral characterization of an ASD-associated de novo mutation in the hDAT. We demonstrate that the hDAT T356M displays anomalous function, characterized as a persistent reverse transport of DA (substrate efflux). Importantly, in the bacterial homolog leucine transporter, substitution of A289 (the homologous site to T356) with a Met promotes an outward-facing conformation upon substrate binding. In the substrate-bound state, an outward-facing transporter conformation is a required for substrate efflux. In Drosophila melanogaster, expression of hDAT T356M in DA neurons lacking Drosophila DAT leads to hyperlocomotion, a trait associated with DA dysfunction and ASD. Taken together, our findings demonstrate that alterations in DA homeostasis, mediated by aberrant DAT function, may confer risk for ASD and related neuropsychiatric conditions.
dopamine; transporter; autism spectrum disorder; anomalous dopamine efflux; de novo mutation; Drosophila melanogaster
There is an urgent need for expanding and enhancing autism spectrum disorder (ASD) samples, in order to better understand causes of ASD.
In a unique public-private partnership, 13 sites with extensive experience in both the assessment and diagnosis of ASD embarked on an ambitious, 2-year program to collect samples for genetic and phenotypic research and begin analyses on these samples. The program was called The Autism Simplex Collection (TASC). TASC sample collection began in 2008 and was completed in 2010, and included nine sites from North America and four sites from Western Europe, as well as a centralized Data Coordinating Center.
Over 1,700 trios are part of this collection, with DNA from transformed cells now available through the National Institute of Mental Health (NIMH). Autism Diagnostic Interview-Revised (ADI-R) and Autism Diagnostic Observation Schedule-Generic (ADOS-G) measures are available for all probands, as are standardized IQ measures, Vineland Adaptive Behavioral Scales (VABS), the Social Responsiveness Scale (SRS), Peabody Picture Vocabulary Test (PPVT), and physical measures (height, weight, and head circumference). At almost every site, additional phenotypic measures were collected, including the Broad Autism Phenotype Questionnaire (BAPQ) and Repetitive Behavior Scale-Revised (RBS-R), as well as the non-word repetition scale, Communication Checklist (Children’s or Adult), and Aberrant Behavior Checklist (ABC). Moreover, for nearly 1,000 trios, the Autism Genome Project Consortium (AGP) has carried out Illumina 1 M SNP genotyping and called copy number variation (CNV) in the samples, with data being made available through the National Institutes of Health (NIH). Whole exome sequencing (WES) has been carried out in over 500 probands, together with ancestry matched controls, and this data is also available through the NIH. Additional WES is being carried out by the Autism Sequencing Consortium (ASC), where the focus is on sequencing complete trios. ASC sequencing for the first 1,000 samples (all from whole-blood DNA) is complete and data will be released in 2014. Data is being made available through NIH databases (database of Genotypes and Phenotypes (dbGaP) and National Database for Autism Research (NDAR)) with DNA released in Dist 11.0. Primary funding for the collection, genotyping, sequencing and distribution of TASC samples was provided by Autism Speaks and the NIH, including the National Institute of Mental Health (NIMH) and the National Human Genetics Research Institute (NHGRI).
TASC represents an important sample set that leverages expert sites. Similar approaches, leveraging expert sites and ongoing studies, represent an important path towards further enhancing available ASD samples.
Given prior evidence for the contribution of rare copy number variations (CNVs) to autism spectrum disorders (ASD), we studied these events in 4,457 individuals from 1,174 simplex families, composed of parents, a proband and, in most kindreds, an unaffected sibling. We find significant association of ASD with de novo duplications of 7q11.23, where the reciprocal deletion causes Williams-Beuren syndrome, featuring a highly social personality. We identify rare recurrent de novo CNVs at five additional regions including two novel ASD loci, 16p13.2 (including the genes USP7 and C16orf72) and Cadherin13, and implement a rigorous new approach to evaluating the statistical significance of these observations. Overall, we find large de novo CNVs carry substantial risk (OR=3.55; CI =2.16-7.46, p=6.9 × 10−6); estimate the presence of 130-234 distinct ASD-related CNV intervals across the genome; and, based on data from multiple studies, present compelling evidence for the association of rare de novo events at 7q11.23, 15q11.2-13.1, 16p11.2, and Neurexin1.
To characterize the role of rare complete human knockouts in autism spectrum disorders (ASD), we identify genes with homozygous or compound heterozygous loss-of-function (LoF) variants (defined as nonsense and essential splice sites) from exome sequencing of 933 cases and 869 controls. We identify a two-fold increase in complete knockouts of autosomal genes with low rates of LoF variation (≤5% frequency) in cases and estimate a 3% contribution to ASD risk by these events, confirming this observation in an independent set of 563 probands and 4,605 controls. Outside the pseudo-autosomal regions on the X-chromosome, we similarly observe a significant 1.5-fold increase in rare hemizygous knockouts in males, contributing to another 2% of ASDs in males. Taken together these results provide compelling evidence that rare autosomal and X-chromosome complete gene knockouts are important inherited risk factors for ASD.
Previously, we identified multiple, rare serotonin (5-HT) transporter (SERT) variants in children with autism spectrum disorder (ASD). Although in our study the SERT Ala56 variant was over-transmitted to ASD probands, it was also seen in some unaffected individuals, suggesting that associated ASD risk is influenced by the epistatic effects of other genetic variation. Subsequently, we established that mice expressing the SERT Ala56 variant on a 129S6/S4 genetic background display multiple biochemical, physiological and behavioral changes, including hyperserotonemia, altered 5-HT receptor sensitivity, and altered social, communication, and repetitive behavior. Here we explore the effects of genetic background on SERT Ala56 knock-in phenotypes.
To explore the effects of genetic background, we backcrossed SERT Ala56 mice on the 129 background into a C57BL/6 (B6) background to achieve congenic B6 SERT Ala56 mice, and assessed autism-relevant behavior, including sociability, ultrasonic vocalizations, and repetitive behavior in the home cage, as well as serotonergic phenotypes, including whole blood serotonin levels and serotonin receptor sensitivity.
One consistent phenotype between the two strains was performance in the tube test for dominance, where mutant mice displayed a greater tendency to withdraw from a social encounter in a narrow tube as compared to wildtype littermate controls. On the B6 background, mutant pup ultrasonic vocalizations were significantly increased, in contrast to decreased vocalizations seen previously on the 129 background. Several phenotypes seen on the 129 background were reduced or absent when the mutation was placed on the B6 background, including hyperserotonemia, 5-HT receptor hypersensivity, and repetitive behavior.
Our findings provide a cogent example of how epistatic interactions can modulate the impact of functional genetic variation and suggest that some aspects of social behavior may be especially sensitive to changes in SERT function. Finally, these results provide a platform for the identification of genes that may modulate the risk of ASD in humans.
Serotonin; Monoamine; Transporter; Receptor; Autism; Compulsive
Rare genetic variation is an important class of autism spectrum disorder (ASD) risk factors and can implicate biological networks for investigation. Altered serotonin (5-HT) signaling has been implicated in ASD, and we and others have discovered multiple, rare, ASD-associated variants in the 5-HT transporter (SERT) gene leading to elevated 5-HT re-uptake and perturbed regulation. We hypothesized that loci encoding SERT regulators harbor variants that impact SERT function and/or regulation and therefore could contribute to ASD risk. The adenosine A3 receptor (A3AR) regulates SERT via protein kinase G (PKG) and other signaling pathways leading to enhanced SERT surface expression and catalytic activity.
To test our hypothesis, we asked whether rare variants in the A3AR gene (ADORA3) were increased in ASD cases vs. controls. Discovery sequencing in a case-control sample and subsequent analysis of comparison exome sequence data were conducted. We evaluated the functional impact of two variants from the discovery sample on A3AR signaling and SERT activity.
Sequencing discovery showed an increase of rare coding variants in cases vs. controls (P=0.013). While comparison exome sequence data did not show a significant enrichment (P=0.071), combined analysis strengthened evidence for association (P=0.0025). Two variants discovered in ASD cases (Leu90Val and Val171Ile) lie in or near the ligand-binding pocket, and Leu90Val was enriched individually in cases (P=0.040). In vitro analysis of cells expressing Val90-A3AR revealed elevated basal cGMP levels compared with the wildtype receptor. Additionally, a specific A3AR agonist increased cGMP levels across the full time course studied in Val90-A3AR cells, compared to wildtype receptor. In Val90-A3AR/SERT co-transfections, agonist stimulation elevated SERT activity over the wildtype receptor with delayed 5-HT uptake activity recovery. In contrast, Ile171-A3AR was unable to support agonist stimulation of SERT. Although both Val90 and Ile171 were present in greater numbers in these ASD cases, segregation analysis in families showed incomplete penetrance, consistent with other rare ASD risk alleles.
Our results validate the hypothesis that the SERT regulatory network harbors rare, functional variants that impact SERT activity and regulation in ASD, and encourages further investigation of this network for other variation that may impact ASD risk.
Autism; Autism spectrum disorder; Serotonin; Serotonin transporter; Adenosine receptor; cGMP; DNA sequencing; Rare variant; Single nucleotide polymorphisms (SNPs); Allelic association
De novo mutations affect risk for many diseases and disorders, especially those with early-onset. An example is autism spectrum disorders (ASD). Four recent whole-exome sequencing (WES) studies of ASD families revealed a handful of novel risk genes, based on independent de novo loss-of-function (LoF) mutations falling in the same gene, and found that de novo LoF mutations occurred at a twofold higher rate than expected by chance. However successful these studies were, they used only a small fraction of the data, excluding other types of de novo mutations and inherited rare variants. Moreover, such analyses cannot readily incorporate data from case-control studies. An important research challenge in gene discovery, therefore, is to develop statistical methods that accommodate a broader class of rare variation. We develop methods that can incorporate WES data regarding de novo mutations, inherited variants present, and variants identified within cases and controls. TADA, for Transmission And De novo Association, integrates these data by a gene-based likelihood model involving parameters for allele frequencies and gene-specific penetrances. Inference is based on a Hierarchical Bayes strategy that borrows information across all genes to infer parameters that would be difficult to estimate for individual genes. In addition to theoretical development we validated TADA using realistic simulations mimicking rare, large-effect mutations affecting risk for ASD and show it has dramatically better power than other common methods of analysis. Thus TADA's integration of various kinds of WES data can be a highly effective means of identifying novel risk genes. Indeed, application of TADA to WES data from subjects with ASD and their families, as well as from a study of ASD subjects and controls, revealed several novel and promising ASD candidate genes with strong statistical support.
The genetic underpinnings of autism spectrum disorder (ASD) have proven difficult to determine, despite a wealth of evidence for genetic causes and ongoing effort to identify genes. Recently investigators sequenced the coding regions of the genomes from ASD children along with their unaffected parents (ASD trios) and identified numerous new candidate genes by pinpointing spontaneously occurring (de novo) mutations in the affected offspring. A gene with a severe (de novo) mutation observed in more than one individual is immediately implicated in ASD; however, the majority of severe mutations are observed only once per gene. These genes create a short list of candidates, and our results suggest about 50% are true risk genes. To strengthen our inferences, we develop a novel statistical method (TADA) that utilizes inherited variation transmitted to affected offspring in conjunction with (de novo) mutations to identify risk genes. Through simulations we show that TADA dramatically increases power. We apply this approach to nearly 1000 ASD trios and 2000 subjects from a case-control study and identify several promising genes. Through simulations and application we show that TADA's integration of sequencing data can be a highly effective means of identifying risk genes.
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.
To determine if the relationships between behavioral phenotypes and clinical diagnoses of different autism spectrum disorders vary across 12 university-based sites.
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.
Participants were recruited through 12 university-based autism service providers into a genetic study of autism.
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.
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.
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.
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.
Autism spectrum disorders (ASD) are believed to have genetic and environmental origins, yet in only a modest fraction of individuals can specific causes be identified1,2. To identify further genetic risk factors, we assess the role of de novo mutations in ASD by sequencing the exomes of ASD cases and their parents (n= 175 trios). Fewer than half of the cases (46.3%) carry a missense or nonsense de novo variant and the overall rate of mutation is only modestly higher than the expected rate. In contrast, there is significantly enriched connectivity among the proteins encoded by genes harboring de novo missense or nonsense mutations, and excess connectivity to prior ASD genes of major effect, suggesting a subset of observed events are relevant to ASD risk. The small increase in rate of de novo events, when taken together with the connections among the proteins themselves and to ASD, are consistent with an important but limited role for de novo point mutations, similar to that documented for de novo copy number variants. Genetic models incorporating these data suggest that the majority of observed de novo events are unconnected to ASD, those that do confer risk are distributed across many genes and are incompletely penetrant (i.e., not necessarily causal). Our results support polygenic models in which spontaneous coding mutations in any of a large number of genes increases risk by 5 to 20-fold. Despite the challenge posed by such models, results from de novo events and a large parallel case-control study provide strong evidence in favor of CHD8 and KATNAL2 as genuine autism risk factors.
Autism is a neurodevelopmental disorder with increasing evidence of heterogeneous genetic etiology including de novo and inherited copy number variants (CNVs). We performed array comparative genomic hybridization using a custom Agilent 1 M oligonucleotide array intended to cover 197 332 unique exons in RefSeq genes; 98% were covered by at least one probe and 95% were covered by three or more probes with the focus on detecting relatively small CNVs that would implicate a single protein-coding gene. The study group included 99 trios from the Simons Simplex Collection. The analysis identified and validated 55 potentially pathogenic CNVs, categorized as de novo autosomal heterozygous, inherited homozygous autosomal, complex autosomal and hemizygous deletions on the X chromosome of probands. Twenty percent (11 of 55) of these CNV calls were rare when compared with the Database of Genomic Variants. Thirty-six percent (20 of 55) of the CNVs were also detected in the same samples in an independent analysis using the 1 M Illumina single-nucleotide polymorphism array. Findings of note included a common and sometimes homozygous 61 bp exonic deletion in SLC38A10, three CNVs found in lymphoblast-derived DNA but not present in whole-blood derived DNA and, most importantly, in a male proband, an exonic deletion of the TMLHE (trimethyllysine hydroxylase epsilon) that encodes the first enzyme in the biosynthesis of carnitine. Data for CNVs present in lymphoblasts but absent in fresh blood DNA suggest that these represent clonal outgrowth of individual B cells with pre-existing somatic mutations rather than artifacts arising in cell culture. GEO accession number GSE23765 (http://www.ncbi.nlm.nih.gov/geo/, date last accessed on 30 August 2011). Genboree accession: http://genboree.org/java-bin/gbrowser.jsp?refSeqId=1868&entryPointId=chr17&from=53496072&to=53694382&isPublic=yes, date last accessed on 30 August 2011.
Autism spectrum disorders (ASD) are early onset neurodevelopmental syndromes typified by impairments in reciprocal social interaction and communication, accompanied by restricted and repetitive behaviors. While rare and especially de novo genetic variation are known to affect liability, whether common genetic polymorphism plays a substantial role is an open question and the relative contribution of genes and environment is contentious. It is probable that the relative contributions of rare and common variation, as well as environment, differs between ASD families having only a single affected individual (simplex) versus multiplex families who have two or more affected individuals.
By using quantitative genetics techniques and the contrast of ASD subjects to controls, we estimate what portion of liability can be explained by additive genetic effects, known as narrow-sense heritability. We evaluate relatives of ASD subjects using the same methods to evaluate the assumptions of the additive model and partition families by simplex/multiplex status to determine how heritability changes with status.
By analyzing common variation throughout the genome, we show that common genetic polymorphism exerts substantial additive genetic effects on ASD liability and that simplex/multiplex family status has an impact on the identified composition of that risk. As a fraction of the total variation in liability, the estimated narrow-sense heritability exceeds 60% for ASD individuals from multiplex families and is approximately 40% for simplex families. By analyzing parents, unaffected siblings and alleles not transmitted from parents to their affected children, we conclude that the data for simplex ASD families follow the expectation for additive models closely. The data from multiplex families deviate somewhat from an additive model, possibly due to parental assortative mating.
Our results, when viewed in the context of results from genome-wide association studies, demonstrate that a myriad of common variants of very small effect impacts ASD liability.
Narrow-sense heritability; Multiplex; Simplex; Quantitative genetics
A promoter-linked insertion/deletion polymorphism of the serotonin transporter gene (SLC6A4) has been implicated in autism spectrum disorders (ASDs) in numerous family-based association studies. However, the results of these investigations have been inconsistent in that both the long and short alleles have been shown to be over-transmitted to affected offspring. In order to further elucidate the relationship between the 5-HTTLPR variant and autism risk, we undertook a thorough study of parent-of-origin effects, maternal genotype effects, and offspring genotype effects in a sample of affected offspring from the Autism Genetic Resource Exchange (AGRE). Both the overall autism phenotype and measures of autism behaviors from the Autism Diagnostic Interview-Revised (Lord et al, 1994) were considered. We found evidence of over-transmission (risk allele short, p=0.012), maternal effects (risk allele long, p=0.035), and parent-of-origin effects (risk allele short from mother, p=0.018) of the 5-HTTLPR variant in the AGRE sample. Population-specific and gender-specific effects were also explored as associations may be heterogeneous across populations and sexes. Parent-of-origin effects of the variant were associated with maternally-inherited copies of the short allele that resulted in more impaired overall level of language (p=0.04). Our study was conducted to further investigate the 5-HTTLPR risk variants by identifying allelic associations that may be population-specific, phenotype-specific, or conferred by maternal or parent-of-origin effects. In light of conflicting observations from previous studies, these are just a few of the possible explanations that deserve attention.
Autism; 5-HTTLPR; maternal effects; parent-of-origin effects; association
Maternal 15q11-q13 duplication is the most common copy number variant in autism, accounting for ∼1-3% of cases. The 15q11-q13 region is subject to epigenetic regulation and genomic copy number losses and gains cause genomic disorders in a parent-of-origin-specific manner. One 15q11-q13 locus encodes the GABAA receptor β3 subunit gene (GABRB3), which has been implicated by several studies in both autism and absence epilepsy, and the co-morbidity of epilepsy in autism is well established. We report that maternal transmission of a GABRB3 signal peptide variant (P11S), previously implicated in childhood absence epilepsy, is associated with autism. Analysis of wild-type and mutant β3 subunit-containing α1β3γ2 GABAA receptors demonstrates reduced whole cell current and decreased β3 subunit protein on the cell surface due to impaired intracellular β3 subunit processing. We thus provide the first evidence for association between a specific GABAA receptor defect and autism, direct evidence that this defect causes synaptic dysfunction that is autism-relevant, and the first maternal risk effect in the 15q11-q13 autism duplication region linked to a coding variant.
autism; GABRB3; epilepsy; GABAA receptor; imprinting; mutation
While it is apparent that rare variation can play an important role in the genetic architecture of autism spectrum disorders (ASDs), the contribution of common variation to the risk of developing ASD is less clear. To produce a more comprehensive picture, we report Stage 2 of the Autism Genome Project genome-wide association study, adding 1301 ASD families and bringing the total to 2705 families analysed (Stages 1 and 2). In addition to evaluating the association of individual single nucleotide polymorphisms (SNPs), we also sought evidence that common variants, en masse, might affect the risk. Despite genotyping over a million SNPs covering the genome, no single SNP shows significant association with ASD or selected phenotypes at a genome-wide level. The SNP that achieves the smallest P-value from secondary analyses is rs1718101. It falls in CNTNAP2, a gene previously implicated in susceptibility for ASD. This SNP also shows modest association with age of word/phrase acquisition in ASD subjects, of interest because features of language development are also associated with other variation in CNTNAP2. In contrast, allele scores derived from the transmission of common alleles to Stage 1 cases significantly predict case status in the independent Stage 2 sample. Despite being significant, the variance explained by these allele scores was small (Vm< 1%). Based on results from individual SNPs and their en masse effect on risk, as inferred from the allele score results, it is reasonable to conclude that common variants affect the risk for ASD but their individual effects are modest.
Autism spectrum disorder (ASD) is characterized by core deficits in social behavior, communication, and behavioral flexibility. Several lines of evidence indicate that oxytocin, signaling through its receptor (OXTR), is important in a wide range of social behaviors. In attempts to determine whether genetic variations in the oxytocin signaling system contribute to ASD susceptibility, seven recent reports indicated association of common genetic polymorphisms in the OXTR gene with ASD. Each involved relatively small sample sizes (57 to 436 families) and, where it was examined, failed to identify association of OXTR polymorphisms with measures of social behavior in individuals with ASD. We report genetic association analysis of 25 markers spanning the OXTR locus in 1,238 pedigrees including 2,333 individuals with ASD. Association of three markers previously implicated in ASD susceptibility, rs2268493 (P=0.043), rs1042778 (P=0.037), and rs7632287 (P=0.016), was observed. Further, these genetic markers were associated with multiple core ASD phenotypes, including social domain dysfunction, measured by standardized instruments used to diagnose and describe ASD. The data suggest association of OXTR genetic polymorphisms with ASD, although the results should be interpreted with caution because none of the significant associations would survive appropriate correction for multiple comparisons. However, the current findings of association in a large independent cohort are consistent with previous results, and the biological plausibility of participation of the oxytocin signaling system in modulating social disruptions characteristic of ASD, suggest that functional polymorphisms of OXTR may contribute to ASD risk in a subset of families.
Oxytocin; Autism; ADI-R; ADOS; SRS; Association
Autism spectrum disorder is a severe early onset neurodevelopmental disorder with high heritability but significant heterogeneity. Traditional genome-wide approaches to test for an association of common variants with autism susceptibility risk have met with limited success. However, novel methods to identify moderate risk alleles in attainable sample sizes are now gaining momentum.
In this study, we utilized publically available genome-wide association study data from the Autism Genome Project and annotated the results (P <0.001) for expression quantitative trait loci present in the parietal lobe (GSE35977), cerebellum (GSE35974) and lymphoblastoid cell lines (GSE7761). We then performed a test of enrichment by comparing these results to simulated data conditioned on minor allele frequency to generate an empirical P-value indicating statistically significant enrichment of expression quantitative trait loci in top results from the autism genome-wide association study.
Our findings show a global enrichment of brain expression quantitative trait loci, but not lymphoblastoid cell line expression quantitative trait loci, among top single nucleotide polymorphisms from an autism genome-wide association study. Additionally, the data implicates individual genes SLC25A12, PANX1 and PANX2 as well as pathways previously implicated in autism.
These findings provide supportive rationale for the use of annotation-based approaches to genome-wide association studies.
Autism; annotation; cerebellum; enrichment; expression quantitative trait (eQTL); GWAS; LCL; pannexin; parietal; SLC25A12
Genome Wide Association Studies (GWAS) are a standard approach for large-scale common variation characterization and for identification of single loci predisposing to disease. However, due to issues of moderate sample sizes and particularly multiple testing correction, many variants of smaller effect size are not detected within a single allele analysis framework. Thus, small main effects and potential epistatic effects are not consistently observed in GWAS using standard analytical approaches that consider only single SNP alleles. Here we propose unique methodology that aggregates variants of interest (for example, genes in a biological pathway) using GWAS results. Multiple testing and type I error concerns are minimized using empirical genomic randomization to estimate significance. Randomization corrects for common pathway-based analysis biases such as SNP coverage and density, linkage disequilibrium, gene size and pathway size. PARIS (Pathway Analysis by Randomization Incorporating Structure) applies this randomization and in doing so directly accounts for linkage disequilibrium effects. PARIS is independent of association analysis method and is thus applicable to GWAS datasets of all study designs. Using the KEGG database as an example, we apply PARIS to the publicly available Autism Genetic Resource Exchange (AGRE) GWA dataset, revealing pathways with a significant enrichment of positive association results.
pathway analysis; genomic randomization; gene set; enrichment
Autism spectrum disorder (ASD) is a highly heritable disorder of complex and heterogeneous aetiology. It is primarily characterized by altered cognitive ability including impaired language and communication skills and fundamental deficits in social reciprocity. Despite some notable successes in neuropsychiatric genetics, overall, the high heritability of ASD (~90%) remains poorly explained by common genetic risk variants. However, recent studies suggest that rare genomic variation, in particular copy number variation, may account for a significant proportion of the genetic basis of ASD. We present a large scale analysis to identify candidate genes which may contain low-frequency recessive variation contributing to ASD while taking into account the potential contribution of population differences to the genetic heterogeneity of ASD. Our strategy, homozygous haplotype (HH) mapping, aims to detect homozygous segments of identical haplotype structure that are shared at a higher frequency amongst ASD patients compared to parental controls. The analysis was performed on 1,402 Autism Genome Project trios genotyped for 1 million single nucleotide polymorphisms (SNPs). We identified 25 known and 1,218 novel ASD candidate genes in the discovery analysis including CADM2, ABHD14A, CHRFAM7A, GRIK2, GRM3, EPHA3, FGF10, KCND2, PDZK1, IMMP2L and FOXP2. Furthermore, 10 of the previously reported ASD genes and 300 of the novel candidates identified in the discovery analysis were replicated in an independent sample of 1,182 trios. Our results demonstrate that regions of HH are significantly enriched for previously reported ASD candidate genes and the observed association is independent of gene size (odds ratio 2.10). Our findings highlight the applicability of HH mapping in complex disorders such as ASD and offer an alternative approach to the analysis of genome-wide association data.
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Autism spectrum disorder (ASD) is characterized by core deficits in social behavior, communication, and behavioral flexibility. Several lines of evidence indicate that oxytocin, signaling through its receptor (OXTR), is important in a wide range of social behaviors. In attempts to determine whether genetic variations in the oxytocin signaling system contribute to ASD susceptibility, seven recent reports indicated association of common genetic polymorphisms in the OXTR gene with ASD. Each involved relatively small sample sizes (57 to 436 families) and, where it was examined, failed to identify association of OXTR polymorphisms with measures of social behavior in individuals with ASD. We report genetic association analysis of 25 markers spanning the OXTR locus in 1,238 pedigrees including 2,333 individuals with ASD. Association of three markers previously implicated in ASD susceptibility, rs2268493 (P = 0.043), rs1042778 (P = 0.037), and rs7632287 (P = 0.016), was observed. Further, these genetic markers were associated with multiple core ASD phenotypes, including social domain dysfunction, measured by standardized instruments used to diagnose and describe ASD. The data suggest association of OXTR genetic polymorphisms with ASD, although the results should be interpreted with caution because none of the significant associations would survive appropriate correction for multiple comparisons. However, the current findings of association in a large independent cohort are consistent with previous results, and the biological plausibility of participation of the oxytocin signaling system in modulating social disruptions characteristic of ASD, suggest that functional polymorphisms of OXTR may contribute to ASD risk in a subset of families.
Oxytocin; Autism; ADI-R; ADOS; SRS; Association
The Autism Genome Project has assembled two large datasets originally designed for linkage analysis and genome-wide association analysis, respectively: 1,069 multiplex families genotyped on the Affymetrix 10 K platform, and 1,129 autism trios genotyped on the Illumina 1 M platform. We set out to exploit this unique pair of resources by analyzing the combined data with a novel statistical method, based on the PPL statistical framework, simultaneously searching for linkage and association to loci involved in autism spectrum disorders (ASD). Our analysis also allowed for potential differences in genetic architecture for ASD in the presence or absence of lower IQ, an important clinical indicator of ASD subtypes. We found strong evidence of multiple linked loci; however, association evidence implicating specific genes was low even under the linkage peaks. Distinct loci were found in the lower IQ families, and these families showed stronger and more numerous linkage peaks, while the normal IQ group yielded the strongest association evidence. It appears that presence/absence of lower IQ (LIQ) demarcates more genetically homogeneous subgroups of ASD patients, with not just different sets of loci acting in the two groups, but possibly distinct genetic architecture between them, such that the LIQ group involves more major gene effects (amenable to linkage mapping), while the normal IQ group potentially involves more common alleles with lower penetrances. The possibility of distinct genetic architecture across subtypes of ASD has implications for further research and perhaps for research approaches to other complex disorders as well.
Autism; Linkage analysis; Genome-wide association; PPL; PPLD; IQ