Variation in Gene Expression in Autism Spectrum Disorders: An Extensive Review of Transcriptomic Studies

Database-assisted screening of autism spectrum disorder related gene set

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by social and communication difficulties, along with repetitive behaviors. While genetic factors play a significant role in ASD, the precise genetic landscape remains complex and not fully understood, particularly in non-syndromic cases. The study performed an in silico comparison of three genetic databases. ClinVar, SFARI Gene, and AutDB were utilized to identify relevant gene subset and genetic variations associated with non-syndromic ASD. Gene set enrichment analysis (GSEA) and protein-protein interaction (PPI) network analysis were conducted to elucidate the biological significance of the identified genes. The integrity of ASD-related gene subset and the distribution of their variations were statistically assessed. A subset of twenty overlapping genes potentially specific for non-syndromic ASD was identified. GSEA revealed enrichment of biological processes related to neuronal development and differentiation, synaptic function, and social skills, highlighting their importance in ASD pathogenesis. PPI network analysis demonstrated functional relationships among the identified genes. Analysis of genetic variations showed predominance of rare variants and database-specific distribution patterns. The results provide valuable insights into the genetic landscape of ASD and outline the genes and biological processes involved in the condition, while taking into account that the study relied exclusively on in silico analyses, which may be subject to biases inherent to database methodologies. Further research incorporating multi-omics data and experimental validation is warranted to enhance our understanding of non-syndromic ASD genetics and facilitate the development of targeted research, interventions and therapies.

Candidate biomarkers from the integration of methylation and gene expression in discordant autistic sibling pairs

While the genetics of autism spectrum disorders (ASD) has been intensively studied, resulting in the identification of over 100 putative risk genes, the epigenetics of ASD has received less attention, and results have been inconsistent across studies. We aimed to investigate the contribution of DNA methylation (DNAm) to the risk of ASD and identify candidate biomarkers arising from the interaction of epigenetic mechanisms with genotype, gene expression, and cellular proportions. We performed DNAm differential analysis using whole blood samples from 75 discordant sibling pairs of the Italian Autism Network collection and estimated their cellular composition. We studied the correlation between DNAm and gene expression accounting for the potential effects of different genotypes on DNAm. We showed that the proportion of NK cells was significantly reduced in ASD siblings suggesting an imbalance in their immune system. We identified differentially methylated regions (DMRs) involved in neurogenesis and synaptic organization. Among candidate loci for ASD, we detected a DMR mapping to CLEC11A (neighboring SHANK1) where DNAm and gene expression were significantly and negatively correlated, independently from genotype effects. As reported in previous studies, we confirmed the involvement of immune functions in the pathophysiology of ASD. Notwithstanding the complexity of the disorder, suitable biomarkers such as CLEC11A and its neighbor SHANK1 can be discovered using integrative analyses even with peripheral tissues.

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.

Biomarker prediction in autism spectrum disorder using a network-based approach

BACKGROUND

Autism is a neurodevelopmental disorder that is usually diagnosed in early childhood. Timely diagnosis and early initiation of treatments such as behavioral therapy are important in autistic people. Discovering critical genes and regulators in this disorder can lead to early diagnosis. Since the contribution of miRNAs along their targets can lead us to a better understanding of autism, we propose a framework containing two steps for gene and miRNA discovery.

METHODS

The first step, called the FA_gene algorithm, finds a small set of genes involved in autism. This algorithm uses the WGCNA package to construct a co-expression network for control samples and seek modules of genes that are not reproducible in the corresponding co-expression network for autistic samples. Then, the protein-protein interaction network is constructed for genes in the non-reproducible modules and a small set of genes that may have potential roles in autism is selected based on this network. The second step, named the DMN_miRNA algorithm, detects the minimum number of miRNAs related to autism. To do this, DMN_miRNA defines an extended Set Cover algorithm over the mRNA-miRNA network, consisting of the selected genes and corresponding miRNA regulators.

RESULTS

In the first step of the framework, the FA_gene algorithm finds a set of important genes; TP53, TNF, MAPK3, ACTB, TLR7, LCK, RAC2, EEF2, CAT, ZAP70, CD19, RPLP0, CDKN1A, CCL2, CDK4, CCL5, CTSD, CD4, RACK1, CD74; using co-expression and protein-protein interaction networks. In the second step, the DMN_miRNA algorithm extracts critical miRNAs, hsa-mir-155-5p, hsa-mir-17-5p, hsa-mir-181a-5p, hsa-mir-18a-5p, and hsa-mir-92a-1-5p, as signature regulators for autism using important genes and mRNA-miRNA network. The importance of these key genes and miRNAs is confirmed by previous studies and enrichment analysis.

CONCLUSION

This study suggests FA_gene and DMN_miRNA algorithms for biomarker discovery, which lead us to a list of important players in ASD with potential roles in the nervous system or neurological disorders that can be experimentally investigated as candidates for ASD diagnostic tests.

Key role of Rho GTPases in motor disorders associated with neurodevelopmental pathologies

Growing evidence suggests that Rho GTPases and molecules involved in their signaling pathways play a major role in the development of the central nervous system (CNS). Whole exome sequencing (WES) and de novo examination of mutations, including SNP (Single Nucleotide Polymorphism) in genes coding for the molecules of their signaling cascade, has allowed the recent discovery of dominant autosomic mutations and duplication or deletion of candidates in the field of neurodevelopmental diseases (NDD). Epidemiological studies show that the co-occurrence of several of these neurological pathologies may indeed be the rule. The regulators of Rho GTPases have often been considered for cognitive diseases such as intellectual disability (ID) and autism. But, in a remarkable way, mild to severe motor symptoms are now reported in autism and other cognitive NDD. Although a more abundant litterature reports the involvement of Rho GTPases and signaling partners in cognitive development, molecular investigations on their roles in central nervous system (CNS) development or degenerative CNS pathologies also reveal their role in embryonic and perinatal motor wiring through axon guidance and later in synaptic plasticity. Thus, Rho family small GTPases have been revealed to play a key role in brain functions including learning and memory but their precise role in motor development and associated symptoms in NDD has been poorly scoped so far, despite increasing clinical data highlighting the links between cognition and motor development. Indeed, early impairements in fine or gross motor performance is often an associated feature of NDDs, which then impact social communication, cognition, emotion, and behavior. We review here recent insights derived from clinical developmental neurobiology in the field of Rho GTPases and NDD (autism spectrum related disorder (ASD), ID, schizophrenia, hypotonia, spastic paraplegia, bipolar disorder and dyslexia), with a specific focus on genetic alterations affecting Rho GTPases that are involved in motor circuit development.

Pathology and Astrocytes in Autism

A distinct pathology for autism spectrum disorder (ASD) remains elusive. Human and animal studies have focused on investigating the role of neurons in ASD. However, recent studies have hinted that glial cell pathology could be a characteristic of ASD. Astrocytes are the most abundant glial cell in the brain and play an important role in neuronal function, both during development and in adult. They regulate neuronal migration, dendritic and spine development, and control the concentration of neurotransmitters at the synaptic cleft. They are also responsible for synaptogenesis, synaptic development, and synaptic function. Therefore, any change in astrocyte number and/or function could contribute to the impairment of connectivity that has been reported in ASD. Data available to date is scarce but indicates that while the number of astrocytes is reduced, their state of activation and their GFAP expression is increased in ASD. Disruption of astrocyte function in ASD may affect proper neurotransmitter metabolism, synaptogenesis, and the state of brain inflammation. Astrocytes alterations are common to ASD and other neurodevelopmental disorders. Future studies about the role of astrocytes in ASD are required to better understand this disorder.

Persistent Inflammation Initiated by TORCH Infections and Dysbiotic Microbiome in Autism Spectrum Disorders: A Prospect for Future Interventions

Autism spectrum disorders (ASD) are a range of neurodevelopmental conditions that are clinically present early in childhood with the symptoms of social withdrawal and repetitive behavior. Despite an extensive research on ASD, no commonly accepted theory on the disease etiology exists. Hence, we reviewed several scientific publications, including reviews, preclinical and clinical investigations, and published hypotheses to analyze various opinions on the nature and cause of the disorder. Many studies suggest that infections and inflammation during pregnancy play a significant role in genetic and epigenetic changes in the developing fetus, resulting in an autistic phenotype in a child. Still, there is a lack of comprehensive literature about the multitude of autism inducing factors. Therefore, this article reviews and discusses available scientific evidence on the roles of viral, bacterial, fungal, and parasitic infections, overactivation of the immune system, and intestinal microflora in the pathogenesis and clinical manifestation of ASD. The overview of the scientific publications, including our own studies, suggests that TORCH infections, imbalanced microbiome, and persistent inflammation are significantly associated with the disruption of the social domain in ASD children. The ASD-related changes begin prenatally as maternal-to-fetal immune activation triggered by infection. It results in continuous low-grade inflammation and oxidative stress in a fetus, causing germline and somatic genetic changes in the developing brain and the establishment of the dysregulated immune system. These changes and dysregulations result in central and peripheral nervous systems dysfunctions as well as other comorbid conditions found in autistic children.

Linking neuroanatomical abnormalities in autism spectrum disorder with gene expression of candidate ASD genes: A meta-analytic and network-oriented approach

BACKGROUND

Autism spectrum disorder (ASD) is a set of developmental conditions with widespread neuroanatomical abnormalities and a strong genetic basis. Although neuroimaging studies have indicated anatomical changes in grey matter (GM) morphometry, their associations with gene expression remain elusive.

METHODS

Here, we aim to understand how gene expression correlates with neuroanatomical atypicalities in ASD. To do so, we performed a coordinate-based meta-analysis to determine the common GM variation pattern in the autistic brain. From the Allen Human Brain Atlas, we selected eight genes from the SHANK, NRXN, NLGN family and MECP2, which have been implicated with ASD, particularly in regards to altered synaptic transmission and plasticity. The gene expression maps for each gene were built. We then assessed the correlation between the gene expression maps and the GM alteration maps. Lastly, we projected the obtained clusters of GM alteration-gene correlations on top of the canonical resting state networks, in order to provide a functional characterization of the structural evidence.

RESULTS

We found that gene expression of most genes correlated with GM alteration (both increase and decrease) in regions located in the default mode network. Decreased GM was also correlated with gene expression of some ASD genes in areas associated with the dorsal attention and cerebellar network. Lastly, single genes were found to be significantly correlated with increased GM in areas located in the somatomotor, limbic and ganglia/thalamus networks.

CONCLUSIONS

This approach allowed us to combine the well beaten path of genetic and brain imaging in a novel way, to specifically investigate the relation between gene expression and brain with structural damage, and individuate genes of potential interest for further investigation in the functional domain.

Otizm Spektrum Bozukluğu Olan Hastalarda Öğrenme ve Hafıza Bozukluklarının NEURL1 ve RGS14 Genleri ile İlişkisi

Aim: We aimed to evaluate the relationship between learning-memory difficulties and NEURL1 and RGS14 genes in patients with autism spectrum disorders (ASD). Method: Forty children with ASD (20 ASD, 20 high functioning autism (HFA)) and 20 healthy controls were enrolled in this study. NEURL1 and RGS14 gene expressions in the blood samples of volunteers were assessed by quantitative Real-Time PCR (qRT-PCR). The clinical and demographical findings in patients were determined and examined relation with the gene expressions. Results: According to our findings, NEURL1 gene expression was decreased in both patient groups compared to the control (p0.05). A statistically significant correlation was found between learning and memory difficulties and RGS14 gene expression in HFA patients (p = 0.045). There was a positive correlation between between NEURL1 and RGS14 gene expressions of ASD patients (p=0.032, r=0,59). Conclusion: According to this study, NEURL1 gene may be proposed as a candidate gene for ASD. Nonetheless, we recommend that both genes be studied with more patients and preferably with brain tissues. These genes were evaluated for the first time in a clinical study on autism, and we believe that they will contribute to the literature in this respect.

Trans-genetic effects of circular RNA expression quantitative trait loci and potential causal mechanisms in autism

Genetic risk variants and transcriptional expression changes in autism spectrum disorder (ASD) were widely investigated, but their causal relationship remains largely unknown. Circular RNAs (circRNAs) are abundant in brain and often serve as upstream regulators of mRNAs. By integrating RNA-sequencing with genotype data from autistic brains, we assessed expression quantitative trait loci of circRNAs (circQTLs) that cis-regulated expression of nearby circRNAs and trans-regulated expression of distant genes (trans-eGenes) simultaneously. We thus identified 3619 circQTLs that were also trans-eQTLs and constructed 19,804 circQTL-circRNA-trans-eGene regulatory axes. We conducted two different types of approaches, mediation and partial correlation tests (MPT), to determine the axes with mediation effects of circQTLs on trans-eGene expression through circRNA expression. We showed that the mediation effects of the circQTLs (trans-eQTLs) on circRNA expression were positively correlated with the magnitude of circRNA-trans-eGene correlation of expression profile. The positive correlation became more significant after adjustment for the circQTLs. Of the 19,804 axes, 8103 passed MPT. Meanwhile, we performed causal inference test (CIT) and identified 2070 circQTL-trans-eGene-ASD diagnosis propagation paths. We showed that the CIT-passing genes were significantly enriched for ASD risk genes, genes encoding postsynaptic density proteins, and other ASD-relevant genes, supporting the relevance of the CIT-passing genes to ASD pathophysiology. Integration of MPT- and CIT-passing axes further constructed 352 circQTL-circRNA-trans-eGene-ASD diagnosis propagation paths, wherein the circRNA-trans-eGene axes may act as causal mediators for the circQTL-ASD diagnosis associations. These analyses were also successfully applied to an independent dataset from schizophrenia brains. Collectively, this study provided the first framework for systematically investigating trans-genetic effects of circQTLs and inferring the corresponding causal relations in diseases. The identified circQTL-circRNA-trans-eGene regulatory interactions, particularly the internal modules that were previously implicated in the examined disorders, also provided a helpful dataset for further investigating causative biology and cryptic regulatory mechanisms underlying the neuropsychiatric diseases.

Re-emerging concepts of immune dysregulation in autism spectrum disorders

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by communication and social interaction deficits, and by restricted interests and stereotyped, repetitive behavior patterns. ASD has a strong genetic component and a complex architecture characterized by the interplay of rare and common genetic variants. Recently, increasing evidence suggest a significant contribution of immune system dysregulation in ASD. The present paper reviews the latest updates regarding the altered immune landscape of this complex disorder highlighting areas with potential for biomarkers discovery as well as personalization of therapeutic approaches. Cross-talk between the central nervous system and immune system has long been envisaged and recent evidence brings insights into the pathways connecting the brain to the immune system. Disturbance of cytokine levels plays an important role in the establishment of a neuroinflammatory milieu in ASD. Several other immune molecules involved in antigen presentation and inflammatory cellular phenotypes are also at play in ASD. Maternal immune activation, the presence of brain-reactive antibodies and autoimmunity are other potential prenatal and postnatal contributors to ASD pathophysiology. The molecular players involved in oxidative-stress response and mitochondrial system function, are discussed as contributors to the pro-inflammatory pattern. The gastrointestinal inflammation pathways proposed to play a role in ASD are also discussed. Moreover, the body of evidence regarding some of the genetic factors linked to the immune system dysregulation is reviewed and discussed. Last, but not least, the epigenetic traits and their interactions with the immune system are reviewed as an expanding field in ASD research. Understanding the immune-mediated pathways that influence brain development and function, metabolism, and intestinal homeostasis, may lead to the identification of robust diagnostic or predictive biomarkers for ASD individuals. Thus, novel therapeutic approaches could be developed, ultimately aiming to improve their quality of life.

FOXP2 down expression is associated with executive dysfunctions and electrophysiological abnormalities of brain in Autism spectrum disorder; a neuroimaging genetic study

BACKGROUND AND AIMS

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by language impairment, and challenges with social interaction, communication, and repetitive behaviors. Although genetics are a primary cause of ASD, the exact genes and molecular mechanisms involved in its pathogenesis are not completely clear. The FOXP2 gene encodes a transcription factor that is known for its major role in language development and severe speech problems. The present study aimed to evaluate the role of FOXP2 in ASD etiology, executive functions, and brain activities.

METHODS

In the present study, we recruited 450 children with ASD and 490 neurotypical control children. Three domains of executive functions (working memory, response inhibition, and vigilance) were assessed. In addition, five-minute eyes closed electroencephalography was obtained from some of the children with ASD and neurotypical children. DNA sequence and expression level of FOXP2 in blood samples of children with ASD and the control group were evaluated by using sequencing and Real-time PCR, respectively.

RESULTS

The results showed no mutations but a significant down expression of FOXP2 genes in children with ASD vs. neurotypical children. Several cognitive and executive function deficiencies were detected in children with ASD. Low alpha and gamma bands in the frontal lobe and high theta bands in the occipital lobe were revealed in children with ASD. We also found several correlations between FOXP2 expression levels and clinical assessments.

CONCLUSIONS

Our finding revealed the down expression of FOXP2, which could be considered as a biomarker for ASD as well as cognitive and executive dysfunction. Based on brain mapping data, FOXP2 may be related to the theta wave abnormality of children with ASD. FOXP2 may be considered a target of novel treatment to improve memory and executive functions.

IMPLICATIONS

Our findings highlight the role of FOXP2 mRNA level in ASD etiology, executive functions, and brain wave frequencies.

Pre-treatment clinical and gene expression patterns predict developmental change in early intervention in autism

Early detection and intervention are believed to be key to facilitating better outcomes in children with autism, yet the impact of age at treatment start on the outcome is poorly understood. While clinical traits such as language ability have been shown to predict treatment outcome, whether or not and how information at the genomic level can predict treatment outcome is unknown. Leveraging a cohort of toddlers with autism who all received the same standardized intervention at a very young age and provided a blood sample, here we find that very early treatment engagement (i.e., <24 months) leads to greater gains while controlling for time in treatment. Pre-treatment clinical behavioral measures predict 21% of the variance in the rate of skill growth during early intervention. Pre-treatment blood leukocyte gene expression patterns also predict the rate of skill growth, accounting for 13% of the variance in treatment slopes. Results indicated that 295 genes can be prioritized as driving this effect. These treatment-relevant genes highly interact at the protein level, are enriched for differentially histone acetylated genes in autism postmortem cortical tissue, and are normatively highly expressed in a variety of subcortical and cortical areas important for social communication and language development. This work suggests that pre-treatment biological and clinical behavioral characteristics are important for predicting developmental change in the context of early intervention and that individualized pre-treatment biology related to histone acetylation may be key.

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.

Dysregulation of NF-κB-Associated LncRNAs in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a long-standing neurodevelopmental condition with prominent effects on social behavior of affected children. This disorder has been linked with neuroinflammatory responses. NF-κB has been shown to affect these responses in the orbitofrontal cortex of patients with ASD, thus being implicated in the pathogenesis of ASD. We measured expression of some NF-κB-associated lncRNAs and mRNAs (DILC, ANRIL, PACER, CHAST, ADINR, DICER1-AS1, HNF1A-AS1, NKILA, ATG5 and CEBPA) in the peripheral blood of ASD kids vs. healthy children. Expression quantities of ADINR, ANRIL, DILC, NKILA and CHAST were meaningfully higher in ASD cases compared with healthy kids (Posterior Beta = 1.402, P value < 0.0001; Posterior Beta = 2.959, P value < 0.0001; Posterior Beta = 0.882, P value = 0.012; Posterior Beta = 1.461, P value < 0.0001; Posterior Beta = 0.541, P value = 0.043, respectively). The Bonferroni corrected P values for these lncRNAs remained significant except for CHAST and DILC. Expression levels of other genes were not considerably different between cases and controls. Expressions of ATG5, DICER-AS1 and DILC were correlated with age of ASD patients (P < 0.0001). Among ASD cases, the most robust correlation has been detected between ADINR and NKILA (r = 0.87, P < 0.0001). Expression of none of genes has been correlated with age of healthy children. Among this group of children, expression levels of ADINR and CHAST were robustly correlated (r = 0.83, P < 0.0001). ANRIL had the greatest AUC value (AUC = 0.857), thus the best diagnostic power among the assessed genes. NKILA ranked the second position in this regard (AUC = 0.757). Thus, NF-κB-associated lncRNAs might partake in the pathogenesis of ASD.

Human iPSC-Derived Glia as a Tool for Neuropsychiatric Research and Drug Development

Neuropsychiatric disorders such as schizophrenia or autism spectrum disorder represent a leading and growing burden on worldwide mental health. Fundamental lack in understanding the underlying pathobiology compromises efficient drug development despite the immense medical need. So far, antipsychotic drugs reduce symptom severity and enhance quality of life, but there is no cure available. On the molecular level, schizophrenia and autism spectrum disorders correlate with compromised neuronal phenotypes. There is increasing evidence that aberrant neuroinflammatory responses of glial cells account for synaptic pathologies through deregulated communication and reciprocal modulation. Consequently, microglia and astrocytes emerge as central targets for anti-inflammatory treatment to preserve organization and homeostasis of the central nervous system. Studying the impact of neuroinflammation in the context of neuropsychiatric disorders is, however, limited by the lack of relevant human cellular test systems that are able to represent the dynamic cellular processes and molecular changes observed in human tissue. Today, patient-derived induced pluripotent stem cells offer the opportunity to study neuroinflammatory mechanisms in vitro that comprise the genetic background of affected patients. In this review, we summarize the major findings of iPSC-based microglia and astrocyte research in the context of neuropsychiatric diseases and highlight the benefit of 2D and 3D co-culture models for the generation of efficient in vitro models for target screening and drug development.

A Maternal High-Fat Diet during Early Development Provokes Molecular Changes Related to Autism Spectrum Disorder in the Rat Offspring Brain

Autism spectrum disorder (ASD) is a disruptive neurodevelopmental disorder manifested by abnormal social interactions, communication, emotional circuits, and repetitive behaviors and is more often diagnosed in boys than in girls. It is postulated that ASD is caused by a complex interaction between genetic and environmental factors. Epigenetics provides a mechanistic link between exposure to an unbalanced maternal diet and persistent modifications in gene expression levels that can lead to phenotype changes in the offspring. To better understand the impact of the early development environment on the risk of ASD in offspring, we assessed the effect of maternal high-fat (HFD), high-carbohydrate, and mixed diets on molecular changes in adolescent and young adult offspring frontal cortex and hippocampus. Our results showed that maternal HFD significantly altered the expression of 48 ASD-related genes in the frontal cortex of male offspring. Moreover, exposure to maternal HFD led to sex- and age-dependent changes in the protein levels of ANKRD11, EIF4E, NF1, SETD1B, SHANK1 and TAOK2, as well as differences in DNA methylation levels in the frontal cortex and hippocampus of the offspring. Taken together, it was concluded that a maternal HFD during pregnancy and lactation periods can lead to abnormal brain development within the transcription and translation of ASD-related genes mainly in male offspring.

Alteration of the Early Development Environment by Maternal Diet and the Occurrence of Autistic-like Phenotypes in Rat Offspring

Epidemiological and preclinical studies suggest that maternal obesity increases the risk of autism spectrum disorder (ASD) in offspring. Here, we assessed the effects of exposure to modified maternal diets limited to pregnancy and lactation on brain development and behavior in rat offspring of both sexes. Among the studied diets, a maternal high-fat diet (HFD) disturbed the expression of ASD-related genes (Cacna1d, Nlgn3, and Shank1) and proteins (SHANK1 and TAOK2) in the prefrontal cortex of male offspring during adolescence. In addition, a maternal high-fat diet induced epigenetic changes by increasing cortical global DNA methylation and the expression of miR-423 and miR-494. As well as the molecular changes, behavioral studies have shown male-specific disturbances in social interaction and an increase in repetitive behavior during adolescence. Most of the observed changes disappeared in adulthood. In conclusion, we demonstrated the contribution of a maternal HFD to the predisposition to an ASD-like phenotype in male adolescent offspring, while a protective effect occurred in females.

Atypical genomic cortical patterning in autism with poor early language outcome

Cortical regionalization develops via genomic patterning along anterior-posterior (A-P) and dorsal-ventral (D-V) gradients. Here, we find that normative A-P and D-V genomic patterning of cortical surface area (SA) and thickness (CT), present in typically developing and autistic toddlers with good early language outcome, is absent in autistic toddlers with poor early language outcome. Autistic toddlers with poor early language outcome are instead specifically characterized by a secondary and independent genomic patterning effect on CT. Genes involved in these effects can be traced back to midgestational A-P and D-V gene expression gradients and different prenatal cell types (e.g., progenitor cells and excitatory neurons), are functionally important for vocal learning and human-specific evolution, and are prominent in prenatal coexpression networks enriched for high-penetrance autism risk genes. Autism with poor early language outcome may be explained by atypical genomic cortical patterning starting in prenatal development, which may detrimentally affect later regional functional specialization and circuit formation.

Peripheral Expression of MACROD2 Gene Is Reduced Among a Sample of Turkish Children with Autism Spectrum Disorder

Background

Genomic variations in mono-ADP ribosylhydrolase 2 (MACROD2) have been associated with autism spectrum disorder (ASD) in recent genome-wide studies and case reports. In this study, we aimed to evaluate the MACROD2 expression profile in patients with ASD.

Methods

The study group included 100 children with a DSM-5 diagnosis of ASD, and the control group consisted of 105 healthy controls. Blood samples were obtained from all participants in this study, and the gene expression level was determined using quantitative reverse transcription PCR (RT-qPCR). Statistical analysis was performed with R 3.4.0 and Statistical Program for Social Sciences (SPSS for Windows, 21.0).

Results

The mean ages of the participants in the study and control groups were 9.22 ± 3.62 and 9.27 ± 3.86 years, respectively. There was no significant difference concerning gender (P = .944) and age (P = .914) between the 2 groups. MACROD2 gene expression was found to be decreased in the study group compared to the control group (study group = 5.73, control group = 89.56; fold change =-3.967; P < .001). While the level of MACROD2 expression was not correlated with the ASD severity, it was associated with the severity of the hyperactivity/impulsivity symptoms (P = .008).

Conclusions

This is the first study in the literature investigating the peripheral expression of the MACROD2 gene. We showed that the expression level of MACROD2 was decreased in patients with ASD when compared to the control group. As the relationship between the MACROD2 gene expression profile and ASD remains to be further investigated, this study may provide an insight for further studies.

Expression Analysis of Ermin and Listerin E3 Ubiquitin Protein Ligase 1 Genes in Autistic Patients

Autism spectrum disorder (ASD) is a severe neurodevelopmental disorder that involves social interaction defects, impairment of non-verbal and verbal interactions, and limited interests along with stereotypic activities. Its incidence has been increasing rapidly in recent decades. Despite numerous attempts to understand the pathophysiology of ASD, its exact etiology is still unclear. Recent data shows the role of accurate myelination and translational regulation in ASD's pathogenesis. In this study, we assessed Ermin (ERMN) and Listerin E3 Ubiquitin Protein Ligase 1 (LTN1) genes expression in Iranian ASD patients and age- and gender-matched healthy subjects' peripheral blood using quantitative real-time PCR to recognize any probable dysregulation in the expression of these genes and propose this disorder's mechanisms. Analysis of the expression demonstrated a significant ERMN downregulation in total ASD patients compared to the healthy individuals (posterior beta = -0.794, adjusted P-value = 0.025). LTN1 expression was suggestively higher in ASD patients in comparison with the corresponding control individuals. Considering the gender of study participants, the analysis showed that the mentioned genes' different expression levels were significant only in male subjects. Besides, a significant correlation was found between expression of the mentioned genes (r = -0.49, P < 0.0001). The present study provides further supports for the contribution of ERMN and LTN1 in ASD's pathogenesis.

The neuropathology of autism: A systematic review of post-mortem studies of autism and related disorders

Post-mortem studies allow for the direct investigation of brain tissue in those with autism and related disorders. Several review articles have focused on aspects of post-mortem abnormalities but none has brought together the entire post-mortem literature. Here, we systematically review the evidence from post-mortem studies of autism, and of related disorders that present with autistic features. The literature consists of a small body of studies with small sample sizes, but several remarkably consistent findings are evident. Cortical layering is largely undisturbed, but there are consistent reductions in minicolumn numbers and aberrant myelination. Transcriptomics repeatedly implicate abberant synaptic, metabolic, proliferation, apoptosis and immune pathways. Sufficient replicated evidence is available to implicate non-coding RNA, aberrant epigenetic profiles, GABAergic, glutamatergic and glial dysfunction in autism pathogenesis. Overall, the cerebellum and frontal cortex are most consistently implicated, sometimes revealing distinct region-specific alterations. The literature on related disorders such as Rett syndrome, Fragile X and copy number variations (CNVs) predisposing to autism is particularly small and inconclusive. Larger studies, matched for gender, developmental stage, co-morbidities and drug treatment are required.

R.ROSETTA: an interpretable machine learning framework

BACKGROUND

Machine learning involves strategies and algorithms that may assist bioinformatics analyses in terms of data mining and knowledge discovery. In several applications, viz. in Life Sciences, it is often more important to understand how a prediction was obtained rather than knowing what prediction was made. To this end so-called interpretable machine learning has been recently advocated. In this study, we implemented an interpretable machine learning package based on the rough set theory. An important aim of our work was provision of statistical properties of the models and their components.

RESULTS

We present the R.ROSETTA package, which is an R wrapper of ROSETTA framework. The original ROSETTA functions have been improved and adapted to the R programming environment. The package allows for building and analyzing non-linear interpretable machine learning models. R.ROSETTA gathers combinatorial statistics via rule-based modelling for accessible and transparent results, well-suited for adoption within the greater scientific community. The package also provides statistics and visualization tools that facilitate minimization of analysis bias and noise. The R.ROSETTA package is freely available at https://github.com/komorowskilab/R.ROSETTA . To illustrate the usage of the package, we applied it to a transcriptome dataset from an autism case-control study. Our tool provided hypotheses for potential co-predictive mechanisms among features that discerned phenotype classes. These co-predictors represented neurodevelopmental and autism-related genes.

CONCLUSIONS

R.ROSETTA provides new insights for interpretable machine learning analyses and knowledge-based systems. We demonstrated that our package facilitated detection of dependencies for autism-related genes. Although the sample application of R.ROSETTA illustrates transcriptome data analysis, the package can be used to analyze any data organized in decision tables.

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.

ASDmiR: A Stepwise Method to Uncover miRNA Regulation Related to Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a class of neurodevelopmental disorders characterized by genetic and environmental risk factors. The pathogenesis of ASD has a strong genetic basis, consisting of rare de novo or inherited variants among a variety of multiple molecules. Previous studies have shown that microRNAs (miRNAs) are involved in neurogenesis and brain development and are closely associated with the pathogenesis of ASD. However, the regulatory mechanisms of miRNAs in ASD are largely unclear. In this work, we present a stepwise method, ASDmiR, for the identification of underlying pathogenic genes, networks, and modules associated with ASD. First, we conduct a comparison study on 12 miRNA target prediction methods by using the matched miRNA, lncRNA, and mRNA expression data in ASD. In terms of the number of experimentally confirmed miRNA-target interactions predicted by each method, we choose the best method for identifying miRNA-target regulatory network. Based on the miRNA-target interaction network identified by the best method, we further infer miRNA-target regulatory bicliques or modules. In addition, by integrating high-confidence miRNA-target interactions and gene expression data, we identify three types of networks, including lncRNA-lncRNA, lncRNA-mRNA, and mRNA-mRNA related miRNA sponge interaction networks. To reveal the community of miRNA sponges, we further infer miRNA sponge modules from the identified miRNA sponge interaction network. Functional analysis results show that the identified hub genes, as well as miRNA-associated networks and modules, are closely linked with ASD. ASDmiR is freely available at https://github.com/chenchenxiong/ASDmiR.

Expression Changes in Epigenetic Gene Pathways Associated With One-Carbon Nutritional Metabolites in Maternal Blood From Pregnancies Resulting in Autism and Non-Typical Neurodevelopment

The prenatal period is a critical window for the development of autism spectrum disorder (ASD). The relationship between prenatal nutrients and gestational gene expression in mothers of children later diagnosed with ASD or non-typical development (Non-TD) is poorly understood. Maternal blood collected prospectively during pregnancy provides insights into the effects of nutrition, particularly one-carbon metabolites, on gene pathways and neurodevelopment. Genome-wide transcriptomes were measured with microarrays in 300 maternal blood samples in Markers of Autism Risk in Babies-Learning Early Signs. Sixteen different one-carbon metabolites, including folic acid, betaine, 5'-methyltretrahydrofolate (5-MeTHF), and dimethylglycine (DMG) were measured. Differential expression analysis and weighted gene correlation network analysis (WGCNA) were used to compare gene expression between children later diagnosed as typical development (TD), Non-TD and ASD, and to one-carbon metabolites. Using differential gene expression analysis, six transcripts (TGR-AS1, SQSTM1, HLA-C, and RFESD) were associated with child outcomes (ASD, Non-TD, and TD) with genome-wide significance. Genes nominally differentially expressed between ASD and TD significantly overlapped with seven high confidence ASD genes. WGCNA identified co-expressed gene modules significantly correlated with 5-MeTHF, folic acid, DMG, and betaine. A module enriched in DNA methylation functions showed a suggestive protective association with folic acid/5-MeTHF concentrations and ASD risk. Maternal plasma betaine and DMG concentrations were associated with a block of co-expressed genes enriched for adaptive immune, histone modification, and RNA processing functions. These results suggest that the prenatal maternal blood transcriptome is a sensitive indicator of gestational one-carbon metabolite status and changes relevant to children's later neurodevelopmental outcomes. LAY SUMMARY: Pregnancy is a time when maternal nutrition could interact with genetic risk for autism spectrum disorder. Blood samples collected during pregnancy from mothers who had a prior child with autism were examined for gene expression and nutrient metabolites, then compared to the diagnosis of the child at age three. Expression differences in gene pathways related to the immune system and gene regulation were observed for pregnancies of children with autism and non-typical neurodevelopment and were associated with maternal nutrients.

Microbiota, Immune System and Autism Spectrum Disorders: An Integrative Model towards Novel Treatment Options

BACKGROUND

Autism Spectrum Disorder (ASD) is a condition strongly associated with genetic predisposition and familial aggregation. Among ASD patients, different levels of symptoms severity are detectable, while the presence of intermediate autism phenotypes in close relatives of ASD probands is also known in literature. Recently, increasing attention has been paid to environmental factors that might play a role in modulating the relationship between genomic risk and development and severity of ASD. Within this framework, an increasing body of evidence has stressed a possible role of both gut microbiota and inflammation in the pathophysiology of neurodevelopment. The aim of this paper is to review findings about the link between microbiota dysbiosis, inflammation and ASD.

METHODS

Articles ranging from 1990 to 2018 were identified on PUBMED and Google Scholar databases, with keyword combinations as: microbiota, immune system, inflammation, ASD, autism, broad autism phenotype, adult.

RESULTS

Recent evidence suggests that microbiota alterations, immune system and neurodevelopment may be deeply intertwined, shaping each other during early life. However, results from both animal models and human samples are still heterogeneous, while few studies focused on adult patients and ASD intermediate phenotypes.

CONCLUSION

A better understanding of these pathways, within an integrative framework between central and peripheral systems, might not only shed more light on neural basis of ASD symptoms, clarifying brain pathophysiology, but it may also allow to develop new therapeutic strategies for these disorders, still poorly responsive to available treatments.

An Overview of Bioinformatics Methods for Analyzing Autism Spectrum Disorders

Autism Spectrum Disorders (ASD) are a group of neurodevelopmental disorders and are well recognized to be biologically heterogeneous in which various factors are associated, including genetic, metabolic, and environmental ones. Despite its high prevalence, only a few drugs have been approved for the treatment of ASD. Therefore, extensive studies have been conducted to identify ASD risk genes and novel drug targets. Since many genes and many other factors are associated with ASD, various bioinformatics methods have also been developed for the analysis of ASD. In this paper, we review bioinformatics methods for analyzing ASD data with the focus on computational aspects. We classify existing methods into two categories: (i) methods based on genomic variants and gene expression data, and (ii) methods using biological networks, which include gene co-expression networks and protein-protein interaction networks. Next, for each method, we provide an overall flow and elaborate on the computational techniques used. We also briefly review other approaches and discuss possible future directions and strategies for developing bioinformatics approaches to analyze ASD.

Potential Associations Among Alteration of Salivary miRNAs, Saliva Microbiome Structure, and Cognitive Impairments in Autistic Children

Recent evidence has demonstrated that salivary molecules, as well as bacterial populations, can be perturbed by several pathological conditions, including neuro-psychiatric diseases. This relationship between brain functionality and saliva composition could be exploited to unveil new pathological mechanisms of elusive diseases, such as Autistic Spectrum Disorder (ASD). We performed a combined approach of miRNA expression profiling by NanoString technology, followed by validation experiments in qPCR, and 16S rRNA microbiome analysis on saliva from 53 ASD and 27 neurologically unaffected control (NUC) children. MiR-29a-3p and miR-141-3p were upregulated, while miR-16-5p, let-7b-5p, and miR-451a were downregulated in ASD compared to NUCs. Microbiome analysis on the same subjects revealed that Rothia, Filifactor, Actinobacillus, Weeksellaceae, Ralstonia, Pasteurellaceae, and Aggregatibacter increased their abundance in ASD patients, while Tannerella, Moryella and TM7-3 decreased. Variations of both miRNAs and microbes were statistically associated to different neuropsychological scores related to anomalies in social interaction and communication. Among miRNA/bacteria associations, the most relevant was the negative correlation between salivary miR-141-3p expression and Tannerella abundance. MiRNA and microbiome dysregulations found in the saliva of ASD children are potentially associated with cognitive impairments of the subjects. Furthermore, a potential cross-talking between circulating miRNAs and resident bacteria could occur in saliva of ASD.

Towards a Multivariate Biomarker-Based Diagnosis of Autism Spectrum Disorder: Review and Discussion of Recent Advancements

An ever-evolving understanding of autism spectrum disorder (ASD) pathophysiology necessitates that diagnostic standards also evolve from being observation-based to include quantifiable clinical measurements. The multisystem nature of ASD motivates the use of multivariate methods of statistical analysis over common univariate approaches for discovering clinical biomarkers relevant to this goal. In addition to characterization of important behavioral patterns for improving current diagnostic instruments, multivariate analyses to date have allowed for thorough investigation of neuroimaging-based, genetic, and metabolic abnormalities in individuals with ASD. This review highlights current research using multivariate statistical analyses to quantify the value of these behavioral and physiological markers for ASD diagnosis. A detailed discussion of a blood-based diagnostic test for ASD using specific metabolite concentrations is also provided. The advancement of ASD biomarker research promises to provide earlier and more accurate diagnoses of the disorder.

IGF-1 treatment causes unique transcriptional response in neurons from individuals with idiopathic autism

BACKGROUND

Research evidence accumulated in the past years in both rodent and human models for autism spectrum disorders (ASD) have established insulin-like growth factor 1 (IGF-1) as one of the most promising ASD therapeutic interventions to date. ASD is phenotypically and etiologically heterogeneous, making it challenging to uncover the underlying genetic and cellular pathophysiology of the condition; and to efficiently design drugs with widespread clinical benefits. While IGF-1 effects have been comprehensively studied in the literature, how IGF-1 activity may lead to therapeutic recovery in the ASD context is still largely unknown.

METHODS

In this study, we used a previously characterized neuronal population derived from induced pluripotent stem cells (iPSC) from neurotypical controls and idiopathic ASD individuals to study the transcriptional signature of acutely and chronically IGF-1-treated cells.

RESULTS

We present a comprehensive list of differentially regulated genes and molecular interactions resulting from IGF-1 exposure in developing neurons from controls and ASD individuals. Our results indicate that IGF-1 treatment has a different impact on neurons from ASD patients compared to controls. Response to IGF-1 treatment in neurons derived from ASD patients was heterogeneous and correlated with IGF-1 receptor expression, indicating that IGF-1 response may have responder and non-responder distinctions across cohorts of ASD patients. Our results suggest that caution should be used when predicting the effect of IGF-1 treatment on ASD patients using neurotypical controls. Instead, IGF-1 response should be studied in the context of ASD patients' neural cells.

LIMITATIONS

The limitation of our study is that our cohort of eight sporadic ASD individuals is comorbid with macrocephaly in childhood. Future studies will address weather downstream transcriptional response of IGF-1 is comparable in non-macrocephalic ASD cohorts.

CONCLUSIONS

The results presented in this study provide an important resource for researchers in the ASD field and underscore the necessity of using ASD patient lines to explore ASD neuronal-specific responses to drugs such as IGF-1. This study further helps to identify candidate pathways and targets for effective clinical intervention and may help to inform clinical trials in the future.

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.

Genome-wide, integrative analysis of circular RNA dysregulation and the corresponding circular RNA-microRNA-mRNA regulatory axes in autism

Circular RNAs (circRNAs), a class of long noncoding RNAs, are known to be enriched in mammalian neural tissues. Although a wide range of dysregulation of gene expression in autism spectrum disorder (ASD) have been reported, the role of circRNAs in ASD remains largely unknown. Here, we performed genome-wide circRNA expression profiling in postmortem brains from individuals with ASD and controls and identified 60 circRNAs and three coregulated modules that were perturbed in ASD. By integrating circRNA, microRNA, and mRNA dysregulation data derived from the same cortex samples, we identified 8170 ASD-associated circRNA-microRNA-mRNA interactions. Putative targets of the axes were enriched for ASD risk genes and genes encoding inhibitory postsynaptic density (PSD) proteins, but not for genes implicated in monogenetic forms of other brain disorders or genes encoding excitatory PSD proteins. This reflects the previous observation that ASD-derived organoids show overproduction of inhibitory neurons. We further confirmed that some ASD risk genes (NLGN1, STAG1, HSD11B1, VIP, and UBA6) were regulated by an up-regulated circRNA (circARID1A) via sponging a down-regulated microRNA (miR-204-3p) in human neuronal cells. Particularly, alteration of NLGN1 expression is known to affect the dynamic processes of memory consolidation and strengthening. To the best of our knowledge, this is the first systems-level view of circRNA regulatory networks in ASD cortex samples. We provided a rich set of ASD-associated circRNA candidates and the corresponding circRNA-microRNA-mRNA axes, particularly those involving ASD risk genes. Our findings thus support a role for circRNA dysregulation and the corresponding circRNA-microRNA-mRNA axes in ASD pathophysiology.

Single-cell sperm transcriptomes and variants from fathers of children with and without autism spectrum disorder

The human sperm is one of the smallest cells in the body, but also one of the most important, as it serves as the entire paternal genetic contribution to a child. Investigating RNA and mutations in sperm is especially relevant for diseases such as autism spectrum disorders (ASD), which have been correlated with advanced paternal age. Historically, studies have focused on the assessment of bulk sperm, wherein millions of individual sperm are present and only high-frequency variants can be detected. Using 10× Chromium single-cell sequencing technology, we assessed the transcriptome from >65,000 single spermatozoa across six sperm donors (scSperm-RNA-seq), including two who fathered multiple children with ASD and four fathers of neurotypical children. Using RNA-seq methods for differential expression and variant analysis, we found clusters of sperm mutations in each donor that are indicative of the sperm being produced by different stem cell pools. Finally, we have shown that genetic variations can be found in single sperm.

Cell Therapy Targets for Autism Spectrum Disorders: Hopes, Challenges and Future Directions

Autism spectrum disorders as a group of pediatric neurodevelopmental diseases is a crucial part of the worldwide disabilities which have influence in communication skills, social interactions, and ability to understand the concepts. The precise pathophysiology of autism spectrum disorders due to the abundance of involved mechanisms is unknown. Some of these involved mechanisms are related to genetic factors, chronic neuro inflammation, mitochondrial dysfunction, oxidative stress, immune dysregulation, hormonal imbalance, and environmental factors. Current main treatments for autisms are behavioral, nutritional and medical therapies, however there is not definitive treatment approach. Therein, more novel therapies are still required to improve the symptoms. Several preclinical and clinical evidence were shown that stem cell therapy is a potential treatment option for autism spectrum disorders individuals. Considering the significant factors which can affect the outcome of stem cell therapeutic effects including stem cell types, route and dosage of administration, and mechanism of activity along with selecting best animal models can be very important in performing clinical trials.

Association of genes with phenotype in autism spectrum disorder

Autism spectrum disorder (ASD) is a genetic heterogeneous neurodevelopmental disorder that is characterized by impairments in social interaction and speech development and is accompanied by stereotypical behaviors such as body rocking, hand flapping, spinning objects, sniffing and restricted behaviors. The considerable significance of the genetics associated with autism has led to the identification of many risk genes for ASD used for the probing of ASD specificity and shared cognitive features over the past few decades. Identification of ASD risk genes helps to unravel various genetic variants and signaling pathways which are involved in ASD. This review highlights the role of ASD risk genes in gene transcription and translation regulation processes, as well as neuronal activity modulation, synaptic plasticity, disrupted key biological signaling pathways, and the novel candidate genes that play a significant role in the pathophysiology of ASD. The current emphasis on autism spectrum disorders has generated new opportunities in the field of neuroscience, and further advancements in the identification of different biomarkers, risk genes, and genetic pathways can help in the early diagnosis and development of new clinical and pharmacological treatments for ASD.

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.

Pathobiology of Christianson syndrome: Linking disrupted endosomal-lysosomal function with intellectual disability and sensory impairments

Christianson syndrome (CS) is a recently described rare neurogenetic disorder presenting early in life with a broad range of neurological symptoms, including severe intellectual disability with nonverbal status, hyperactivity, epilepsy, and progressive ataxia due to cerebellar atrophy. CS is due to loss-of-function mutations in SLC9A6, encoding NHE6, a sodium-hydrogen exchanger involved in the regulation of early endosomal pH. Here we review what is currently known about the neuropathogenesis of CS, based on insights from experimental models, which to date have focused on mechanisms that affect the CNS, specifically the brain. In addition, parental reports of sensory disturbances in their children with CS, including an apparent insensitivity to pain, led us to explore sensory function and related neuropathology in Slc9a6 KO mice. We present new data showing sensory deficits in Slc9a6 KO mice, which had reduced behavioral responses to noxious thermal and mechanical stimuli (Hargreaves and Von Frey assays, respectively) compared to wild type (WT) littermates. Immunohistochemical and ultrastructural analysis of the spinal cord and peripheral nervous system revealed intracellular accumulation of the glycosphingolipid GM2 ganglioside in KO but not WT mice. This cellular storage phenotype was most abundant in neurons of lamina I-II of the dorsal horn, a major relay site in the processing of painful stimuli. Spinal cords of KO mice also exhibited changes in astroglial and microglial populations throughout the gray matter suggestive of a neuroinflammatory process. Our findings establish the Slc9a6 KO mouse as a relevant tool for studying the sensory deficits in CS, and highlight selective vulnerabilities in relevant cell populations that may contribute to this phenotype. How NHE6 loss of function leads to such a multifaceted neurological syndrome is still undefined, and it is likely that NHE6 is involved with many cellular processes critical to normal nervous system development and function. In addition, the sensory issues exhibited by Slc9a6 KO mice, in combination with our neuropathological findings, are consistent with NHE6 loss of function impacting the entire nervous system. Sensory dysfunction in intellectually disabled individuals is challenging to assess and may impair patient safety and quality of life. Further mechanistic studies of the neurological impairments underlying CS and other genetic intellectual disability disorders must also take into account mechanisms affecting broader nervous system function in order to understand the full range of associated disabilities.

Biomarkers for Autism Spectrum Disorders (ASD): A Meta-analysis

OBJECTIVE

To compare the reported accuracy and sensitivity of the various modalities used to diagnose autism spectrum disorders (ASD) in efforts to help focus further biomarker research on the most promising methods for early diagnosis.

METHODS

The Medline scientific literature database was searched to identify publications assessing potential clinical ASD biomarkers. Reports were categorized by the modality used to assess the putative markers, including protein, genetic, metabolic, or objective imaging methods. The reported sensitivity, specificity, area under the curve, and overall agreement were summarized and analyzed to determine weighted averages for each diagnostic modality. Heterogeneity was measured using the I² test.

RESULTS

Of the 71 papers included in this analysis, each belonging to one of five modalities, protein-based followed by metabolite-based markers provided the highest diagnostic accuracy, each with a pooled overall agreement of 83.3% and respective weighted area under the curve (AUC) of 89.5% and 88.3%. Sensitivity provided by protein markers was highest (85.5%), while metabolic (85.9%) and protein markers (84.7%) had the highest specificity. Other modalities showed degrees of sensitivity, specificity, and overall agreements in the range of 73%-80%.

CONCLUSIONS

Each modality provided for diagnostic accuracy and specificity similar or slightly higher than those reported for the gold-standard Autism Diagnostic Observation Schedule (ADOS) instrument. Further studies are required to identify the most predictive markers within each modality and to evaluate biological pathways or clustering with possible etiological relevance. Analyses will also be necessary to determine the potential of these novel biomarkers in diagnosing pediatric patients, thereby enabling early intervention.

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.

Single-cell RNA sequencing of a European and an African lymphoblastoid cell line

In biomedical research, lymphoblastoid cell lines (LCLs), often established by in vitro infection of resting B cells with Epstein-Barr virus, are commonly used as surrogates for peripheral blood lymphocytes. Genomic and transcriptomic information on LCLs has been used to study the impact of genetic variation on gene expression in humans. Here we present single-cell RNA sequencing (scRNA-seq) data on GM12878 and GM18502—two LCLs derived from the blood of female donors of European and African ancestry, respectively. Cells from three samples (the two LCLs and a 1:1 mixture of the two) were prepared separately using a 10x Genomics Chromium Controller and deeply sequenced. The final dataset contained 7,045 cells from GM12878, 5,189 from GM18502, and 5,820 from the mixture, offering valuable information on single-cell gene expression in highly homogenous cell populations. This dataset is a suitable reference for population differentiation in gene expression at the single-cell level. Data from the mixture provide additional valuable information facilitating the development of statistical methods for data normalization and batch effect correction.

Design Type(s)	transcription profiling design • strain comparison design
Measurement Type(s)	transcription profiling assay
Technology Type(s)	RNA sequencing
Factor Type(s)	ancestry status • sex
Sample Characteristic(s)	GM12878 cell • GM18502 cell • immortal human peripheral vein-derived B cell line cell

Machine-accessible metadata file describing the reported data (ISA-Tab format)

Persistence of dysfunctional natural killer cells in adults with high-functioning autism spectrum disorders: stigma/consequence of unresolved early infectious events?

Background

Autism spectrum disorders (ASD) are characterized by abnormal neurodevelopment, genetic, and environmental risk factors, as well as immune dysfunctions. Several lines of evidence suggest alterations in innate immune responses in children with ASD. To address this question in adults with high-functioning ASD (hf-ASD), we sought to investigate the role of natural killer (NK) cells in the persistence of ASD.

Methods

NK cells from 35 adults with hf-ASD were compared to that of 35 healthy controls (HC), selected for the absence of any immune dysfunctions, at different time-points, and over a 2-year follow-up period for four patients. The phenotype and polyfunctional capacities of NK cells were explored according to infectious stigma and clinical parameters (IQ, social, and communication scores).

Results

As compared to HC, NK cells from patients with hf-ASD showed a high level of cell activation (p < 0.0001), spontaneous degranulation (p < 0.0001), and interferon-gamma production (p = 0.0004), whereas they were exhausted after in vitro stimulations (p = 0.0006). These data yielded a specific HLA-DR⁺KIR2DL1⁺NKG2C⁺ NK-cell signature. Significant overexpression of NKG2C in hf-ASD patients (p = 0.0005), indicative of viral infections, was inversely correlated with the NKp46 receptor level (r = − 0.67; p < 0.0001), regardless of the IgG status of tested pathogens. Multivariate linear regression analysis also revealed that expression of the late-activating HLA-DR marker was both associated with structural language (r = 0.48; p = 0.007) and social awareness (r = 0.60; p = 0.0007) scores in adult patients with hf-ASD, while KIR2DL1 expression correlated with IQ scores (p = 0.0083).

Conclusions

This study demonstrates that adults with hf-ASD have specific NK-cell profile. Presence of NKG2C overexpression together with high-level activation of NK cells suggest an association with underlying pathogens, a hypothesis warranting further exploration in future studies.

Electronic supplementary material

The online version of this article (10.1186/s13229-019-0269-1) contains supplementary material, which is available to authorized users.

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.

Glutamate, Glutamine and GABA Levels in Rat Brain Measured Using MRS, HPLC and NMR Methods in Study of Two Models of Autism

The disorders of the glutamatergic neurotransmission have been associated with pathogenesis of autism. In this study we evaluated the impact of the in vivo and ex vivo test methodology on measurements of levels of neurotransmitter amino acids in hippocampus of rats for valproic acid- (VPA) and thalidomide- (THAL) induced models of autism. The main goal was to compare the changes in concentrations of glutamate (Glu), glutamine (Gln) and GABA between both autistic groups and the control, measured in vivo and ex vivo in homogenates. The rat pups underwent three in vivo tests: ultrasonic vocalization (USV), magnetic resonance spectroscopy (MRS) and unilateral microdialysis of the hippocampus. Analyses of homogenates of rat hippocampus were performed using high-performance liquid chromatography (HPLC) and nuclear magnetic resonance (NMR) spectroscopy. For the statistical analysis, we performed univariate and multivariate tests. USV test, which is considered in rodents as an indicator of pathology similar to autism, showed decreased USV in VPA and THAL groups. In vivo MRS studies demonstrated increases of Glu content in male rat's hippocampus in VPA and THAL groups, while the microdialysis, which allows examination of the contents in the extracellular space, detected decreases in the basal level of Gln concentrations in VPA and THAL groups. Ex vivo HPLC studies showed that levels of Glu, Gln and GABA significantly increased in male rat's hippocampus in the VPA and THAL groups, while NMR studies showed increased levels of Gln and GABA in the VPA group. Collectively, these results are consistent with the hypothesis suggesting the role of the glutamatergic disturbances on the pathogenesis of autism. For all methods used, the values of measured changes were in the same direction. The orthogonal partial least square discriminant analysis confirmed that both animal models of autism tested here can be used to trace neurochemical changes in the brain.

Brain Connectivity and Neuroimaging of Social Networks in Autism

Impairments in social communication (SC) predominate among the core diagnostic features of autism spectrum disorders (ASDs). Neuroimaging has revealed numerous findings of atypical activity and connectivity of 'social brain' networks, yet no consensus view on crucial developmental causes of SC deficits has emerged. Aside from methodological challenges, the deeper problem concerns the clinical label of ASD. While genetic studies have not comprehensively explained the causes of nonsyndromic ASDs, they highlight that the clinical label encompasses many etiologically different disorders. The question of how potential causes and etiologies converge onto a comparatively narrow set of SC deficits remains. Only neuroimaging designs searching for subtypes within ASD cohorts (rather than conventional group level designs) can provide translationally informative answers.

Developmental protein kinase C hyper-activation results in microcephaly and behavioral abnormalities in zebrafish

Susceptible genetic polymorphisms and altered expression levels of protein kinase C (PKC)-encoding genes suggest overactivation of PKC in autism spectrum disorder (ASD) development. To delineate the pathological role of PKC, we pharmacologically stimulated its activity during the early development of zebrafish. Results demonstrated that PKC hyper-activation perturbs zebrafish development and induces a long-lasting head size deficit. The anatomical and cellular analysis revealed reduced neural precursor proliferation and newborn neuron formation. β-Catenin that is essential for brain growth is dramatically degraded. Stabilization of β-catenin by gsk3β inhibition partially restores the head size deficit. In addition, the neuropathogenic effect of developmental PKC hyper-activation was further supported by the alterations in the behavioral domain including motor abnormalities, heightened stress reactivity and impaired habituation learning. Taken together, by causally connecting early-life PKC hyper-activation to these neuropathological traits and the impaired neurogenesis, these results suggest that PKC could be a critical pathway in ASD pathogenesis.

The evolution of a series of behavioral traits is associated with autism-risk genes in cavefish

Background

An essential question in evolutionary biology is whether shifts in a set of polygenic behaviors share a genetic basis across species. Such a behavioral shift is seen in the cave-dwelling Mexican tetra, Astyanax mexicanus. Relative to surface-dwelling conspecifics, cavefish do not school (asocial), are hyperactive and sleepless, adhere to a particular vibration stimulus (imbalanced attention), behave repetitively, and show elevated stress hormone levels. Interestingly, these traits largely overlap with the core symptoms of human autism spectrum disorder (ASD), raising the possibility that these behavioral traits are underpinned by a similar set of genes (i.e. a repeatedly used suite of genes).

Result

Here, we explored whether modification of ASD-risk genes underlies cavefish evolution. Transcriptomic analyses revealed that > 58.5% of 3152 cavefish orthologs to ASD-risk genes are significantly up- or down-regulated in the same direction as genes in postmortem brains from ASD patients. Enrichment tests suggest that ASD-risk gene orthologs in A. mexicanus have experienced more positive selection than other genes across the genome. Notably, these positively selected cavefish ASD-risk genes are enriched for pathways involved in gut function, inflammatory diseases, and lipid/energy metabolism, similar to symptoms that frequently coexist in ASD patients. Lastly, ASD drugs mitigated cavefish’s ASD-like behaviors, implying shared aspects of neural processing.

Conclusion

Overall, our study indicates that ASD-risk genes and associated pathways (especially digestive, immune and metabolic pathways) may be repeatedly used for shifts in polygenic behaviors across evolutionary time.

Electronic supplementary material

The online version of this article (10.1186/s12862-018-1199-9) contains supplementary material, which is available to authorized users.