Explore the vast range of titles available.

Progress in understanding the genetic etiology of autism spectrum disorders (ASD) has fueled remarkable advances in our understanding of its potential neurobiological mechanisms. Yet, at the same time, these findings highlight extraordinary causal diversity and complexity at many levels ranging from molecules to circuits and emphasize the gaps in our current knowledge. Here we review current understanding of the genetic architecture of ASD and integrate genetic evidence, neuropathology and studies in model systems with how they inform mechanistic models of ASD pathophysiology. Despite the challenges, these advances provide a solid foundation for the development of rational, targeted molecular therapies.

The genetics of autism The autism spectrum disorders (ASDs) are a group of conditions typically characterized by repetitive behaviour, severely restricted interests and difficulties with social interactions and communication. ASDs are highly heritable, yet the underlying genetic determinants remain largely unknown. A genome-wide analysis reveals that people with ASDs carry a higher load of rare copy-number variants — segments of DNA for which the copy number differs between individual genomes — which are either inherited or arise de novo . The results implicate several novel genes as ASD candidates and point to the importance of cellular proliferation, projection and motility as well as specific signalling pathways in this disorder. The autistic spectrum disorders (ASDs) are highly heritable, yet the underlying genetic determinants remain largely unknown. Here, a genome-wide analysis of rare copy number variants (CNVs) has been carried out, revealing that ASD sufferers carry a higher load of rare, genic CNVs than do controls. Many of these CNVs are de novo and inherited. The results implicate several novel genes in ASDs, and point to the importance of cellular proliferation, projection and motility, as well as specific signalling pathways, in these disorders. The autism spectrum disorders (ASDs) are a group of conditions characterized by impairments in reciprocal social interaction and communication, and the presence of restricted and repetitive behaviours 1 . Individuals with an ASD vary greatly in cognitive development, which can range from above average to intellectual disability 2 . Although ASDs are known to be highly heritable (∼90%) 3 , the underlying genetic determinants are still largely unknown. Here we analysed the genome-wide characteristics of rare (<1% frequency) copy number variation in ASD using dense genotyping arrays. When comparing 996 ASD individuals of European ancestry to 1,287 matched controls, cases were found to carry a higher global burden of rare, genic copy number variants (CNVs) (1.19 fold, P = 0.012), especially so for loci previously implicated in either ASD and/or intellectual disability (1.69 fold, P = 3.4 × 10 -4 ). Among the CNVs there were numerous de novo and inherited events, sometimes in combination in a given family, implicating many novel ASD genes such as SHANK2, SYNGAP1 , DLGAP2 and the X-linked DDX53–PTCHD1 locus. We also discovered an enrichment of CNVs disrupting functional gene sets involved in cellular proliferation, projection and motility, and GTPase/Ras signalling. Our results reveal many new genetic and functional targets in ASD that may lead to final connected pathways.

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. Whole-exome sequencing in a large autism study identifies over 100 autosomal genes that are likely to affect risk for the disorder; these genes, which show unusual evolutionary constraint against mutations, carry de novo loss-of-function mutations in over 5% of autistic subjects and many function in synaptic, transcriptional and chromatin-remodelling pathways. Autism-linked genetic factors analysed Autism spectrum disorder (ASD) is a broad group of brain development disorders, including autism, childhood disintegrative disorder and Asperger's syndrome, characterized by impaired social interaction and communication, repetitive behaviour and restricted interests. Two groups reporting in this issue of Nature have used large-scale whole-exome sequencing to examine the contribution of inherited and germline de novo mutations to ASD risk. Silvia De Rubeis et al . analysed DNA samples from 3,871 autism cases and 9,937 ancestry-matched or parental controls and identify more than 100 autosomal genes that are likely to affect risk for the disease. De novo loss-of-function mutations were detected in more than 5% of autistic subjects. Many of the associated gene products appear to function in synaptic, transcriptional, and chromatin remodelling pathways. Ivan Iossifov et al . sequenced exomes from more than 2,500 families, each with one child with ASD. They identify 27 high-confidence gene targets and estimate that 13% of de novo missense mutations and 43% of de novo 'likely gene-disrupting' (LGD) mutations contribute to 12% and 9% of diagnoses, respectively.

Neuronal activity induces the post-translational modification of synaptic molecules, promotes localized protein synthesis within dendrites and activates gene transcription, thereby regulating synaptic function and allowing neuronal circuits to respond dynamically to experience. Evidence indicates that many of the genes that are mutated in autism spectrum disorder are crucial components of the activity-dependent signalling networks that regulate synapse development and plasticity. Dysregulation of activity-dependent signalling pathways in neurons may, therefore, have a key role in the aetiology of autism spectrum disorder.

Autism spectrum disorders (ASDs) represent a formidable challenge for psychiatry and neuroscience because of their high prevalence, lifelong nature, complexity and substantial heterogeneity. Facing these obstacles requires large-scale multidisciplinary efforts. Although the field of genetics has pioneered data sharing for these reasons, neuroimaging had not kept pace. In response, we introduce the Autism Brain Imaging Data Exchange (ABIDE)—a grassroots consortium aggregating and openly sharing 1112 existing resting-state functional magnetic resonance imaging (R-fMRI) data sets with corresponding structural MRI and phenotypic information from 539 individuals with ASDs and 573 age-matched typical controls (TCs; 7–64 years) (http://fcon_1000.projects.nitrc.org/indi/abide/). Here, we present this resource and demonstrate its suitability for advancing knowledge of ASD neurobiology based on analyses of 360 male subjects with ASDs and 403 male age-matched TCs. We focused on whole-brain intrinsic functional connectivity and also survey a range of voxel-wise measures of intrinsic functional brain architecture. Whole-brain analyses reconciled seemingly disparate themes of both hypo- and hyperconnectivity in the ASD literature; both were detected, although hypoconnectivity dominated, particularly for corticocortical and interhemispheric functional connectivity. Exploratory analyses using an array of regional metrics of intrinsic brain function converged on common loci of dysfunction in ASDs (mid- and posterior insula and posterior cingulate cortex), and highlighted less commonly explored regions such as the thalamus. The survey of the ABIDE R-fMRI data sets provides unprecedented demonstrations of both replication and novel discovery. By pooling multiple international data sets, ABIDE is expected to accelerate the pace of discovery setting the stage for the next generation of ASD studies.

Autism spectrum disorders (ASD) are a group of neurodevelopmental conditions characterized by dysfunction in social interaction, communication and stereotypic behavior. Genetic and environmental factors have been implicated in the development of ASD, but the molecular mechanisms underlying their interaction are not clear. Epigenetic modifications have been suggested as molecular mechanism that can mediate the interaction between the environment and the genome to produce adaptive or maladaptive behaviors. Here, using the Illumina 450 K methylation array we have determined the existence of many dysregulated CpGs in two cortical regions, Brodmann area 10 (BA10) and Brodmann area 24 (BA24), of individuals who had ASD. In BA10 we found a very significant enrichment for genomic areas responsible for immune functions among the hypomethylated CpGs, whereas genes related to synaptic membrane were enriched among hypermethylated CpGs. By comparing our methylome data with previously published transcriptome data, and by performing real-time PCR on selected genes that were dysregulated in our study, we show that hypomethylated genes are often overexpressed, and that there is an inverse correlation between gene expression and DNA methylation within the individuals. Among these genes there were C1Q , C3 , ITGB2 (C3R) , TNF- α , IRF8 and SPI1 , which have recently been implicated in synaptic pruning and microglial cell specification. Finally, we determined the epigenetic dysregulation of the gene HDAC4 , and we confirm that the locus encompassing C11orf21/TSPAN32 has multiple hypomethylated CpGs in the autistic brain, as previously demonstrated. Our data suggest a possible role for epigenetic processes in the etiology of ASD.

Behavioral studies of facial emotion recognition (FER) in autism spectrum disorders (ASD) have yielded mixed results. Here we address demographic and experiment-related factors that may account for these inconsistent findings. We also discuss the possibility that compensatory mechanisms might enable some individuals with ASD to perform well on certain types of FER tasks in spite of atypical processing of the stimuli, and difficulties with real-life emotion recognition. Evidence for such mechanisms comes in part from eye-tracking, electrophysiological, and brain imaging studies, which often show abnormal eye gaze patterns, delayed event-related-potential components in response to face stimuli, and anomalous activity in emotion-processing circuitry in ASD, in spite of intact behavioral performance during FER tasks. We suggest that future studies of FER in ASD: 1) incorporate longitudinal (or cross-sectional) designs to examine the developmental trajectory of (or age-related changes in) FER in ASD and 2) employ behavioral and brain imaging paradigms that can identify and characterize compensatory mechanisms or atypical processing styles in these individuals.

Rationale Autism spectrum disorder (ASD) is a complex heterogeneous neurodevelopmental disorder with onset during early childhood and typically a life-long course. The majority of ASD cases stems from complex, ‘multiple-hit’, oligogenic/polygenic underpinnings involving several loci and possibly gene–environment interactions. These multiple layers of complexity spur interest into the identification of biomarkers able to define biologically homogeneous subgroups, predict autism risk prior to the onset of behavioural abnormalities, aid early diagnoses, predict the developmental trajectory of ASD children, predict response to treatment and identify children at risk for severe adverse reactions to psychoactive drugs. Objectives The present paper reviews (a) similarities and differences between the concepts of ‘biomarker’ and ‘endophenotype’, (b) established biomarkers and endophenotypes in autism research (biochemical, morphological, hormonal, immunological, neurophysiological and neuroanatomical, neuropsychological, behavioural), (c) -omics approaches towards the discovery of novel biomarker panels for ASD, (d) bioresource infrastructures and (e) data management for biomarker research in autism. Results Known biomarkers, such as abnormal blood levels of serotonin, oxytocin, melatonin, immune cytokines and lymphocyte subtypes, multiple neuropsychological, electrophysiological and brain imaging parameters, will eventually merge with novel biomarkers identified using unbiased genomic, epigenomic, transcriptomic, proteomic and metabolomic methods, to generate multimarker panels. Bioresource infrastructures, data management and data analysis using artificial intelligence networks will be instrumental in supporting efforts to identify these biomarker panels. Conclusions Biomarker research has great heuristic potential in targeting autism diagnosis and treatment.

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition that occurs within the first 3 years of life, which is marked by social skills and communication deficits along with stereotyped repetitive behavior. Although great efforts have been made to clarify the underlying neuroanatomical abnormalities and brain-behavior relationships in adolescents and adults with ASD, literature is still limited in information about the neurobiology of ASD in the early age of life. Brain images of 50 toddlers with ASD and 28 age, gender, and developmental quotient matched toddlers with developmental delay (DD) (control group) between ages 2 and 3 years were captured using combined magnetic resonance-based structural imaging and diffusion tensor imaging (DTI). Structural magnetic resonance imaging was applied to assess overall gray matter (GM) and white matter (WM) volumes, and regional alterations were assessed by voxel-based morphometry. DTI was used to investigate the white matter tract integrity. Compared with DD, significant increases were observed in ASD, primarily in global GM and WM volumes and in right superior temporal gyrus regional GM and WM volumes. Higher fractional anisotropy value was also observed in the corpus callosum, posterior cingulate cortex, and limbic lobes of ASD. The converging findings of structural and white matter abnormalities in ASD suggest that alterations in neural-anatomy of different brain regions may be involved in behavioral and cognitive deficits associated with ASD, especially in an early age of 2–3 years old toddlers.

Autism is a heterogeneous disorder with multiple behavioral and biological phenotypes. Accelerated brain growth during early childhood is a well-established biological feature of autism. Onset pattern, i.e., early onset or regressive, is an intensely studied behavioral phenotype of autism. There is currently little known, however, about whether, or how, onset status maps onto the abnormal brain growth. We examined the relationship between total brain volume and onset status in a large sample of 2- to 4-y-old boys and girls with autism spectrum disorder (ASD) [n = 53, no regression (nREG); n = 61, regression (REG)] and a comparison group of age-matched typically developing controls (n = 66). We also examined retrospective head circumference measurements from birth through 18 mo of age. We found that abnormal brain enlargement was most commonly found in boys with regressive autism. Brain size in boys without regression did not differ from controls. Retrospective head circumference measurements indicate that head circumference in boys with regressive autism is normal at birth but diverges from the other groups around 4–6 mo of age. There were no differences in brain size in girls with autism (n = 22, ASD; n = 24, controls). These results suggest that there may be distinct neural phenotypes associated with different onsets of autism. For boys with regressive autism, divergence in brain size occurs well before loss of skills is commonly reported. Thus, rapid head growth may be a risk factor for regressive autism.