Autism Genetic Resource Exchange Research Articles

Recurrence rates provide evidence for sex-differential, familial genetic liability for autism spectrum disorders in multiplex families and twins.

BackgroundAutism spectrum disorders (ASDs) are more prevalent in males, suggesting a multiple threshold liability model in which females are, on average, protected by sex-differential mechanisms. Under this model, autistic females are predicted to carry a more penetrant risk variant load than males and to share this greater genetic liability with their siblings. However, reported ASD recurrence rates have not demonstrated significantly increased risk to siblings of affected girls. Here, we characterize recurrence patterns in multiplex families from the Autism Genetics Resource Exchange (AGRE) to determine if risk in these families follows a female protective model.MethodsWe assess recurrence rates and quantitative traits in full siblings from 1,120 multiplex nuclear families and concordance rates in 305 twin pairs from AGRE. We consider the first two affected children per family, and one randomly selected autistic twin per pair, as probands. We then compare recurrence rates and phenotypes between males and females and between twin pairs or families with at least one female proband (female-containing (FC)) versus those with only male probands (male-only (MO)).ResultsAmong children born after two probands, we observe significantly higher recurrence in males (47.5%) than in females (21.1%; relative risk, RR = 2.25; adjusted P = 6.22e−08) and in siblings of female (44.3%) versus siblings of male probands (30.4%; RR = 1.46; adj. P = 0.036). This sex-differential recurrence is also robust in dizygotic twin pairs (males = 61.5%, females = 19.1%; RR = 3.23; adj. P = 7.66e−09). Additionally, we find a significant negative relationship between interbirth interval and ASD recurrence that is driven by children in MO families.ConclusionsBy classifying families as MO or FC using two probands instead of one, we observe significant recurrence rate differences between families harboring sex-differential familial liability. However, a significant sex difference in risk to children within FC families suggests that female protective mechanisms are still operative in families carrying high genetic risk loads. Furthermore, the male-specific relationship between shorter interbirth intervals and increased ASD risk is consistent with a potentially greater contribution from environmental factors in males versus higher genetic risk in affected females and their families. Understanding the mechanisms driving these sex-differential risk profiles will be useful for treatment development and prevention.Electronic supplementary materialThe online version of this article (doi:10.1186/s13229-015-0004-5) contains supplementary material, which is available to authorized users.

Protein interaction networks reveal novel autism risk genes within GWAS statistical noise.

Genome-wide association studies (GWAS) for Autism Spectrum Disorder (ASD) thus far met limited success in the identification of common risk variants, consistent with the notion that variants with small individual effects cannot be detected individually in single SNP analysis. To further capture disease risk gene information from ASD association studies, we applied a network-based strategy to the Autism Genome Project (AGP) and the Autism Genetics Resource Exchange GWAS datasets, combining family-based association data with Human Protein-Protein interaction (PPI) data. Our analysis showed that autism-associated proteins at higher than conventional levels of significance (P<0.1) directly interact more than random expectation and are involved in a limited number of interconnected biological processes, indicating that they are functionally related. The functionally coherent networks generated by this approach contain ASD-relevant disease biology, as demonstrated by an improved positive predictive value and sensitivity in retrieving known ASD candidate genes relative to the top associated genes from either GWAS, as well as a higher gene overlap between the two ASD datasets. Analysis of the intersection between the networks obtained from the two ASD GWAS and six unrelated disease datasets identified fourteen genes exclusively present in the ASD networks. These are mostly novel genes involved in abnormal nervous system phenotypes in animal models, and in fundamental biological processes previously implicated in ASD, such as axon guidance, cell adhesion or cytoskeleton organization. Overall, our results highlighted novel susceptibility genes previously hidden within GWAS statistical “noise” that warrant further analysis for causal variants.

Social responsiveness, an autism endophenotype: genomewide significant linkage to two regions on chromosome 8.

Autism spectrum disorder is characterized by deficits in social function and the presence of repetitive and restrictive behaviors. Following a previous test of principle, the authors adopted a quantitative approach to discovering genes contributing to the broader autism phenotype by using social responsiveness as an endophenotype for autism spectrum disorder. Linkage analyses using scores from the Social Responsiveness Scale were performed in 590 families from the Autism Genetic Resource Exchange, a largely multiplex autism spectrum disorder cohort. Regional and genomewide association analyses were performed to search for common variants contributing to social responsiveness. Social Responsiveness Scale scores were unimodally distributed in male offspring from multiplex autism families, in contrast with a bimodal distribution observed in female offspring. In correlated analyses differing by Social Responsiveness Scale respondent, genomewide significant linkage for social responsiveness was identified at chr8p21.3 (multipoint LOD=4.11; teacher/parent scores) and chr8q24.22 (multipoint LOD=4.54; parent-only scores), respectively. Genomewide or linkage-directed association analyses did not detect common variants contributing to social responsiveness. The sex-differential distributions of Social Responsiveness Scale scores in multiplex autism families likely reflect mechanisms contributing to the sex ratio for autism observed in the general population and form a quantitative signature of reduced penetrance of inherited liability to autism spectrum disorder among females. The identification of two strong loci for social responsiveness validates the endophenotype approach for the identification of genetic variants contributing to complex traits such as autism spectrum disorder. While causal mutations have yet to be identified, these findings are consistent with segregation of rare genetic variants influencing social responsiveness and underscore the increasingly recognized role of rare inherited variants in the genetic architecture of autism spectrum disorder.

A mitochondrial bioenergetic hypothesis for autism spectrum disorder (570.3)

We are testing the hypothesis that a significant proportion of the risk for developing Autism Spectrum Disorder (ASD) is the result of inheriting partial defects in genes for mitochondrial bioenergetics. To test our hypothesis, first we determined if ancient human mtDNA variation is associated with ASD risk. To accomplish this, we used two independently generated and genotyped cohorts, the Autism Genetic Resource Exchange (AGRE) and the CHOP Autism Case‐Control (ACC). These pre‐existing mtDNA SNP data were generated by Illumina chip analysis. We deduced the mtDNA haplogroups for all samples and utilized cases and controls that harbored European haplogroups. Generalized linear modeling analysis of the AGRE cohort suggests that J mitochondrial lineage and T2 haplogroup are risk factors for ASD (J lineage: OR = 2.22, CI=1.21‐4.05, p=0.0094; T2 haplogroup: OR= 1.79, CI= 1.26‐2.55, p=0.0012). Congruently, in the ACC cohort we found that haplogroup T2 is strongly associated with ASD and represents a risk factor (OR=1.45, CI=1.04‐2.03, p=0.0284). These data demonstrate that ASD risk is modified by mtDNA haplogroup thus supporting our mitochondrial bioenergetic hypothesis of ASD.Grant Funding Source: Supported by Simons Foundation Autism Research Initiative and National Institutes of Health

Investigation of maternal genotype effects in autism by genome-wide association.

Like most psychiatric disorders, autism spectrum disorders have both a genetic and an environmental component. While previous studies have clearly demonstrated the contribution of in utero (prenatal) environment on autism risk, most of them focused on transient environmental factors. Based on a recent sibling study, we hypothesized that environmental factors could also come from the maternal genome, which would result in persistent effects across siblings. In this study, the possibility of maternal genotype effects was examined by looking for common variants (single-nucleotide polymorphisms or SNPs) in the maternal genome associated with increased risk of autism in children. A case/control genome-wide association study was performed using mothers of probands as cases, and either fathers of probands or normal females as controls. Autism Genetic Resource Exchange and Illumina Genotype Control Database were used as our discovery cohort (n = 1616). The same analysis was then replicated on Simon Simplex Collection and Study of Addiction: Genetics and Environment datasets (n = 2732). We did not identify any SNP that reached genome-wide significance (P < 10(-8) ), and thus a common variant of large effect is unlikely. However, there was evidence for the possibility of a large number of alleles of effective size marginally below our power to detect.

Replication of linkage at chromosome 20p13 and identification of suggestive sex-differential risk loci for autism spectrum disorder

BackgroundAutism spectrum disorders (ASDs) are male-biased and genetically heterogeneous. While sequencing of sporadic cases has identified de novo risk variants, the heritable genetic contribution and mechanisms driving the male bias are less understood. Here, we aimed to identify familial and sex-differential risk loci in the largest available, uniformly ascertained, densely genotyped sample of multiplex ASD families from the Autism Genetics Resource Exchange (AGRE), and to compare results with earlier findings from AGRE.MethodsFrom a total sample of 1,008 multiplex families, we performed genome-wide, non-parametric linkage analysis in a discovery sample of 847 families, and separately on subsets of families with only male, affected children (male-only, MO) or with at least one female, affected child (female-containing, FC). Loci showing evidence for suggestive linkage (logarithm of odds ≥2.2) in this discovery sample, or in previous AGRE samples, were re-evaluated in an extension study utilizing all 1,008 available families. For regions with genome-wide significant linkage signal in the discovery stage, those families not included in the corresponding discovery sample were then evaluated for independent replication of linkage. Association testing of common single nucleotide polymorphisms (SNPs) was also performed within suggestive linkage regions.ResultsWe observed an independent replication of previously observed linkage at chromosome 20p13 (P < 0.01), while loci at 6q27 and 8q13.2 showed suggestive linkage in our extended sample. Suggestive sex-differential linkage was observed at 1p31.3 (MO), 8p21.2 (FC), and 8p12 (FC) in our discovery sample, and the MO signal at 1p31.3 was supported in our expanded sample. No sex-differential signals met replication criteria, and no common SNPs were significantly associated with ASD within any identified linkage regions.ConclusionsWith few exceptions, analyses of subsets of families from the AGRE cohort identify different risk loci, consistent with extreme locus heterogeneity in ASD. Large samples appear to yield more consistent results, and sex-stratified analyses facilitate the identification of sex-differential risk loci, suggesting that linkage analyses in large cohorts are useful for identifying heritable risk loci. Additional work, such as targeted re-sequencing, is needed to identify the specific variants within these loci that are responsible for increasing ASD risk.

Genetically meaningful phenotypic subgroups in autism spectrum disorders

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder with strong evidence for genetic susceptibility. However, the effect sizes for implicated chromosomal loci are small, hard to replicate and current evidence does not explain the majority of the estimated heritability. Phenotypic heterogeneity could be one phenomenon complicating identification of genetic factors. We used data from the Autism Diagnostic Interview-Revised, Autism Diagnostic Observation Schedule, Vineland Adaptive Behavior Scales, head circumferences, and ages at exams as classifying variables to identify more clinically similar subgroups of individuals with ASD. We identified two distinct subgroups of cases within the Autism Genetic Resource Exchange dataset, primarily defined by the overall severity of evaluated traits. In addition, there was significant familial clustering within subgroups (odds ratio, OR ≈ 1.38-1.42, P < 0.00001), and genotypes were more similar within subgroups compared to the unsubgrouped dataset (Fst = 0.17 ± 0.0.0009). These results suggest that the subgroups recapitulate genetic etiology. Using the same approach in an independent dataset from the Autism Genome Project, we similarly identified two distinct subgroups of cases and confirmed this severity-based dichotomy. We also observed evidence for genetic contributions to subgroups identified in the replication dataset. Our results provide more effective methods of phenotype definition that should increase power to detect genetic factors influencing risk for ASD.

Behavioral signatures related to genetic disorders in autism

BackgroundAutism spectrum disorder (ASD) is well recognized to be genetically heterogeneous. It is assumed that the genetic risk factors give rise to a broad spectrum of indistinguishable behavioral presentations.MethodsWe tested this assumption by analyzing the Autism Diagnostic Interview-Revised (ADI-R) symptom profiles in samples comprising six genetic disorders that carry an increased risk for ASD (22q11.2 deletion, Down’s syndrome, Prader-Willi, supernumerary marker chromosome 15, tuberous sclerosis complex and Klinefelter syndrome; total n = 322 cases, groups ranging in sample sizes from 21 to 90 cases). We mined the data to test the existence and specificity of ADI-R profiles using a multiclass extension of support vector machine (SVM) learning. We subsequently applied the SVM genetic disorder algorithm on idiopathic ASD profiles from the Autism Genetics Resource Exchange (AGRE).ResultsGenetic disorders were associated with behavioral specificity, indicated by the accuracy and certainty of SVM predictions; one-by-one genetic disorder stratifications were highly accurate leading to 63% accuracy of correct genotype prediction when all six genetic disorder groups were analyzed simultaneously. Application of the SVM algorithm to AGRE cases indicated that the algorithm could detect similarity of genetic behavioral signatures in idiopathic ASD subjects. Also, affected sib pairs in the AGRE were behaviorally more similar when they had been allocated to the same genetic disorder group.ConclusionsOur findings provide evidence for genotype-phenotype correlations in relation to autistic symptomatology. SVM algorithms may be used to stratify idiopathic cases of ASD according to behavioral signature patterns associated with genetic disorders. Together, the results suggest a new approach for disentangling the heterogeneity of ASD.

A scoring strategy combining statistics and functional genomics supports a possible role for common polygenic variation in autism.

Autism spectrum disorders (ASD) are highly heritable complex neurodevelopmental disorders with a 4:1 male: female ratio. Common genetic variation could explain 40–60% of the variance in liability to autism. Because of their small effect, genome-wide association studies (GWASs) have only identified a small number of individual single-nucleotide polymorphisms (SNPs). To increase the power of GWASs in complex disorders, methods like convergent functional genomics (CFG) have emerged to extract true association signals from noise and to identify and prioritize genes from SNPs using a scoring strategy combining statistics and functional genomics. We adapted and applied this approach to analyze data from a GWAS performed on families with multiple children affected with autism from Autism Speaks Autism Genetic Resource Exchange (AGRE). We identified a set of 133 candidate markers that were localized in or close to genes with functional relevance in ASD from a discovery population (545 multiplex families); a gender specific genetic score (GS) based on these common variants explained 1% (P = 0.01 in males) and 5% (P = 8.7 × 10−7 in females) of genetic variance in an independent sample of multiplex families. Overall, our work demonstrates that prioritization of GWAS data based on functional genomics identified common variants associated with autism and provided additional support for a common polygenic background in autism.

Variability in the common genetic architecture of social-communication spectrum phenotypes during childhood and adolescence

BackgroundSocial-communication abilities are heritable traits, and their impairments overlap with the autism continuum. To characterise the genetic architecture of social-communication difficulties developmentally and identify genetic links with the autistic dimension, we conducted a genome-wide screen of social-communication problems at multiple time-points during childhood and adolescence.MethodsSocial-communication difficulties were ascertained at ages 8, 11, 14 and 17 years in a UK population-based birth cohort (Avon Longitudinal Study of Parents and Children; N ≤ 5,628) using mother-reported Social Communication Disorder Checklist scores. Genome-wide Complex Trait Analysis (GCTA) was conducted for all phenotypes. The time-points with the highest GCTA heritability were subsequently analysed for single SNP association genome-wide. Type I error in the presence of measurement relatedness and the likelihood of observing SNP signals near known autism susceptibility loci (co-location) were assessed via large-scale, genome-wide permutations. Association signals (P ≤ 10−5) were also followed up in Autism Genetic Resource Exchange pedigrees (N = 793) and the Autism Case Control cohort (Ncases/Ncontrols = 1,204/6,491).ResultsGCTA heritability was strongest in childhood (h2(8 years) = 0.24) and especially in later adolescence (h2(17 years) = 0.45), with a marked drop during early to middle adolescence (h2(11 years) = 0.16 and h2(14 years) = 0.08). Genome-wide screens at ages 8 and 17 years identified for the latter time-point evidence for association at 3p22.2 near SCN11A (rs4453791, P = 9.3 × 10−9; genome-wide empirical P = 0.011) and suggestive evidence at 20p12.3 at PLCB1 (rs3761168, P = 7.9 × 10−8; genome-wide empirical P = 0.085). None of these signals contributed to risk for autism. However, the co-location of population-based signals and autism susceptibility loci harbouring rare mutations, such as PLCB1, is unlikely to be due to chance (genome-wide empirical Pco-location = 0.007).ConclusionsOur findings suggest that measurable common genetic effects for social-communication difficulties vary developmentally and that these changes may affect detectable overlaps with the autism spectrum.

Does epilepsy in multiplex autism pedigrees define a different subgroup in terms of clinical characteristics and genetic risk?

BackgroundAutism spectrum disorders (ASD) and epilepsy frequently occur together. Prevalence rates are variable, and have been attributed to age, gender, comorbidity, subtype of pervasive developmental disorder (PDD) and risk factors. Recent studies have suggested disparate clinical and genetic settings depending on simplex or multiplex autism. The aim of this study was to assess: 1) the prevalence of epilepsy in multiplex autism and its association with genetic and non-genetic risk factors of major effect, intellectual disability and gender; and 2) whether autism and epilepsy cosegregate within multiplex autism families.MethodsWe extracted from the Autism Genetic Resource Exchange (AGRE) database (n = 3,818 children from 1,264 families) all families with relevant medical data (n = 664 children from 290 families). The sample included 478 children with ASD and 186 siblings without ASD. We analyzed the following variables: seizures, genetic and non-genetic risk factors, gender, and cognitive functioning as assessed by Raven’s Colored Progressive Matrices (RCPM) and Vineland Adaptive Behavior Scales (VABS).ResultsThe prevalence of epilepsy was 12.8% in cases with ASD and 2.2% in siblings without ASD (P <10-5). With each RCPM or VABS measure, the risk of epilepsy in multiplex autism was significantly associated with intellectual disability, but not with gender. Identified risk factors (genetic or non-genetic) of autism tended to be significantly associated with epilepsy (P = 0.052). When children with prematurity, pre- or perinatal insult, or cerebral palsy were excluded, a genetic risk factor was reported for 6/59 (10.2%) of children with epilepsy and 12/395 (3.0%) of children without epilepsy (P = 0.002). Finally, using a permutation test, there was significant evidence that the epilepsy phenotype co-segregated within families (P <10-4).ConclusionsEpilepsy in multiplex autism may define a different subgroup in terms of clinical characteristics and genetic risk.

Sex‐specific association of a common variant of the XG gene with autism spectrum disorders

Autism spectrum disorders (ASD) are much more common in males than in females. Studies using both linkage and candidate gene association approaches have identified genetic variants specific to families in which all affected cases were male, suggesting that sex may interact with or otherwise influence the expression of specific genes in association with ASD. In this study, we specifically evaluated the sex-specific genetic effects of ASD with a family-based genome-wide association study approach using the data from the Autism Genetic Resource Exchange repository. We evaluated the male-specific genetic effects of ASD in 374 multiplex families of European ancestry in which all affected were male (male-only; MO) and identified a novel genome-wide significant association in the pseudoautosomal boundary on chromosome Xp22.33/Yp11.31 in the MO families of predominantly paternal origin (rs2535443, p = 3.8 × 10(-8) ). Five markers that reside within a 550 kb intergenic region on chromosome 13q33.3, between the MYO16 and IRS2 genes, also showed suggestive association with ASD in the MO families (p = 3.3 × 10(-5) to 5.3 × 10(-7) ). In contrast, none of these markers appeared to be associated with ASD in the families containing any affected females. Our results suggest that the pseudoautosomal boundary on Xp22.33/Yp11.31 may harbor male-specific genetic variants for ASD.

Mode of Genetic Inheritance Modifies the Association of Head Circumference and Autism-Related Symptoms: A Cross-Sectional Study

BackgroundFrequently individuals with autism spectrum disorder (ASD) have been noted with a larger head circumference (HC) than their typical developing peers. Biologic hypotheses suggest that an overly rapid brain growth leads to the core symptoms of ASD by impairing connectivity. Literature is divided however where deleterious, protective and null associations of HC with ASD symptoms in individuals with ASD have been found.MethodIndividuals (n = 1,416) from the Autism Genetic Resource Exchange with ASD were examined for associations of HC with ASD like symptoms. Mixed models controlling for sex, age, race/ethnicity, simplex/multiplex status and accounting for correlations between siblings were used. Interactions by simplex/multiplex were explored. Adjustments for height in a sub-population with available data were explored as well.ResultsA Significant interaction term (p = 0.03) suggested that the effect of HC was dependent on whether the individual was simplex or multiplex. In simplex individuals at mean age (8.9 years) 1 cm increase in head circumference was associated with a 24% increase in the odds of a high social diagnostic score from the Autism Diagnostic Interview – Revised (odds ratio = 1.24, p = 0.01). There was no association in multiplex individuals. Additionally, individuals classified with a non-verbal IQ <70 were 90% simplex and had a significantly increased head circumference (0.7 cm p = 0.03) relative to a mid-range non-verbal IQ group. Interestingly, children classified with a >110 non-verbal IQ also had an increased HC (0.4 cm p = 0.04), relative to a mid-range non-verbal IQ group, and were 90% multiplex. HC effects do not appear to be confounded by height, however, larger samples with height information are needed.ConclusionThe potential link between brain growth and autism like symptoms is complex and could depend on specific etiologies. Further investigations accounting for a likely mode of inheritance will help identify an ASD subtype related to HC.

Brain-reactive IgG correlates with autoimmunity in mothers of a child with an autism spectrum disorder

It is believed that in utero environmental factors contribute to autism spectrum disorder (ASD). The goal of this study was to demonstrate, using the largest cohort reported so far, that mothers of an ASD child have an elevated frequency of anti-brain antibodies and to assess whether brain reactivity is associated with an autoimmune diathesis of the mother. We screened plasma of 2431 mothers of an ASD child from Simon Simplex Collection and plasma of 653 unselected women of child-bearing age for anti-brain antibodies using immunohistology on mouse brain. Positive and negative plasma from mothers with an ASD child were analyzed for anti-nuclear antibodies and for autoimmune disorders. Mothers of an ASD child were four times more likely to harbor anti-brain antibodies than unselected women of child-bearing age (10.5 vs 2.6%). A second cohort from The Autism Genetic Resource Exchange with multiplex families displayed an 8.8% prevalence of anti-brain antibodies in the mothers of these families. Fifty-three percent of these mothers with anti-brain antibodies also exhibited anti-nuclear autoantibodies compared with 13.4% of mothers of an ASD child without anti-brain antibodies and 15% of control women of child-bearing age. The analysis of ASD mothers with brain-reactive antibodies also revealed an increased prevalence of autoimmune diseases, especially rheumatoid arthritis and systemic lupus erythematosus. This study provides robust evidence that brain-reactive antibodies are increased in mothers of an ASD child and may be associated with autoimmunity. The current study serves as a benchmark and justification for studying the potential pathogenicity of these antibodies on the developing brain. The detailed characterization of the specificity of these antibodies will provide practical benefits for the management and prevention of this disorder.

Necrosis is increased in lymphoblastoid cell lines from children with autism compared with their non-autistic siblings under conditions of oxidative and nitrosative stress

Autism spectrum disorders are a heterogeneous group of neurodevelopmental conditions characterised by impairments in reciprocal social interaction, communication and stereotyped behaviours. As increased DNA damage events have been observed in a range of other neurological disorders, it was hypothesised that they would be elevated in lymphoblastoid cell lines (LCLs) obtained from children with autism compared with their non-autistic siblings. Six case-sibling pairs of LCLs from children with autistic disorder and their non-autistic siblings were obtained from the Autism Genetic Resource Exchange (AGRE) and cultured in standard RPMI-1640 tissue culture medium. Cells were exposed to medium containing either 0, 25, 50, 100 and 200 µM hydrogen peroxide (an oxidative stressor) or 0, 5, 10, 20 and 40 µM s-nitroprusside (a nitric oxide producer) for 1h. Following exposure, the cells were microscopically scored for DNA damage, cytostasis and cytotoxicity biomarkers as measured using the cytokinesis-block micronucleus cytome assay. Necrosis was significantly increased in cases relative to controls when exposed to oxidative and nitrosative stress (P = 0.001 and 0.01, respectively). Nuclear division index was significantly lower in LCLs from children with autistic disorder than their non-autistic siblings when exposed to hydrogen peroxide (P = 0.016), but there was no difference in apoptosis, micronucleus frequency, nucleoplasmic bridges or nuclear buds. Exposure to s-nitroprusside significantly increased the number of micronuclei in non-autistic siblings compared with cases (P = 0.003); however, other DNA damage biomarkers, apoptosis and nuclear division did not differ significantly between groups. The findings of this study show (i) that LCLs from children with autism are more sensitive to necrosis under conditions of oxidative and nitrosative stress than their non-autistic siblings and (ii) refutes the hypothesis that children with autistic disorder are abnormally susceptible to DNA damage.

Haplotype structure enables prioritization of common markers and candidate genes in autism spectrum disorder

Autism spectrum disorder (ASD) is a neurodevelopmental condition that results in behavioral, social and communication impairments. ASD has a substantial genetic component, with 88–95% trait concordance among monozygotic twins. Efforts to elucidate the causes of ASD have uncovered hundreds of susceptibility loci and candidate genes. However, owing to its polygenic nature and clinical heterogeneity, only a few of these markers represent clear targets for further analyses. In the present study, we used the linkage structure associated with published genetic markers of ASD to simultaneously improve candidate gene detection while providing a means of prioritizing markers of common genetic variation in ASD. We first mined the literature for linkage and association studies of single-nucleotide polymorphisms, copy-number variations and multi-allelic markers in Autism Genetic Resource Exchange (AGRE) families. From markers that reached genome-wide significance, we calculated male-specific genetic distances, in light of the observed strong male bias in ASD. Four of 67 autism-implicated regions, 3p26.1, 3p26.3, 3q25-27 and 5p15, were enriched with differentially expressed genes in blood and brain from individuals with ASD. Of 30 genes differentially expressed across multiple expression data sets, 21 were within 10 cM of an autism-implicated locus. Among them, CNTN4, CADPS2, SUMF1, SLC9A9, NTRK3 have been previously implicated in autism, whereas others have been implicated in neurological disorders comorbid with ASD. This work leverages the rich multimodal genomic information collected on AGRE families to present an efficient integrative strategy for prioritizing autism candidates and improving our understanding of the relationships among the vast collection of past genetic studies.

The Evidence for Association of ATP2B2 Polymorphisms with Autism in Chinese Han Population

BackgroundAutism is a neurodevelopmental disorder with a high estimated heritability. ATP2B2, located on human chromosome 3p25.3, encodes the plasma membrane calcium-transporting ATPase 2 which extrudes Ca2+ from cytosol into extracellular space. Recent studies reported association between ATP2B2 and autism in samples from Autism Genetic Resource Exchange (AGRE) and Italy. In this study, we investigated whether ATP2B2 polymorphisms were associated with autism in Chinese Han population.MethodsWe performed a family based association study between five SNPs (rs35678 in exon, rs241509, rs3774180, rs3774179, and rs2278556 in introns) in ATP2B2 and autism in 427 autism trios of Han Chinese descent. All SNPs were genotyped using the Sequenom genotyping platform. The family-based association test (FBAT) program was used to perform association test for SNPs and haplotype analyses.ResultsThis study demonstrated a preferential transmission of T allele of rs3774179 to affected offsprings under an additive model (T>C, Z = 2.482, p = 0.013). While C allele of rs3774179 showed an undertransmission from parents to affected children under an additive and a dominant model, respectively (Z = −2.482, p = 0.013; Z = −2.591, p = 0.0096). Haplotype analyses revealed that three haplotypes were significantly associated with autism. The haplotype C-C (rs3774180–rs3774179) showed a significant undertransmission from parents to affected offsprings both in specific and global haplotype FBAT (Z = −2.037, p = 0.042; Global p = 0.03). As for the haplotype constructed by rs3774179 and rs2278556, C-A might be a protective haplotype (Z = −2.206, p = 0.027; Global p = 0.04), while T-A demonstrated an excess transmission from parents to affected offsprings (Z = 2.143, p = 0.032). These results were still significant after using the permutation method to obtain empirical p values.ConclusionsOur research suggested that ATP2B2 might play a role in the etiology of autism in Chinese Han population.

Support for calcium channel gene defects in autism spectrum disorders

BackgroundAlternation of synaptic homeostasis is a biological process whose disruption might predispose children to autism spectrum disorders (ASD). Calcium channel genes (CCG) contribute to modulating neuronal function and evidence implicating CCG in ASD has been accumulating. We conducted a targeted association analysis of CCG using existing genome-wide association study (GWAS) data and imputation methods in a combined sample of parent/affected child trios from two ASD family collections to explore this hypothesis.MethodsA total of 2,176 single-nucleotide polymorphisms (SNP) (703 genotyped and 1,473 imputed) covering the genes that encode the α1 subunit proteins of 10 calcium channels were tested for association with ASD in a combined sample of 2,781 parent/affected child trios from 543 multiplex Caucasian ASD families from the Autism Genetics Resource Exchange (AGRE) and 1,651 multiplex and simplex Caucasian ASD families from the Autism Genome Project (AGP). SNP imputation using IMPUTE2 and a combined reference panel from the HapMap3 and the 1,000 Genomes Project increased coverage density of the CCG. Family-based association was tested using the FBAT software which controls for population stratification and accounts for the non-independence of siblings within multiplex families. The level of significance for association was set at 2.3E-05, providing a Bonferroni correction for this targeted 10-gene panel.ResultsFour SNPs in three CCGs were associated with ASD. One, rs10848653, is located in CACNA1C, a gene in which rare de novo mutations are responsible for Timothy syndrome, a Mendelian disorder that features ASD. Two others, rs198538 and rs198545, located in CACN1G, and a fourth, rs5750860, located in CACNA1I, are in CCGs that encode T-type calcium channels, genes with previous ASD associations.ConclusionsThese associations support a role for common CCG SNPs in ASD.

The Effects of Birth Order and Birth Interval on the Phenotypic Expression of Autism Spectrum Disorder

A rise in the prevalence of diagnosed cases of autism spectrum disorder (ASD) has been reported in several studies in recent years. While this rise in ASD prevalence is at least partially related to increased awareness and broadened diagnostic criteria, the role of environmental factors cannot be ruled out, especially considering that the cause of most cases of ASD remains unknown. The study of families with multiple affected children can provide clues about ASD etiology. While the majority of research on ASD multiplex families has focused on identifying genetic anomalies that may underlie the disorder, the study of symptom severity across ASD birth order may provide evidence for environmental factors in ASD. We compared social and cognitive measures of behavior between over 300 first and second affected siblings within multiplex autism families obtained from the Autism Genetic Resource Exchange dataset. Measures included nonverbal IQ assessed with the Ravens Colored Progressive Matrices, verbal IQ assessed with the Peabody Picture Vocabulary Test, and autism severity assessed with the Social Responsiveness Scale (SRS), an instrument established as a quantitative measure of autism. The results indicated that females were more severely impacted by ASD than males, especially first affected siblings. When first and second affected siblings were compared, significant declines in nonverbal and verbal IQ scores were observed. In addition, SRS results demonstrated a significant increase in autism severity between first and second affected siblings consistent with an overall decline in function as indicated by the IQ data. These results remained significant after controlling for the age and sex of the siblings. Surprisingly, the SRS scores were found to only be significant when the age difference between siblings was less than 2 years. These results suggest that some cases of ASD are influenced by a dosage effect involving unknown epigenetic, environmental, and/or immunological factors.

Predicting the diagnosis of autism spectrum disorder using gene pathway analysis

Autism spectrum disorder (ASD) depends on a clinical interview with no biomarkers to aid diagnosis. The current investigation interrogated single-nucleotide polymorphisms (SNPs) of individuals with ASD from the Autism Genetic Resource Exchange (AGRE) database. SNPs were mapped to Kyoto Encyclopedia of Genes and Genomes (KEGG)-derived pathways to identify affected cellular processes and develop a diagnostic test. This test was then applied to two independent samples from the Simons Foundation Autism Research Initiative (SFARI) and Wellcome Trust 1958 normal birth cohort (WTBC) for validation. Using AGRE SNP data from a Central European (CEU) cohort, we created a genetic diagnostic classifier consisting of 237 SNPs in 146 genes that correctly predicted ASD diagnosis in 85.6% of CEU cases. This classifier also predicted 84.3% of cases in an ethnically related Tuscan cohort; however, prediction was less accurate (56.4%) in a genetically dissimilar Han Chinese cohort (HAN). Eight SNPs in three genes (KCNMB4, GNAO1, GRM5) had the largest effect in the classifier with some acting as vulnerability SNPs, whereas others were protective. Prediction accuracy diminished as the number of SNPs analyzed in the model was decreased. Our diagnostic classifier correctly predicted ASD diagnosis with an accuracy of 71.7% in CEU individuals from the SFARI (ASD) and WTBC (controls) validation data sets. In conclusion, we have developed an accurate diagnostic test for a genetically homogeneous group to aid in early detection of ASD. While SNPs differ across ethnic groups, our pathway approach identified cellular processes common to ASD across ethnicities. Our results have wide implications for detection, intervention and prevention of ASD.