Genetic studies in children with intellectual disability and autistic spectrum of disorders

Autism is one of the five disorders that falls under the umbrella of Pervasive Developmental Disorders (PDD) or Autism Spectrum Disorder (ASD), a category of neurological disorders characterized by "severe and pervasive impairment in several areas of development." ASD is characterized by varying degrees of impairment in communication skills, social interaction and restricted, repetitive stereotyped patterns of behavior. The five disorders under PDD are autistic disorder, Asperger's disorder, childhood disintegrative disorder, Rett's disorder and PDD-not otherwise specified. ASD can often be reliably detected by the age of 3 years and, in some cases, as early as 18 months. The appearance of any warning signs of ASD is reason to have the child evaluated by a professional specializing in these disorders.     

Whole Genome Sequencing Reveals a De Novo SHANK3 Mutation in Familial Autism Spectrum Disorder

IntroductionClinical genomics promise to be especially suitable for the study of etiologically heterogeneous conditions such as Autism Spectrum Disorder (ASD). Here we present three siblings with ASD where we evaluated the usefulness of Whole Genome Sequencing (WGS) for the diagnostic approach to ASD.MethodsWe identified a family segregating ASD in three siblings with an unidentified cause. We performed WGS in the three probands and used a state-of-the-art comprehensive bioinformatic analysis pipeline and prioritized the identified variants located in genes likely to be related to ASD. We validated the finding by Sanger sequencing in the probands and their parents.ResultsThree male siblings presented a syndrome characterized by severe intellectual disability, absence of language, autism spectrum symptoms and epilepsy with negative family history for mental retardation, language disorders, ASD or other psychiatric disorders. We found germline mosaicism for a heterozygous deletion of a cytosine in the exon 21 of the SHANK3 gene, resulting in a missense sequence of 5 codons followed by a premature stop codon ({"type":"entrez-nucleotide","attrs":{"text":"NM_033517","term_id":"380748962","term_text":"NM_033517"}}NM_033517:c.3259_3259delC, p.Ser1088Profs*6).ConclusionsWe reported an infrequent form of familial ASD where WGS proved useful in the clinic. We identified a mutation in SHANK3 that underscores its relevance in Autism Spectrum Disorder.     

Cell adhesion molecules and their involvement in autism spectrum disorder

Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders characterized by abnormalities in social interaction, language development and behavior. Recent genetic studies demonstrate that alterations in synaptic genes including those encoding cell adhesion molecules and their interaction partners play important roles in the pathogenesis of ASD. Systematic analyses of different cell adhesion molecule genes will help elucidate their normal functions and regulatory mechanisms in the establishment and maintenance of normal neural circuits and uncover genetic aberrations contributing to ASD.     

Prevalence,Comorbidity and Heritability of Hoarding Symptoms in Adolescence: A Population Based Twin Study in 15-Year Olds

Background

Hoarding Disorder (HD) is often assumed to be an ‘old age’ problem, but many individuals diagnosed with HD retrospectively report first experiencing symptoms in childhood or adolescence. We examined the prevalence, comorbidity and etiology of hoarding symptoms in adolescence.

Methods

To determine the presence of clinically significant hoarding symptoms, a population-based sample of 15-year old twins (N = 3,974) completed the Hoarding Rating Scale-Self Report. Co-occurring Obsessive Compulsive Disorder (OCD), Autism Spectrum Disorders (ASD) and Attention Deficit Hyperactivity Disorder (ADHD) were estimated from parental report. Model-fitting analyses divided hoarding symptom scores into additive genetic, shared, and non-shared environmental effects.

Results

The prevalence of clinically significant hoarding symptoms was 2% (95% CI 1.6–2.5%), with a significantly higher prevalence in girls than boys. Exclusion of the clutter criterion (as adolescents do not have control over their environment) increased the prevalence rate to 3.7% (95% CI 3.1–4.3%). Excessive acquisition was reported by 30–40% among those with clinically significant hoarding symptoms. The prevalence of co-occurring OCD (2.9%), ASD (2.9%) and ADHD (10.0%) was comparable in hoarding and non-hoarding teenagers. Model-fitting analyses suggested that, in boys, additive genetic (32%; 95% CI 13–44%) and non-shared environmental effects accounted for most of the variance. In contrast, among girls, shared and non-shared environmental effects explained most of the variance, while additive genetic factors played a negligible role.

Conclusions

Hoarding symptoms are relatively prevalent in adolescents, particularly in girls, and cause distress and/or impairment. Hoarding was rarely associated with other common neurodevelopmental disorders, supporting its DSM-5 status as an independent diagnosis. The relative importance of genetic and shared environmental factors for hoarding differed across sexes. The findings are suggestive of dynamic developmental genetic and environmental effects operating from adolescence onto adulthood.     

Genetic architecture in autism spectrum disorder

Autism spectrum disorder (ASD) is characterized by impairments in reciprocal social interaction and communication, and by restricted and repetitive behaviors. Family studies indicate a significant genetic basis for ASD susceptibility, and genomic scanning is beginning to elucidate the underlying genetic architecture. Some 5-15% of individuals with ASD have an identifiable genetic etiology corresponding to known chromosomal rearrangements or single gene disorders. Rare (<1% frequency) de novo or inherited copy number variations (CNVs) (especially those that affect genes with synaptic function) are observed in 5-10% of idiopathic ASD cases. These findings, coupled with genome sequencing data suggest the existence of hundreds of ASD risk genes. Common variants, yet unidentified, exert only small effects on risk. Identification of ASD risk genes with high penetrance will broaden the targets amenable to genetic testing; while the biological pathways revealed by the deeper list of ASD genes should narrow the targets for therapeutic intervention.     

The complex genetics in autism spectrum disorders

Autism spectrum disorders(ASD) are a pervasive neurodevelopmental disease characterized by deficits in social interaction and nonverbal communication, as well as restricted interests and stereotypical behavior. Genetic changes/heritability is one of the major contributing factors, and hundreds to thousands of causative and susceptible genes, copy number variants(CNVs), linkage regions, and micro RNAs have been associated with ASD which clearly indicates that ASD is a complex genetic disorder. Here, we will briefly summarize some of the high-confidence genetic changes in ASD and their possible roles in their pathogenesis.     

自闭症谱系障碍的分子遗传学研究进展

自闭症谱系障碍(Autism spectrum disorder, ASD)是一类常见神经发育疾病,以社会交往障碍、刻板重复行为与狭隘的兴趣为主要临床特征。在过去40年间,ASD患病率呈不断上升趋势,因而日益受到人们关注。近年来由于大规模外显子测序的应用,发现了许多新的ASD易感基因。这些易感基因富集在几个共同的遗传信号通路中,参与突触形成和染色质重构等。最新的动物模型研究表明,ASD的发病机制包括神经突触可塑性异常和神经回路兴奋性-抑制性平衡紊乱。本文从ASD遗传病因的高度异质性、众多致病基因突变影响的共同生物学过程以及遗传诊断方法和药物研发的进展等几个方面进行了综述,以期帮助人们深入了解ASD的遗传基础和转化研究现状。     

Expression profiling of autism candidate genes during human brain development implicates central immune signaling pathways

The Autism Spectrum Disorders (ASD) represent a clinically heterogeneous set of conditions with strong hereditary components. Despite substantial efforts to uncover the genetic basis of ASD, the genomic etiology appears complex and a clear understanding of the molecular mechanisms underlying Autism remains elusive. We hypothesized that focusing gene interaction networks on ASD-implicated genes that are highly expressed in the developing brain may reveal core mechanisms that are otherwise obscured by the genomic heterogeneity of the disorder. Here we report an in silico study of the gene expression profile from ASD-implicated genes in the unaffected developing human brain. By implementing a biologically relevant approach, we identified a subset of highly expressed ASD-candidate genes from which interactome networks were derived. Strikingly, immune signaling through NFκB, Tnf, and Jnk was central to ASD networks at multiple levels of our analysis, and cell-type specific expression suggested glia--in addition to neurons--deserve consideration. This work provides integrated genomic evidence that ASD-implicated genes may converge on central cytokine signaling pathways.     

Role of glucose 6-phosphate dehydrogenase (G6PD) deficiency and its association to Autism Spectrum Disorders

Autism Spectrum Disorder (ASD) is a common group of neurodevelopmental disorders which causes significant alterations in social and communication skills along with repetitive behavior and limited interests. The physiological understanding of ASD is ambiguous. Several reports suggested that environmental, genetic and epigenetic changes, neuroinflammation, mitochondrial dysfunction and metabolic alterations orchestrate the pathological outcomes of ASD. A recent report from Saudi Arabia found a mutation in X-chromosomal housekeeping glucose 6-phosphate dehydrogenase (G6PD) gene in two male ASD patients. Although, the involvement of G6PD-deficiency in the pathogenesis of ASD is poorly understood. Several reports suggested that G6PD deficiency impedes cellular detoxification of reactive oxygen species (ROS), which may result in neuronal damage and neuroinflammation. A deficiency of G6PD in newborn children may play a fundamental role in the pathogenesis of ASD. In this review, we will discuss the implications of G6PD deficiency in pathogenesis, male biasness and theranostics in ASD patients.     

Network- and attribute-based classifiers can prioritize genes and pathways for autism spectrum disorders and intellectual disability

Autism spectrum disorders (ASD) are a group of related neurodevelopmental disorders with significant combined prevalence (～1%) and high heritability. Dozens of individually rare genes and loci associated with high-risk for ASD have been identified, which overlap extensively with genes for intellectual disability (ID). However, studies indicate that there may be hundreds of genes that remain to be identified. The advent of inexpensive massively parallel nucleotide sequencing can reveal the genetic underpinnings of heritable complex diseases, including ASD and ID. However, whole exome sequencing (WES) and whole genome sequencing (WGS) provides an embarrassment of riches, where many candidate variants emerge. It has been argued that genetic variation for ASD and ID will cluster in genes involved in distinct pathways and protein complexes. For this reason, computational methods that prioritize candidate genes based on additional functional information such as protein-protein interactions or association with specific canonical or empirical pathways, or other attributes, can be useful. In this study we applied several supervised learning approaches to prioritize ASD or ID disease gene candidates based on curated lists of known ASD and ID disease genes. We implemented two network-based classifiers and one attribute-based classifier to show that we can rank and classify known, and predict new, genes for these neurodevelopmental disorders. We also show that ID and ASD share common pathways that perturb an overlapping synaptic regulatory subnetwork. We also show that features relating to neuronal phenotypes in mouse knockouts can help in classifying neurodevelopmental genes. Our methods can be applied broadly to other diseases helping in prioritizing newly identified genetic variation that emerge from disease gene discovery based on WES and WGS.     

A novel approach of homozygous haplotype sharing identifies candidate genes in autism spectrum disorder

Autism spectrum disorder (ASD) is a highly heritable disorder of complex and heterogeneous aetiology. It is primarily characterized by altered cognitive ability including impaired language and communication skills and fundamental deficits in social reciprocity. Despite some notable successes in neuropsychiatric genetics, overall, the high heritability of ASD (~90%) remains poorly explained by common genetic risk variants. However, recent studies suggest that rare genomic variation, in particular copy number variation, may account for a significant proportion of the genetic basis of ASD. We present a large scale analysis to identify candidate genes which may contain low-frequency recessive variation contributing to ASD while taking into account the potential contribution of population differences to the genetic heterogeneity of ASD. Our strategy, homozygous haplotype (HH) mapping, aims to detect homozygous segments of identical haplotype structure that are shared at a higher frequency amongst ASD patients compared to parental controls. The analysis was performed on 1,402 Autism Genome Project trios genotyped for 1 million single nucleotide polymorphisms (SNPs). We identified 25 known and 1,218 novel ASD candidate genes in the discovery analysis including CADM2, ABHD14A, CHRFAM7A, GRIK2, GRM3, EPHA3, FGF10, KCND2, PDZK1, IMMP2L and FOXP2. Furthermore, 10 of the previously reported ASD genes and 300 of the novel candidates identified in the discovery analysis were replicated in an independent sample of 1,182 trios. Our results demonstrate that regions of HH are significantly enriched for previously reported ASD candidate genes and the observed association is independent of gene size (odds ratio 2.10). Our findings highlight the applicability of HH mapping in complex disorders such as ASD and offer an alternative approach to the analysis of genome-wide association data.     

Detection of Clinically Relevant Genetic Variants in Autism Spectrum Disorder by Whole-Genome Sequencing

Autism Spectrum Disorder (ASD) demonstrates high heritability and familial clustering, yet the genetic causes remain only partially understood as a result of extensive clinical and genomic heterogeneity. Whole-genome sequencing (WGS) shows promise as a tool for identifying ASD risk genes as well as unreported mutations in known loci, but an assessment of its full utility in an ASD group has not been performed. We used WGS to examine 32 families with ASD to detect de novo or rare inherited genetic variants predicted to be deleterious (loss-of-function and damaging missense mutations). Among ASD probands, we identified deleterious de novo mutations in six of 32 (19%) families and X-linked or autosomal inherited alterations in ten of 32 (31%) families (some had combinations of mutations). The proportion of families identified with such putative mutations was larger than has been previously reported; this yield was in part due to the comprehensive and uniform coverage afforded by WGS. Deleterious variants were found in four unrecognized, nine known, and eight candidate ASD risk genes. Examples include CAPRIN1 and AFF2 (both linked to FMR1, which is involved in fragile X syndrome), VIP (involved in social-cognitive deficits), and other genes such as SCN2A and KCNQ2 (linked to epilepsy), NRXN1, and CHD7, which causes ASD-associated CHARGE syndrome. Taken together, these results suggest that WGS and thorough bioinformatic analyses for de novo and rare inherited mutations will improve the detection of genetic variants likely to be associated with ASD or its accompanying clinical symptoms.     

Protein Interaction Networks Reveal Novel Autism Risk Genes within GWAS Statistical Noise

Genome-wide association studies (GWAS) for Autism Spectrum Disorder (ASD) thus far met limited success in the identification of common risk variants, consistent with the notion that variants with small individual effects cannot be detected individually in single SNP analysis. To further capture disease risk gene information from ASD association studies, we applied a network-based strategy to the Autism Genome Project (AGP) and the Autism Genetics Resource Exchange GWAS datasets, combining family-based association data with Human Protein-Protein interaction (PPI) data. Our analysis showed that autism-associated proteins at higher than conventional levels of significance (P<0.1) directly interact more than random expectation and are involved in a limited number of interconnected biological processes, indicating that they are functionally related. The functionally coherent networks generated by this approach contain ASD-relevant disease biology, as demonstrated by an improved positive predictive value and sensitivity in retrieving known ASD candidate genes relative to the top associated genes from either GWAS, as well as a higher gene overlap between the two ASD datasets. Analysis of the intersection between the networks obtained from the two ASD GWAS and six unrelated disease datasets identified fourteen genes exclusively present in the ASD networks. These are mostly novel genes involved in abnormal nervous system phenotypes in animal models, and in fundamental biological processes previously implicated in ASD, such as axon guidance, cell adhesion or cytoskeleton organization. Overall, our results highlighted novel susceptibility genes previously hidden within GWAS statistical “noise” that warrant further analysis for causal variants.     

Using a mouse model to gain insights into developmental coordination disorder

Motor impairments are a common feature of many neurodevelopmental disorders; in fact, over 50% of children with Attentional Deficit Hyperactivity Disorder or Autism Spectrum Disorder may have a co‐occurring diagnosis of developmental coordination disorder (DCD). DCD is a neurodevelopmental disorder of unknown etiology that affects motor coordination and learning, significantly impacting a child's ability to carry out everyday activities. Animal models play an important role in scientific investigation of behaviour and the mechanisms and processes that are involved in control of motor actions. The purpose of this paper is to present an approach in the mouse directed to gain behavioral and genetic insights into DCD that is designed with high face validity, construct validity and predictive validity. Pre‐clinical and clinical expertise is used to establish a set of scientific criteria that the model will meet in order to investigate the potential underlying causes of DCD.     

Structural,Genetic, and Functional Signatures of Disordered Neuro-Immunological Development in Autism Spectrum Disorder

Background

Numerous linkage studies have been performed in pedigrees of Autism Spectrum Disorders, and these studies point to diverse loci and etiologies of autism in different pedigrees. The underlying pattern may be identified by an integrative approach, especially since ASD is a complex disorder manifested through many loci.

Method

Autism spectrum disorder (ASD) was studied through two different and independent genome-scale measurement modalities. We analyzed the results of copy number variation in autism and triangulated these with linkage studies.

Results

Consistently across both genome-scale measurements, the same two molecular themes emerged: immune/chemokine pathways and developmental pathways.

Conclusion

Linkage studies in aggregate do indeed share a thematic consistency, one which structural analyses recapitulate with high significance. These results also show for the first time that genomic profiling of pathways using a recombination distance metric can capture pathways that are consistent with those obtained from copy number variations (CNV).     

A population genetic approach to mapping neurological disorder genes using deep resequencing

Deep resequencing of functional regions in human genomes is key to identifying potentially causal rare variants for complex disorders. Here, we present the results from a large-sample resequencing (n = 285 patients) study of candidate genes coupled with population genetics and statistical methods to identify rare variants associated with Autism Spectrum Disorder and Schizophrenia. Three genes, MAP1A, GRIN2B, and CACNA1F, were consistently identified by different methods as having significant excess of rare missense mutations in either one or both disease cohorts. In a broader context, we also found that the overall site frequency spectrum of variation in these cases is best explained by population models of both selection and complex demography rather than neutral models or models accounting for complex demography alone. Mutations in the three disease-associated genes explained much of the difference in the overall site frequency spectrum among the cases versus controls. This study demonstrates that genes associated with complex disorders can be mapped using resequencing and analytical methods with sample sizes far smaller than those required by genome-wide association studies. Additionally, our findings support the hypothesis that rare mutations account for a proportion of the phenotypic variance of these complex disorders.     

Metal and essential element levels in hair and association with autism severity

BackgroundAutism Spectrum Disorder (ASD) is a complex disorder with heterogeneous etiology and wide clinical severity which supports the needs of recognizing biological and clinical features in patient subsets. The present study aimed to understand possible associations between the hair levels of metals and essential elements and some specific features of ASD measured by the Autism Diagnostic Observation Schedule (ADOS) that represents the gold-standard instrument to objectively confirm ASD diagnosis.MethodsA cross-sectional study was performed in the province of Catania (Sicily, South Italy). Forty-eight subjects with ASD (70.8% male), aged from 2 to 17 years were studied. Metals (Li, Be, Al, Ni, As, Mo, Cd, Hg, U, Pb) and essential trace elements (Cr, Co, Mn, Zn, Cu, Se) were quantified in hair by inductively coupled plasma mass spectrometry analysis. Participants were characterized by measuring the severity of autism symptoms and cognitive levels.ResultsA significant and positive correlation was found between hair metal burden (lead, aluminum, arsenic and cadmium levels) and severity of ASD symptoms (social communication deficits and repetitive, restrictive behaviors). Hair zinc level were inversely related with age while there was a negative, significant association between hair zinc level and severity of autistic symptoms (defective functional play and creativity and increase of stereotyped behavior). Lead, molybdenum and manganese hair levels were inversely correlated with cognitive level (full intelligence quotient) in ASD individuals.ConclusionsThe present study suggests the importance to combine metallomics analysis with pertinent disease features in ASD to identify potential environmental risk factors on an individual level possibly in the early developmental period.     

Cellular reprogramming: a novel tool for investigating autism spectrum disorders

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impairment in reciprocal social interaction and communication, as well as the manifestation of stereotyped behaviors. Despite much effort, ASDs are not yet fully understood. Advanced genetics and genomics technologies have recently identified novel ASD genes, and approaches using genetically engineered murine models or postmortem human brain have facilitated understanding ASD. Reprogramming somatic cells into induced pluripotent stem cells (iPSCs) provides unprecedented opportunities in generating human disease models. Here, we present an overview of applying iPSCs in developing cellular models for understanding ASD. We also discuss future perspectives in the use of iPSCs as a source of cell therapy and as a screening platform for identifying small molecules with efficacy for alleviating ASD.