ASD-risk Genes Research Articles

Females with autism spectrum disorders show stronger DNA methylation signatures than males in perinatal tissues.

Autism spectrum disorder (ASD) comprises a group of neurodevelopmental conditions currently diagnosed by behavioral assessment in childhood, with reported underdiagnosis in females. Though diagnosis in early life is linked to improved outcomes, we currently lack objective screening tools for newborns. To address this gap, we sought to identify a sex-specific DNA methylation signature for ASD using perinatal tissues that reflect dysregulation in the brain. DNA methylation was assayed from ASD and typically developing (TD) newborn blood, umbilical cord blood, placenta, and post-mortem cortex samples using whole genome bisulfite sequencing (WGBS) in a total of 511 samples. We found that methylation levels of differentially methylated regions (DMRs) differentiated samples by ASD diagnosis in females more than males across the perinatal tissues. We tested three theories for ASD sex differences in newborn blood, finding epigenetic support for an X chromosome-related female protective effect, as well as a high replication rate of DMRs (48.1%) in females across two independent cohorts. In our pan-tissue analysis, three genes (X-linked BCOR, GALNT9, OPCML) mapped to ASD DMRs replicated in all four female tissues. ASD DMRs from all tissues were enriched for neuro-related processes (females) and SFARI ASD-risk genes (females and males). Overall, we found a highly replicated methylation signature of ASD in females across perinatal tissues that reflected dysregulation in the brain and involvement of X chromosome epigenetics. This comparative study of perinatal tissues shows the promise of newborn blood DNA methylation biomarkers for early detection of females at risk for ASD and emphasizes the importance of sex-stratification in ASD studies.

Phenotypic and genetic analysis of children with unexplained neurodevelopmental delay and neurodevelopmental comorbidities in a Chinese cohort using trio-based whole-exome sequencing

BackgroundTrio-based whole-exome sequencing (trio-WES) enables identification of pathogenic variants, including copy-number variants (CNVs), in children with unexplained neurodevelopmental delay (NDD) and neurodevelopmental comorbidities (NDCs), including autism spectrum disorder (ASD), epilepsy, and attention deficit hyperactivity disorder. Further phenotypic and genetic analysis on trio-WES-tested NDD-NDCs cases may help to identify key phenotypic factors related to higher diagnostic yield of using trio-WES and novel risk genes associated with NDCs in clinical settings.MethodsIn this study, we retrospectively performed phenotypic analysis on 163 trio-WES-tested NDD-NDCs children to determine the phenotypic differences between genetically diagnosed and non-genetically diagnosed groups. Additionally, we conducted genetic analysis of ASD genes with the help of Simons Foundation for Autism Research Institute (SFARI) Gene database to identify novel possible ASD-risk genes underlying genetic NDD conditions.ResultsAmong these 163 patients, pathogenic variants were identified in 82 cases (82/163, 50.3%), including 20 cases with CNVs. By comparing phenotypic variables between genetically diagnosed group (82 cases) and non-genetically diagnosed group (81 cases) with multivariate binary logistic regression analysis, we revealed that NDD-NDCs cases presenting with severe-profound NDD [53/82 vs 17/81, adjusted-OR (95%CI): 4.865 (2.213 – 10.694), adjusted-P < 0.001] or having multiple NDCs [26/82 vs 8/81, adjusted-OR (95%CI): 3.731 (1.399 – 9.950), adjusted-P = 0.009] or accompanying ASD [64/82 vs 35/81, adjusted-OR (95%CI): 3.256 (1.479 – 7.168), adjusted-P = 0.003] and head circumference abnormality [33/82 vs 11/81, adjusted-OR (95%CI): 2.788 (1.148 – 6.774), adjusted-P = 0.024] were more likely to have a genetic diagnosis using trio-WES. Moreover, 37 genes with monogenetic variants were identified in 48 patients genetically diagnosed with NDD-ASD, and 15 dosage-sensitive genes were identified in 16 individuals with NDD-ASD carrying CNVs. Most of those genes had been proven to be ASD-related genes. However, some of them (9 genes) were not proven sufficiently to correlate with ASD. By literature review and constructing protein-protein interaction networks among these 9 candidate ASD-risk genes and 102 established ASD genes obtained from the SFARI Gene database, we identified CUL4B, KCNH1, and PLA2G6 as novel possible ASD-risk genes underlying genetic NDD conditions.ConclusionsTrio-WES testing is recommended for patients with unexplained NDD-NDCs that have severe-profound NDD or multiple NDCs, particularly those with accompanying ASD and head circumference abnormality, as these independent factors may increase the likelihood of genetic diagnosis using trio-WES. Moreover, NDD patients with pathogenic variants in CUL4B, KCNH1 and PLA2G6 should be aware of potential risks of developing ASD during their disease courses.

Identification of a molecular network regulated by multiple ASD high risk genes.

Genetic sequencing has identified high-confidence ASD risk genes with loss-of-function mutations. How the haploinsufficiency of distinct ASD risk genes causes ASD remains to be elucidated. In this study, we examined the role of four top-ranking ASD risk genes, ADNP, KDM6B, CHD2, and MED13, in gene expression regulation. ChIP-seq analysis reveals that gene targets with the binding of these ASD risk genes at promoters are enriched in RNA processing and DNA repair. Many of these targets are found in ASD gene database (SFARI), and are involved in transcription regulation and chromatin remodeling. Common gene targets of these ASD risk genes include a network of high confidence ASD genes associated with gene expression regulation, such as CTNNB1 and SMARCA4. We further directly examined the transcriptional impact of the deficiency of these ASD risk genes. Our mRNA profiling with qPCR assays in cells with the knockdown of Adnp, Kdm6b, Chd2 or Med13 has revealed an intricate pattern of their cross-regulation, as well as their influence on the expression of other ASD genes. In addition, some synaptic genes, such as Snap25 and Nrxn1, are strongly regulated by deficiency of the four ASD risk genes, which could be through the direct binding at promoters or indirectly through the targets like Ctnnb1 or Smarca4. The identification of convergent and divergent gene targets that are regulated by multiple ASD risk genes will help to understand the molecular mechanisms underlying common and unique phenotypes associated with haploinsufficiency of ASD-associated genes.

Altered motor learning and coordination in mouse models of autism spectrum disorder.

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder with increasing prevalence. Over 1,000 risk genes have now been implicated in ASD, suggesting diverse etiology. However, the diagnostic criteria for the disorder still comprise two major behavioral domains - deficits in social communication and interaction, and the presence of restricted and repetitive patterns of behavior (RRBs). The RRBs associated with ASD include both stereotyped repetitive movements and other motor manifestations including changes in gait, balance, coordination, and motor skill learning. In recent years, the striatum, the primary input center of the basal ganglia, has been implicated in these ASD-associated motor behaviors, due to the striatum's role in action selection, motor learning, and habit formation. Numerous mouse models with mutations in ASD risk genes have been developed and shown to have alterations in ASD-relevant behaviors. One commonly used assay, the accelerating rotarod, allows for assessment of both basic motor coordination and motor skill learning. In this corticostriatal-dependent task, mice walk on a rotating rod that gradually increases in speed. In the extended version of this task, mice engage striatal-dependent learning mechanisms to optimize their motor routine and stay on the rod for longer periods. This review summarizes the findings of studies examining rotarod performance across a range of ASD mouse models, and the resulting implications for the involvement of striatal circuits in ASD-related motor behaviors. While performance in this task is not uniform across mouse models, there is a cohort of models that show increased rotarod performance. A growing number of studies suggest that this increased propensity to learn a fixed motor routine may reflect a common enhancement of corticostriatal drive across a subset of mice with mutations in ASD-risk genes.

The autism spectrum disorder risk gene NEXMIF over-synchronizes hippocampal CA1 network and alters neuronal coding.

Mutations in autism spectrum disorder (ASD) risk genes disrupt neural network dynamics that ultimately lead to abnormal behavior. To understand how ASD-risk genes influence neural circuit computation during behavior, we analyzed the hippocampal network by performing large-scale cellular calcium imaging from hundreds of individual CA1 neurons simultaneously in transgenic mice with total knockout of the X-linked ASD-risk gene NEXMIF (neurite extension and migration factor). As NEXMIF knockout in mice led to profound learning and memory deficits, we examined the CA1 network during voluntary locomotion, a fundamental component of spatial memory. We found that NEXMIF knockout does not alter the overall excitability of individual neurons but exaggerates movement-related neuronal responses. To quantify network functional connectivity changes, we applied closeness centrality analysis from graph theory to our large-scale calcium imaging datasets, in addition to using the conventional pairwise correlation analysis. Closeness centrality analysis considers both the number of connections and the connection strength between neurons within a network. We found that in wild-type mice the CA1 network desynchronizes during locomotion, consistent with increased network information coding during active behavior. Upon NEXMIF knockout, CA1 network is over-synchronized regardless of behavioral state and fails to desynchronize during locomotion, highlighting how perturbations in ASD-implicated genes create abnormal network synchronization that could contribute to ASD-related behaviors.

DeepASDPred: a CNN-LSTM-based deep learning method for Autism spectrum disorders risk RNA identification

BackgroundAutism spectrum disorders (ASD) are a group of neurodevelopmental disorders characterized by difficulty communicating with society and others, behavioral difficulties, and a brain that processes information differently than normal. Genetics has a strong impact on ASD associated with early onset and distinctive signs. Currently, all known ASD risk genes are able to encode proteins, and some de novo mutations disrupting protein-coding genes have been demonstrated to cause ASD. Next-generation sequencing technology enables high-throughput identification of ASD risk RNAs. However, these efforts are time-consuming and expensive, so an efficient computational model for ASD risk gene prediction is necessary.ResultsIn this study, we propose DeepASDPerd, a predictor for ASD risk RNA based on deep learning. Firstly, we use K-mer to feature encode the RNA transcript sequences, and then fuse them with corresponding gene expression values to construct a feature matrix. After combining chi-square test and logistic regression to select the best feature subset, we input them into a binary classification prediction model constructed by convolutional neural network and long short-term memory for training and classification. The results of the tenfold cross-validation proved our method outperformed the state-of-the-art methods. Dataset and source code are available at https://github.com/Onebear-X/DeepASDPred is freely available.ConclusionsOur experimental results show that DeepASDPred has outstanding performance in identifying ASD risk RNA genes.

Neuroimaging genetics approaches to identify new biomarkers for the early diagnosis of autism spectrum disorder

Autism-spectrum disorders (ASDs) are developmental disabilities that manifest in early childhood and are characterized by qualitative abnormalities in social behaviors, communication skills, and restrictive or repetitive behaviors. To explore the neurobiological mechanisms in ASD, extensive research has been done to identify potential diagnostic biomarkers through a neuroimaging genetics approach. Neuroimaging genetics helps to identify ASD-risk genes that contribute to structural and functional variations in brain circuitry and validate biological changes by elucidating the mechanisms and pathways that confer genetic risk. Integrating artificial intelligence models with neuroimaging data lays the groundwork for accurate diagnosis and facilitates the identification of early diagnostic biomarkers for ASD. This review discusses the significance of neuroimaging genetics approaches to gaining a better understanding of the perturbed neurochemical system and molecular pathways in ASD and how these approaches can detect structural, functional, and metabolic changes and lead to the discovery of novel biomarkers for the early diagnosis of ASD.

Dysregulation of the chromatin environment leads to differential alternative splicing as a mechanism of disease in a human model of autism spectrum disorder.

Autism spectrum disorder (ASD) affects 1 in 44 children. Chromatin regulatory proteins are overrepresented among genes that contain high risk variants in ASD. Disruption of the chromatin environment leads to widespread dysregulation of gene expression, which is traditionally thought of as a mechanism of disease pathogenesis associated with ASD. Alternatively, alterations in chromatin dynamics could also lead to dysregulation of alternative splicing, which is understudied as a mechanism of ASD pathogenesis. The anticonvulsant valproic acid (VPA) is a well-known environmental risk factor for ASD that acts as a class I histone deacetylase inhibitor. However, the precise molecular mechanisms underlying defects in human neuronal development associated with exposure to VPA are understudied. To dissect how VPA exposure and subsequent chromatin hyperacetylation influence molecular signatures involved in ASD pathogenesis, we conducted RNA sequencing (RNA-seq) in human cortical neurons that were treated with VPA. We observed that differentially expressed genes (DEGs) were enriched for mRNA splicing, mRNA processing, histone modification and metabolism related gene sets. Furthermore, we observed widespread increases in the number and the type of alternative splicing events. Analysis of differential transcript usage (DTU) showed that exposure to VPA induces extensive alterations in transcript isoform usage across neurodevelopmentally important genes. Finally, we find that DEGs and genes that display DTU overlap with known ASD-risk genes. Altogether, these findings suggest that, in addition to differential gene expression, changes in alternative splicing correlated with alterations in the chromatin environment could act as an additional mechanism of disease in ASD.

Impaired OTUD7A-dependent Ankyrin regulation mediates neuronal dysfunction in mouse and human models of the 15q13.3 microdeletion syndrome

Copy number variations (CNVs) are associated with psychiatric and neurodevelopmental disorders (NDDs), and most, including the recurrent 15q13.3 microdeletion disorder, have unknown disease mechanisms. We used a heterozygous 15q13.3 microdeletion mouse model and patient iPSC-derived neurons to reveal developmental defects in neuronal maturation and network activity. To identify the underlying molecular dysfunction, we developed a neuron-specific proximity-labeling proteomics (BioID2) pipeline, combined with patient mutations, to target the 15q13.3 CNV genetic driver OTUD7A. OTUD7A is an emerging independent NDD risk gene with no known function in the brain, but has putative deubiquitinase function. The OTUD7A protein–protein interaction network included synaptic, axonal, and cytoskeletal proteins and was enriched for ASD and epilepsy risk genes (Ank3, Ank2, SPTAN1, SPTBN1). The interactions between OTUD7A and Ankyrin-G (Ank3) and Ankyrin-B (Ank2) were disrupted by an epilepsy-associated OTUD7A L233F variant. Further investigation of Ankyrin-G in mouse and human 15q13.3 microdeletion and OTUD7AL233F/L233F models revealed protein instability, increased polyubiquitination, and decreased levels in the axon initial segment, while structured illumination microscopy identified reduced Ankyrin-G nanodomains in dendritic spines. Functional analysis of human 15q13.3 microdeletion and OTUD7AL233F/L233F models revealed shared and distinct impairments to axonal growth and intrinsic excitability. Importantly, restoring OTUD7A or Ankyrin-G expression in 15q13.3 microdeletion neurons led to a reversal of abnormalities. These data reveal a critical OTUD7A-Ankyrin pathway in neuronal development, which is impaired in the 15q13.3 microdeletion syndrome, leading to neuronal dysfunction. Furthermore, our study highlights the utility of targeting CNV genes using cell type-specific proteomics to identify shared and unexplored disease mechanisms across NDDs.

Structural variants identified using non-Mendelian inheritance patterns advance the mechanistic understanding of autism spectrum disorder.

The heritability of autism spectrum disorder (ASD), based on 680,000 families and five countries, is estimated to be nearly 80%, yet heritability reported from SNP-based studies are consistently lower, and few significant loci have been identified with genome-wide association studies. This gap in genomic information may reside in rare variants, interaction among variants (epistasis), or cryptic structural variation (SV) and may provide mechanisms that underlie ASD. Here we use a method to identify potential SVs based on non-Mendelian inheritance patterns in pedigrees using parent-child genotypes from ASD families and demonstrate that they are enriched in ASD-risk genes. Most are in non-coding genic space and are over-represented in expression quantitative trait loci, suggesting that they affect gene regulation, which we confirm with their overlap of differentially expressed genes in postmortem brain tissue of ASD individuals. We then identify an SV in the GRIK2 gene that alters RNA splicing and a regulatory region of the ACMSD gene in the kynurenine pathway as significantly associated with a non-verbal ASD phenotype, supporting our hypothesis that these currently excluded loci can provide a clearer mechanistic understanding of ASD. Finally, we use an explainable artificial intelligence approach to define subgroups demonstrating their use in the context of precision medicine.

Brain region and gene dosage-differential transcriptomic changes in Shank2-mutant mice.

Shank2 is an abundant excitatory postsynaptic scaffolding protein that has been implicated in various neurodevelopmental and psychiatric disorders, including autism spectrum disorder (ASD), intellectual disability, attention-deficit/hyperactivity disorder, and schizophrenia. Shank2-mutant mice show ASD-like behavioral deficits and altered synaptic and neuronal functions, but little is known about how different brain regions and gene dosages affect the transcriptomic phenotypes of these mice. Here, we performed RNA-Seq-based transcriptomic analyses of the prefrontal cortex, hippocampus, and striatum in adult Shank2 heterozygous (HT)- and homozygous (HM)-mutant mice lacking exons 6–7. The prefrontal cortical, hippocampal, and striatal regions showed distinct transcriptomic patterns associated with synapse, ribosome, mitochondria, spliceosome, and extracellular matrix (ECM). The three brain regions were also distinct in the expression of ASD-related and ASD-risk genes. These differential patterns were stronger in the prefrontal cortex where the HT transcriptome displayed increased synaptic gene expression and reverse-ASD patterns whereas the HM transcriptome showed decreased synaptic gene expression and ASD-like patterns. These results suggest brain region- and gene dosage-differential transcriptomic changes in Shank2-mutant mice.

Integrative Functional Genomic Analysis in Multiplex Autism Families from Kazakhstan.

The study of extended pedigrees containing autism spectrum disorder- (ASD-) related broader autism phenotypes (BAP) offers a promising approach to the search for ASD candidate variants. Here, a total of 650,000 genetic markers were tested in four Kazakhstani multiplex families with ASD and BAP to obtain data on de novo mutations (DNMs), common, and rare inherited variants that may contribute to the genetic risk for developing autistic traits. The variants were analyzed in the context of gene networks and pathways. Several previously well-described enriched pathways were identified, including ion channel activity, regulation of synaptic function, and membrane depolarization. Perhaps these pathways are crucial not only for the development of ASD but also for ВАР. The results also point to several additional biological pathways (circadian entrainment, NCAM and BTN family interactions, and interaction between L1 and Ankyrins) and hub genes (CFTR, NOD2, PPP2R2B, and TTR). The obtained results suggest that further exploration of PPI networks combining ASD and BAP risk genes can be used to identify novel or overlooked ASD molecular mechanisms.

Whole Genome Analysis of Dizygotic Twins With Autism Reveals Prevalent Transposon Insertion Within Neuronal Regulatory Elements: Potential Implications for Disease Etiology and Clinical Assessment.

Transposable elements (TEs) have been implicated in autism spectrum disorder (ASD). However, our understanding of their roles is far from complete. Herein, we explored de novo TE insertions (dnTEIs) and de novo variants (DNVs) across the genomes of dizygotic twins with ASD and their parents. The neuronal regulatory elements had a tendency to harbor dnTEIs that were shared between twins, but ASD-risk genes had dnTEIs that were unique to each twin. The dnTEIs were 4.6-fold enriched in enhancers that are active in embryonic stem cell (ESC)-neurons (p < 0.001), but DNVs were 1.5-fold enriched in active enhancers of astrocytes (p = 0.0051). Our findings suggest that dnTEIs and DNVs play a role in ASD etiology by disrupting enhancers of neurons and astrocytes.

A Bayesian framework to integrate multi-level genome-scale data for Autism risk gene prioritization

BackgroundAutism spectrum disorder (ASD) is a group of complex neurodevelopment disorders with a strong genetic basis. Large scale sequencing studies have identified over one hundred ASD risk genes. Nevertheless, the vast majority of ASD risk genes remain to be discovered, as it is estimated that more than 1000 genes are likely to be involved in ASD risk. Prioritization of risk genes is an effective strategy to increase the power of identifying novel risk genes in genetics studies of ASD. As ASD risk genes are likely to exhibit distinct properties from multiple angles, we reason that integrating multiple levels of genomic data is a powerful approach to pinpoint genuine ASD risk genes.ResultsWe present BNScore, a Bayesian model selection framework to probabilistically prioritize ASD risk genes through explicitly integrating evidence from sequencing-identified ASD genes, biological annotations, and gene functional network. We demonstrate the validity of our approach and its improved performance over existing methods by examining the resulting top candidate ASD risk genes against sets of high-confidence benchmark genes and large-scale ASD genome-wide association studies. We assess the tissue-, cell type- and development stage-specific expression properties of top prioritized genes, and find strong expression specificity in brain tissues, striatal medium spiny neurons, and fetal developmental stages.ConclusionsIn summary, we show that by integrating sequencing findings, functional annotation profiles, and gene-gene functional network, our proposed BNScore provides competitive performance compared to current state-of-the-art methods in prioritizing ASD genes. Our method offers a general and flexible strategy to risk gene prioritization that can potentially be applied to other complex traits as well.

Placental methylome reveals a 22q13.33 brain regulatory gene locus associated with autism

BackgroundAutism spectrum disorder (ASD) involves complex genetics interacting with the perinatal environment, complicating the discovery of common genetic risk. The epigenetic layer of DNA methylation shows dynamic developmental changes and molecular memory of in utero experiences, particularly in placenta, a fetal tissue discarded at birth. However, current array-based methods to identify novel ASD risk genes lack coverage of the most structurally and epigenetically variable regions of the human genome.ResultsWe use whole genome bisulfite sequencing in placenta samples from prospective ASD studies to discover a previously uncharacterized ASD risk gene, LOC105373085, renamed NHIP. Out of 134 differentially methylated regions associated with ASD in placental samples, a cluster at 22q13.33 corresponds to a 118-kb hypomethylated block that replicates in two additional cohorts. Within this locus, NHIP is functionally characterized as a nuclear peptide-encoding transcript with high expression in brain, and increased expression following neuronal differentiation or hypoxia, but decreased expression in ASD placenta and brain. NHIP overexpression increases cellular proliferation and alters expression of genes regulating synapses and neurogenesis, overlapping significantly with known ASD risk genes and NHIP-associated genes in ASD brain. A common structural variant disrupting the proximity of NHIP to a fetal brain enhancer is associated with NHIP expression and methylation levels and ASD risk, demonstrating a common genetic influence.ConclusionsTogether, these results identify and initially characterize a novel environmentally responsive ASD risk gene relevant to brain development in a hitherto under-characterized region of the human genome.

Experience-dependent weakening of callosal synaptic connections in the absence of postsynaptic FMRP.

Reduced structural and functional interhemispheric connectivity correlates with the severity of Autism Spectrum Disorder (ASD) behaviors in humans. Little is known of how ASD-risk genes regulate callosal connectivity. Here, we show that Fmr1, whose loss-of-function leads to Fragile X Syndrome (FXS), cell autonomously promotes maturation of callosal excitatory synapses between somatosensory barrel cortices in mice. Postnatal, cell-autonomous deletion of Fmr1 in postsynaptic Layer (L) 2/3 or L5 neurons results in a selective weakening of AMPA receptor- (R), but not NMDA receptor-, mediated callosal synaptic function, indicative of immature synapses. Sensory deprivation by contralateral whisker trimming normalizes callosal input strength, suggesting that experience-driven activity of postsynaptic Fmr1 KO L2/3 neurons weakens callosal synapses. In contrast to callosal inputs, synapses originating from local L4 and L2/3 circuits are normal, revealing an input-specific role for postsynaptic Fmr1 in regulation of synaptic connectivity within local and callosal neocortical circuits. These results suggest direct cell autonomous and postnatal roles for FMRP in development of specific cortical circuits and suggest a synaptic basis for long-range functional underconnectivity observed in FXS patients.

Potassium channels and autism spectrum disorder: An overview.

Autism spectrum disorder (ASD) comprises a group of neurodevelopmental disorders characterized by impaired social interaction and communication, and restricted, repetitive patterns of behaviors, interests, or activities. It had been demonstrated that potassium channels played a key role in regulating neuronal excitability, which was closely associated with neurological diseases including epilepsy, ataxia, myoclonus, and psychiatric disorders. In recent years, a growing body of evidence from whole-genome sequencing and whole-exome sequencing had identified several ASD susceptibility genes of potassium channels in ASD subjects. Genetically dysfunction of potassium channels may be involved in altered neuronal excitability and abnormal brain function in the pathogenesis of ASD. This review summarizes current findings on the features of ASD-risk genes (KCND2, KCNQ2, KCNQ3, KCNH5, KCNJ2, KCNJ10, and KCNMA1) and further expatiate their potential role in the pathogenicity of ASD.

An Epigenetically Distinct Subset of Children With Autism Spectrum Disorder Resulting From Differences in Blood Cell Composition.

Background: Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder that often involves impaired cognition, communication difficulties and restrictive, repetitive behaviors. ASD is extremely heterogeneous both clinically and etiologically, which represents one of the greatest challenges in studying the molecular underpinnings of ASD. While hundreds of ASD-associated genes have been identified that confer varying degrees of risk, no single gene variant accounts for >1% of ASD cases. Notably, a large number of ASD-risk genes function as epigenetic regulators, indicating potential epigenetic dysregulation in ASD. As such, we compared genome-wide DNA methylation (DNAm) in the blood of children with ASD (n = 265) to samples from age- and sex-matched, neurotypical controls (n = 122) using the Illumina Infinium HumanMethylation450 arrays.Results: While DNAm patterns did not distinctly separate ASD cases from controls, our analysis identified an epigenetically unique subset of ASD cases (n = 32); these individuals exhibited significant differential methylation from both controls than the remaining ASD cases. The CpG sites at which this subset was differentially methylated mapped to known ASD risk genes that encode proteins of the nervous and immune systems. Moreover, the observed DNAm differences were attributable to altered blood cell composition, i.e., lower granulocyte proportion and granulocyte-to-lymphocyte ratio in the ASD subset, as compared to the remaining ASD cases and controls. This ASD subset did not differ from the rest of the ASD cases in the frequency or type of high-risk genomic variants.Conclusion: Within our ASD cohort, we identified a subset of individuals that exhibit differential methylation from both controls and the remaining ASD group tightly associated with shifts in immune cell type proportions. This is an important feature that should be assessed in all epigenetic studies of blood cells in ASD. This finding also builds on past reports of changes in the immune systems of children with ASD, supporting the potential role of altered immunological mechanisms in the complex pathophysiology of ASD. The discovery of significant molecular and immunological features in subgroups of individuals with ASD may allow clinicians to better stratify patients, facilitating personalized interventions and improved outcomes.

Autism-associated miR-873 regulates ARID1B, SHANK3 and NRXN2 involved in neurodevelopment

Autism spectrum disorders (ASD) are highly heritable neurodevelopmental disorders with significant genetic heterogeneity. Noncoding microRNAs (miRNAs) are recognised as playing key roles in development of ASD albeit the function of these regulatory genes remains unclear. We previously conducted whole-exome sequencing of Australian families with ASD and identified four novel single nucleotide variations in mature miRNA sequences. A pull-down transcriptome analysis using transfected SH-SY5Y cells proposed a mechanistic model to examine changes in binding affinity associated with a unique mutation found in the conserved ‘seed’ region of miR-873-5p (rs777143952: T > A). Results suggested several ASD-risk genes were differentially targeted by wild-type and mutant miR-873 variants. In the current study, a dual-luciferase reporter assay confirmed miR-873 variants have a 20-30% inhibition/dysregulation effect on candidate autism risk genes ARID1B, SHANK3 and NRXN2 and also confirmed the affected expression with qPCR. In vitro mouse hippocampal neurons transfected with mutant miR-873 showed less morphological complexity and enhanced sodium currents and excitatory neurotransmission compared to cells transfected with wild-type miR-873. A second in vitro study showed CRISPR/Cas9 miR-873 disrupted SH-SY5Y neuroblastoma cells acquired a neuronal-like morphology and increased expression of ASD important genes ARID1B, SHANK3, ADNP2, ANK2 and CHD8. These results represent the first functional evidence that miR-873 regulates key neural genes involved in development and cell differentiation.

Brief Report: Associations Between Self-injurious Behaviors and Abdominal Pain Among Individuals with ASD-Associated Disruptive Mutations.

Self-injurious behaviors (SIB) are elevated in autism spectrum disorder (ASD) and related genetic disorders, but the genetic and biological mechanisms that contribute to SIB in ASD are poorly understood. This study examined rates and predictors of SIB in 112 individuals with disruptive mutations to ASD-risk genes. Current SIB were reported in 30% of participants and associated with poorer cognitive and adaptive skills. History of severe abdominal pain predicted higher rates of SIB and SIB severity after controlling for age and adaptive behavior; individuals with a history of severe abdominal pain were eight times more likely to exhibit SIB than those with no history. Future research is needed to examine associations between genetic risk, pain, and SIB in this population.