Networks of neuronal genes affected by common and rare variants in autism spectrum disorders

Autism spectrum disorders (ASD) are neurodevelopmental disorders with phenotypic and genetic heterogeneity. Recent studies have reported rare and de novo mutations in ASD, but the allelic architecture of ASD remains unclear. To assess the role of common and rare variations in ASD, we constructed a gene co-expression network based on a widespread survey of gene expression in the human brain. We identified modules associated with specific cell types and processes. By integrating known rare mutations and the results of an ASD genome-wide association study (GWAS), we identified two neuronal modules that are perturbed by both rare and common variations. These modules contain highly connected genes that are involved in synaptic and neuronal plasticity and that are expressed in areas associated with learning and memory and sensory perception. The enrichment of common risk variants was replicated in two additional samples which include both simplex and multiplex families. An analysis of the combined contribution of common variants in the neuronal modules revealed a polygenic component to the risk of ASD. The results of this study point toward contribution of minor and major perturbations in the two sub-networks of neuronal genes to ASD risk.     

Exploiting aberrant mRNA expression in autism for gene discovery and diagnosis

Autism spectrum disorder (ASD) is characterized by substantial phenotypic and genetic heterogeneity, which greatly complicates the identification of genetic factors that contribute to the disease. Study designs have mainly focused on group differences between cases and controls. The problem is that, by their nature, group difference-based methods (e.g., differential expression analysis) blur or collapse the heterogeneity within groups. By ignoring genes with variable within-group expression, an important axis of genetic heterogeneity contributing to expression variability among affected individuals has been overlooked. To this end, we develop a new gene expression analysis method—aberrant gene expression analysis, based on the multivariate distance commonly used for outlier detection. Our method detects the discrepancies in gene expression dispersion between groups and identifies genes with significantly different expression variability. Using this new method, we re-visited RNA sequencing data generated from post-mortem brain tissues of 47 ASD and 57 control samples. We identified 54 functional gene sets whose expression dispersion in ASD samples is more pronounced than that in controls, as well as 76 co-expression modules present in controls but absent in ASD samples due to ASD-specific aberrant gene expression. We also exploited aberrantly expressed genes as biomarkers for ASD diagnosis. With a whole blood expression data set, we identified three aberrantly expressed gene sets whose expression levels serve as discriminating variables achieving >70 % classification accuracy. In summary, our method represents a novel discovery and diagnostic strategy for ASD. Our findings may help open an expression variability-centered research avenue for other genetically heterogeneous disorders.     

Pathway Network Analyses for Autism Reveal Multisystem Involvement,Major Overlaps with Other Diseases and Convergence upon MAPK and Calcium Signaling

We used established databases in standard ways to systematically characterize gene ontologies, pathways and functional linkages in the large set of genes now associated with autism spectrum disorders (ASDs). These conditions are particularly challenging—they lack clear pathognomonic biological markers, they involve great heterogeneity across multiple levels (genes, systemic biological and brain characteristics, and nuances of behavioral manifestations)—and yet everyone with this diagnosis meets the same defining behavioral criteria. Using the human gene list from Simons Foundation Autism Research Initiative (SFARI) we performed gene set enrichment analysis with the Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway Database, and then derived a pathway network from pathway-pathway functional interactions again in reference to KEGG. Through identifying the GO (Gene Ontology) groups in which SFARI genes were enriched, mapping the coherence between pathways and GO groups, and ranking the relative strengths of representation of pathway network components, we 1) identified 10 disease-associated and 30 function-associated pathways 2) revealed calcium signaling pathway and neuroactive ligand-receptor interaction as the most enriched, statistically significant pathways from the enrichment analysis, 3) showed calcium signaling pathways and MAPK signaling pathway to be interactive hubs with other pathways and also to be involved with pervasively present biological processes, 4) found convergent indications that the process “calcium-PRC (protein kinase C)-Ras-Raf-MAPK/ERK” is likely a major contributor to ASD pathophysiology, and 5) noted that perturbations associated with KEGG’s category of environmental information processing were common. These findings support the idea that ASD-associated genes may contribute not only to core features of ASD themselves but also to vulnerability to other chronic and systemic problems potentially including cancer, metabolic conditions and heart diseases. ASDs may thus arise, or emerge, from underlying vulnerabilities related to pleiotropic genes associated with pervasively important molecular mechanisms, vulnerability to environmental input and multiple systemic co-morbidities.     

Autism-associated gene expression in peripheral leucocytes commonly observed between subjects with autism and healthy women having autistic children

Autism spectrum disorder (ASD) is a severe neuropsychiatric disorder which has complex pathobiology with profound influences of genetic factors in its development. Although the numerous autism susceptible genes were identified, the etiology of autism is not fully explained. Using DNA microarray, we examined gene expression profiling in peripheral blood from 21 individuals in each of the four groups; young adults with ASD, age- and gender-matched healthy subjects (ASD control), healthy mothers having children with ASD (asdMO), and asdMO control. There was no blood relationship between ASD and asdMO. Comparing the ASD group with control, 19 genes were found to be significantly changed. These genes were mainly involved in cell morphology, cellular assembly and organization, and nerve system development and function. In addition, the asdMO group possessed a unique gene expression signature shown as significant alterations of protein synthesis despite of their nonautistic diagnostic status. Moreover, an ASD-associated gene expression signature was commonly observed in both individuals with ASD and asdMO. This unique gene expression profiling detected in peripheral leukocytes from affected subjects with ASD and unaffected mothers having ASD children suggest that a genetic predisposition to ASD may be detectable even in peripheral cells. Altered expression of several autism candidate genes such as FMR-1 and MECP2, could be detected in leukocytes. Taken together, these findings suggest that the ASD-associated genes identified in leukocytes are informative to explore the genetic, epigenetic, and environmental background of ASD and might become potential tools to assess the crucial factors related to the clinical onset of the disorder.     

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.     

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.     

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.     

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.     

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.     

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.     

A systems biological study on the comorbidity of autism spectrum disorders and bipolar disorder

Autism Spectrum Disorder (ASD) is a "spectrum" of disorders, characterized by varying degrees of symptoms ranging from mild to severe. Among Psychiatric disorders, Autism Spectrum Disorders have the strongest evidence for a genetic basis, yet the search for specific genes contributing to these often devastating developmental syndromes has proven extraordinarily difficult. Bipolar Disorder (BP) is a manic-depressive disorder whose symptoms are characterized by extremities in moods. It is also called as the "Mood disorder". BP, like, ASD also has a strong genetic basis and identification of the candidate genes still remains an ongoing effort. Literature studies point to the hypothesis that ASD and BP have good chances of comorbidity and that they may share common pathways for their manifestation. But this hypothesis has not been worked on in depth. Thus, the study focuses on identifying the chances of their comorbidity by identifying their common pathways and the genes involved in the pathways and also discuss the degree of chances of their comorbidity based on the genes involved in the common pathways. Networks for the genes are also constructed to represent their commonness or uniqueness for the disorders.     

Genetically meaningful phenotypic subgroups in autism spectrum disorders

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder with strong evidence for genetic susceptibility. However, the effect sizes for implicated chromosomal loci are small, hard to replicate and current evidence does not explain the majority of the estimated heritability. Phenotypic heterogeneity could be one phenomenon complicating identification of genetic factors. We used data from the Autism Diagnostic Interview‐Revised, Autism Diagnostic Observation Schedule, Vineland Adaptive Behavior Scales, head circumferences, and ages at exams as classifying variables to identify more clinically similar subgroups of individuals with ASD. We identified two distinct subgroups of cases within the Autism Genetic Resource Exchange dataset, primarily defined by the overall severity of evaluated traits. In addition, there was significant familial clustering within subgroups (odds ratio, OR ≈ 1.38–1.42, P < 0.00001), and genotypes were more similar within subgroups compared to the unsubgrouped dataset (Fst = 0.17 ± 0.0.0009). These results suggest that the subgroups recapitulate genetic etiology. Using the same approach in an independent dataset from the Autism Genome Project, we similarly identified two distinct subgroups of cases and confirmed this severity‐based dichotomy. We also observed evidence for genetic contributions to subgroups identified in the replication dataset. Our results provide more effective methods of phenotype definition that should increase power to detect genetic factors influencing risk for ASD .     

Lack of Association between NLGN3, NLGN4, SHANK2 and SHANK3 Gene Variants and Autism Spectrum Disorder in a Chinese Population

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social communication, absence or delay in language development, and stereotyped or repetitive behaviors. Genetic studies show that neurexin-neuroligin (NRXN-NLGN) pathway genes contribute susceptibility to ASD, which include cell adhesion molecules NLGN3, NLGN4 and scaffolding proteins SHANK2 and SHANK3. Neuroligin proteins play an important role in synaptic function and trans-synaptic signaling by interacting with presynaptic neurexins. Shank proteins are scaffolding molecules of excitatory synapses, which function as central organizers of the postsynaptic density. Sequence level mutations and structural variations in these genes have been identified in ASD cases, while few studies were performed in Chinese population. In this study, we examined the copy numbers of four genes NLGN4, NLGN3, SHANK2, and SHANK3 in 285 ASD cases using multiplex fluorescence competitive polymerase chain reaction (PCR). We also screened the regulatory region including the promoter region and 5′/3′ untranslated regions (UTR) and the entire coding region of NLGN4 in a cohort of 285 ASD patients and 384 controls by direct sequencing of genomic DNA using the Sanger method. DNA copy number calculation in four genes showed no deletion or duplication in our cases. No missense mutations in NLGN4 were identified in our cohort. Association analysis of 6 common SNPs in NLGN4 did not find significant difference between ASD cases and controls. These findings showed that these genes may not be major disease genes in Chinese ASD cases.     

Co-expression analysis reveals a group of genes potentially involved in regulation of plant response to iron-deficiency

Iron (Fe) is an essential element for plant growth and development. Iron deficiency results in abnormal metabolisms from respiration to photosynthesis. Exploration of Fe-deficient responsive genes and their networks is critically important to understand molecular mechanisms leading to the plant adaptation to soil Fe-limitation. Co-expression genes are a cluster of genes that have a similar expression pattern to execute relatively biological functions at a stage of development or under a certain environmental condition. They may share a common regulatory mechanism. In this study, we investigated Fe-starved-related co-expression genes from Arabidopsis. From the biological process GO annotation of TAIR (The Arabidopsis Information Resource), 180 iron-deficient responsive genes were detected. Using ATTED-II database, we generated six gene co-expression networks. Among these, two modules of PYE and IRT1 were successfully constructed. There are 30 co-expression genes that are incorporated in the two modules (12 in PYE-module and 18 in IRT1-module). Sixteen of the co-expression genes were well characterized. The remaining genes (14) are poorly or not functionally identified with iron stress. Validation of the 14 genes using real-time PCR showed differential expression under iron-deficiency. Most of the co-expression genes (23/30) could be validated in pye and fit mutant plants with iron-deficiency. We further identified iron-responsive cis-elements upstream of the co-expression genes and found that 22 out of 30 genes contain the iron-responsive motif IDE1. Furthermore, some auxin and ethylene-responsive elements were detected in the promoters of the co-expression genes. These results suggest that some of the genes can be also involved in iron stress response through the phytohormone-responsive pathways.     

Intracellular calcium dysregulation in autism spectrum disorder: An analysis of converging organelle signaling pathways

Autism spectrum disorder (ASD) is a group of complex, neurological disorders that affect early cognitive, social, and verbal development. Our understanding of ASD has vastly improved with advances in genomic sequencing technology and genetic models that have identified >800 loci with variants that increase susceptibility to ASD. Although these findings have confirmed its high heritability, the underlying mechanisms by which these genes produce the ASD phenotypes have not been defined. Current efforts have begun to “functionalize” many of these variants and envisage how these susceptibility factors converge at key biochemical and biophysical pathways. In this review, we discuss recent work on intracellular calcium signaling in ASD, including our own work, which begins to suggest it as a compelling candidate mechanism in the pathophysiology of autism and a potential therapeutic target. We consider how known variants in the calcium signaling genomic architecture of ASD may exert their deleterious effects along pathways particularly involving organelle dysfunction including the endoplasmic reticulum (ER), a major calcium store, and the mitochondria, a major calcium ion buffer, and theorize how many of these pathways intersect.     

Analysis of gene co-expression networks and function modules at different developmental stages of chicken breast muscle

The development of poultry muscle fibers after hatching is closely related to meat quality and production efficiency. It is necessary to identify functional modules (groups of functionally related genes) related to muscle development at different developmental stages, and to investigate their relationships based on the weighted gene co-expression network analysis (WGCNA) methods. Accordingly, we investigated the co-expression associations between genes related to chicken breast muscle at four different developmental stages (between 2 and 14 weeks of age), and systematically analyzed the network topology in Jinmao Hua chicken. As a result, 2341 differentially expressed genes were identified and subjected to co-expression analysis. Four modules were identified to be related to a particular growth stage for the development of breast muscle. A series of genes with the highest connectivity were identified in the pink (2 weeks), yellow (6 weeks), green (10 weeks) and black modules (14 weeks), respectively, and visualized by Cytoscape. These hub genes (FGF, MAPKAPK5, NRG1, SCD, ACSL1, PPAR etc.) were mainly enriched in 15 pathways, such as MAPK signaling pathway, NRG/ErbB signaling pathway, and insulin signaling pathway. They shared biological functions related to development of breast muscle and adipogenesis. This is the first study of gene network with different stages of muscle development in Jinmao Hua chicken to observe co-expression patterns. It may contribute to the underlied molecular mechanisms of chicken breast muscle development.