Phenotypically driven subgroups of ASD display distinct metabolomic profiles.

Autism Spectrum Disorder (ASD) is a heterogeneous condition that includes a broad range of characteristics and associated comorbidities; however, the biology underlying the variability in phenotypes is not well understood. As ASD impacts approximately 1 in 100 children globally, there is an urgent need to better understand the biological mechanisms that contribute to features of ASD. In this study, we leveraged rich phenotypic and diagnostic information related to ASD in 2001 individuals aged 4 to 17 years from the Simons Simplex Collection to derive phenotypically driven subgroups and investigate their respective metabolomes. We performed hierarchical clustering on 40 phenotypes spanning four ASD clinical domains, resulting in three subgroups with distinct phenotype patterns. Using global plasma metabolomic profiling generated by ultrahigh-performance liquid chromatography mass spectrometry, we characterized the metabolome of individuals in each subgroup to interrogate underlying biology related to the subgroups. Subgroup 1 included children with the least maladaptive behavioral traits (N = 862); global decreases in lipid metabolites and concomitant increases in amino acid and nucleotide pathways were observed for children in this subgroup. Subgroup 2 included children with the highest degree of challenges across all phenotype domains (N = 631), and their metabolome profiles demonstrated aberrant metabolism of membrane lipids and increases in lipid oxidation products. Subgroup 3 included children with maladaptive behaviors and co-occurring conditions that showed the highest IQ scores (N = 508); these individuals had increases in sphingolipid metabolites and fatty acid byproducts. Overall, these findings indicated distinct metabolic patterns within ASD subgroups, which may reflect the biological mechanisms giving rise to specific patterns of ASD characteristics. Our results may have important clinical applications relevant to personalized medicine approaches towards managing ASD symptoms.

de novo variant calling identifies cancer mutation signatures in the 1000 Genomes Project.

Detection of de novo variants (DNVs) is critical for studies of disease-related variation and mutation rates. To accelerate DNV calling, we developed a graphics processing units-based workflow. We applied our workflow to whole-genome sequencing data from three parent-child sequenced cohorts including the Simons Simplex Collection (SSC), Simons Foundation Powering Autism Research (SPARK), and the 1000 Genomes Project (1000G) that were sequenced using DNA from blood, saliva, and lymphoblastoid cell lines (LCLs), respectively. The SSC and SPARK DNV callsets were within expectations for number of DNVs, percent at CpG sites, phasing to the paternal chromosome of origin, and average allele balance. However, the 1000G DNV callset was not within expectations and contained excessive DNVs that are likely cell line artifacts. Mutation signature analysis revealed 30% of 1000G DNV signatures matched B-cell lymphoma. Furthermore, we found variants in DNA repair genes and at Clinvar pathogenic or likely-pathogenic sites and significant excess of protein-coding DNVs in IGLL5; a gene known to be involved in B-cell lymphomas. Our study provides a new rapid DNV caller for the field and elucidates important implications of using sequencing data from LCLs for reference building and disease-related projects.

Data-driven dissection of the fever effect in autism spectrum disorder.

Some individuals with autism spectrum disorder (ASD) demonstrate marked behavioral improvements during febrile episodes, in what is perhaps the only present-day means of modulating the core ASD phenotype. Understanding the nature of this so-called fever effect is therefore essential for leveraging this natural temporary relief of symptoms to a sustained efficacious intervention. Toward this goal, we used machine learning to analyze the rich clinical data of the Simons Simplex Collection, in which one out of every six children with ASD was reported to improve during febrile episodes, across multiple ASD domains. Reported behavioral improvements during febrile episodes were associated with maternal infection in pregnancy (OR = 1.7, 95% CI = [1.42, 2.03], P = 4.24 × 10-4 ) and gastrointestinal (GI) dysfunction (OR = 1.46, 95% CI = [1.15, 1.81], P = 1.94 × 10-3 ). Family members of children reported to improve when febrile have an increased prevalence of autoimmune disorders (OR = 1.43, 95% CI = [1.23, 1.67], P = 3.0 × 10-6 ), language disorders (OR = 1.63, 95% CI = [1.29, 2.04], P = 2.5 × 10-5 ), and neuropsychiatric disorders (OR = 1.59, 95% CI = [1.34, 1.89], P < 1 × 10-6 ). Since both GI abnormalities and maternal immune activation have been linked to ASD via proinflammatory cytokines, these results might suggest a possible involvement of immune dysregulation in the fever effect, consistent with findings in mouse models. This work advances our understanding of the fever-responsive ASD subtype and motivates the future studies to directly test the link between proinflammatory cytokines and behavioral modifications in individuals with ASD.

Genetic control of mRNA splicing as a potential mechanism for incomplete penetrance of rare coding variants.

Exonic variants present some of the strongest links between genotype and phenotype. However, these variants can have significant inter-individual pathogenicity differences, known as variable penetrance. In this study, we propose a model where genetically controlled mRNA splicing modulates the pathogenicity of exonic variants. By first cataloging exonic inclusion from RNA-sequencing data in GTEx V8, we find that pathogenic alleles are depleted on highly included exons. Using a large-scale phased whole genome sequencing data from the TOPMed consortium, we observe that this effect may be driven by common splice-regulatory genetic variants, and that natural selection acts on haplotype configurations that reduce the transcript inclusion of putatively pathogenic variants, especially when limiting to haploinsufficient genes. Finally, we test if this effect may be relevant for autism risk using families from the Simons Simplex Collection, but find that splicing of pathogenic alleles has a penetrance reducing effect here as well. Overall, our results indicate that common splice-regulatory variants may play a role in reducing the damaging effects of rare exonic variants.

Variations in Genes Related to Sleep Patterns in Children With Autism Spectrum Disorder.

BACKGROUND: Sleep disturbance is a frequent comorbidity in children with autism spectrum disorder (ASD), affecting an estimated 40-80% of cases. Previous reports have shown relationships between several circadian rhythm-related genes and sleep problems in ASD. The purpose of the present study was to relate variation in and around melatonin synthesis and suprachiasmatic nucleus genes to sleep problems in a large sample of children with ASD. METHOD: This secondary analysis used existing genotypic and phenotypic data for 2,065 children, aged 4-18 years, from the Simons Simplex Collection (SSC). Sleep problems were measured with the SSC Sleep Interview. Expression quantitative trait loci and single nucleotide polymorphisms in 25 circadian genes were chosen primarily for their impact on expression levels of target genes in the brain. Associations between variants and composite sleep problems, nighttime problems, daytime problems, and sleep duration problems were calculated using logistic regression analysis. Age, sex, nonverbal IQ, ASD severity, gastrointestinal distress, seizures, and ancestry were included as covariates. Transmission disequilibrium tests were performed to test for overtransmission of alleles in the same variants. RESULTS: No significant associations or transmission disequilibrium were found between gene variants and sleep problems in this sample of children with ASD. CONCLUSION: Variation in expression of investigated genes in the melatonin synthesis and suprachiasmatic nucleus pathways did not have notable impacts on sleep problems in this large sample of children with ASD. Future research could explore translational and posttranslational effects of these genes or the effects of genes in other sleep-homeostasis pathways on sleep patterns.

Children with autism spectrum disorder who improve with fever: Insights from the Simons Simplex Collection.

Literature indicates that some children with ASD may show behavioral improvements during fever; however, little is known about the behavioral profiles of these children. This study aims to (a) investigate the subset of children who show parent-reported behavioral improvements associated with fever and (b) compare the demographic, behavioral, and genetic characteristics of this subset of children to children whose parents report no change during fever. Parents of 2,152 children from the Simons Simplex Collection provided information about whether and in which areas their child improved during fever. Children were randomly assigned into discovery or replication samples. In discovery analyses, children who reportedly improved with fever (Improve Group) were compared to those who reportedly did not improve (No Improve Group) on demographics, medical history, ASD symptoms, adaptive skills, and presence of de novo ASD-associated mutations. Significant and marginal results from discovery analyses were tested in the replication sample. Parent reports of 17% of children indicated improvements during fever across a range of domains. Discovery and replication analyses revealed that the Improve Group had significantly lower non-verbal cognitive skills (NVIQ) and language levels and more repetitive behaviors. Groups did not differ on demographic variables, parent-report of current ASD symptoms or the presence of de novo mutations. Understanding the profiles of children who improve during episodes of fever may provide insights into innovative treatments for ASD. Autism Res 2018, 11: 175-184. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: This study explored characteristics of children with ASD who are reported to improve during fever. Parents of 17% of children with ASD report improvements across a range of domains during fever including cognition, communication, repetitive behaviors, social interaction, and behavior. Children who are reported to improve during fever have significantly lower non-verbal cognitive skills and language levels and more repetitive behaviors. Understanding the profiles of children who improve during episodes of fever may provide insights into new treatments for ASD.

Case-control meta-analysis of blood DNA methylation and autism spectrum disorder.

Background: Several reports have suggested a role for epigenetic mechanisms in ASD etiology. Epigenome-wide association studies (EWAS) in autism spectrum disorder (ASD) may shed light on particular biological mechanisms. However, studies of ASD cases versus controls have been limited by post-mortem timing and severely small sample sizes. Reports from in-life sampling of blood or saliva have also been very limited in sample size and/or genomic coverage. We present the largest case-control EWAS for ASD to date, combining data from population-based case-control and case-sibling pair studies. Methods: DNA from 968 blood samples from children in the Study to Explore Early Development (SEED 1) was used to generate epigenome-wide array DNA methylation (DNAm) data at 485,512 CpG sites for 453 cases and 515 controls, using the Illumina 450K Beadchip. The Simons Simplex Collection (SSC) provided 450K array DNAm data on an additional 343 cases and their unaffected siblings. We performed EWAS meta-analysis across results from the two data sets, with adjustment for sex and surrogate variables that reflect major sources of biological variation and technical confounding such as cell type, batch, and ancestry. We compared top EWAS results to those from a previous brain-based analysis. We also tested for enrichment of ASD EWAS CpGs for being targets of meQTL associations using available SNP genotype data in the SEED sample. Findings: In this meta-analysis of blood-based DNA from 796 cases and 858 controls, no single CpG met a Bonferroni discovery threshold of p < 1.12 × 10- 7. Seven CpGs showed differences at p < 1 × 10- 5 and 48 at 1 × 10- 4. Of the top 7, 5 showed brain-based ASD associations as well, often with larger effect sizes, and the top 48 overall showed modest concordance (r = 0.31) in direction of effect with cerebellum samples. Finally, we observed suggestive evidence for enrichment of CpG sites controlled by SNPs (meQTL targets) among the EWAS CpG hits, which was consistent across EWAS and meQTL discovery p value thresholds. Conclusions: No single CpG site showed a large enough DNAm difference between cases and controls to achieve epigenome-wide significance in this sample size. However, our results suggest the potential to observe disease associations from blood-based samples. Among the seven sites achieving suggestive statistical significance, we observed consistent, and stronger, effects at the same sites among brain samples. Discovery-oriented EWAS for ASD using blood samples will likely need even larger samples and unified genetic data to further understand DNAm differences in ASD.

Identification of Developmental and Behavioral Markers Associated With Genetic Abnormalities in Autism Spectrum Disorder.

OBJECTIVE: Aside from features associated with risk of neurogenetic syndromes in general (e.g., cognitive impairment), limited progress has been made in identifying phenotype-genotype relationships in autism spectrum disorder (ASD). The objective of this study was to extend work in the Simons Simplex Collection by comparing the phenotypic profiles of ASD probands with or without identified de novo loss of function mutations or copy number variants in high-confidence ASD-associated genes or loci. METHOD: Analyses preemptively accounted for documented differences in sex and IQ in affected individuals with de novo mutations by matching probands with and without these genetic events on sex, IQ, and age before comparing them on multiple behavioral domains. RESULTS: Children with de novo mutations (N=112) had a greater likelihood of motor delay during early development (later age at walking), but they were less impaired on certain measures of ASD core symptoms (parent-rated social communication abnormalities and clinician-rated diagnostic certainty about ASD) in later childhood. These children also showed relative strengths in verbal and language abilities, including a smaller discrepancy between nonverbal and verbal IQ and a greater likelihood of having achieved fluent language (i.e., regular use of complex sentences). CONCLUSIONS: Children with ASD with de novo mutations may exhibit a "muted" symptom profile with respect to social communication and language deficits relative to those with ASD with no identified genetic abnormalities. Such findings suggest that examining early milestone differences and standardized testing results may be helpful in etiologic efforts, and potentially in clinical differentiation of various subtypes of ASD, but only if developmental and demographic variables are properly accounted for first.

VARPRISM: incorporating variant prioritization in tests of de novo mutation association.

BACKGROUND: Patients with certain genetic diseases, such as autism spectrum disorder, have increased rates of de novo mutations within some protein-coding genes. RESULTS: We introduce the VARiant PRIoritization SuM (VARPRISM), a software package which incorporates functional variant prioritization information to improve the power to detect de novo mutations influencing disease risk. VARPRISM evaluates the consequence of any given exonic mutation on the protein sequence to estimate the likelihood that the mutation is benign or damaging and conducts a likelihood ratio test on the gene level. We analyzed the Simons Simplex Collection of 2508 parent-offspring autism trios using VARPRISM, replicating 44 genes previously implicated in autism susceptibility and identifying 20 additional candidate genes, including MYO1E, KCND3, PDCD1, DLX3, and TSPAN4 (false discovery rate < 0.3). CONCLUSION: By incorporating functional predictions, VARPRISM improved the statistical power to identify de novo mutations increasing disease risks. VARPRISM is available at http://www.hufflab.org/software/VARPRISM .

Psychotropic medication use among children with autism spectrum disorders within the Simons Simplex Collection: are core features of autism spectrum disorder related?

Psychotropic medication use and its relationship to autism spectrum core features were examined in a well-characterized but nonstratified North American sample (N = 1605) of children/adolescents diagnosed with autism spectrum disorders utilizing the Autism Diagnostic Observation Schedule and the Autism Diagnostic Interview-Revised, from the multisite Simons Simplex Collection. Analyses included (a) prevalence of psychotropic use (overall, and by classes), (b) correlations between prevalence of use and autism spectrum core features, age, and cognitive functioning, and (c) logistic regression to identify whether these factors were predictive of psychotropic use. Results indicated 41.7% ever used one or more classes of psychotropic medications, with attention deficit hyperactivity disorder medications used most. Small but significant correlations between psychotropic medication use and (a) social impairment (p < .001) and (b) repetitive behaviors (p < .001) were found. Overall, however, autism spectrum disorder core features are weakly related to medication use. Older children used more psychotropics (p < .001), and higher cognitive functioning was associated with less overall psychotropic use (p < .001). Logistic regression indicated that use of psychotropics was predicted by repetitive behaviors (both clinician-observed and parent-reported), age, and cognitive ability level. Limitations inherent to the Simons Simplex Collection sample, methodology, and the correlational analyses are discussed. Directions for future research include investigation of factors more influential than core symptoms on psychotropic treatment (e.g. parent perceptions, comorbid symptoms).