Neurodevelopmental disorders are the most prevalent chronic medical conditions encountered in pediatric primary care. In addition to identifying appropriate descriptive diagnoses and guiding families to evidence-based treatments and supports, comprehensive care for individuals with neurodevelopmental disorders includes a search for an underlying etiologic diagnosis, primarily through a genetic evaluation. Identification of an underlying genetic etiology can inform prognosis, clarify recurrence risk, shape clinical management, and direct patients and families to condition-specific resources and supports. Here we review the utility of genetic testing in patients with neurodevelopmental disorders and describe the three major testing modalities and their yields – chromosomal microarray, exome sequencing (with/without copy number variant calling), and FMR1 CGG repeat analysis for fragile X syndrome. Given the diagnostic yield of genetic testing and the potential for clinical and personal utility, there is consensus that genetic testing should be offered to all patients with global developmental delay, intellectual disability, and/or autism spectrum disorder. Despite this recommendation, data suggest that a minority of children with autism spectrum disorder and intellectual disability have undergone genetic testing. To address this gap in care, we describe a structured but flexible approach to facilitate integration of genetic testing into clinical practice across pediatric specialties and discuss future considerations for genetic testing in neurodevelopmental disorders to prepare pediatric providers to care for patients with such diagnoses today and tomorrow.

The etiology of autism spectrum disorder (ASD) is complex, involving both genetic and environmental contributions to individual and population-level liability. Early researchers hypothesized that ASD arises from polygenic inheritance, but later results, such as the identification of mutations in certain genes that are responsible for syndromes associated with ASD, led others to propose that de novo mutations of major effect would account for most cases. This yin and yang of monogenic causes and polygenic inheritance continues to this day. The development of genome-wide genotyping and sequencing techniques has resulted in remarkable advances in our understanding of the genetic architecture of risk for ASD. The combined research findings provide solid evidence that ASD is a complex polygenic disorder. Rare de novo and inherited variations act within the context of a common-variant genetic load, and this load accounts for the largest portion of ASD liability.

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.

The genetic architecture of autism spectrum disorder involves the interplay of common and rare variants and their impact on hundreds of genes. Using exome sequencing, here we show that analysis of rare coding variation in 3,871 autism cases and 9,937 ancestry-matched or parental controls implicates 22 autosomal genes at a false discovery rate (FDR) < 0.05, plus a set of 107 autosomal genes strongly enriched for those likely to affect risk (FDR < 0.30). These 107 genes, which show unusual evolutionary constraint against mutations, incur de novo loss-of-function mutations in over 5% of autistic subjects. Many of the genes implicated encode proteins for synaptic formation, transcriptional regulation and chromatin-remodelling pathways. These include voltage-gated ion channels regulating the propagation of action potentials, pacemaking and excitability–transcription coupling, as well as histone-modifying enzymes and chromatin remodellers—most prominently those that mediate post-translational lysine methylation/demethylation modifications of histones.

Background:Autism spectrum disorder (ASD) is characterized by high heritability estimates and recurrence rates; its genetic underpinnings are very heterogeneous and include variable combinations of common and rare variants. Array-comparative genomic hybridization (aCGH) offers significant sensitivity for the identification of copy number variants (CNVs), which can act as susceptibility or causal factors for ASD.

Methods: The aim of this study was to evaluate both diagnostic yield and clinical impact of aCGH in 329 ASD patients of Italian descent.

Results: Pathogenic/likely pathogenic CNVs were identified in 50/329 (15.2%) patients, whereas 89/329 (27.1%) carry variants of uncertain significance. The 10 most enriched gene sets identified by Gene Ontology Enrichment Analysis are primarily involved in neuronal function and synaptic connectivity. In 13/50 (26.0%) patients with pathogenic/likely pathogenic CNVs, the outcome of array-CGH led to the request of 25 additional medical exams which would not have otherwise been prescribed, mainly including brain MRI, EEG, EKG, and/or cardiac ultrasound. A positive outcome was obtained in 12/25 (48.0%) of these additional tests.

Conclusions:This study confirms the satisfactory diagnostic yield of aCGH, underscoring its potential for better, more in-depth care of children with autism when genetic results are analyzed also with a focus on patient management.

Background: Autism spectrum disorder (ASD) is a neurodevelopmental disorder with strong genetic underpinnings. Microarray-based comparative genomic hybridization (aCGH) technology has been proposed as a first-level test in the genetic diagnosis of ASD and of neurodevelopmental disorders in general.

Methods: We performed aCGH on 98 Tunisian children (83 boys and 15 girls) diagnosed with ASD according to DSM-IV criteria.

Results: “Pathogenic” or “likely pathogenic” copy number variants (CNVs) were detected in 11 (11.2%) patients, CNVs of “uncertain clinical significance” in 26 (26.5%), “likely benign” or “benign” CNVs were found in 37 (37.8%) and 24 (24.5%) patients, respectively. Gene set enrichment analysis involving genes spanning rare “pathogenic,” “likely pathogenic,” or “uncertain clinical significance” CNVs, as well as SFARI database “autism genes” in common CNVs, detected eight neuronal Gene Ontology classes among the top 10 most significant, including synapse, neuron differentiation, synaptic signaling, neurogenesis, and others. Similar results were obtained performing g: Profiler analysis. Neither transcriptional regulation nor immune pathways reached significance.

Conclusions: aCGH confirms its sizable diagnostic yield in a novel sample of autistic children from North Africa. Recruitment of additional families is under way, to verify whether genetic contributions to ASD in the Tunisian population, differently from other ethnic groups, may involve primarily neuronal genes, more than transcriptional regulation and immune-related pathways.

Despite evidence that deleterious variants in the same genes are implicated across multiple neurodevelopmental and neuropsychiatric disorders, there has been considerable interest in identifying genes that, when mutated, confer risk that is largely specific for autism spectrum disorder (ASD). Here, we review the findings and limitations of recent efforts to identify relatively “autism-specific” genes, efforts which focus on rare variants of large effect size that are thought to account for the observed phenotypes. We present a divergent interpretation of published evidence; discuss practical and theoretical issues related to studying the relationships between rare, large-effect deleterious variants and neurodevelopmental phenotypes; and describe potential future directions of this research. We argue that there is currently insufficient evidence to establish meaningful ASD specificity of any genes based on large-effect rare-variant data.

Identification of genetic biomarkers associated with autism spectrum disorders (ASDs) could improve recurrence prediction for families with a child with ASD. Here, we describe clinical microarray findings for 253 longitudinally phenotyped ASD families from the Baby Siblings Research Consortium (BSRC), encompassing 288 infant siblings. By age 3, 103 siblings (35.8%) were diagnosed with ASD and 54 (18.8%) were developing atypically. Thirteen siblings have copy number variants (CNVs) involving ASD-relevant genes: 6 with ASD, 5 atypically developing, and 2 typically developing. Within these families, an ASD-related CNV in a sibling has a positive predictive value (PPV) for ASD or atypical development of 0.83; the Simons Simplex Collection of ASD families shows similar PPVs. Polygenic risk analyses suggest that common genetic variants may also contribute to ASD. CNV findings would have been pre-symptomatically predictive of ASD or atypical development in 11 (7%) of the 157 BSRC siblings who were eventually diagnosed clinically.

Autism spectrum disorder (ASD) defines a group of common, complex neurodevelopmental disorders. Although the aetiology of ASD has a strong genetic component, there is considerable monozygotic (MZ) twin discordance indicating a role for non-genetic factors. Because MZ twins share an identical DNA sequence, disease-discordant MZ twin pairs provide an ideal model for examining the contribution of environmentally driven epigenetic factors in disease. We performed a genome-wide analysis of DNA methylation in a sample of 50 MZ twin pairs (100 individuals) sampled from a representative population cohort that included twins discordant and concordant for ASD, ASD-associated traits and no autistic phenotype. Within-twin and between-group analyses identified numerous differentially methylated regions associated with ASD. In addition, we report significant correlations between DNA methylation and quantitatively measured autistic trait scores across our sample cohort. This study represents the first systematic epigenomic analyses of MZ twins discordant for ASD and implicates a role for altered DNA methylation in autism.

Background: Autism comprises a spectrum of behavioral and cognitive disturbances of childhood development and is known to be highly heritable. Although numerous approaches have been used to identify genes implicated in the development of autism, less than 10% of autism cases have been attributed to single gene disorders.

Methods: We describe the use of high-resolution genome-wide tilepath microarrays and comparative genomic hybridization to identify copy number variants within 119 probands from multiplex autism families. We next carried out DNA methylation analysis by bisulfite sequencing in a proband and his family, expanding this analysis to methylation analysis of peripheral blood and temporal cortex DNA of autism cases and matched controls from independent datasets. We also assessed oxytocin receptor (OXTR) gene expression within the temporal cortex tissue by quantitative real-time polymerase chain reaction (PCR).

Results: Our analysis revealed a genomic deletion containing the oxytocin receptor gene, OXTR (MIM accession no.: 167055), previously implicated in autism, was present in an autism proband and his mother who exhibits symptoms of obsessive-compulsive disorder. The proband’s affected sibling did not harbor this deletion but instead may exhibit epigenetic misregulation of this gene through aberrant gene silencing by DNA methylation. Further DNA methylation analysis of the CpG island known to regulate OXTR expression identified several CpG dinucleotides that show independent statistically significant increases in the DNA methylation status in the peripheral blood cells and temporal cortex in independent datasets of individuals with autism as compared to control samples. Associated with the increase in methylation of these CpG dinucleotides is our finding that OXTR mRNA showed decreased expression in the temporal cortex tissue of autism cases matched for age and sex compared to controls.

Conclusion: Together, these data provide further evidence for the role of OXTR and the oxytocin signaling pathway in the etiology of autism and, for the first time, implicate the epigenetic regulation of OXTR in the development of the disorder.

Integration of emerging epigenetic information with autism spectrum disorder (ASD) genetic results may elucidate functional insights not possible via either type of information in isolation. Here we use the genotype and DNA methylation (DNAm) data from cord blood and peripheral blood to identify SNPs associated with DNA methylation (meQTL lists). Additionally, we use publicly available fetal brain and lung meQTL lists to assess enrichment of ASD GWAS results for tissue-specific meQTLs. ASD-associated SNPs are enriched for fetal brain (OR = 3.55; P < 0.001) and peripheral blood meQTLs (OR = 1.58; P < 0.001). The CpG targets of ASD meQTLs across cord, blood, and brain tissues are enriched for immune-related pathways, consistent with other expression and DNAm results in ASD, and reveal pathways not implicated by genetic findings. This joint analysis of genotype and DNAm demonstrates the potential of both brain and blood-based DNAm for insights into ASD and psychiatric phenotypes more broadly.

Autism is a severe disorder that involves both genetic and environmental factors. Expression profiling of the superior temporal gyrus of six autistic subjects and matched controls revealed increased transcript levels of many immune system-related genes. We also noticed changes in transcripts related to cell communication, differentiation, cell cycle regulation and chaperone systems. Critical expression changes were confirmed by qPCR (BCL6, CHI3L1, CYR61, IFI16, IFITM3, MAP2K3, PTDSR, RFX4, SPP1, RELN, NOTCH2, RIT1, SFN, GADD45B, HSPA6, HSPB8 and SERPINH1). Overall, these expression patterns appear to be more associated with the late recovery phase of autoimmune brain disorders, than with the innate immune response characteristic of neurodegenerative diseases. Moreover, a variance-based analysis revealed much greater transcript variability in brains from autistic subjects compared to the control group, suggesting that these genes may represent autism susceptibility genes and should be assessed in follow-up genetic studies.

Autism was a spectrum of multiple complex diseases that required an interdisciplinary group of experts to make a diagnostic decision. Both genetic and environmental factors play essential roles in causing the onset of Autism. Therefore, this study hypothesized that methylomic biomarkers may facilitate the accurate Autism detection. A comprehensive series of biomarker detection algorithms were utilized to find the best methylomic biomarkers for the Autism detection using the methylomic data of the peripheral blood samples. The best model achieved 99.70% in accuracy with 678 methylomic biomarkers and a tenfold cross validation strategy. Some of the methylomic biomarkers were experimentally confirmed to be associated with the onset or development of Autism.

Background: Autism spectrum disorder (ASD) is a neurodevelopmental disorder with complex heritability and higher prevalence in males. The neonatal epigenome has the potential to reflect past interactions between genetic and environmental factors during early development and influence future health outcomes.

Methods: We performed whole-genome bisulfite sequencing of 152 umbilical cord blood samples from the MARBLES and EARLI high-familial risk prospective cohorts to identify an epigenomic signature of ASD at birth. Samples were split into discovery and replication sets and stratified by sex, and their DNA methylation profiles were tested for differentially methylated regions (DMRs) between ASD and typically developing control cord blood samples. DMRs were mapped to genes and assessed for enrichment in gene function, tissue expression, chromosome location, and overlap with prior ASD studies. DMR coordinates were tested for enrichment in chromatin states and transcription factor binding motifs. Results were compared between discovery and replication sets and between males and females.

Results: We identified DMRs stratified by sex that discriminated ASD from control cord blood samples in discovery and replication sets. At a region level, 7 DMRs in males and 31 DMRs in females replicated across two independent groups of subjects, while 537 DMR genes in males and 1762 DMR genes in females replicated by gene association. These DMR genes were significantly enriched for brain and embryonic expression, X chromosome location, and identification in prior epigenetic studies of ASD in post-mortem brain. In males and females, autosomal ASD DMRs were significantly enriched for promoter and bivalent chromatin states across most cell types, while sex differences were observed for X-linked ASD DMRs. Lastly, these DMRs identified in cord blood were significantly enriched for binding sites of methyl-sensitive transcription factors relevant to fetal brain development.

Conclusions: At birth, prior to the diagnosis of ASD, a distinct DNA methylation signature was detected in cord blood over regulatory regions and genes relevant to early fetal neurodevelopment. Differential cord methylation in ASD supports the developmental and sex-biased etiology of ASD and provides novel insights for early diagnosis and therapy.

Background: Autism spectrum disorder (ASD) is a neurodevelopmental disorder with complex heritability and higher prevalence in males. The neonatal epigenome has the potential to reflect past interactions between genetic and environmental factors during early development and influence future health outcomes.

Methods: We performed whole-genome bisulfite sequencing of 152 umbilical cord blood samples from the MARBLES and EARLI high-familial risk prospective cohorts to identify an epigenomic signature of ASD at birth. Samples were split into discovery and replication sets and stratified by sex, and their DNA methylation profiles were tested for differentially methylated regions (DMRs) between ASD and typically developing control cord blood samples. DMRs were mapped to genes and assessed for enrichment in gene function, tissue expression, chromosome location, and overlap with prior ASD studies. DMR coordinates were tested for enrichment in chromatin states and transcription factor binding motifs. Results were compared between discovery and replication sets and between males and females.

Results: We identified DMRs stratified by sex that discriminated ASD from control cord blood samples in discovery and replication sets. At a region level, 7 DMRs in males and 31 DMRs in females replicated across two independent groups of subjects, while 537 DMR genes in males and 1762 DMR genes in females replicated by gene association. These DMR genes were significantly enriched for brain and embryonic expression, X chromosome location, and identification in prior epigenetic studies of ASD in post-mortem brain. In males and females, autosomal ASD DMRs were significantly enriched for promoter and bivalent chromatin states across most cell types, while sex differences were observed for X-linked ASD DMRs. Lastly, these DMRs identified in cord blood were significantly enriched for binding sites of methyl-sensitive transcription factors relevant to fetal brain development.

Conclusions: At birth, prior to the diagnosis of ASD, a distinct DNA methylation signature was detected in cord blood over regulatory regions and genes relevant to early fetal neurodevelopment. Differential cord methylation in ASD supports the developmental and sex-biased etiology of ASD and provides novel insights for early diagnosis and therapy.

Background: Epigenetic mechanisms such as altered DNA methylation have been suggested to play a role in autism, beginning with the classical association of Prader-Willi syndrome, an imprinting disorder, with autistic features.

Objectives: Here we tested for the relationship of paternal sperm DNA methylation with autism risk in offspring, examining an enriched-risk cohort of fathers of autistic children.

Methods: We examined genome-wide DNA methylation (DNAm) in paternal semen biosamples obtained from an autism spectrum disorder (ASD) enriched-risk pregnancy cohort, the Early Autism Risk Longitudinal Investigation (EARLI) cohort, to estimate associations between sperm DNAm and prospective ASD development, using a 12-month ASD symptoms assessment, the Autism Observation Scale for Infants (AOSI). We analysed methylation data from 44 sperm samples run on the CHARM 3.0 array, which contains over 4 million probes (over 7 million CpG sites), including 30 samples also run on the Illumina Infinium HumanMethylation450 (450K) BeadChip platform (∼485 000 CpG sites). We also examined associated regions in an independent sample of post-mortem human brain ASD and control samples for which Illumina 450K DNA methylation data were available.

Results: Using region-based statistical approaches, we identified 193 differentially methylated regions (DMRs) in paternal sperm with a family-wise empirical P-value [family-wise error rate (FWER)] <0.05 associated with performance on the Autism Observational Scale for Infants (AOSI) at 12 months of age in offspring. The DMRs clustered near genes involved in developmental processes, including many genes in the SNORD family, within the Prader-Willi syndrome gene cluster. These results were consistent among the 75 probes on the Illumina 450K array that cover AOSI-associated DMRs from CHARM. Further, 18 of 75 (24%) 450K array probes showed consistent differences in the cerebellums of autistic individuals compared with controls. Conclusions: These data suggest that epigenetic differences in paternal sperm may contribute to autism risk in offspring, and provide evidence that directionally consistent, potentially related epigenetic mechanisms may be operating in the cerebellum of individuals with autism.

Autism spectrum disorder (ASD) is a common, highly heritable neurodevelopmental condition characterized by marked genetic heterogeneity1,2,3. Thus, a fundamental question is whether autism represents an aetiologically heterogeneous disorder in which the myriad genetic or environmental risk factors perturb common underlying molecular pathways in the brain4. Here, we demonstrate consistent differences in transcriptome organization between autistic and normal brain by gene co-expression network analysis. Remarkably, regional patterns of gene expression that typically distinguish frontal and temporal cortex are significantly attenuated in the ASD brain, suggesting abnormalities in cortical patterning. We further identify discrete modules of co-expressed genes associated with autism: a neuronal module enriched for known autism susceptibility genes, including the neuronal specific splicing factor A2BP1 (also known as FOX1), and a module enriched for immune genes and glial markers. Using high-throughput RNA sequencing we demonstrate dysregulated splicing of A2BP1-dependent alternative exons in the ASD brain. Moreover, using a published autism genome-wide association study (GWAS) data set, we show that the neuronal module is enriched for genetically associated variants, providing independent support for the causal involvement of these genes in autism. In contrast, the immune-glial module showed no enrichment for autism GWAS signals, indicating a non-genetic aetiology for this process. Collectively, our results provide strong evidence for convergent molecular abnormalities in ASD, and implicate transcriptional and splicing dysregulation as underlying mechanisms of neuronal dysfunction in this disorder.

Receptor for Activated C-Kinase 1 (RACK1) belongs to the WD40 family of proteins, known to act as scaffolding proteins in interaction networks. Accordingly, RACK1 is found to have numerous interacting partners ranging from kinases and signaling proteins to membrane bound receptors and ion channels. Interestingly, RACK1 has also been identified as a ribosomal protein present in all eukaryotic ribosomes. Structures of eukaryotic ribosomes have shown RACK1 to be located at the back of the head of the small ribosomal subunit. This suggests that RACK1 could act as a ribosomal scaffolding protein recruiting regulators of translation to the ribosome, and several studies have in fact found RACK1 to play a role in regulation of translation. To fully understand the role of RACK1 we need to understand whether the many reported interaction partners of RACK1 bind to free or ribosomal RACK1. In this review we provide a structural analysis of ribosome-bound RACK1 to provide a basis for answering this fundamental question. Our analysis shows that RACK1 is tightly bound to the ribosome through highly conserved and specific interactions confirming RACK1 as an integral ribosomal protein. Furthermore, we have analyzed whether reported binding sites for RACK1 interacting partners with a proposed role in translational control are accessible on ribosomal RACK1. Our analysis shows that most of the interaction partners with putative regulatory functions have binding sites that are available on ribosomal RACK1, supporting the role of RACK1 as a ribosomal signaling hub. We also discuss the possible role for RACK1 in recruitment of ribosomes to focal adhesion sites and regulation of local translation during cell spreading and migration.

Proteomics, the large-scale study of protein expression in cells and tissues, is a powerful tool to study the biology of clinical conditions and has provided significant insights in many experimental systems. Herein, we review the basics of proteomic methodology and discuss challenges in using proteomic approaches to study autism. Unlike other experimental approaches, such as genomic approaches, there have been few large-scale studies of proteins in tissues from persons with autism. Most of the proteomic studies on autism used blood or other peripheral tissues; few studies used brain tissue. Some studies found dysregulation of aspects of the immune system or of aspects of lipid metabolism, but no consistent findings were noted. Based on the challenges in using proteomics to study autism, we discuss considerations for future studies. Apart from the complex technical considerations implicit in any proteomic analysis, key nontechnical matters include attention to subject and specimen inclusion/exclusion criteria, having adequate sample size to ensure appropriate powering of the study, attention to the state of specimens prior to proteomic analysis, and the use of a replicate set of specimens, when possible. We conclude by discussing some potentially productive uses of proteomics, potentially coupled with other approaches, for future autism research including: (1) proteomic analysis of banked human brain specimens; (2) proteomic analysis of tissues from animal models of autism; and (3) proteomic analysis of induced pluripotent stem cells that are differentiated into various types of brain cells and neural organoids. Autism Res 2017, 10: 1460–1469. © 2017 International Society for Autism Research, Wiley Periodicals, Inc.

Background: Autism spectrum disorder (ASD) is still diagnosed through behavioral observation, due to a lack of laboratory biomarkers, which could greatly aid clinicians in providing earlier and more reliable diagnoses. Metabolomics on human biofluids provides a sensitive tool to identify metabolite profiles potentially usable as biomarkers for ASD. Initial metabolomic studies, analyzing urines and plasma of ASD and control individuals, suggested that autistic patients may share some metabolic abnormalities, despite several inconsistencies stemming from differences in technology, ethnicity, age range, and definition of “control” status.

Methods: ASD-specific urinary metabolomic patterns were explored at an early age in 30 ASD children and 30 matched controls (age range 2–7, M:F = 22:8) using hydrophilic interaction chromatography (HILIC)-UHPLC and mass spectrometry, a highly sensitive, accurate, and unbiased approach. Metabolites were then subjected to multivariate statistical analysis and grouped by metabolic pathway.

Results: Urinary metabolites displaying the largest differences between young ASD and control children belonged to the tryptophan and purine metabolic pathways. Also, vitamin B6, riboflavin, phenylalanine-tyrosine-tryptophan biosynthesis, pantothenate and CoA, and pyrimidine metabolism differed significantly. ASD children preferentially transform tryptophan into xanthurenic acid and quinolinic acid (two catabolites of the kynurenine pathway), at the expense of kynurenic acid and especially of melatonin. Also, the gut microbiome contributes to altered tryptophan metabolism, yielding increased levels of indolyl 3-acetic acid and indolyl lactate.

Conclusions: The metabolic pathways most distinctive of young Italian autistic children largely overlap with those found in rodent models of ASD following maternal immune activation or genetic manipulations. These results are consistent with the proposal of a purine-driven cell danger response, accompanied by overproduction of epileptogenic and excitotoxic quinolinic acid, large reductions in melatonin synthesis, and gut dysbiosis. These metabolic abnormalities could underlie several comorbidities frequently associated to ASD, such as seizures, sleep disorders, and gastrointestinal symptoms, and could contribute to autism severity. Their diagnostic sensitivity, disease-specificity, and interethnic variability will merit further investigation.

Autism spectrum disorder (ASD) is a set of complex neurodevelopmental disorders. Recent studies reported that children with ASD have altered gut microbiota profiles compared with typical development (TD) children. However, few studies on gut bacteria of children with ASD have been conducted in China. Here, in order to elucidate changes of fecal microbiota in children with ASD, 16S rRNA sequencing was conducted and the 16S rRNA (V3-V4) gene tags were amplified. We investigated differences in fecal microbiota between 35 children with ASD and 6 TD children. At the phylum level, the fecal microbiota of ASD group indicated a significant increase of the Bacteroidetes/Firmicutes ratio. At the genus level, we found that the relative abundance of Sutterella, Odoribacter and Butyricimonas was much more abundant in the ASD group whereas the abundance of Veillonella and Streptococcus was decreased significantly compared to the control group. Functional analysis demonstrated that butyrate and lactate producers were less abundant in the ASD group. In addition, we downloaded the association data set of microbe–disease from human microbe–disease association database and constructed a human disease network including ASD using our gut microbiome results. In this microbe–disease network based on microbe similarity of diseases, we found that ASD is positively correlated with periodontal, negatively related to type 1 diabetes. Therefore, these results suggest that microbe-based disease analysis is able to predict novel connection between ASD and other diseases and may play a role in revealing the pathogenesis of ASD.

Autism spectrum disorder (ASD) manifests as alterations in complex human behaviors including social communication and stereotypies. In addition to genetic risks, the gut microbiome differs between typically developing (TD) and ASD individuals, though it remains unclear whether the microbiome contributes to symptoms. We transplanted gut microbiota from human donors with ASD or TD controls into germ-free mice and reveal that colonization with ASD microbiota is sufficient to induce hallmark autistic behaviors. The brains of mice colonized with ASD microbiota display alternative splicing of ASD-relevant genes. Microbiome and metabolome profiles of mice harboring human microbiota predict that specific bacterial taxa and their metabolites modulate ASD behaviors. Indeed, treatment of an ASD mouse model with candidate microbial metabolites improves behavioral abnormalities and modulates neuronal excitability in the brain. We propose that the gut microbiota regulates behaviors in mice via production of neuroactive metabolites, suggesting that gut-brain connections contribute to the pathophysiology of ASD.

Whole-brain voxel-based unbiased resting state functional connectivity was analysed in 418 subjects with autism and 509 matched typically developing individuals. We identified a key system in the middle temporal gyrus/superior temporal sulcus region that has reduced cortical functional connectivity (and increased with the medial thalamus), which is implicated in face expression processing involved in social behaviour. This system has reduced functional connectivity with the ventromedial prefrontal cortex, which is implicated in emotion and social communication. The middle temporal gyrus system is also implicated in theory of mind processing. We also identified in autism a second key system in the precuneus/superior parietal lobule region with reduced functional connectivity, which is implicated in spatial functions including of oneself, and of the spatial environment. It is proposed that these two types of functionality, face expression-related, and of one’s self and the environment, are important components of the computations involved in theory of mind, whether of oneself or of others, and that reduced connectivity within and between these regions may make a major contribution to the symptoms of autism.

Autism spectrum disorder (ASD) has been associated with a reduction in resting state functional connectivity, though this assertion has recently been challenged by reports of increased connectivity in ASD. To address these contradictory findings, we examined both inter- and intrahemispheric functional connectivity in several resting state data sets acquired from adults with high-functioning ASD and matched control participants. Our results reveal areas of both increased and decreased connectivity in multiple ASD groups as compared to control groups. We propose that this heterogeneity stems from a previously unrecognized ASD characteristic: idiosyncratic distortions of the functional connectivity pattern relative to the typical, canonical template. The magnitude of an individual’s pattern distortion in homotopic interhemispheric connectivity correlated significantly with behavioral symptoms of ASD. We propose that individualized alterations in functional connectivity organization are a core characteristic of high-functioning ASD, and that this may account for previous discrepant findings.

Background: There is little consensus and controversial evidence on anatomical alterations in the brains of people with autism spectrum disorder (ASD), due in part to the large heterogeneity present in ASD, which in turn is a major drawback for developing therapies. One strategy to characterize this heterogeneity in ASD is to cluster large-scale functional brain connectivity profiles.

Methods: A subtyping approach based on consensus clustering of functional brain connectivity patterns was applied to a population of 657 autistic individuals with quality-assured neuroimaging data. We then used high-resolution gene transcriptomic data to characterize the molecular mechanism behind each subtype by performing enrichment analysis of the set of genes showing a high spatial similarity with the profiles of functional connectivity alterations between each subtype and a group of typically developing control participants.

Results: Two major stable subtypes were found: subtype 1 exhibited hypoconnectivity (less average connectivity than typically developing control participants) and subtype 2, hyperconnectivity. The 2 subtypes did not differ in structural imaging metrics in any of the analyzed regions (68 cortical and 14 subcortical) or in any of the behavioral scores (including IQ, Autism Diagnostic Interview, and Autism Diagnostic Observation Schedule). Finally, only subtype 2, comprising about 43% of ASD participants, led to significant enrichments after multiple testing corrections. Notably, the dominant enrichment corresponded to excitation/inhibition imbalance, a leading well-known primary mechanism in the pathophysiology of ASD.

Conclusions: Our results support a link between excitation/inhibition imbalance and functional connectivity alterations, but only in one ASD subtype, overall characterized by brain hyperconnectivity and major alterations in somatomotor and default mode networks.

Postmortem studies have revealed increased density of excitatory synapses in the brains of individuals with autism spectrum disorder (ASD), with a putative link to aberrant mTOR-dependent synaptic pruning. ASD is also characterized by atypical macroscale functional connectivity as measured with resting-state fMRI (rsfMRI). These observations raise the question of whether excess of synapses causes aberrant functional connectivity in ASD. Using rsfMRI, electrophysiology and in silico modelling in Tsc2 haploinsufficient mice, we show that mTOR-dependent increased spine density is associated with ASD -like stereotypies and cortico-striatal hyperconnectivity. These deficits are completely rescued by pharmacological inhibition of mTOR. Notably, we further demonstrate that children with idiopathic ASD exhibit analogous cortical-striatal hyperconnectivity, and document that this connectivity fingerprint is enriched for ASD-dysregulated genes interacting with mTOR or Tsc2. Finally, we show that the identified transcriptomic signature is predominantly expressed in a subset of children with autism, thereby defining a segregable autism subtype. Our findings causally link mTOR-related synaptic pathology to large-scale network aberrations, revealing a unifying multi-scale framework that mechanistically reconciles developmental synaptopathy and functional hyperconnectivity in autism.

The process of translation requires substantial cellular resources. Cells have therefore evolved complex mechanisms to control overall protein synthesis as well as the translation of specific mRNAs that are crucial for cell growth and proliferation. At the heart of this process is the mammalian target of rapamycin (mTOR) signalling pathway, which senses and responds to nutrient availability, energy sufficiency, stress, hormones and mitogens to modulate protein synthesis. Here, we highlight recent findings on the regulators and effectors of mTOR and discuss specific cases that serve as paradigms for the different modes of mTOR regulation and its control of translation.

The most common clinical sign of autism spectrum disorders (ASD) is social interaction impairment, which is associated with communication deficits and stereotyped behaviors. Based on recent brain-imaging results, our hypothesis is that abnormalities in the superior temporal sulcus (STS) are highly implicated in ASD. STS abnormalities are characterized by decreased gray matter concentration, rest hypoperfusion and abnormal activation during social tasks. STS anatomical and functional anomalies occurring during early brain development could constitute the first step in the cascade of neural dysfunction underlying ASD. We will focus this review on the STS, which has been highly implicated in social cognition. We will review recent data on the contribution of the STS to normal social cognition and review brain-imaging data implicating this area in ASD. This review is part of the INMED/TINS special issue “Nature and nurture in brain development and neurological disorders”, based on presentations at the annual INMED/TINS symposium (http://inmednet.com/).

Autism spectrum disorder (ASD) is a neurodevelopmental condition with onset in early childhood, still diagnosed only through clinical observation due to the lack of laboratory biomarkers. Early detection strategies would be especially useful in screening high-risk newborn siblings of children already diagnosed with ASD. We performed RNA sequencing on peripheral blood, comparing 27 pairs of ASD children vs their sex- and age-matched unaffected siblings. Differential gene expression profiling, performed applying an unpaired model found two immune genes, EGR1 and IGKV3D-15, significantly upregulated in ASD patients (both p adj = 0.037). Weighted gene correlation network analysis identified 18 co-expressed modules. One of these modules was downregulated among autistic individuals (p = 0.035) and a ROC curve using its eigengene values yielded an AUC of 0.62. Genes in this module are primarily involved in transcriptional control and its hub gene, RACK1, encodes for a signaling protein critical for neurodevelopment and innate immunity, whose expression is influenced by various hormones and known “endocrine disruptors”. These results indicate that transcriptomic biomarkers can contribute to the sensitivity of an intra-familial multimarker panel for ASD and provide further evidence that neurodevelopment, innate immunity and transcriptional regulation are key to ASD pathogenesis.