Large-Scale Exome Sequencing Study Implicates Both Developmental and Functional Changes in the Neurobiology of Autism.

We present the largest exome sequencing study of autism spectrum disorder (ASD) to date (n = 35,584 total samples, 11,986 with ASD). Using an enhanced analytical framework to integrate de novo and case-control rare variation, we identify 102 risk genes at a false discovery rate of 0.1 or less. Of these genes, 49 show higher frequencies of disruptive de novo variants in individuals ascertained to have severe neurodevelopmental delay, whereas 53 show higher frequencies in individuals ascertained to have ASD; comparing ASD cases with mutations in these groups reveals phenotypic differences. Expressed early in brain development, most risk genes have roles in regulation of gene expression or neuronal communication (i.e., mutations effect neurodevelopmental and neurophysiological changes), and 13 fall within loci recurrently hit by copy number variants. In cells from the human cortex, expression of risk genes is enriched in excitatory and inhibitory neuronal lineages, consistent with multiple paths to an excitatory-inhibitory imbalance underlying ASD.

A framework for an evidence-based gene list relevant to autism spectrum disorder.

Autism spectrum disorder (ASD) is often grouped with other brain-related phenotypes into a broader category of neurodevelopmental disorders (NDDs). In clinical practice, providers need to decide which genes to test in individuals with ASD phenotypes, which requires an understanding of the level of evidence for individual NDD genes that supports an association with ASD. Consensus is currently lacking about which NDD genes have sufficient evidence to support a relationship to ASD. Estimates of the number of genes relevant to ASD differ greatly among research groups and clinical sequencing panels, varying from a few to several hundred. This Roadmap discusses important considerations necessary to provide an evidence-based framework for the curation of NDD genes based on the level of information supporting a clinically relevant relationship between a given gene and ASD.

Successful Electroconvulsive Therapy in a Patient With Catatonia and Maternal Duplication 15q11-13 Syndrome.

ABSTRACT: The 15q11-q13 chromosomal region contains genes encoding for GABA-A receptor subunits and is a known region of epigenetic modification associated with the development of neurodevelopmental disorders. The presence of at least one additional copy of the maternal 15q11-q13 results in a syndrome (maternal dup15q) characterized by intellectual disability, autism spectrum disorder, mood disorders, and epilepsy. Catatonia is a serious syndrome of behavioral and motor dysfunction, which occurs across a variety of psychiatric, neurologic, and general medical conditions, which has successfully been treated with benzodiazepines and electroconvulsive therapy. In this case report, we describe the treatment course of a patient with established maternal dup 15q with comorbid intellectual disability, autism spectrum disorder, bipolar mood disorder, and juvenile epilepsy who developed hypokinetic catatonia refractory to high-dose benzodiazepine therapy. In contrast with benzodiazepine treatment, electroconvulsive therapy resulted in rapid improvement in catatonic symptoms and return to premorbid baseline. This case suggests that electroconvulsive therapy can be safely delivered for some patients with maternal dup 15q and may be rapidly effective when benzodiazepine treatment results in inadequate symptom improvement.

Clinical and neurocognitive issues associated with Bosch-Boonstra-Schaaf optic atrophy syndrome: A case study.

Nuclear receptor subfamily 2 group F member 1 (NR2F1) is an orphan receptor and transcriptional regulator that is involved in neurogenesis, visual processing and development, and cortical patterning. Alterations in NR2F1 cause Bosch-Boonstra-Schaaf optic atrophy syndrome (BBSOAS), a recently described autosomal dominant disorder characterized by intellectual and developmental disabilities and optic atrophy. This study describes the clinical and neurocognitive features of an individual with a de novo nonsense variant in NR2F1 (NM_005654.5:c.82C > T, p.Gln28*), identified by whole exome sequencing. The patient was diagnosed with autism spectrum disorder (ASD) and unlike most previously reported cases, he had no developmental delay, superior verbal abilities (verbal IQ = 141), and high educational attainment despite reduced nonverbal abilities (nonverbal IQ = 63). He had optic nerve hypoplasia with minimal visual impairment as well as mild dysmorphic features. Compared to both age-matched individuals with ASD and healthy controls, the patient showed reductions in manual motor speed, accuracy of saccadic eye movements, and rates of successful behavioral response inhibition. Although the majority of previously reported cases of BBSOAS have been associated with more global intellectual dysfunction, we report on a patient with selective disruption of nonverbal abilities and superior verbal abilities.

Behavioral characterization of dup15q syndrome: Toward meaningful endpoints for clinical trials.

Duplication of 15q11.2-q13.1 (dup15q syndrome) is one of the most common copy number variations associated with autism spectrum disorders (ASD) and intellectual disability (ID). As with many neurogenetic conditions, accurate behavioral assessment is challenging due to the level of impairment and heterogeneity across individuals. Large-scale phenotyping studies are necessary to inform future clinical trials in this and similar ID syndromes. This study assessed developmental and behavioral characteristics in a large cohort of children with dup15q syndrome, and examined differences based on genetic subtype and epilepsy status. Participants included 62 children (2.5-18 years). Across individuals, there was a wide range of abilities. Although adaptive behavior was strongly associated with cognitive ability, adaptive abilities were higher than cognitive scores. Measures of ASD symptoms were associated with cognitive ability, while parent report of challenging behavior was not. Both genetic subtype and epilepsy were related to degree of impairment across cognitive, language, motor, and adaptive domains. Children with isodicentric duplications and epilepsy showed the greatest impairment, while children with interstitial duplications showed the least. On average, participants with epilepsy experienced seizures over 53% of their lives, and half of children with epilepsy had infantile spasms. Parents of children with isodicentric duplications reported more concerns regarding challenging behaviors. Future trials in ID syndromes should employ a flexible set of assessments, allowing each participant to receive assessments that capture their skills. Multiple sources of information should be considered, and the impact of language and cognitive ability should be taken into consideration when interpreting results.

Phenotypic association of 15q11.2 CNVs of the region of breakpoints 1-2 (BP1-BP2) in a large cohort of samples referred for genetic diagnosis.

In view of conflicting reports on the pathogenicity of 15q11.2 CNVs of the breakpoints 1-2 (BP1-BP2) region and lack of association with a specific phenotype, we collected phenotypic data on 51,462 patients referred for genetic testing at two centers (Magee-Womens Hospital of UPMC and Baylor Genetics Laboratories, Baylor College of Medicine). Using array CGH, 262 patients with deletions and 215 with duplications were identified and tested for their association with four phenotypes (developmental delay, dysmorphic features, autism group of disorders, and epilepsy/seizures). Only association of deletions with dysmorphic features was observed (P = 0.013) with low penetrance (3.8%). Our results, viewed in the context of other reports suggesting the lack of a clear phenotypic outcome, underscore the need for detailed phenotypic studies to better understand the pathogenicity of 15q11.2 (BP1-BP2) CNVs.

Cognitive mechanisms of inhibitory control deficits in autism spectrum disorder.

BACKGROUND: Inhibitory control deficits are common in autism spectrum disorder (ASD) and associated with more severe repetitive behaviors. Inhibitory control deficits may reflect slower execution of stopping processes, or a reduced ability to delay the onset of behavioral responses in contexts of uncertainty. Previous studies have documented relatively spared stopping processes in ASD, but whether inhibitory control deficits in ASD reflect failures to delay response onset has not been systematically assessed. Further, while improvements in stopping abilities and response slowing are seen through adolescence/early adulthood in health, their development in ASD is less clear. METHODS: A stop-signal test (SST) was administered to 121 individuals with ASD and 76 age and IQ-matched healthy controls (ages 5-28). This test included 'GO trials' in which participants pressed a button when a peripheral target appeared and interleaved 'STOP trials' in which they were cued to inhibit button-presses when a stop-signal appeared at variable times following the GO cue. STOP trial accuracy, RT of the stopping process (SSRT), and reaction time (RT) slowing during GO trials were examined. RESULTS: Relative to controls, individuals with ASD had reduced accuracy on STOP trials. SSRTs were similar across control and ASD participants, but RT slowing was reduced in patients compared to controls. Age-related increases in stopping ability and RT slowing were attenuated in ASD. Reduced stopping accuracy and RT slowing were associated with more severe repetitive behaviors in ASD. DISCUSSION: Our findings show that inhibitory control deficits in ASD involve failures to strategically delay behavioral response onset. These results suggest that reduced preparatory behavioral control may underpin inhibitory control deficits as well as repetitive behaviors in ASD. Typical age-related improvements in inhibitory control during late childhood/early adolescence are reduced in ASD, highlighting an important developmental window during which treatments may mitigate cognitive alterations contributing to repetitive behaviors.

STAMS: STRING-assisted module search for genome wide association studies and application to autism.

MOTIVATION: Analyzing genome wide association data in the context of biological pathways helps us understand how genetic variation influences phenotype and increases power to find associations. However, the utility of pathway-based analysis tools is hampered by undercuration and reliance on a distribution of signal across all of the genes in a pathway. Methods that combine genome wide association results with genetic networks to infer the key phenotype-modulating subnetworks combat these issues, but have primarily been limited to network definitions with yes/no labels for gene-gene interactions. A recent method (EW_dmGWAS) incorporates a biological network with weighted edge probability by requiring a secondary phenotype-specific expression dataset. In this article, we combine an algorithm for weighted-edge module searching and a probabilistic interaction network in order to develop a method, STAMS, for recovering modules of genes with strong associations to the phenotype and probable biologic coherence. Our method builds on EW_dmGWAS but does not require a secondary expression dataset and performs better in six test cases. RESULTS: We show that our algorithm improves over EW_dmGWAS and standard gene-based analysis by measuring precision and recall of each method on separately identified associations. In the Wellcome Trust Rheumatoid Arthritis study, STAMS-identified modules were more enriched for separately identified associations than EW_dmGWAS (STAMS P-value 3.0 × 10-4; EW_dmGWAS- P-value = 0.8). We demonstrate that the area under the Precision-Recall curve is 5.9 times higher with STAMS than EW_dmGWAS run on the Wellcome Trust Type 1 Diabetes data. AVAILABILITY AND IMPLEMENTATION: STAMS is implemented as an R package and is freely available at https://simtk.org/projects/stams CONTACT: rbaltman@stanford.eduSupplementary information: Supplementary data are available at Bioinformatics online.

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.

Feedforward and feedback motor control abnormalities implicate cerebellar dysfunctions in autism spectrum disorder.

Sensorimotor abnormalities are common in autism spectrum disorder (ASD) and among the earliest manifestations of the disorder. They have been studied far less than the social-communication and cognitive deficits that define ASD, but a mechanistic understanding of sensorimotor abnormalities in ASD may provide key insights into the neural underpinnings of the disorder. In this human study, we examined rapid, precision grip force contractions to determine whether feedforward mechanisms supporting initial motor output before sensory feedback can be processed are disrupted in ASD. Sustained force contractions also were examined to determine whether reactive adjustments to ongoing motor behavior based on visual feedback are altered. Sustained force was studied across multiple force levels and visual gains to assess motor and visuomotor mechanisms, respectively. Primary force contractions of individuals with ASD showed greater peak rate of force increases and large transient overshoots. Individuals with ASD also showed increased sustained force variability that scaled with force level and was more severe when visual gain was highly amplified or highly degraded. When sustaining a constant force level, their reactive adjustments were more periodic than controls, and they showed increased reliance on slower feedback mechanisms. Feedforward and feedback mechanism alterations each were associated with more severe social-communication impairments in ASD. These findings implicate anterior cerebellar circuits involved in feedforward motor control and posterior cerebellar circuits involved in transforming visual feedback into precise motor adjustments in ASD.

Intellectual disability is associated with increased runs of homozygosity in simplex autism.

Intellectual disability (ID), often attributed to autosomal-recessive mutations, occurs in 40% of autism spectrum disorders (ASDs). For this reason, we conducted a genome-wide analysis of runs of homozygosity (ROH) in simplex ASD-affected families consisting of a proband diagnosed with ASD and at least one unaffected sibling. In these families, probands with an IQ ≤ 70 show more ROH than their unaffected siblings, whereas probands with an IQ > 70 do not show this excess. Although ASD is far more common in males than in females, the proportion of females increases with decreasing IQ. Our data do support an association between ROH burden and autism diagnosis in girls; however, we are not able to show that this effect is independent of low IQ. We have also discovered several autism candidate genes on the basis of finding (1) a single gene that is within an ROH interval and that is recurrent in autism or (2) a gene that is within an autism ROH block and that harbors a homozygous, rare deleterious variant upon analysis of exome-sequencing data. In summary, our data suggest a distinct genetic architecture for participants with autism and co-occurring intellectual disability and that this architecture could involve a role for recessively inherited loci for this autism subgroup.

Consensus Genotyper for Exome Sequencing (CGES): improving the quality of exome variant genotypes.

MOTIVATION: The development of cost-effective next-generation sequencing methods has spurred the development of high-throughput bioinformatics tools for detection of sequence variation. With many disparate variant-calling algorithms available, investigators must ask, 'Which method is best for my data?' Machine learning research has shown that so-called ensemble methods that combine the output of multiple models can dramatically improve classifier performance. Here we describe a novel variant-calling approach based on an ensemble of variant-calling algorithms, which we term the Consensus Genotyper for Exome Sequencing (CGES). CGES uses a two-stage voting scheme among four algorithm implementations. While our ensemble method can accept variants generated by any variant-calling algorithm, we used GATK2.8, SAMtools, FreeBayes and Atlas-SNP2 in building CGES because of their performance, widespread adoption and diverse but complementary algorithms. RESULTS: We apply CGES to 132 samples sequenced at the Hudson Alpha Institute for Biotechnology (HAIB, Huntsville, AL) using the Nimblegen Exome Capture and Illumina sequencing technology. Our sample set consisted of 40 complete trios, two families of four, one parent-child duo and two unrelated individuals. CGES yielded the fewest total variant calls (N(CGES) = 139° 897), the highest Ts/Tv ratio (3.02), the lowest Mendelian error rate across all genotypes (0.028%), the highest rediscovery rate from the Exome Variant Server (EVS; 89.3%) and 1000 Genomes (1KG; 84.1%) and the highest positive predictive value (PPV; 96.1%) for a random sample of previously validated de novo variants. We describe these and other quality control (QC) metrics from consensus data and explain how the CGES pipeline can be used to generate call sets of varying quality stringency, including consensus calls present across all four algorithms, calls that are consistent across any three out of four algorithms, calls that are consistent across any two out of four algorithms or a more liberal set of all calls made by any algorithm. AVAILABILITY AND IMPLEMENTATION: To enable accessible, efficient and reproducible analysis, we implement CGES both as a stand-alone command line tool available for download in GitHub and as a set of Galaxy tools and workflows configured to execute on parallel computers. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A haplotype-based framework for group-wise transmission/disequilibrium tests for rare variant association analysis.

MOTIVATION: A major focus of current sequencing studies for human genetics is to identify rare variants associated with complex diseases. Aside from reduced power of detecting associated rare variants, controlling for population stratification is particularly challenging for rare variants. Transmission/disequilibrium tests (TDT) based on family designs are robust to population stratification and admixture, and therefore provide an effective approach to rare variant association studies to eliminate spurious associations. To increase power of rare variant association analysis, gene-based collapsing methods become standard approaches for analyzing rare variants. Existing methods that extend this strategy to rare variants in families usually combine TDT statistics at individual variants and therefore lack the flexibility of incorporating other genetic models. RESULTS: In this study, we describe a haplotype-based framework for group-wise TDT (gTDT) that is flexible to encompass a variety of genetic models such as additive, dominant and compound heterozygous (CH) (i.e. recessive) models as well as other complex interactions. Unlike existing methods, gTDT constructs haplotypes by transmission when possible and inherently takes into account the linkage disequilibrium among variants. Through extensive simulations we showed that type I error was correctly controlled for rare variants under all models investigated, and this remained true in the presence of population stratification. Under a variety of genetic models, gTDT showed increased power compared with the single marker TDT. Application of gTDT to an autism exome sequencing data of 118 trios identified potentially interesting candidate genes with CH rare variants. AVAILABILITY AND IMPLEMENTATION: We implemented gTDT in C++ and the source code and the detailed usage are available on the authors' website (https://medschool.vanderbilt.edu/cgg). CONTACT: bingshan.li@vanderbilt.edu or wei.chen@chp.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Separating Family-Level and Direct Exposure Effects of Smoking During Pregnancy on Offspring Externalizing Symptoms: Bridging the Behavior Genetic and Behavior Teratologic Divide.

Maternal smoking during pregnancy (MSDP) has been robustly associated with externalizing problems and their developmental precursors in offspring in studies using behavioral teratologic designs (Wakschlag et al., Am J Public Health 92(6):966-974, 2002; Espy et al., Dev Psychol 47(1):153-169, 2011). In contrast, the use of behavior genetic approaches has shown that the effects commonly attributed to MSDP can be explained by family-level variables (D'Onofrio et al., Dev Psychopathol 20(01):139-164, 2008). Reconciling these conflicting findings requires integration of these study designs. We utilize longitudinal data on a preschool proband and his/her sibling from the Midwest Infant Development Study-Preschool (MIDS-P) to test for teratologic and family level effects of MSDP. We find considerable variation in prenatal smoking patterns both within and across pregnancies within families, indicating that binary smoking measures are not sufficiently capturing exposure. Structural equation models indicate that both conduct disorder and oppositional defiant disorder symptoms showed unique effects of MSDP over and above family level effects. Blending high quality exposure measurement with a within-family design suggests that it is premature to foreclose the possibility of a teratologic effect of MSDP on externalizing problems. Implications and recommendations for future studies are discussed.

CYP2A6 Longitudinal Effects in Young Smokers.

INTRODUCTION: The present study sought to identify time-dependent within-participant effects of CYP2A6 genotypes on smoking frequency and nicotine dependence in young smokers. METHODS: Predicted nicotine metabolic rate based on CYP2A6 diplotypes (CYP2A6 diplotype predicted rate [CDPR]) was partitioned into Normal, Intermediate, and Slow categories using a metabolism metric. Growth-curve models characterized baseline and longitudinal CDPR effects with data from eight longitudinal assessments during a 6-year period (from approximately age 16-22) in young smokers of European descent (N = 296, 57% female) who had smoked less than 100 cigarettes lifetime at baseline and more than that amount by Year 6. Phenotypes were number of days smoked during the previous 30 days and a youth version of the Nicotine Dependence Syndrome Scale (NDSS). A zero-inflated Poisson growth-curve model was used to account for the preponderance of zero days smoked. RESULTS: At baseline, Intermediate CDPR was a risk factor relative to both Normal and Slow CDPR for smoking frequency and the NDSS. Slow CDPR was associated with the highest probability of smoking discontinuation at baseline. However, due to CDPR time trend differences, by young adulthood these baseline effects had been reordered such that the greatest risks for smoking frequency and the NDSS were associated with Normal CDPR. CONCLUSIONS: Reduced metabolism CYP2A6 genotypes are associated with both risk and protective effects in novice smokers. However, differences in the time-by-CDPR effects result in a reordering of genotype effects such that normal metabolism becomes the risk variant by young adulthood, as has been reliably reported in older smokers.

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.

Partitioning the heritability of Tourette syndrome and obsessive compulsive disorder reveals differences in genetic architecture.

The direct estimation of heritability from genome-wide common variant data as implemented in the program Genome-wide Complex Trait Analysis (GCTA) has provided a means to quantify heritability attributable to all interrogated variants. We have quantified the variance in liability to disease explained by all SNPs for two phenotypically-related neurobehavioral disorders, obsessive-compulsive disorder (OCD) and Tourette Syndrome (TS), using GCTA. Our analysis yielded a heritability point estimate of 0.58 (se = 0.09, p = 5.64e-12) for TS, and 0.37 (se = 0.07, p = 1.5e-07) for OCD. In addition, we conducted multiple genomic partitioning analyses to identify genomic elements that concentrate this heritability. We examined genomic architectures of TS and OCD by chromosome, MAF bin, and functional annotations. In addition, we assessed heritability for early onset and adult onset OCD. Among other notable results, we found that SNPs with a minor allele frequency of less than 5% accounted for 21% of the TS heritability and 0% of the OCD heritability. Additionally, we identified a significant contribution to TS and OCD heritability by variants significantly associated with gene expression in two regions of the brain (parietal cortex and cerebellum) for which we had available expression quantitative trait loci (eQTLs). Finally we analyzed the genetic correlation between TS and OCD, revealing a genetic correlation of 0.41 (se = 0.15, p = 0.002). These results are very close to previous heritability estimates for TS and OCD based on twin and family studies, suggesting that very little, if any, heritability is truly missing (i.e., unassayed) from TS and OCD GWAS studies of common variation. The results also indicate that there is some genetic overlap between these two phenotypically-related neuropsychiatric disorders, but suggest that the two disorders have distinct genetic architectures.

Escitalopram pharmacogenetics: CYP2C19 relationships with dosing and clinical outcomes in autism spectrum disorder.

BACKGROUND AND AIM: Selective serotonin reuptake inhibitors such as escitalopram are commonly used to treat patients with autism spectrum disorder (ASD), but there are individual differences in treatment response and tolerability. CYP2C19 encodes the primary enzyme responsible for escitalopram metabolism and we investigated whether polymorphisms in CYP2C19 were related to symptoms and dosing in a pharmacogenetic study of ASD. PARTICIPANTS AND METHODS: Participants completed the Aberrant Behavior Checklist--Community Version (ABC-CV) weekly for 6 weeks. Escitalopram was initiated at a dose of 2.5 mg per day, with weekly increases to 20 mg unless intolerable side-effects occurred. Three CYP2C19 metabolizer groups, including ultrarapid, extensive, and reduced metabolizers, were examined in relation to symptom improvement and tolerated dose. RESULTS: ABC-CV scores improved over the course of treatment (P<0.0001). No differences were identified in the rate of improvement across metabolizer groups for the ABC-CV irritability subscale, which was the primary outcome for clinical symptoms. There was a trend for a metabolizer group by time interaction with respect to dose (P=0.10). This interaction was driven by the linear rate of change from week 1 to study endpoint between the reduced metabolizers and ultrarapid metabolizer groups (P=0.05). Post-hoc analyses identified significant differences in the rate of dose escalation between ultrarapid metabolizers and extensive metabolizers and for ultrarapid metabolizers compared with reduced metabolizers (P's<0.04), whereby ultrarapid metabolizers showed a slower rate of change in dose over time. CONCLUSION: CYP2C19 ultrarapid metabolizers were associated with reduced tolerance to a fixed titration schedule of open-label escitalopram in this ASD study sample. Possible explanations may involve the altered kinetics of faster metabolizers or previously unknown activities of escitalopram metabolites.

Environmental and state-level regulatory factors affect the incidence of autism and intellectual disability.

Many factors affect the risks for neurodevelopmental maladies such as autism spectrum disorders (ASD) and intellectual disability (ID). To compare environmental, phenotypic, socioeconomic and state-policy factors in a unified geospatial framework, we analyzed the spatial incidence patterns of ASD and ID using an insurance claims dataset covering nearly one third of the US population. Following epidemiologic evidence, we used the rate of congenital malformations of the reproductive system as a surrogate for environmental exposure of parents to unmeasured developmental risk factors, including toxins. Adjusted for gender, ethnic, socioeconomic, and geopolitical factors, the ASD incidence rates were strongly linked to population-normalized rates of congenital malformations of the reproductive system in males (an increase in ASD incidence by 283% for every percent increase in incidence of malformations, 95% CI: [91%, 576%], p<6×10(-5)). Such congenital malformations were barely significant for ID (94% increase, 95% CI: [1%, 250%], p = 0.0384). Other congenital malformations in males (excluding those affecting the reproductive system) appeared to significantly affect both phenotypes: 31.8% ASD rate increase (CI: [12%, 52%], p<6×10(-5)), and 43% ID rate increase (CI: [23%, 67%], p<6×10(-5)). Furthermore, the state-mandated rigor of diagnosis of ASD by a pediatrician or clinician for consideration in the special education system was predictive of a considerable decrease in ASD and ID incidence rates (98.6%, CI: [28%, 99.99%], p = 0.02475 and 99% CI: [68%, 99.99%], p = 0.00637 respectively). Thus, the observed spatial variability of both ID and ASD rates is associated with environmental and state-level regulatory factors; the magnitude of influence of compound environmental predictors was approximately three times greater than that of state-level incentives. The estimated county-level random effects exhibited marked spatial clustering, strongly indicating existence of as yet unidentified localized factors driving apparent disease incidence. Finally, we found that the rates of ASD and ID at the county level were weakly but significantly correlated (Pearson product-moment correlation 0.0589, p = 0.00101), while for females the correlation was much stronger (0.197, p<2.26×10(-16)).

An ontology for Autism Spectrum Disorder (ASD) to infer ASD phenotypes from Autism Diagnostic Interview-Revised data.

OBJECTIVE: Our goal is to create an ontology that will allow data integration and reasoning with subject data to classify subjects, and based on this classification, to infer new knowledge on Autism Spectrum Disorder (ASD) and related neurodevelopmental disorders (NDD). We take a first step toward this goal by extending an existing autism ontology to allow automatic inference of ASD phenotypes and Diagnostic & Statistical Manual of Mental Disorders (DSM) criteria based on subjects' Autism Diagnostic Interview-Revised (ADI-R) assessment data. MATERIALS AND METHODS: Knowledge regarding diagnostic instruments, ASD phenotypes and risk factors was added to augment an existing autism ontology via Ontology Web Language class definitions and semantic web rules. We developed a custom Protégé plugin for enumerating combinatorial OWL axioms to support the many-to-many relations of ADI-R items to diagnostic categories in the DSM. We utilized a reasoner to infer whether 2642 subjects, whose data was obtained from the Simons Foundation Autism Research Initiative, meet DSM-IV-TR (DSM-IV) and DSM-5 diagnostic criteria based on their ADI-R data. RESULTS: We extended the ontology by adding 443 classes and 632 rules that represent phenotypes, along with their synonyms, environmental risk factors, and frequency of comorbidities. Applying the rules on the data set showed that the method produced accurate results: the true positive and true negative rates for inferring autistic disorder diagnosis according to DSM-IV criteria were 1 and 0.065, respectively; the true positive rate for inferring ASD based on DSM-5 criteria was 0.94. DISCUSSION: The ontology allows automatic inference of subjects' disease phenotypes and diagnosis with high accuracy. CONCLUSION: The ontology may benefit future studies by serving as a knowledge base for ASD. In addition, by adding knowledge of related NDDs, commonalities and differences in manifestations and risk factors could be automatically inferred, contributing to the understanding of ASD pathophysiology.