Gene expression changes in children with autism

Dysregulated plasma autoantibodies are associated with B cell dysfunction in young Arab children with autism spectrum disorder in Qatar

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impaired social interaction and communication, as well as the occurrence of stereotyped and repetitive behaviors. Previous studies have provided solid evidence of dysregulated immune system in ASD; however, limited studies have investigated autoantibody profiles in individuals with ASD. This study aims to screen plasma autoantibodies in a well-defined cohort of young children with ASD (n = 100) and their matched controls (n = 60) utilizing a high-throughput KoRectly Expressed (KREX) i-Ome protein-array technology. We identified differential protein expression of 16 autoantibodies in ASD, which were correlated with differential gene expression of these markers in independent ASD cohorts. Meanwhile, we identified a distinct list of 33 autoantibodies associated with ASD severity; several of which were correlated with maternal age and birth weight in ASD. In addition, we found dysregulated numbers of circulating B cells and activated HLADR+ B cells in ASD, which were correlated with altered levels of several autoantibodies. Further in-depth analysis of B cell subpopulations revealed an increased frequency of activated naïve B cells in ASD, as well as an association of resting naïve B cells and transitional B cells with ASD severity. Pathway enrichment analysis revealed disrupted MAPK signaling in ASD, suggesting a potential relevance of this pathway to altered autoantibodies and B cell dysfunction in ASD. Finally, we found that a combination of eight autoantibodies associated with ASD severity showed an area under the curve (ROC-AUC) of 0.937 (95% CI = 0.890, 0.983; p < 0.001), which demonstrated the diagnostic accuracy of the eight-marker signature in the severity classification of ASD cases. Overall, this study determined dysregulated autoantibody profiles and B cell dysfunction in children with ASD and identified an eight-autoantibody panel for ASD severity classification.

NARP-related alterations in the excitatory and inhibitory circuitry of socially isolated mice: developmental insights and implications for autism spectrum disorder

Background

Social isolation during critical periods of development is associated with alterations in behavior and neuronal circuitry. This study aimed to investigate the immediate and developmental effects of social isolation on firing properties, neuronal activity-regulated pentraxin (NARP) and parvalbumin (PV) expression in the prefrontal cortex (PFC), social behavior in juvenile socially isolated mice, and the biological relevance of NARP expression in autism spectrum disorder (ASD).

Methods

Mice were subjected to social isolation during postnatal days 21-35 (P21-P35) and were compared with group-housed control mice. Firing properties in the PFC pyramidal neurons were altered in P35 socially isolated mice, which might be associated with alterations in NARP and PV expression.

Results

In adulthood, mice that underwent juvenile social isolation exhibited difficulty distinguishing between novel and familiar mice during a social memory task, while maintaining similar levels of social interaction as the control mice. Furthermore, a marked decrease in NARP expression in lymphoblastoid cell lines derived from adolescent humans with ASD as compared to typically developing (TD) humans was found.

Conclusion

Our study highlights the role of electrophysiological properties, as well as NARP and PV expression in the PFC in mediating the developmental consequences of social isolation on behavior.

Exploring key genes and pathways associated with sex differences in autism spectrum disorder: integrated bioinformatic analysis

Autism spectrum disorder (ASD) is a heterogenous neurodevelopmental disorder marked by functional abnormalities in brain that causes social and linguistic difficulties. The incidence of ASD is more prevalent in males compared to females, but the underlying mechanism, as well as molecular indications for identifying sex-specific differences in ASD symptoms remain unknown. Thus, impacting the development of personalized strategy towards pharmacotherapy of ASD. The current study employs an integrated bioinformatic approach to investigate the genes and pathways uniquely associated with sex specific differences in autistic individuals. Based on microarray dataset (GSE6575) extracted from the gene expression omnibus, the dysregulated genes between the autistic and the neurotypical individuals for both sexes were identified. Gene set enrichment analysis was performed to ascertain biological activities linked to the dysregulated genes. Protein-protein interaction network analysis was carried out to identify hub genes. The identified hub genes were examined to determine their functions and involvement in the associated pathways using Enrichr. Additionally, hub genes were validated from autism-associated databases and the potential small molecules targeting the hub genes were identified. The present study utilized whole blood transcriptomic gene expression analysis data and identified 2211 and 958 differentially expressed unique genes in males and females respectively. The functional enrichment analysis revealed that male hub genes were functionally associated with RNA polymerase II mediated transcriptional regulation whereas female hub genes were involved in intracellular signal transduction and cell migration. The top male hub genes exhibited functional enrichment in tyrosine kinase signalling pathway. The pathway enrichment analysis of male hub genes indicates the enrichment of papillomavirus infection. Female hub genes were enriched in androgen receptor signalling pathway and functionally enriched in focal adhesion specific excision repair. Identified drug like candidates targeting these genes may serve as a potential sex specific therapeutics. Wortmannin for males, 5-Fluorouracil for females had the highest scores. Targeted and sex-specific pharmacotherapies may be created for the management of ASD. The current investigation identifies sex-specific molecular signatures derived from whole blood which may serve as a potential peripheral sex-specific biomarkers for ASD. The study also uncovers the possible pharmacological interventions against the selected genes/pathway, providing support in development of therapeutic strategies to mitigate ASD. However, experimental proofs on biological systems are warranted.

Innate Immune Dysfunction and Neuroinflammation in Autism Spectrum Disorder (ASD)

Autism spectrum disorder (ASD) is a highly heterogeneous neurodevelopmental disorder characterized by communication and social behavior deficits. The presence of restricted and repetitive behaviors often accompanies these deficits, and these characteristics can range from mild to severe. The past several decades have seen a significant rise in the prevalence of ASD. The etiology of ASD remains unknown; however, genetic and environmental risk factors play a role. Multiple hypotheses converge to suggest that neuroinflammation, or at least the interaction between immune and neural systems, may be involved in the etiology of some ASD cases or groups. Repeated evidence of innate immune dysfunction has been seen in ASD, often associated with worsening behaviors. This evidence includes data from circulating myeloid cells and brain resident macrophages/microglia in both human and animal models. This comprehensive review presents recent findings of innate immune dysfunction in ASD, including aberrant innate cellular function, evidence of neuroinflammation, and microglia activation. Appeared originally in Brain Behav Immun 2023; 108:245-254.

Expression alteration of Neuroligin family gene in attention deficit and hyperactivity disorder and autism spectrum disorder

BACKGROUND

Autism spectrum disorder (ASD) is a complex neurodevelopment disorder with social and communicational deficiency, language impairment, and ritualistic behaviors. Attention deficit hyperactivity disorder (ADHD) is a pediatric psychiatric disorder with symptoms, including attention deficit, hyperactivity, and impulsiveness. ADHD is a childhood-onset disorder that can persist into adult life. Neuroligins are post-synaptic cell-adhesion molecules that connect neurons and have an essential role in the mediation of trans-synaptic signaling and shaping the synapse and circuits and neural network functioning.

AIMS

Present study aimed to shed light on the role of the Neuroligin gene family in ASD and ADHD.

METHODS AND PROCEDURES

mRNA levels of the Neuroligin gene family (NLGN1, NLGN2, NLGN3, and NLGN4X) were studied in the peripheral blood of 450 unrelated ASD patients, 450 unrelated ADHD patients, and the normal group included 490 unrelated non-psychiatric children by quantitative PCR. Also, clinical situations were considered.

OUTCOMES AND RESULTS

Results showed that mRNA levels of NLGN1, NLGN2, and NLGN3 were significantly down-regulated in the ASD group vs. control subjects. In ADHD, a significant reduction of NLGN2 and NLGN3 was detected in comparison with normal children. A comparison of ASD and ADHD subjects revealed that NLGN2 was significantly down-regulated in ASD subjects.

CONCLUSIONS

The Neuroligin family gene may play an essential role in the etiology of ASD and ADHD and thus be a source for a better understanding of neurodevelopment disorders.

IMPLICATIONS

Similar patterns of deficiency of Neuroligin family genes in ASDs and ADHDs may indicate the role of these genes in functions that have been affected in both disorders.

Overexpression of EphB6 and EphrinB2 controls soma spacing of cortical neurons in a mutual inhibitory way

To establish functional circuitry, neurons settle down in a particular spatial domain by spacing their cell bodies, which requires proper positioning of the soma and establishing of a zone with unique connections. Deficits in this process are implicated in neurodevelopmental diseases. In this study, we examined the function of EphB6 in the development of cerebral cortex. Overexpression of EphB6 via in utero electroporation results in clumping of cortical neurons, while reducing its expression has no effect. In addition, overexpression of EphrinB2, a ligand of EphB6, also induces soma clumping in the cortex. Unexpectedly, the soma clumping phenotypes disappear when both of them are overexpressed in cortical neurons. The mutual inhibitory effect of EphB6/ EphrinB2 on preventing soma clumping is likely to be achieved via interaction of their specific domains. Thus, our results reveal a combinational role of EphrinB2/EphB6 overexpression in controlling soma spacing in cortical development.

Exploring potential impacts of pregnancy-related maternal immune activation and extracellular vesicles on immune alterations observed in autism spectrum disorder

Autism Spectrum Disorder (ASD) is a set of neurodevelopmental disorders usually observed in early life, with impacts on behavioral and social skills. Incidence of ASD has been dramatically increasing worldwide, possibly due to increase in awareness/diagnosis as well as to genetic and environmental triggers. Currently, it is estimated that ∼1% of the world population presents ASD symptoms. In addition to its genetic background, environmental and immune-related factors also influence the ASD etiology. In this context, maternal immune activation (MIA) has recently been suggested as a component potentially involved in ASD development. In addition, extracellular vesicles (EVs) are abundant at the maternal-fetal interface and are actively involved in the immunoregulation required for a healthy pregnancy. Considering that alterations in concentration and content of EVs have also been associated with ASD, this article raises a debate about the potential roles of EVs in the processes surrounding MIA. This represents the major differential of the present review compared to other ASD studies. To support the suggested correlations and hypotheses, findings regarding the roles of EVs during pregnancy and potential influences on ASD are discussed, along with a review and update concerning the participation of infections, cytokine unbalances, overweight and obesity, maternal anti-fetal brain antibodies, maternal fever, gestational diabetes, preeclampsia, labor type and microbiota unbalances in MIA and ASD.

Methodology to identify a gene expression signature by merging microarray datasets

A vast number of microarray datasets have been produced as a way to identify differentially expressed genes and gene expression signatures. A better understanding of these biological processes can help in the diagnosis and prognosis of diseases, as well as in the therapeutic response to drugs. However, most of the available datasets are composed of a reduced number of samples, leading to low statistical, predictive and generalization power. One way to overcome this problem is by merging several microarray datasets into a single dataset, which is typically a challenging task. Statistical methods or supervised machine learning algorithms are usually used to determine gene expression signatures. Nevertheless, statistical methods require an arbitrary threshold to be defined, and supervised machine learning methods can be ineffective when applied to high-dimensional datasets like microarrays. We propose a methodology to identify gene expression signatures by merging microarray datasets. This methodology uses statistical methods to obtain several sets of differentially expressed genes and uses supervised machine learning algorithms to select the gene expression signature. This methodology was validated using two distinct research applications: one using heart failure and the other using autism spectrum disorder microarray datasets. For the first, we obtained a gene expression signature composed of 117 genes, with a classification accuracy of approximately 98%. For the second use case, we obtained a gene expression signature composed of 79 genes, with a classification accuracy of approximately 82%. This methodology was implemented in R language and is available, under the MIT licence, at https://github.com/bioinformatics-ua/MicroGES.

Innate immune dysfunction and neuroinflammation in autism spectrum disorder (ASD)

Autism spectrum disorder (ASD) is a highly heterogeneous neurodevelopmental disorder characterized by communication and social behavior deficits. The presence of restricted and repetitive behaviors often accompanies these deficits, and these characteristics can range from mild to severe. The past several decades have seen a significant rise in the prevalence of ASD. The etiology of ASD remains unknown; however, genetic and environmental risk factors play a role. Multiple hypotheses converge to suggest that neuroinflammation, or at least the interaction between immune and neural systems, may be involved in the etiology of some ASD cases or groups. Repeated evidence of innate immune dysfunction has been seen in ASD, often associated with worsening behaviors. This evidence includes data from circulating myeloid cells and brain resident macrophages/microglia in both human and animal models. This comprehensive review presents recent findings of innate immune dysfunction in ASD, including aberrant innate cellular function, evidence of neuroinflammation, and microglia activation.

A predictive ensemble classifier for the gene expression diagnosis of ASD at ages 1 to 4 years

Autism Spectrum Disorder (ASD) diagnosis remains behavior-based and the median age of diagnosis is ~52 months, nearly 5 years after its first-trimester origin. Accurate and clinically-translatable early-age diagnostics do not exist due to ASD genetic and clinical heterogeneity. Here we collected clinical, diagnostic, and leukocyte RNA data from 240 ASD and typically developing (TD) toddlers (175 toddlers for training and 65 for test). To identify gene expression ASD diagnostic classifiers, we developed 42,840 models composed of 3570 gene expression feature selection sets and 12 classification methods. We found that 742 models had AUC-ROC ≥ 0.8 on both Training and Test sets. Weighted Bayesian model averaging of these 742 models yielded an ensemble classifier model with accurate performance in Training and Test gene expression datasets with ASD diagnostic classification AUC-ROC scores of 85-89% and AUC-PR scores of 84-92%. ASD toddlers with ensemble scores above and below the overall ASD ensemble mean of 0.723 (on a scale of 0 to 1) had similar diagnostic and psychometric scores, but those below this ASD ensemble mean had more prenatal risk events than TD toddlers. Ensemble model feature genes were involved in cell cycle, inflammation/immune response, transcriptional gene regulation, cytokine response, and PI3K-AKT, RAS and Wnt signaling pathways. We additionally collected targeted DNA sequencing smMIPs data on a subset of ASD risk genes from 217 of the 240 ASD and TD toddlers. This DNA sequencing found about the same percentage of SFARI Level 1 and 2 ASD risk gene mutations in TD (12 of 105) as in ASD (13 of 112) toddlers, and classification based only on the presence of mutation in these risk genes performed at a chance level of 49%. By contrast, the leukocyte ensemble gene expression classifier correctly diagnostically classified 88% of TD and ASD toddlers with ASD risk gene mutations. Our ensemble ASD gene expression classifier is diagnostically predictive and replicable across different toddler ages, races, and ethnicities; out-performs a risk gene mutation classifier; and has potential for clinical translation.

Novel insights into the immune cell landscape and gene signatures in autism spectrum disorder by bioinformatics and clinical analysis

The pathogenesis of autism spectrum disorder (ASD) is not well understood, especially in terms of immunity and inflammation, and there are currently no early diagnostic or treatment methods. In this study, we obtained six existing Gene Expression Omnibus transcriptome datasets from the blood of ASD patients. We performed functional enrichment analysis, PPI analysis, CIBERSORT algorithm, and Spearman correlation analysis, with a focus on expression profiling in hub genes and immune cells. We validated that monocytes and nonclassical monocytes were upregulated in the ASD group using peripheral blood (30 children with ASD and 30 age and sex-matched typically developing children) using flow cytometry. The receiver operating characteristic curves (PSMC4 and ALAS2) and analysis stratified by ASD severity (LIlRB1 and CD69) showed that they had predictive value using the "training" and verification groups. Three immune cell types - monocytes, M2 macrophages, and activated dendritic cells - had different degrees of correlation with 15 identified hub genes. In addition, we analyzed the miRNA-mRNA network and agents-gene interactions using miRNA databases (starBase and miRDB) and the DSigDB database. Two miRNAs (miR-342-3p and miR-1321) and 23 agents were linked with ASD. These findings suggest that dysregulation of the immune system may contribute to ASD development, especially dysregulation of monocytes and monocyte-derived cells. ASD-related hub genes may serve as potential predictors for ASD, and the potential ASD-related miRNAs and agents identified here may open up new strategies for the prevention and treatment of ASD.

Nuclear access of DNlg3 c-terminal fragment and its function in regulating innate immune response genes

Neuroligins (NLGNs) are one of the autism susceptibility genes, however, the mechanism that how dysfunction of NLGNs leads to Autism remains unclear. More and more studies have shown that the transcriptome alteration may be one of the important factors to generate Autism. Therefore, we are very concerned about whether Neuroligins would affect transcriptional regulation, which may at last lead to Autism. As a single-transmembrane receptor, proteolytic cleavage is one of the most important posttranslational modifications of NLGN proteins. In this study, we demonstrated the existence of DNlg3 C-terminal fragment. Studies in the S2 cells and HEK293T cells showed the evidence for nuclear access of the DNlg3 C-terminal fragment. Then we identified the possible targets of DNlg3 C-terminal fragment after its nuclear access by RNA-seq. The bioinformatics analysis indicated the transcriptome alteration between dnlg3 null flies and wild type flies focused on genes for the innate immune responses. These results were consistent with the infection hypotheses for autism. Our study revealed the nuclear access ability of DNlg3 c-terminal fragment and its possible function in transcriptional regulation of the innate immune response genes. This work provides the new links between synaptic adhesion molecule NLGNs and immune activation, which may help us to get a deeper understanding on the relationship between NLGNs and Autism.

RNA sequencing of blood from sex- and age-matched discordant siblings supports immune and transcriptional dysregulation in autism spectrum disorder

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.

Ectopic Expression of Arabidopsis thaliana zDof1.3 in Tomato (Solanum lycopersicum L.) Is Associated with Improved Greenhouse Productivity and Enhanced Carbon and Nitrogen Use

A large collection of transgenic tomato lines, each ectopically expressing a different Arabidopsis thaliana transcription factor, was screened for variants with alterations in leaf starch. Such lines may be affected in carbon partitioning, and in allocation to the sinks. We focused on ‘L4080’, which harbored an A. thaliana zDof (DNA-binding one zinc finger) isoform 1.3 (AtzDof1.3) gene, and which had a 2−4-fold higher starch-to-sucrose ratio in source leaves over the diel (p < 0.05). Our aim was to determine whether there were associated effects on productivity. L4080 plants were altered in nitrogen (N) and carbon (C) metabolism. The N-to-C ratio was higher in six-week-old L4080, and when treated with 1/10 N, L4080 growth was less inhibited compared to the wild-type and this was accompanied by faster root elongation (p < 0.05). The six-week-old L4080 acquired 42% more dry matter at 720 ppm CO2, compared to ambient CO2 (p < 0.05), while the wild-type (WT) remained unchanged. GC-MS-TOF data showed that L4080 source leaves were enriched in amino acids compared to the WT, and at 49 DPA, fruit had 25% greater mass, higher sucrose, and increased yield (25%; p < 0.05) compared to the WT. An Affymetrix cDNA array analysis suggested that only 0.39% of the 9000 cDNAs were altered by 1.5-fold (p < 0.01) in L4080 source leaves. 14C-labeling of fruit disks identified potential differences in 14-DPA fruit metabolism suggesting that post-transcriptional regulation was important. We conclude that AtzDof1.3 and the germplasm derived therefrom, should be investigated for their ‘climate-change adaptive’ potential.

Blood RNA Sequencing Indicates Upregulated BATF2 and LY6E and Downregulated ISG15 and MT2A Expression in Children with Autism Spectrum Disorder

Mutations in over 100 genes are implicated in autism spectrum disorder (ASD). DNA SNPs, CNVs, and epigenomic modifications also contribute to ASD. Transcriptomics analysis of blood samples may offer clues for pathways dysregulated in ASD. To expand and validate published findings of RNA-sequencing (RNA-seq) studies, we performed RNA-seq of whole blood samples from an Israeli discovery cohort of eight children with ASD compared with nine age- and sex-matched neurotypical children. This revealed 10 genes with differential expression. Using quantitative real-time PCR, we compared RNAs from whole blood samples of 73 Israeli and American children with ASD and 26 matched neurotypical children for the 10 dysregulated genes detected by RNA-seq. This revealed higher expression levels of the pro-inflammatory transcripts BATF2 and LY6E and lower expression levels of the anti-inflammatory transcripts ISG15 and MT2A in the ASD compared to neurotypical children. BATF2 was recently reported as upregulated in blood samples of Japanese adults with ASD. Our findings support an involvement of these genes in ASD phenotypes, independent of age and ethnicity. Upregulation of BATF2 and downregulation of ISG15 and MT2A were reported to reduce cancer risk. Implications of the dysregulated genes for pro-inflammatory phenotypes, immunity, and cancer risk in ASD are discussed.

Genome-wide DNA methylation profiles of autism spectrum disorder

OBJECTIVES

We aimed to identify differentially methylated genes and related signaling pathways in autism spectrum disorder (ASD).

METHODS

First, the DNA methylation profile in the brain samples (GSE131706 and GSE80017) and peripheral blood samples (GSE109905) was downloaded from the Gene Expression Omnibus database (GEO) dataset, followed by identification of differentially methylated genes and functional analysis. Second, the GSE109905 data set was used to further validate the methylation state and test the ability to diagnose disease of identified differentially methylated genes. Third, expression measurement of selected differentially methylated genes was performed in whole blood from an independent sample. Finally, protein-protein interaction (PPI) network of core differentially methylated genes was constructed.

RESULTS

Totally, 74 differentially methylated genes were identified in ASD, including 38 hypermethylated genes and 36 hypomethylated genes. 15 differentially methylated genes were further identified after validation in the GSE109905 data set. Among these, major histocompatibility complex (HLA)-DQA1 was involved in the molecular function of myosin heavy chain class II receptor activity; HLA-DRB5 was involved in the signaling pathways of cell adhesion molecules, Epstein-Barr virus infection and antigen processing and presentation. In the PPI analysis, the interaction pairs of HLA-DQA1 and HLA-DRB5, FMN2 and ACTR3, and CALCOCO2 and BAZ2B were identified. Interestingly, FMN2, BAZ2B, HLA-DRB5, CALCOCO2 and DUSP22 had a potential diagnostic value for patients with ASD. The expression result of four differentially methylated genes (HLA-DRB5, NTM, IL16 and COL5A3) in the independent sample was consistent with the integrated analysis.

CONCLUSIONS

Identified differentially methylated genes and enriched signaling pathway could be associated with ASD.

Decreased Empathy Response to Other's Pain in Parents of Children With Autism Spectrum Disorder

We aimed to investigate pain empathy ability and self-reported empathy among parents of children with autism spectrum disorder (ASD). Twenty-four parents of children with ASD and 26 parents of typically developing children completed the Empathy Quotient (EQ) self-report scale and responded to painful or neutral images during an empathy-for-pain paradigm test. Parents of children with ASD had lower EQ scores, lower accuracy, and longer reaction time (RT) for pain empathy task response (all p < 0.05) compared with controls. There was a negative relationship between cognitive empathy, social skills, total EQ scores, and RT of response in parents of children with ASD. Our findings indicate that self-reported empathy deficits and decreased empathy response to the sight of others' pain in parents of children with ASD are part of a broader autistic phenotype.

Analysis of Faecal Microbiota and Small ncRNAs in Autism: Detection of miRNAs and piRNAs with Possible Implications in Host-Gut Microbiota Cross-Talk

Intestinal microorganisms impact health by maintaining gut homeostasis and shaping the host immunity, while gut dysbiosis associates with many conditions, including autism, a complex neurodevelopmental disorder with multifactorial aetiology. In autism, gut dysbiosis correlates with symptom severity and is characterised by a reduced bacterial variability and a diminished beneficial commensal relationship. Microbiota can influence the expression of host microRNAs that, in turn, regulate the growth of intestinal bacteria by means of bidirectional host-gut microbiota cross-talk. We investigated possible interactions among intestinal microbes and between them and host transcriptional modulators in autism. To this purpose, we analysed, by "omics" technologies, faecal microbiome, mycobiome, and small non-coding-RNAs (particularly miRNAs and piRNAs) of children with autism and neurotypical development. Patients displayed gut dysbiosis related to a reduction of healthy gut micro- and mycobiota as well as up-regulated transcriptional modulators. The targets of dysregulated non-coding-RNAs are involved in intestinal permeability, inflammation, and autism. Furthermore, microbial families, underrepresented in patients, participate in the production of human essential metabolites negatively influencing the health condition. Here, we propose a novel approach to analyse faeces as a whole, and for the first time, we detected miRNAs and piRNAs in faecal samples of patients with autism.

Dysregulated gene expression associated with inflammatory and translation pathways in activated monocytes from children with autism spectrum disorder

Autism spectrum disorder (ASD) is a complex developmental disorder characterized by deficits in social interactions, communication, and stereotypical behaviors. Immune dysfunction is a common co-morbidity seen in ASD, with innate immune activation seen both in the brain and periphery. We previously identified significant differences in peripheral monocyte cytokine responses after stimulation with lipoteichoic acid (LTA) and lipopolysaccharide (LPS), which activate toll-like receptors (TLR)-2 and 4 respectively. However, an unbiased examination of monocyte gene expression in response to these stimulants had not yet been performed. To identify how TLR activation impacts gene expression in ASD monocytes, we isolated peripheral blood monocytes from 26 children diagnosed with autistic disorder (AD) or pervasive developmental disorder-not otherwise specified (PDDNOS) and 22 typically developing (TD) children and cultured them with LTA or LPS for 24 h, then performed RNA sequencing. Activation of both TLR2 and TLR4 induced expression of immune genes, with a subset that were differentially regulated in AD compared to TD samples. In response to LPS, monocytes from AD children showed a unique increase in KEGG pathways and GO terms that include key immune regulator genes. In contrast, monocytes from TD children showed a consistent decrease in expression of genes associated with translation in response to TLR stimulation. This decrease was not observed in AD or PDDNOS monocytes, suggesting a failure to properly downregulate a prolonged immune response in monocytes from children with ASD. As monocytes are involved in early orchestration of the immune response, our findings will help elucidate the mechanisms regulating immune dysfunction in ASD.

Brain exosomes as minuscule information hub for Autism Spectrum Disorder

INTRODUCTION

Autism spectrum disorder (ASD) is a neurodevelopmental disorder initiating in the first three years of life. Early initiation of management therapies can significantly improve the health and quality of life of ASD subjects. Thus, indicating the need for suitable biomarkers for the early identification of ASD. Various biological domains were investigated in the quest for reliable biomarkers. However, most biomarkers are in the preliminary stage, and clinical validation is yet to be defined. Exosome based research gained momentum in various Central Nervous System disorders for biomarker identification. However, the utility and prospect of exosomes in ASD is still underexplored.

AREAS COVERED

In the present review, we summarized the biomarker discovery current status and the future of brain-specific exosomes in understanding pathophysiology and its potential as a biomarker. The studies reviewed herein were identified via systematic search (dated: June 2021) of PubMed using variations related to autism (ASD OR autism OR Autism spectrum disorder) AND exosomes AND/OR biomarkers.

EXPERT OPINION

As exosomess are highly relevant in brain disorders like ASD, direct access to brain tissue for molecular assessment is ethically impossible. Thus investigating the brain-derived exosomes would undoubtedly answer many unsolved aspects of the pathogenesis and provide reliable biomarkers.

Wnt/β-Catenin-Dependent Transcription in Autism Spectrum Disorders

Autism spectrum disorders (ASD) is a heterogeneous group of neurodevelopmental disorders characterized by synaptic dysfunction and defects in dendritic spine morphology. In the past decade, an extensive list of genes associated with ASD has been identified by genome-wide sequencing initiatives. Several of these genes functionally converge in the regulation of the Wnt/β-catenin signaling pathway, a conserved cascade essential for stem cell pluripotency and cell fate decisions during development. Here, we review current information regarding the transcriptional program of Wnt/β-catenin signaling in ASD. First, we discuss that Wnt/β-catenin gain and loss of function studies recapitulate brain developmental abnormalities associated with ASD. Second, transcriptomic approaches using patient-derived induced pluripotent stem cells (iPSC) cells, featuring mutations in high confidence ASD genes, reveal a significant dysregulation in the expression of Wnt signaling components. Finally, we focus on the activity of chromatin-remodeling proteins and transcription factors considered high confidence ASD genes, including CHD8, ARID1B, ADNP, and TBR1, that regulate Wnt/β-catenin-dependent transcriptional activity in multiple cell types, including pyramidal neurons, interneurons and oligodendrocytes, cells which are becoming increasingly relevant in the study of ASD. We conclude that the level of Wnt/β-catenin signaling activation could explain the high phenotypical heterogeneity of ASD and be instrumental in the development of new diagnostics tools and therapies.

Interpretable Machine Learning Reveals Dissimilarities Between Subtypes of Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a heterogeneous neuropsychiatric disorder with a complex genetic background. Analysis of altered molecular processes in ASD patients requires linear and nonlinear methods that provide interpretable solutions. Interpretable machine learning provides legible models that allow explaining biological mechanisms and support analysis of clinical subgroups. In this work, we investigated several case-control studies of gene expression measurements of ASD individuals. We constructed a rule-based learning model from three independent datasets that we further visualized as a nonlinear gene-gene co-predictive network. To find dissimilarities between ASD subtypes, we scrutinized a topological structure of the network and estimated a centrality distance. Our analysis revealed that autism is the most severe subtype of ASD, while pervasive developmental disorder-not otherwise specified and Asperger syndrome are closely related and milder ASD subtypes. Furthermore, we analyzed the most important ASD-related features that were described in terms of gene co-predictors. Among others, we found a strong co-predictive mechanism between EMC4 and TMEM30A, which may suggest a co-regulation between these genes. The present study demonstrates the potential of applying interpretable machine learning in bioinformatics analyses. Although the proposed methodology was designed for transcriptomics data, it can be applied to other omics disciplines.

Autism spectrum disorders and natural killer cells: a review on pathogenesis and treatment

Introduction: Autism spectrum disorder (ASD), as a wide spectrum of neurodevelopmental disorders, is characterized by early-onset impairments in social-communication, repetitive behaviors, and restrictive interests.Areas covered: Although still unknown, there are some pieces of evidence suggesting altered immune function in the etiology of ASD. This review aims to summarize studies linking Natural Killer (NK) cells to ASD by searching through databases like MEDLINE and Scopus up to October 2020. NK cells play important roles in the innate immune system and immune regulation. As parts of the immune system, they interact with the neural system as well. Immune dysregulations such as autoimmunity and improper immune responses to both internal and external stimulations, especially in early developmental stages of the brain, may induce neurodevelopmental disorders. NK cells' dysfunction in children with ASD as well as their parents have been highlighted in many studies.Expert opinion: Changes in the frequency, gene expressions, cytotoxicity features, and receptors of NK cells are reported in children with ASD. Immune therapy for children with ASD with immune abnormality has shown promising results. However, further studies are needed to elucidate the exact role of NK cells in the pathogenesis of ASD providing future treatment options for these children.

Phenotypic Subtyping and Re-analyses of Existing Transcriptomic Data from Autistic Probands in Simplex Families Reveal Differentially Expressed and ASD Trait-Associated Genes

Autism spectrum disorder (ASD) describes a collection of neurodevelopmental disorders characterized by core symptoms that include social communication deficits and repetitive, stereotyped behaviors often coupled with restricted interests. Primary challenges to understanding and treating ASD are the genetic and phenotypic heterogeneity of cases that complicates all omics analyses as well as a lack of information on relationships among genes, pathways, and autistic traits. In this study, we re-analyze existing transcriptomic data from simplex families by subtyping individuals with ASD according to multivariate cluster analyses of clinical ADI-R scores that encompass a broad range of behavioral symptoms. We also correlate multiple ASD traits, such as deficits in verbal and non-verbal communication, play and social skills, ritualistic behaviors, and savant skills, with expression profiles using Weighted Gene Correlation Network Analyses (WGCNA). Our results show that subtyping greatly enhances the ability to identify differentially expressed genes involved in specific canonical pathways and biological functions associated with ASD within each phenotypic subgroup. Moreover, using WGCNA, we identify gene modules that correlate significantly with specific ASD traits. Network prediction analyses of the genes in these modules reveal canonical pathways as well as neurological functions and disorders relevant to the pathobiology of ASD. Finally, we compare the WGCNA-derived data on autistic traits in simplex families with analogous data from multiplex families using transcriptomic data from our previous studies. The comparison reveals overlapping trait-associated pathways as well as upstream regulators of the module-associated genes that may serve as useful targets for a precision medicine approach to ASD.

Integrated Systems Analysis Explores Dysfunctional Molecular Modules and Regulatory Factors in Children with Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a genetic neurodevelopmental disorder involving multiple genes that occurs in early childhood, and a number of risk genes have been reported in previous studies. However, the molecular mechanism of the polygenic regulation leading to pathological changes in ASD remains unclear. First, we identified 8 dysregulated gene coexpression modules by analyzing blood transcriptome data from 96 children with ASD and 42 controls. These modules are rich in ASD risk genes and function related to metabolism, immunity, neurodevelopment, and signaling. The regulatory factors of each module including microRNA (miRNA) and transcription factors (TFs) were subsequently predicted based on transcriptional and posttranscriptional regulation. We identified a set of miRNAs that regulate metabolic and immune modules, as well as transcription factors that cause dysregulation of the modules, and we constructed a coregulatory network between the regulatory factors and modules. Our work reveals dysfunctional modules in children with ASD, elucidates the role of miRNA and transcription factor dysregulation in the pathophysiology of ASD, and helps us to further understand the underlying molecular mechanism of ASD.

Transcriptome signatures from discordant sibling pairs reveal changes in peripheral blood immune cell composition in Autism Spectrum Disorder

Notwithstanding several research efforts in the past years, robust and replicable molecular signatures for autism spectrum disorders from peripheral blood remain elusive. The available literature on blood transcriptome in ASD suggests that through accurate experimental design it is possible to extract important information on the disease pathophysiology at the peripheral level. Here we exploit the availability of a resource for molecular biomarkers in ASD, the Italian Autism Network (ITAN) collection, for the investigation of transcriptomic signatures in ASD based on a discordant sibling pair design. Whole blood samples from 75 discordant sibling pairs selected from the ITAN network where submitted to RNASeq analysis and data analyzed by complementary approaches. Overall, differences in gene expression between affected and unaffected siblings were small. In order to assess the contribution of differences in the relative proportion of blood cells between discordant siblings, we have applied two different cell deconvolution algorithms, showing that the observed molecular signatures mainly reflect changes in peripheral blood immune cell composition, in particular NK cells. The results obtained by the cell deconvolution approach are supported by the analysis performed by WGCNA. Our report describes the largest differential gene expression profiling in peripheral blood of ASD subjects and controls conducted by RNASeq. The observed signatures are consistent with the hypothesis of immune alterations in autism and an increased risk of developing autism in subjects exposed to prenatal infections or stress. Our study also points to a potential role of NMUR1, HMGB3, and PTPRN2 in ASD.

Network Structure Analysis Identifying Key Genes of Autism and Its Mechanism

Identifying the key genes of autism is of great significance for understanding its pathogenesis and improving the clinical level of medicine. In this paper, we use the structural parameters (average degree) of gene correlation networks to identify genes related to autism and study its pathogenesis. Based on the gene expression profiles of 82 autistic patients (the experimental group, E) and 64 healthy persons (the control group, C) in NCBI database, spearman correlation networks are established, and their average degrees under different thresholds are analyzed. It is found that average degrees of C and E are basically separable at the full thresholds. This indicates that there is a clear difference between the network structures of C and E, and it also suggests that this difference is related to the mechanism of disease. By annotating and enrichment analysis of the first 20 genes (MD-Gs) with significant difference in the average degree, we find that they are significantly related to gland development, cardiovascular development, and embryogenesis of nervous system, which support the results in Alter et al.'s original research. In addition, FIGF and CSF3 may play an important role in the mechanism of autism.

Transcriptomic Analysis Reveals Abnormal Expression of Prion Disease Gene Pathway in Brains from Patients with Autism Spectrum Disorders

The role of infections in the pathogenesis of autism spectrum disorder (ASD) is still controversial. In this study, we aimed to evaluate markers of infections and immune activation in ASD by performing a meta-analysis of publicly available whole-genome transcriptomic datasets of brain samples from autistic patients and otherwise normal people. Among the differentially expressed genes, no significant enrichment was observed for infectious diseases previously associated with ASD, including herpes simplex virus-1 (HSV-1), cytomegalovirus and Epstein–Barr virus in brain samples, nor was it found in peripheral blood from ASD patients. Interestingly, a significant number of genes belonging to the “prion diseases” pathway were found to be modulated in our ASD brain meta-analysis. Overall, our data do not support an association between infection and ASD. However, the data do provide support for the involvement of pathways related to other neurodegenerative diseases and give input to uncover novel pathogenetic mechanisms underlying ASD.

Effects of aging on the motor, cognitive and affective behaviors, neuroimmune responses and hippocampal gene expression

The known effects of aging on the brain and behavior include impaired cognition, increases in anxiety and depressive-like behaviors, and reduced locomotor activity. Environmental exposures and interventions also influence brain functions during aging. We investigated the effects of normal aging under controlled environmental conditions and in the absence of external interventions on locomotor activity, cognition, anxiety and depressive-like behaviors, immune function and hippocampal gene expression in C57BL/6 mice. Healthy mice at 4, 9, and 14 months of age underwent behavioral testing using an established behavioral battery, followed by cellular and molecular analysis using flow cytometry, immunohistochemistry, and quantitative PCR. We found that 14-month-old mice showed significantly reduced baseline locomotion, increased anxiety, and impaired spatial memory compared to younger counterparts. However, no significant differences were observed for depressive-like behavior in the forced-swim test. Microglia numbers in the dentate gyrus, as well as CD8+ memory T cells increased towards late middle age. Aging processes exerted a significant effect on the expression of 43 genes of interest in the hippocampus. We conclude that aging is associated with specific changes in locomotor activity, cognition, anxiety-like behaviors, neuroimmune responses and hippocampal gene expression.

New Horizons for Molecular Genetics Diagnostic and Research in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a highly heritable, heterogeneous, and complex pervasive neurodevelopmental disorder (PND) characterized by distinctive abnormalities of human cognitive functions, social interaction, and speech development.Nowadays, several genetic changes including chromosome abnormalities, genetic variations, transcriptional epigenetics, and noncoding RNA have been identified in ASD. However, the association between these genetic modifications and ASDs has not been confirmed yet.The aim of this review is to summarize the key findings in ASD from genetic viewpoint that have been identified from the last few decades of genetic and molecular research.

RNA sequencing of identical twins discordant for autism reveals blood-based signatures implicating immune and transcriptional dysregulation

Background

A gap exists in our mechanistic understanding of how genetic and environmental risk factors converge at the molecular level to result in the emergence of autism symptoms. We compared blood-based gene expression signatures in identical twins concordant and discordant for autism spectrum condition (ASC) to differentiate genetic and environmentally driven transcription differences, and establish convergent evidence for biological mechanisms involved in ASC.

Methods

Genome-wide gene expression data were generated using RNA-seq on whole blood samples taken from 16 pairs of monozygotic (MZ) twins and seven twin pair members (39 individuals in total), who had been assessed for ASC and autism traits at age 12. Differential expression (DE) analyses were performed between (a) affected and unaffected subjects (N = 36) and (b) within discordant ASC MZ twin pairs (total N = 11) to identify environmental-driven DE. Gene set enrichment and pathway testing was performed on DE gene lists. Finally, an integrative analysis using DNA methylation data aimed to identify genes with consistent evidence for altered regulation in cis.

Results

In the discordant twin analysis, three genes showed evidence for DE at FDR < 10%: IGHG4, EVI2A and SNORD15B. In the case-control analysis, four DE genes were identified at FDR < 10% including IGHG4, PRR13P5, DEPDC1B, and ZNF501. We find enrichment for DE of genes curated in the SFARI human gene database. Pathways showing evidence of enrichment included those related to immune cell signalling and immune response, transcriptional control and cell cycle/proliferation. Integrative methylomic and transcriptomic analysis identified a number of genes showing suggestive evidence for cis dysregulation.

Limitations

Identical twins stably discordant for ASC are rare, and as such the sample size was limited and constrained to the use of peripheral blood tissue for transcriptomic and methylomic profiling. Given these primary limitations, we focused on transcript-level analysis.

Conclusions

Using a cohort of ASC discordant and concordant MZ twins, we add to the growing body of transcriptomic-based evidence for an immune-based component in the molecular aetiology of ASC. Whilst the sample size was limited, the study demonstrates the utility of the discordant MZ twin design combined with multi-omics integration for maximising the potential to identify disease-associated molecular signals.

A meta-analysis of two high-risk prospective cohort studies reveals autism-specific transcriptional changes to chromatin, autoimmune, and environmental response genes in umbilical cord blood

Background

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that affects more than 1% of children in the USA. ASD risk is thought to arise from both genetic and environmental factors, with the perinatal period as a critical window. Understanding early transcriptional changes in ASD would assist in clarifying disease pathogenesis and identifying biomarkers. However, little is known about umbilical cord blood gene expression profiles in babies later diagnosed with ASD compared to non-typically developing and non-ASD (Non-TD) or typically developing (TD) children.

Methods

Genome-wide transcript levels were measured by Affymetrix Human Gene 2.0 array in RNA from cord blood samples from both the Markers of Autism Risk in Babies-Learning Early Signs (MARBLES) and the Early Autism Risk Longitudinal Investigation (EARLI) high-risk pregnancy cohorts that enroll younger siblings of a child previously diagnosed with ASD. Younger siblings were diagnosed based on assessments at 36 months, and 59 ASD, 92 Non-TD, and 120 TD subjects were included. Using both differential expression analysis and weighted gene correlation network analysis, gene expression between ASD and TD, and between Non-TD and TD, was compared within each study and via meta-analysis.

Results

While cord blood gene expression differences comparing either ASD or Non-TD to TD did not reach genome-wide significance, 172 genes were nominally differentially expressed between ASD and TD cord blood (log₂(fold change) > 0.1, p < 0.01). These genes were significantly enriched for functions in xenobiotic metabolism, chromatin regulation, and systemic lupus erythematosus (FDR q < 0.05). In contrast, 66 genes were nominally differentially expressed between Non-TD and TD, including 8 genes that were also differentially expressed in ASD. Gene coexpression modules were significantly correlated with demographic factors and cell type proportions.

Limitations

ASD-associated gene expression differences identified in this study are subtle, as cord blood is not the main affected tissue, it is composed of many cell types, and ASD is a heterogeneous disorder.

Conclusions

This is the first study to identify gene expression differences in cord blood specific to ASD through a meta-analysis across two prospective pregnancy cohorts. The enriched gene pathways support involvement of environmental, immune, and epigenetic mechanisms in ASD etiology.

Solving for X: Evidence for sex-specific autism biomarkers across multiple transcriptomic studies

Autism spectrum disorder (ASD) is a markedly heterogeneous condition with a varied phenotypic presentation. Its high concordance among siblings, as well as its clear association with specific genetic disorders, both point to a strong genetic etiology. However, the molecular basis of ASD is still poorly understood, although recent studies point to the existence of sex-specific ASD pathophysiologies and biomarkers. Despite this, little is known about how exactly sex influences the gene expression signatures of ASD probands. In an effort to identify sex-dependent biomarkers and characterize their function, we present an analysis of a single paired-end postmortem brain RNA-Seq data set and a meta-analysis of six blood-based microarray data sets. Here, we identify several genes with sex-dependent dysregulation, and many more with sex-independent dysregulation. Moreover, through pathway analysis, we find that these sex-independent biomarkers have substantially different biological roles than the sex-dependent biomarkers, and that some of these pathways are ubiquitously dysregulated in both postmortem brain and blood. We conclude by synthesizing the discovered biomarker profiles with the extant literature, by highlighting the advantage of studying sex-specific dysregulation directly, and by making a call for new transcriptomic data that comprise large female cohorts.

Network-Based Integrative Analysis of Genomics, Epigenomics and Transcriptomics in Autism Spectrum Disorders

Current studies suggest that autism spectrum disorders (ASDs) may be caused by many genetic factors. In fact, collectively considering multiple studies aimed at characterizing the basic pathophysiology of ASDs, a large number of genes has been proposed. Addressing the problem of molecular data interpretation using gene networks helps to explain genetic heterogeneity in terms of shared pathways. Besides, the integrative analysis of multiple omics has emerged as an approach to provide a more comprehensive view of a disease. In this work, we carry out a network-based meta-analysis of the genes reported as associated with ASDs by studies that involved genomics, epigenomics, and transcriptomics. Collectively, our analysis provides a prioritization of the large number of genes proposed to be associated with ASDs, based on genes' relevance within the intracellular circuits, the strength of the supporting evidence of association with ASDs, and the number of different molecular alterations affecting genes. We discuss the presence of the prioritized genes in the SFARI (Simons Foundation Autism Research Initiative) database and in gene networks associated with ASDs by other investigations. Lastly, we provide the full results of our analyses to encourage further studies on common targets amenable to therapy.

Phenotypic subgrouping and multi-omics analyses reveal reduced diazepam-binding inhibitor (DBI) protein levels in autism spectrum disorder with severe language impairment

BACKGROUND

The mechanisms underlying autism spectrum disorder (ASD) remain unclear, and clinical biomarkers are not yet available for ASD. Differences in dysregulated proteins in ASD have shown little reproducibility, which is partly due to ASD heterogeneity. Recent studies have demonstrated that subgrouping ASD cases based on clinical phenotypes is useful for identifying candidate genes that are dysregulated in ASD subgroups. However, this strategy has not been employed in proteome profiling analyses to identify ASD biomarker proteins for specific subgroups.

METHODS

We therefore conducted a cluster analysis of the Autism Diagnostic Interview-Revised (ADI-R) scores from 85 individuals with ASD to predict subgroups and subsequently identified dysregulated genes by reanalyzing the transcriptome profiles of individuals with ASD and unaffected individuals. Proteome profiling of lymphoblastoid cell lines from these individuals was performed via 2D-gel electrophoresis, and then mass spectrometry. Disrupted proteins were identified and compared to the dysregulated transcripts and reported dysregulated proteins from previous proteome studies. Biological functions were predicted using the Ingenuity Pathway Analysis (IPA) program. Selected proteins were also analyzed by Western blotting.

RESULTS

The cluster analysis of ADI-R data revealed four ASD subgroups, including ASD with severe language impairment, and transcriptome profiling identified dysregulated genes in each subgroup. Screening via proteome analysis revealed 82 altered proteins in the ASD subgroup with severe language impairment. Eighteen of these proteins were further identified by nano-LC-MS/MS. Among these proteins, fourteen were predicted by IPA to be associated with neurological functions and inflammation. Among these proteins, diazepam-binding inhibitor (DBI) protein was confirmed by Western blot analysis to be expressed at significantly decreased levels in the ASD subgroup with severe language impairment, and the DBI expression levels were correlated with the scores of several ADI-R items.

CONCLUSIONS

By subgrouping individuals with ASD based on clinical phenotypes, and then performing an integrated transcriptome-proteome analysis, we identified DBI as a novel candidate protein for ASD with severe language impairment. The mechanisms of this protein and its potential use as an ASD biomarker warrant further study.

Regression in autism spectrum disorder: A critical overview of retrospective findings and recommendations for future research

Historically, two onset patterns in autism spectrum disorder (ASD) were described: early onset of symptoms and regression in which one-third appear to show a loss of previously established skills in the second year of life. Since this phenomenon could represent a distinct ASD subtype and provide more insight into the etiology, diagnosis, and prognosis, many studies have compared these two groups. The present review discusses definitions, etiology, and methods used in research with a retrospective design and provides an overview of the results on early development and outcomes. However, retrospective research has not provided clear answers on regression as a distinct subtype of ASD and the historic division between early onset and regression does not seem to fit the empirical findings. Based on inconsistent results, future research on onset patterns in ASD needs to be more systematic on the definitions and methods used. Several recommendations to enhance the reliability of future retrospective results are discussed. The combination of a categorical and dimensional approach provides a new interesting framework.

Advances in Biomarker Studies in Autism Spectrum Disorders

Autism spectrum disorder (ASD) is a neurological and developmental condition that begins early in childhood and lasts throughout life. The epidemiology of ASD is continuously increasing all over the world with huge social and economical burdens. As the etiology of autism is not completely understood, there is still no medication available for the treatment of this disorder. However, some behavioral interventions are available to improve the core and associated symptoms of autism, particularly when initiated at an early stage. Thus, there is an increasing demand for finding biomarkers for ASD. Although diagnostic biomarkers have not yet been established, research efforts have been carried out in neuroimaging and biological analyses including genomics and gene testing, proteomics, metabolomics, transcriptomics, and studies of the immune system, inflammation, and microRNAs. Here, we will review the current progress in these fields and focus on new methods, developments, research strategies, and studies of blood-based biomarkers.

A systematic review of gut-immune-brain mechanisms in Autism Spectrum Disorder

Despite decades of research, the etiological origins of Autism Spectrum Disorder (ASD) remain elusive. Recently, the mechanisms of ASD have encompassed emerging theories involving the gastrointestinal, immune, and nervous systems. While each of these perspectives presents its own set of supporting evidence, the field requires an integration of these modular concepts and an overarching view of how these subsystems intersect. In this systematic review, we have synthesized relevant evidences from the existing literature, evaluating them in an interdependent manner and in doing so, outlining their possible connections. Specifically, we first discussed gastrointestinal and immuno-inflammation pathways in-depth, exploring the relationships between microbial composition, bacterial metabolites, gut mucosa, and immune system constituents. Accounting for temporal differences in the mechanisms involved in neurodevelopment, prenatal and postnatal phases were further elucidated, where the former focused on maternal immune activation (MIA) and fetal development, while the latter addressed the role of immune dysregulation in contributing to atypical neurodevelopment. As autism remains, foremost, a neurodevelopmental disorder, this review presents an integration of disparate modules into a "Gut-Immune-Brain" paradigm. Existing gaps in the literature have been highlighted, and possible avenues for future research with an integrated physiological perspective underlying ASD have also been suggested.

Neuregulin1 types mRNA level changes in autism spectrum disorder, and is associated with deficit in executive functions

BACKGROUND

Autism spectrum disorder (ASD) is a pediatric heterogeneous psychiatric and neurodevelopmental disorder with social and communication deficits, language impairment and ritualistic or repetitive behaviors. ASD has significant genetic bases but candidate genes and molecular mechanisms of disorder are not clarified. Neuregulin1 (NRG1) gene, located in 8p12 is involved in development of central nervous system and was indicated as candidate gene in schizophrenia.

METHODS

mRNA level of types I, II and III of NRG1 gene were studied in peripheral blood of 1540 ASD patients (IQ > 70) and 1490 control children by quantitative Real Time PCR. Also three domains of executive functions (working memory, response inhibition and vigilance) were examined in all subjects.

FINDINGS

All three types were significantly down regulated in ASD patients. Significant deficiencies in executive functions (EF) were found in ASD patients. EF deficiencies mostly were associated with down expression of mRNA level of types I and III. Also correlations were found between NRG1 expression with gender and severity of ASD symptoms.

INTERPRETATIONS

Findings primarily have been suggested involvement of NRG1 in etiology of ASD. Also correlation of NRG1 mRNA level with EF deficiencies could shed lights on EF mechanisms and may suggest targeted treatments to improve particular executive functions. FUND: Young researchers and elites club funded the project due to the annual grant of special talents of Club that gave to Arvin Haghighatfard.

Early Disruption of the Microbiome Leading to Decreased Antioxidant Capacity and Epigenetic Changes: Implications for the Rise in Autism

Currently, 1 out of every 59 children in the United States is diagnosed with autism. While initial research to find the possible causes for autism were mostly focused on the genome, more recent studies indicate a significant role for epigenetic regulation of gene expression and the microbiome. In this review article, we examine the connections between early disruption of the developing microbiome and gastrointestinal tract function, with particular regard to susceptibility to autism. The biological mechanisms that accompany individuals with autism are reviewed in this manuscript including immune system dysregulation, inflammation, oxidative stress, metabolic and methylation abnormalities as well as gastrointestinal distress. We propose that these autism-associated biological mechanisms may be caused and/or sustained by dysbiosis, an alteration to the composition of resident commensal communities relative to the community found in healthy individuals and its redox and epigenetic consequences, changes that in part can be due to early use and over-use of antibiotics across generations. Further studies are warranted to clarify the contribution of oxidative stress and gut microbiome in the pathophysiology of autism. A better understanding of the microbiome and gastrointestinal tract in relation to autism will provide promising new opportunities to develop novel treatment modalities.

Immune Abnormalities in Autism Spectrum Disorder-Could They Hold Promise for Causative Treatment?

Autism spectrum disorders (ASD) are characterized by impairments in language and communication development, social behavior, and the occurrence of stereotypic patterns of behavior and interests. Despite substantial speculation about causes of ASD, its exact etiology remains unknown. Recent studies highlight a link between immune dysfunction and behavioral traits. Various immune anomalies, including humoral and cellular immunity along with abnormalities at the molecular level, have been reported. There is evidence of altered immune function both in cerebrospinal fluid and peripheral blood. Several studies hypothesize a role for neuroinflammation in ASD and are supported by brain tissue and cerebrospinal fluid analysis, as well as evidence of microglial activation. It has been shown that immune abnormalities occur in a substantial number of individuals with ASD. Identifying subgroups with immune system dysregulation and linking specific cellular immunophenotypes to different symptoms would be key to defining a group of patients with immune abnormalities as a major etiology underlying behavioral symptoms. These determinations would provide the opportunity to investigate causative treatments for a defined patient group that may specifically benefit from such an approach. This review summarizes recent insights into immune system dysfunction in individuals with ASD and discusses the potential implications for future therapies.

An Interstitial 17q11.2 de novo Deletion Involving the CDK5R1 Gene in a High-Functioning Autistic Patient

We describe a 32-year-old male patient diagnosed with high-functioning autism spectrum disorder carrying a de novo 196-kb interstitial deletion at chromosome 17q11.2. The deletion was detected by array CGH (180K Agilent) and confirmed by quantitative PCR on genomic DNA. The deleted region spans the entire PSMD11 and CDK5R1 genes and partially the MYO1D gene. The CDK5R1 gene encodes for a regulatory subunit of the cyclin-dependent kinase 5 responsible for its brain-specific activation. This gene has been previously associated with intellectual disability in humans. A reduction in CDK5R1 transcript was detected, consistent with the genomic deletion. Based on the functional role of CDK5R1, this gene appears as the best candidate to explain the clinical phenotype of our patient, whose neuropsychological profile has more resemblance with some of the higher brain function anomalies recently described in the CreER-p35 conditional knockout mouse model than previously described patients with intellectual disability.

Investigation of epigenetic regulatory networks associated with autism spectrum disorder (ASD) by integrated global LINE-1 methylation and gene expression profiling analyses

BACKGROUND

The exact cause and mechanisms underlying the pathobiology of autism spectrum disorder (ASD) remain unclear. Dysregulation of long interspersed element-1 (LINE-1) has been reported in the brains of ASD-like mutant mice and ASD brain tissues. However, the role and methylation of LINE-1 in individuals with ASD remain unclear. In this study, we aimed to investigate whether LINE-1 insertion is associated with differentially expressed genes (DEGs) and to assess LINE-1 methylation in ASD.

METHODS

To identify DEGs associated with LINE-1 in ASD, we reanalyzed previously published transcriptome profiles and overlapped them with the list of LINE-1-containing genes from the TranspoGene database. An Ingenuity Pathway Analysis (IPA) of DEGs associated with LINE-1 insertion was conducted. DNA methylation of LINE-1 was assessed via combined bisulfite restriction analysis (COBRA) of lymphoblastoid cell lines from ASD individuals and unaffected individuals, and the methylation levels were correlated with the expression levels of LINE-1 and two LINE-1-inserted DEGs, C1orf27 and ARMC8.

RESULTS

We found that LINE-1 insertion was significantly associated with DEGs in ASD. The IPA showed that LINE-1-inserted DEGs were associated with ASD-related mechanisms, including sex hormone receptor signaling and axon guidance signaling. Moreover, we observed that the LINE-1 methylation level was significantly reduced in lymphoblastoid cell lines from ASD individuals with severe language impairment and was inversely correlated with the transcript level. The methylation level of LINE-1 was also correlated with the expression of the LINE-1-inserted DEG C1orf27 but not ARMC8.

CONCLUSIONS

In ASD individuals with severe language impairment, LINE-1 methylation was reduced and correlated with the expression levels of LINE-1 and the LINE-1-inserted DEG C1orf27. Our findings highlight the association of LINE-1 with DEGs in ASD blood samples and warrant further investigation. The molecular mechanisms of LINE-1 and the effects of its methylation in ASD pathobiology deserve further study.

Next-gen sequencing identifies non-coding variation disrupting miRNA-binding sites in neurological disorders

Understanding the genetic factors underlying neurodevelopmental and neuropsychiatric disorders is a major challenge given their prevalence and potential severity for quality of life. While large-scale genomic screens have made major advances in this area, for many disorders the genetic underpinnings are complex and poorly understood. To date the field has focused predominantly on protein coding variation, but given the importance of tightly controlled gene expression for normal brain development and disorder, variation that affects non-coding regulatory regions of the genome is likely to play an important role in these phenotypes. Herein we show the importance of 3 prime untranslated region (3'UTR) non-coding regulatory variants across neurodevelopmental and neuropsychiatric disorders. We devised a pipeline for identifying and functionally validating putatively pathogenic variants from next generation sequencing (NGS) data. We applied this pipeline to a cohort of children with severe specific language impairment (SLI) and identified a functional, SLI-associated variant affecting gene regulation in cells and post-mortem human brain. This variant and the affected gene (ARHGEF39) represent new putative risk factors for SLI. Furthermore, we identified 3'UTR regulatory variants across autism, schizophrenia and bipolar disorder NGS cohorts demonstrating their impact on neurodevelopmental and neuropsychiatric disorders. Our findings show the importance of investigating non-coding regulatory variants when determining risk factors contributing to neurodevelopmental and neuropsychiatric disorders. In the future, integration of such regulatory variation with protein coding changes will be essential for uncovering the genetic causes of complex neurological disorders and the fundamental mechanisms underlying health and disease.

Integrated genome-wide Alu methylation and transcriptome profiling analyses reveal novel epigenetic regulatory networks associated with autism spectrum disorder

Background

Alu elements are a group of repetitive elements that can influence gene expression through CpG residues and transcription factor binding. Altered gene expression and methylation profiles have been reported in various tissues and cell lines from individuals with autism spectrum disorder (ASD). However, the role of Alu elements in ASD remains unclear. We thus investigated whether Alu elements are associated with altered gene expression profiles in ASD.

Methods

We obtained five blood-based gene expression profiles from the Gene Expression Omnibus database and human Alu-inserted gene lists from the TranspoGene database. Differentially expressed genes (DEGs) in ASD were identified from each study and overlapped with the human Alu-inserted genes. The biological functions and networks of Alu-inserted DEGs were then predicted by Ingenuity Pathway Analysis (IPA). A combined bisulfite restriction analysis of lymphoblastoid cell lines (LCLs) derived from 36 ASD and 20 sex- and age-matched unaffected individuals was performed to assess the global DNA methylation levels within Alu elements, and the Alu expression levels were determined by quantitative RT-PCR.

Results

In ASD blood or blood-derived cells, 320 Alu-inserted genes were reproducibly differentially expressed. Biological function and pathway analysis showed that these genes were significantly associated with neurodevelopmental disorders and neurological functions involved in ASD etiology. Interestingly, estrogen receptor and androgen signaling pathways implicated in the sex bias of ASD, as well as IL-6 signaling and neuroinflammation signaling pathways, were also highlighted. Alu methylation was not significantly different between the ASD and sex- and age-matched control groups. However, significantly altered Alu methylation patterns were observed in ASD cases sub-grouped based on Autism Diagnostic Interview-Revised scores compared with matched controls. Quantitative RT-PCR analysis of Alu expression also showed significant differences between ASD subgroups. Interestingly, Alu expression was correlated with methylation status in one phenotypic ASD subgroup.

Conclusion

Alu methylation and expression were altered in LCLs from ASD subgroups. Our findings highlight the association of Alu elements with gene dysregulation in ASD blood samples and warrant further investigation. Moreover, the classification of ASD individuals into subgroups based on phenotypes may be beneficial and could provide insights into the still unknown etiology and the underlying mechanisms of ASD.

Electronic supplementary material

The online version of this article (10.1186/s13229-018-0213-9) contains supplementary material, which is available to authorized users.

Microarray analysis of gene expression in the cyclooxygenase knockout mice - a connection to autism spectrum disorder

The cellular and molecular events that take place during brain development play an important role in governing function of the mature brain. Lipid-signalling molecules such as prostaglandin E₂ (PGE₂ ) play an important role in healthy brain development. Abnormalities along the COX-PGE₂ signalling pathway due to genetic or environmental causes have been linked to autism spectrum disorder (ASD). This study aims to evaluate the effect of altered COX-PGE₂ signalling on development and function of the prenatal brain using male mice lacking cyclooxygenase-1 and cyclooxygenase-2 (COX-1^-/- and COX-2^-/- ) as potential model systems of ASD. Microarray analysis was used to determine global changes in gene expression during embryonic days 16 (E16) and 19 (E19). Gene Ontology: Biological Process (GO:BP) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were implemented to identify affected developmental genes and cellular processes. We found that in both knockouts the brain at E16 had nearly twice as many differentially expressed genes, and affected biological pathways containing various ASD-associated genes important in neuronal function. Interestingly, using GeneMANIA and Cytoscape we also show that the ASD-risk genes identified in both COX-1^-/- and COX-2^-/- models belong to protein-interaction networks important for brain development despite of different cellular localization of these enzymes. Lastly, we identified eight genes that belong to the Wnt signalling pathways exclusively in the COX-2^-/- mice at E16. The level of PKA-phosphorylated β-catenin (S552), a major activator of the Wnt pathway, was increased in this model, suggesting crosstalk between the COX-2-PGE₂ and Wnt pathways during early brain development. Overall, these results provide further molecular insight into the contribution of the COX-PGE₂ pathways to ASD and demonstrate that COX-1^-/- and COX-2^-/- animals might be suitable new model systems for studying the disorders.

Selection and classification of gene expression in autism disorder: Use of a combination of statistical filters and a GBPSO-SVM algorithm

In this work, gene expression in autism spectrum disorder (ASD) is analyzed with the goal of selecting the most attributed genes and performing classification. The objective was achieved by utilizing a combination of various statistical filters and a wrapper-based geometric binary particle swarm optimization-support vector machine (GBPSO-SVM) algorithm. The utilization of different filters was accentuated by incorporating a mean and median ratio criterion to remove very similar genes. The results showed that the most discriminative genes that were identified in the first and last selection steps included the presence of a repetitive gene (CAPS2), which was assigned as the gene most highly related to ASD risk. The merged gene subset that was selected by the GBPSO-SVM algorithm was able to enhance the classification accuracy.

High monocyte level and low lymphocyte to monocyte ratio in autism spectrum disorders

Objective: This study aims to investigate the level of peripheral blood mononuclear cells and their ratios which may point to the immunological mechanisms involved in the etiopathogenesis of ASD. Method: The complete blood count parameters of the 45 ASD cases were compared with those of healthy controls.Childhood Autism Rating Scale (CARS) was performed to measure the disease severity. Results: The monocytes of ASD group were significantly higher; and the lymphocyte-to-monocyte ratio (LMR) was lower than the controls'. LMR and neutrophil-to-lymphocyte ratio were found to be predictors of ASD. The decrease in LMR (B: -0.744; P=0.035; CI: -1.431 to -0.056) and the increase in age (B: 0.432; P=0.045; CI: 0.011-0.853) were related to high CARS scores in linear regression analyses. Conclusions: The results of this study support the role of altered immune cell counts and ratios in ASD. A high monocyte level and low LMR may have diagnostic values in autism.