Predicting the diagnosis of autism spectrum disorder using gene pathway analysis

Atypical dynamic neural configuration in autism spectrum disorder and its relationship to gene expression profiles

Although it is well recognized that autism spectrum disorder (ASD) is associated with atypical dynamic functional connectivity patterns, the dynamic changes in brain intrinsic activity over each time point and the potential molecular mechanisms associated with atypical dynamic temporal characteristics in ASD remain unclear. Here, we employed the Hidden Markov Model (HMM) to explore the atypical neural configuration at every scanning time point in ASD, based on resting-state functional magnetic resonance imaging (rs-fMRI) data from the Autism Brain Imaging Data Exchange. Subsequently, partial least squares regression and pathway enrichment analysis were employed to explore the potential molecular mechanism associated with atypical neural dynamics in ASD. 8 HMM states were inferred from rs-fMRI data. Compared to typically developing, individuals on the autism spectrum showed atypical state-specific temporal characteristics, including number of states and occurrences, mean life time and transition probability between states. Moreover, these atypical temporal characteristics could predict communication difficulties of ASD, and states assoicated with negative activation in default mode network and frontoparietal network, and positive activation in somatomotor network, ventral attention network, and limbic network, had higher predictive contribution. Furthermore, a total of 321 genes was revealed to be significantly associated with atypical dynamic brain states of ASD, and these genes are mainly enriched in neurodevelopmental pathways. Our study provides new insights into characterizing the atypical neural dynamics from a moment-to-moment perspective, and indicates a linkage between atypical neural configuration and gene expression in ASD.

Metabotropic glutamate receptor genetic variants and peripheral receptor expression affects trait scores of autistic probands

Glutamate (Glu) is important for memory and learning. Hence, Glu imbalance is speculated to affect autism spectrum disorder (ASD) pathophysiology. The action of Glu is mediated through receptors and we analyzed four metabotropic Glu receptors (mGluR/GRM) in Indo-Caucasoid families with ASD probands and controls. The trait scores of the ASD probands were assessed using the Childhood Autism Rating Scale2-ST. Peripheral blood was collected, genomic DNA isolated, and GRM5 rs905646, GRM6 rs762724 & rs2067011, and GRM7 rs3792452 were analyzed by PCR/RFLP or Taqman assay. Expression of mGluRs was measured in the peripheral blood by qPCR. Significantly higher frequencies of rs2067011 'A' allele/ AA' genotype were detected in the probands. rs905646 'A 'exhibited significantly higher parental transmission. Genetic variants showed independent as well as interactive effects in the probands. Receptor expression was down-regulated in the probands, especially in the presence of rs905646 'AA', rs762724 'TT', rs2067011 'GG', and rs3792452 'CC'. Trait scores were higher in the presence of rs762724 'T' and rs2067011 'G'. Therefore, in the presence of risk genetic variants, down-regulated mGluR expression may increase autistic trait scores. Since our investigation was confined to the peripheral system, in-depth exploration involving peripheral as well as central nervous systems may validate our observation.

Genomic Machine Learning Meta-regression: Insights on Associations of Study Features With Reported Model Performance

Many studies have been conducted with the goal of correctly predicting diagnostic status of a disorder using the combination of genomic data and machine learning. It is often hard to judge which components of a study led to better results and whether better reported results represent a true improvement or an uncorrected bias inflating performance. We extracted information about the methods used and other differentiating features in genomic machine learning models. We used these features in linear regressions predicting model performance. We tested for univariate and multivariate associations as well as interactions between features. Of the models reviewed, 46% used feature selection methods that can lead to data leakage. Across our models, the number of hyperparameter optimizations reported, data leakage due to feature selection, model type, and modeling an autoimmune disorder were significantly associated with an increase in reported model performance. We found a significant, negative interaction between data leakage and training size. Our results suggest that methods susceptible to data leakage are prevalent among genomic machine learning research, resulting in inflated reported performance. Best practice guidelines that promote the avoidance and recognition of data leakage may help the field avoid biased results.

Molecular and in silico analyses of SYN III gene variants in autism spectrum disorder

BACKGROUND

Defects in neurotransmission and synaptogenesis are noteworthy in the pathogenesis of ASD. Synapsin III (SYN III) is defined as a synaptic vesicle protein that plays an important role in synaptogenesis and regulation of neurotransmitter release and neurite outgrowth. Therefore, SYN III may associate with many neurodevelopmental diseases, including ASD.

AIM

The aim of this study was to investigate whether the SYN III gene -631 C > G (rs133946) and -196 G > A (rs133945) polymorphisms are associated with susceptibility to ASD.

METHODS

SYN III variants and the risk of ASD were investigated in 26 healthy children and 24 ASD children. SYN III gene variants were genotyped by PCR-RFLP methods. The differences in genotype and allele frequencies between the ASD and control groups were calculated using the chi-square (χ2). We analysed the SYN III gene using web-based tools.

RESULTS

Our results suggest that the presence of the AA genotype of the SYN III -196 G > A (rs133945) polymorphism affects the characteristics and development of ASD in children (p = 0.012). SYN III -631 C > G (rs133946) polymorphism was not associated with ASD (p = 0.524). We have shown the prediction of gene-gene interaction that SYN III is co-expressed with 17 genes, physical interaction with 3 genes, and co-localization with 12 genes. The importance of different genes (SYN I, II, III, GABRD, NOS1AP, GNAO1) for ASD pathogenesis was revealed by GO analysis.

CONCLUSION

Considering the role of SYN III and related genes, especially in the synaptic vesicle pathway and neurotransmission, its effect on ASD can be further investigated.

Glutamate receptor genetic variants affected peripheral glutamatergic transmission and treatment induced improvement of Indian ADHD probands

Attention deficit hyperactivity disorder (ADHD), a childhood-onset neurobehavioral disorder, often perturbs scholastic achievement and peer-relationship. The pivotal role of glutamate (Glu) in learning and memory indicated an influence of Glu in ADHD, leading to the exploration of Glu in different brain regions of ADHD subjects. We for the first time analyzed GluR genetic variations, Glu levels, as well as expression of Glu receptors (GluR) in the peripheral blood of eastern Indian ADHD probands to find out the relevance of Glu in ADHD prognosis. After obtaining informed written consent for participation, peripheral blood was collected for analyzing the genetic variants, Glu level, and expression of target genes. Since ADHD probands are often treated with methylphenidate or atomoxetine for providing symptomatic remediation, we have also tested post-therapeutic improvement in the ADHD trait scores in the presence of different GluR genotypes. Two variants, GRM7 rs3749380 "T" and GRIA1 rs2195450 "C", exhibited associations with ADHD (P ≤ 0.05). A few GluR genetic variants showed significant association with higher trait severity, low IQ, lower plasma Glu level, down-regulated GluR mRNA expression, and poor response to medications. This indicates that down-regulated glutamatergic system may have an effect on ADHD etiology and treatment efficacy warranting further in-depth investigation.

A study of genetic heterogeneity in autism spectrum disorders based on plasma proteomic and metabolomic analysis: multiomics study of autism heterogeneity

Genetic heterogeneity poses a challenge to research and clinical translation of autism spectrum disorder (ASD). In this study, we conducted a plasma proteomic and metabolomic study of children with ASD with and without risk genes (de novo mutation) and controls to explore the impact of genetic heterogeneity on the search for biomarkers for ASD. In terms of the proteomic and metabolomic profiles, the groups of children with ASD carrying and those not carrying de novo mutation tended to cluster and overlap, and integrating them yielded differentially expressed proteins and differential metabolites that effectively distinguished ASD from controls. The mechanisms associated with them focus on several common and previously reported mechanisms. Proteomics results highlight the role of complement, inflammation and immunity, and cell adhesion. The main pathways of metabolic perturbations include amino acid, vitamin, glycerophospholipid, tryptophan, and glutamates metabolic pathways and solute carriers-related pathways. Integrating the two omics analyses revealed that L-glutamic acid and malate dehydrogenase may play key roles in the pathogenesis of ASD. These results suggest that children with ASD may have important underlying common mechanisms. They are not only potential therapeutic targets for ASD but also important contributors to the study of biomarkers for the disease.

Inhibition of TREM-1 Ameliorates Lipopolysaccharide-induced Depressive-like Behaviors by Alleviating Neuroinflammation in the PFC via PI3K/Akt Signaling Pathway

Neuroinflammation is closely related to depression and is a key pathophysiological process of depression. Triggering receptor expressed on myeloid cells 1 (TREM-1) has been proven to exert proinflammatory effects in various diseases. However, the role of TREM-1 in depression has not been elucidated. Thus, we hypothesized that TREM-1 inhibition might have protective effects in depression. Here, lipopolysaccharide (LPS) was used to induce depressive-like behaviors in mice, LP17 was treated to inhibit TREM-1, and LY294002 was administrated to inhibit phosphatidylinositol 3-kinase (PI3K) which is one of the downstream of TREM-1. Physical and neurobehavioral tests, Western blot analysis, and immunofluorescence staining were performed in this study. We found that LPS caused significant depressive-like behaviors in mice, including body weight decline, anodynia (sucrose preference decrease), lack of locomotor activity, and desperation in tail suspension test (TST) and forced swimming test (FST). Next, we revealed that TREM-1 was expressed on microglia, neurons, and astrocytes in the prefrontal cortex (PFC) after LPS administration. TREM-1 inhibition by LP17 suppressed the expression of TREM-1 in the PFC. In addition, LP17 could alleviate neuroinflammation and microglial activation in the PFC. Meanwhile, LP17 could prevent damage of LPS to neuronal primary cilia and neuronal activity. Finally, we revealed that PI3K/Akt might exert crucial role in the protective effects of TREM-1 inhibition to depressive-like behaviors induced by LPS. Taken together, TREM-1 inhibition by LP17 could alleviate depressive-like behaviors induced by LPS by mitigating neuroinflammation in the PFC via PI3K/Akt signaling pathway. Finally, we demonstrated that TREM-1 might be a promising therapeutic target for treatment of depression.

Case Report: Clinical delineation of CACNA1D mutation: New cases and literature review

Background

Calcium ions are involved in several human cellular processes; nevertheless, the relationship between calcium channelopathies (CCs) and autism spectrum disorder (ASD) or intellectual disability (ID) has been previously investigated. We delineate the spectrum of clinical phenotypes and the symptoms associated with a syndrome caused by an inherited gain-of-function mutation in CACNA1D in a family with a history of neuropsychiatric disorders. We also review the clinical and molecular phenotype of previously reported variants of CACNA1D.

Case presentation

We report the case of a 9-year-old female patient, diagnosed with ASD, severe ID, hyperactivity, and aggressive impulsive behaviors. The father, who was a 65-year-old at the time of his death, had ID and developed major depressive disorder with catatonic features and nihilistic delusion, followed by rapidly progressive dementia. He died after experiencing prolonged seizures followed by post-cardiac arrest. The patient's sister was a 30-year-old woman, known to have a severe ID with aggressive behaviors and sleep disorders. The sister has been diagnosed with bipolar disorder and psychosis. Through whole exome sequencing, a heterozygous previously identified and functionally characterized missense likely pathogenic variant was identified in the CACNA1D gene NM_001128840.3: c.2015C > T (p.Ser672Leu). These findings are consistent with the genetic diagnosis of autosomal dominant primary aldosteronism, seizures, and neurological abnormalities. This variant was found in the heterozygous status in the patient, her father, and her affected sister.

Conclusion

This case report will help to determine the key clinical features of this syndrome, which exhibits variable clinical presentations.

Advanced theragnostics for the central nervous system (CNS) and neurological disorders using functional inorganic nanomaterials

Various types of inorganic nanomaterials are capable of diagnostic biomarker detection and the therapeutic delivery of a disease or inflammatory modulating agent. Those multi-functional nanomaterials have been utilized to treat neurodegenerative diseases and central nervous system (CNS) injuries in an effective and personalized manner. Even though many nanomaterials can deliver a payload and detect a biomarker of interest, only a few studies have yet to fully utilize this combined strategy to its full potential. Combining a nanomaterial's ability to facilitate targeted delivery, promote cellular proliferation and differentiation, and carry a large amount of material with various sensing approaches makes it possible to diagnose a patient selectively and sensitively while offering preventative measures or early disease-modifying strategies. By tuning the properties of an inorganic nanomaterial, the dimensionality, hydrophilicity, size, charge, shape, surface chemistry, and many other chemical and physical parameters, different types of cells in the central nervous system can be monitored, modulated, or further studies to elucidate underlying disease mechanisms. Scientists and clinicians have better understood the underlying processes of pathologies for many neurologically related diseases and injuries by implementing multi-dimensional 0D, 1D, and 2D theragnostic nanomaterials. The incorporation of nanomaterials has allowed scientists to better understand how to detect and treat these conditions at an early stage. To this end, having the multi-modal ability to both sense and treat ailments of the central nervous system can lead to favorable outcomes for patients suffering from such injuries and diseases.

Pathophysiological Roles of Auxiliary Calcium Channel α2δ Subunits

α2δ proteins serve as auxiliary subunits of voltage-gated calcium channels, which are essential components of excitable cells such as skeletal and heart muscles, nerve cells of the brain and the peripheral nervous system, as well as endocrine cells. Over the recent years, α2δ proteins have been identified as critical regulators of synaptic functions, including the formation and differentiation of synapses. These functions require signalling mechanisms which are partly independent of calcium channels. Hence, in light of these features it is not surprising that the genes encoding for the four α2δ isoforms have recently been linked to neurological and neurodevelopmental disorders including epilepsy, autism spectrum disorders, schizophrenia, and depressive and bipolar disorders. Despite the increasing number of identified disease-associated mutations, the underlying pathophysiological mechanisms are only beginning to emerge. However, a thorough understanding of the pathophysiological role of α2δ proteins ideally serves two purposes: first, it will contribute to our understanding of general pathological mechanisms in synaptic disorders. Second, it may support the future development of novel and specific treatments for brain disorders. In this context, it is noteworthy that the antiepileptic and anti-allodynic drugs gabapentin and pregabalin both act via binding to α2δ proteins and are among the top sold drugs for treating neuropathic pain. In this book chapter, we will discuss recent developments in our understanding of the functions of α2δ proteins, both as calcium channel subunits and as independent regulatory entities. Furthermore, we present and summarize recently identified and likely pathogenic mutations in the genes encoding α2δ proteins and discuss potential underlying pathophysiological consequences at the molecular and structural level.

Association between Downstream Taste Signaling Genes, Oral Microbiome, and Severe Early Childhood Caries

Polymorphisms in taste receptor genes have been shown to play a role in early childhood caries (ECC), a multifactorial, biofilm-mediated disease. This study aimed to evaluate associations between severe-ECC (S-ECC), the oral microbiome, and variants in genes that encode components of the G protein-coupled receptor (GPCR) signaling cascade involved in taste sensation. A total of 176 children (88 caries-free; 88 with S-ECC) were recruited. Analyses of 16S and ITS1 rRNA microbial genes and seven (GNAQ, GNAS, GNAT3, GNAI2, RAC1, RALB, and PLCB2) human genes were pursued using next-generation sequencing. Regression analyses were performed to evaluate associations between genetic variants, S-ECC, and the supragingival plaque microbiome. Results suggest that PLCB2 rs2305645 (T), rs1869901 (G), and rs2305649 (G) alleles had a protective effect on S-ECC (rs2305645, odds ratio (OR) = 0.27 (95% confidence interval (CI): 0.14-0.51); rs1869901, OR = 0.34 (95% CI: 0.20-0.58); and rs2305649, OR = 0.43 (95% CI: 0.26-0.71)). Variants in GNAQ, GNAS, GNAT3, PLCB2, RALB, and RAC1 were associated with oral fungal and bacterial community composition. This study revealed that three loci at PLCB2 are significantly associated with S-ECC. Variants in multiple genes were associated with the composition of dental biofilm. These findings contribute to the current knowledge about the role of genetics in S-ECC.

Gene×environment interactions in autism spectrum disorders

There is credible evidence that environmental factors influence individual risk and/or severity of autism spectrum disorders (hereafter referred to as autism). While it is likely that environmental chemicals contribute to the etiology of autism via multiple mechanisms, identifying specific environmental factors that confer risk for autism and understanding how they contribute to the etiology of autism has been challenging, in part because the influence of environmental chemicals likely varies depending on the genetic substrate of the exposed individual. Current research efforts are focused on elucidating the mechanisms by which environmental chemicals interact with autism genetic susceptibilities to adversely impact neurodevelopment. The goal is to not only generate insights regarding the pathophysiology of autism, but also inform the development of screening platforms to identify specific environmental factors and gene×environment (G×E) interactions that modify autism risk. Data from such studies are needed to support development of intervention strategies for mitigating the burden of this neurodevelopmental condition on individuals, their families and society. In this review, we discuss environmental chemicals identified as putative autism risk factors and proposed mechanisms by which G×E interactions influence autism risk and/or severity using polychlorinated biphenyls (PCBs) as an example.

Genetic ablation of metabotropic glutamate receptor 5 in rats results in an autism-like behavioral phenotype

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by deficits in communication, and social skills, as well as repetitive and/or restrictive interests and behaviors. The severity of ASD varies from mild to severe, drastically interfering with the quality of life of affected individuals. The current occurrence of ASD in the United States is about 1 in 44 children. The precise pathophysiology of ASD is still unknown, but it is believed that ASD is heterogeneous and can arise due to genetic etiology. Although various genes have been implicated in predisposition to ASD, metabotropic glutamate receptor 5 (mGluR5) is one of the most common downstream targets, which may be involved in autism. mGluR5 signaling has been shown to play a crucial role in neurodevelopment and neural transmission making it a very attractive target for understanding the pathogenesis of ASD. In the present study, we determined the effect of genetic ablation of mGluR5 (Grm5) on an ASD-like phenotype using a rat model to better understand the role of mGluR5 signaling in behavior patterns and clinical manifestations of ASD. We observed that mGluR5 Ko rats exhibited exaggerated self-grooming and increased marble burying, as well as deficits in social novelty. Our results suggest that mGluR5 Ko rats demonstrate an ASD-like phenotype, specifically impaired social interaction as well as repetitive and anxiety-like behavior, which are correlates of behavior symptoms observed in individuals with ASD. The mGluR5 Ko rat model characterized in this study may be explored to understand the molecular mechanisms underlying ASD and for developing effective therapeutic modalities.

Modern Biomarkers for Autism Spectrum Disorder: Future Directions

Autism spectrum disorder is an increasingly prevalent neurodevelopmental disorder in the world today, with an estimated 2% of the population being affected in the USA. A major complicating factor in diagnosing, treating, and understanding autism spectrum disorder is that defining the disorder is solely based on the observation of behavior. Thus, recent research has focused on identifying specific biological abnormalities in autism spectrum disorder that can provide clues to diagnosis and treatment. Biomarkers are an objective way to identify and measure biological abnormalities for diagnostic purposes as well as to measure changes resulting from treatment. This current opinion paper discusses the state of research of various biomarkers currently in development for autism spectrum disorder. The types of biomarkers identified include prenatal history, genetics, neurological including neuroimaging, neurophysiologic, and visual attention, metabolic including abnormalities in mitochondrial, folate, trans-methylation, and trans-sulfuration pathways, immune including autoantibodies and cytokine dysregulation, autonomic nervous system, and nutritional. Many of these biomarkers have promising preliminary evidence for prenatal and post-natal pre-symptomatic risk assessment, confirmation of diagnosis, subtyping, and treatment response. However, most biomarkers have not undergone validation studies and most studies do not investigate biomarkers with clinically relevant comparison groups. Although the field of biomarker research in autism spectrum disorder is promising, it appears that it is currently in the early stages of development.

Inhibitory effects on L- and N-type calcium channels by a novel CaVβ1 variant identified in a patient with autism spectrum disorder

Voltage-gated calcium channel (VGCC) subunits have been genetically associated with autism spectrum disorders (ASD). The properties of the pore-forming VGCC subunit are modulated by auxiliary β-subunits, which exist in four isoforms (Ca_Vβ_1-4). Our previous findings suggested that activation of L-type VGCCs is a common feature of Ca_Vβ₂ subunit mutations found in ASD patients. In the current study, we functionally characterized a novel Ca_Vβ_1b variant (p.R296C) identified in an ASD patient. We used whole-cell and single-channel patch clamp to study the effect of Ca_Vβ_{1b_R296C} on the function of L- and N-type VGCCs. Furthermore, we used co-immunoprecipitation followed by Western blot to evaluate the interaction of the Ca_Vβ_1b-subunits with the RGK-protein Gem. Our data obtained at both, whole-cell and single-channel levels, show that compared to a wild-type Ca_Vβ_1b, the Ca_Vβ_{1b_R296C} variant inhibits L- and N-type VGCCs. Interaction with and modulation by the RGK-protein Gem seems to be intact. Our findings indicate functional effects of the Ca_Vβ_{1b_R296C} variant differing from that attributed to Ca_Vβ₂ variants found in ASD patients. Further studies have to detail the effects on different VGCC subtypes and on VGCC expression.

A novel chemo-phenotypic method identifies mixtures of salpn, vitamin D3, and pesticides involved in the development of colorectal and pancreatic cancer

Environmental chemical (EC) exposures and our interactions with them has significantly increased in the recent decades. Toxicity associated biological characterization of these chemicals is challenging and inefficient, even with available high-throughput technologies. In this report, we describe a novel computational method for characterizing toxicity, associated biological perturbations and disease outcome, called the Chemo-Phenotypic Based Toxicity Measurement (CPTM). CPTM is used to quantify the EC "toxicity score" (Z_ts), which serves as a holistic metric of potential toxicity and disease outcome. CPTM quantitative toxicity is the measure of chemical features, biological phenotypic effects, and toxicokinetic properties of the ECs. For proof-of-concept, we subject ECs obtained from the Environmental Protection Agency's (EPA) database to the CPTM. We validated the CPTM toxicity predictions by correlating 'Z_ts' scores with known toxicity effects. We also confirmed the CPTM predictions with in-vitro, and in-vivo experiments. In in-vitro and zebrafish models, we showed that, mixtures of the motor oil and food additive 'Salpn' with endogenous nuclear receptor ligands such as Vitamin D3, dysregulated the nuclear receptors and key transcription pathways involved in Colorectal Cancer. Further, in a human patient derived cell organoid model, we found that a mixture of the widely used pesticides 'Tetramethrin' and 'Fenpropathrin' significantly impacts the population of patient derived pancreatic cancer cells and 3D organoid models to support rapid PDAC disease progression. The CPTM method is, to our knowledge, the first comprehensive toxico-physicochemical, and phenotypic bionetwork-based platform for efficient high-throughput screening of environmental chemical toxicity, mechanisms of action, and connection to disease outcomes.

iTRAQ-Based Proteomics Analysis of Rat Cerebral Cortex Exposed to Valproic Acid before Delivery

Autism spectrum disorder (ASD) is a neurological and developmental disorder characterized by social and communication difficulties. Valproic acid (VPA) injection during pregnancy elicits autism-like behavior in the offspring, making it a classic animal model of ASD. However, the mechanisms involved have not yet been determined. In this study, we used iTRAQ (isobaric tags for relative and absolute quantification) proteomics analysis of the cerebral cortex of a VPA rat model (VPA group) and controls (CON group). The results showed that 79 differentially expressed proteins (DEPs) were identified between the VPA group and the CON group. Based on bioinformatics analysis, the DEPs were mainly enriched at synapses, especially glutamatergic synapses and GABAergic synapses. Some DEPs were involved in energy metabolism, thyroid hormone synthesis pathway, and Na⁺-K⁺-ATPase. Cytoskeleton and endoplasmic reticulum (ER) stress-related proteins were also involved. Some DEPs matched either the ASD gene database or previous reports on cerebral cortical transcriptome studies in VPA rat models. Dysregulation of these DEPs in the cerebral cortex of VPA rats may be responsible for autism-like behavior in rats. We also found that some DEPs were associated with neuropsychiatric disorders, implying that these diseases share common signaling pathways and mechanisms. Moreover, increased expression of DEPs was associated with energy metabolism in the cerebral cortex of VPA rats, implying that ASD may be a distinct type of mitochondrial dysfunction that requires further investigation.

Navigating the pitfalls of applying machine learning in genomics

The scale of genetic, epigenomic, transcriptomic, cheminformatic and proteomic data available today, coupled with easy-to-use machine learning (ML) toolkits, has propelled the application of supervised learning in genomics research. However, the assumptions behind the statistical models and performance evaluations in ML software frequently are not met in biological systems. In this Review, we illustrate the impact of several common pitfalls encountered when applying supervised ML in genomics. We explore how the structure of genomics data can bias performance evaluations and predictions. To address the challenges associated with applying cutting-edge ML methods to genomics, we describe solutions and appropriate use cases where ML modelling shows great potential.

Gene Regulation Analysis Reveals Perturbations of Autism Spectrum Disorder during Neural System Development

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that impedes patients' cognition, social, speech and communication skills. ASD is highly heterogeneous with a variety of etiologies and clinical manifestations. The prevalence rate of ASD increased steadily in recent years. Presently, molecular mechanisms underlying ASD occurrence and development remain to be elucidated. Here, we integrated multi-layer genomics data to investigate the transcriptome and pathway dysregulations in ASD development. The RNA sequencing (RNA-seq) expression profiles of induced pluripotent stem cells (iPSCs), neural progenitor cells (NPCs) and neuron cells from ASD and normal samples were compared in our study. We found that substantially more genes were differentially expressed in the NPCs than the iPSCs. Consistently, gene set variation analysis revealed that the activity of the known ASD pathways in NPCs and neural cells were significantly different from the iPSCs, suggesting that ASD occurred at the early stage of neural system development. We further constructed comprehensive brain- and neural-specific regulatory networks by incorporating transcription factor (TF) and gene interactions with long 5 non-coding RNA(lncRNA) and protein interactions. We then overlaid the transcriptomes of different cell types on the regulatory networks to infer the regulatory cascades. The variations of the regulatory cascades between ASD and normal samples uncovered a set of novel disease-associated genes and gene interactions, particularly highlighting the functional roles of ELF3 and the interaction between STAT1 and lncRNA ELF3-AS 1 in the disease development. These new findings extend our understanding of ASD and offer putative new therapeutic targets for further studies.

A PheWAS Model of Autism Spectrum Disorder

Children with Autism Spectrum Disorder (ASD) exhibit a wide diversity in type, number, and severity of social deficits as well as communicative and cognitive difficulties. It is a challenge to categorize the phenotypes of a particular ASD patient with their unique genetic variants. There is a need for a better understanding of the connections between genotype information and the phenotypes to sort out the heterogeneity of ASD. In this study, single nucleotide polymorphism (SNP) and phenotype data obtained from a simplex ASD sample are combined using a PheWAS-inspired approach to construct a phenotype-phenotype network. The network is clustered, yielding groups of etiologically related phenotypes. These clusters are analyzed to identify relevant genes associated with each set of phenotypes. The results identified multiple discriminant SNPs associated with varied phenotype clusters such as ASD aberrant behavior (self-injury, compulsiveness and hyperactivity), as well as IQ and language skills. Overall, these SNPs were linked to 22 significant genes. An extensive literature search revealed that eight of these are known to have strong evidence of association with ASD. The others have been linked to related disorders such as mental conditions, cognition, and social functioning.Clinical relevance- This study further informs on connections between certain groups of ASD phenotypes and their unique genetic variants. Such insight regarding the heterogeneity of ASD would support clinicians to advance more tailored interventions and improve outcomes for ASD patients.

Family-Based Cohort Association Study of PRKCB1, CBLN1 and KCNMB4 Gene Polymorphisms and Autism in Polish Population

The aim of the study was to perform family-based association analysis of PRKCB1, CBLN1 and KCNMB4 gene polymorphisms and autism disorder. We comprised 206 Caucasian children with autistic spectrum disorder (ASD) and their biological parents. In transmission/disequilibrium test we observed that T-allele of the rs198198 polymorphism of the PRKCB1 gene was more often transmitted to affected children in the male subgroup (p = 0.010). Additionally, the T carrier state was significantly associated with hypotonia (p = 0.048). In the female subgroup, the T-allele carriers more often showed more mobile/vital behavior (p = 0.046). In conclusion, our study showed that the rs198198 of the PRKCB1 gene may be associated with ASD in men and with some features characteristic for the disorder.

FMR1 and Autism, an Intriguing Connection Revisited

Autism Spectrum Disorder (ASD) represents a distinct phenotype of behavioral dysfunction that includes deficiencies in communication and stereotypic behaviors. ASD affects about 2% of the US population. It is a highly heritable spectrum of conditions with substantial genetic heterogeneity. To date, mutations in over 100 genes have been reported in association with ASD phenotypes. Fragile X syndrome (FXS) is the most common single-gene disorder associated with ASD. The gene associated with FXS, FMR1 is located on chromosome X. Accordingly, the condition has more severe manifestations in males. FXS results from the loss of function of FMR1 due to the expansion of an unstable CGG repeat located in the 5'' untranslated region of the gene. About 50% of the FXS males and 20% of the FXS females meet the Diagnostic Statistical Manual 5 (DSM-5) criteria for ASD. Among the individuals with ASD, about 3% test positive for FXS. FMRP, the protein product of FMR1, is a major gene regulator in the central nervous system. Multiple pathways regulated by FMRP are found to be dysfunctional in ASD patients who do not have FXS. Thus, FXS presents the opportunity to study cellular phenomena that may have wider applications in the management of ASD and to develop new strategies for ASD therapy.

Predicting the Risk Genes of Autism Spectrum Disorders

Autism spectrum disorder (ASD) refers to a wide spectrum of neurodevelopmental disorders that emerge during infancy and continue throughout a lifespan. Although substantial efforts have been made to develop therapeutic approaches, core symptoms persist lifelong in ASD patients. Identifying the brain temporospatial regions where the risk genes are expressed in ASD patients may help to improve the therapeutic strategies. Accordingly, this work aims to predict the risk genes of ASD and identify the temporospatial regions of the brain structures at different developmental time points for exploring the specificity of ASD gene expression in the brain that would help in possible ASD detection in the future. A dataset consisting of 13 developmental stages ranging from 8 weeks post-conception to 8 years from 26 brain structures was retrieved from the BrainSpan atlas. This work proposes a support vector machine–based risk gene prediction method ASD-Risk to distinguish the risk genes of ASD and non-ASD genes. ASD-Risk used an optimal feature selection algorithm called inheritable bi-objective combinatorial genetic algorithm to identify the brain temporospatial regions for prediction of the risk genes of ASD. ASD-Risk achieved a 10-fold cross-validation accuracy, sensitivity, specificity, area under a receiver operating characteristic curve, and a test accuracy of 81.83%, 0.84, 0.79, 0.84, and 72.27%, respectively. We prioritized the temporospatial features according to their contribution to the prediction accuracy. The top identified temporospatial regions of the brain for risk gene prediction included the posteroventral parietal cortex at 13 post-conception weeks feature. The identified temporospatial features would help to explore the risk genes that are specifically expressed in different brain regions of ASD patients.

Diagnostic Classification and Prognostic Prediction Using Common Genetic Variants in Autism Spectrum Disorder: Genotype-Based Deep Learning

Background

In the United States, about 3 million people have autism spectrum disorder (ASD), and around 1 out of 59 children are diagnosed with ASD. People with ASD have characteristic social communication deficits and repetitive behaviors. The causes of this disorder remain unknown; however, in up to 25% of cases, a genetic cause can be identified. Detecting ASD as early as possible is desirable because early detection of ASD enables timely interventions in children with ASD. Identification of ASD based on objective pathogenic mutation screening is the major first step toward early intervention and effective treatment of affected children.

Objective

Recent investigation interrogated genomics data for detecting and treating autism disorders, in addition to the conventional clinical interview as a diagnostic test. Since deep neural networks perform better than shallow machine learning models on complex and high-dimensional data, in this study, we sought to apply deep learning to genetic data obtained across thousands of simplex families at risk for ASD to identify contributory mutations and to create an advanced diagnostic classifier for autism screening.

Methods

After preprocessing the genomics data from the Simons Simplex Collection, we extracted top ranking common variants that may be protective or pathogenic for autism based on a chi-square test. A convolutional neural network–based diagnostic classifier was then designed using the identified significant common variants to predict autism. The performance was then compared with shallow machine learning–based classifiers and randomly selected common variants.

Results

The selected contributory common variants were significantly enriched in chromosome X while chromosome Y was also discriminatory in determining the identification of autistic individuals from nonautistic individuals. The ARSD, MAGEB16, and MXRA5 genes had the largest effect in the contributory variants. Thus, screening algorithms were adapted to include these common variants. The deep learning model yielded an area under the receiver operating characteristic curve of 0.955 and an accuracy of 88% for identifying autistic individuals from nonautistic individuals. Our classifier demonstrated a considerable improvement of ~13% in terms of classification accuracy compared to standard autism screening tools.

Conclusions

Common variants are informative for autism identification. Our findings also suggest that the deep learning process is a reliable method for distinguishing the diseased group from the control group based on the common variants of autism.

Synaptic processes and immune-related pathways implicated in Tourette syndrome

Tourette syndrome (TS) is a neuropsychiatric disorder of complex genetic architecture involving multiple interacting genes. Here, we sought to elucidate the pathways that underlie the neurobiology of the disorder through genome-wide analysis. We analyzed genome-wide genotypic data of 3581 individuals with TS and 7682 ancestry-matched controls and investigated associations of TS with sets of genes that are expressed in particular cell types and operate in specific neuronal and glial functions. We employed a self-contained, set-based association method (SBA) as well as a competitive gene set method (MAGMA) using individual-level genotype data to perform a comprehensive investigation of the biological background of TS. Our SBA analysis identified three significant gene sets after Bonferroni correction, implicating ligand-gated ion channel signaling, lymphocytic, and cell adhesion and transsynaptic signaling processes. MAGMA analysis further supported the involvement of the cell adhesion and trans-synaptic signaling gene set. The lymphocytic gene set was driven by variants in FLT3, raising an intriguing hypothesis for the involvement of a neuroinflammatory element in TS pathogenesis. The indications of involvement of ligand-gated ion channel signaling reinforce the role of GABA in TS, while the association of cell adhesion and trans-synaptic signaling gene set provides additional support for the role of adhesion molecules in neuropsychiatric disorders. This study reinforces previous findings but also provides new insights into the neurobiology of TS.

16p11.2 microdeletion imparts transcriptional alterations in human iPSC-derived models of early neural development

Microdeletions and microduplications of the 16p11.2 chromosomal locus are associated with syndromic neurodevelopmental disorders and reciprocal physiological conditions such as macro/microcephaly and high/low body mass index. To facilitate cellular and molecular investigations into these phenotypes, 65 clones of human induced pluripotent stem cells (hiPSCs) were generated from 13 individuals with 16p11.2 copy number variations (CNVs). To ensure these cell lines were suitable for downstream mechanistic investigations, a customizable bioinformatic strategy for the detection of random integration and expression of reprogramming vectors was developed and leveraged towards identifying a subset of ‘footprint’-free hiPSC clones. Transcriptomic profiling of cortical neural progenitor cells derived from these hiPSCs identified alterations in gene expression patterns which precede morphological abnormalities reported at later neurodevelopmental stages. Interpreting clinical information—available with the cell lines by request from the Simons Foundation Autism Research Initiative—with this transcriptional data revealed disruptions in gene programs related to both nervous system function and cellular metabolism. As demonstrated by these analyses, this publicly available resource has the potential to serve as a powerful medium for probing the etiology of developmental disorders associated with 16p11.2 CNVs.

Evidence for secondary-variant genetic burden and non-random distribution across biological modules in a recessive ciliopathy

The influence of genetic background on driver mutations is well established; however, the mechanisms by which the background interacts with Mendelian loci remain unclear. We performed a systematic secondary-variant burden analysis of two independent cohorts of patients with Bardet-Biedl syndrome (BBS) with known recessive biallelic pathogenic mutations in one of 17 BBS genes for each individual. We observed a significant enrichment of trans-acting rare nonsynonymous secondary variants in patients with BBS compared with either population controls or a cohort of individuals with a non-BBS diagnosis and recessive variants in the same gene set. Strikingly, we found a significant over-representation of secondary alleles in chaperonin-encoding genes-a finding corroborated by the observation of epistatic interactions involving this complex in vivo. These data indicate a complex genetic architecture for BBS that informs the biological properties of disease modules and presents a model for secondary-variant burden analysis in recessive disorders.

Proteomics and Metabolomics Approaches towards a Functional Insight onto AUTISM Spectrum Disorders: Phenotype Stratification and Biomarker Discovery

Autism spectrum disorders (ASDs) are neurodevelopmental disorders characterized by behavioral alterations and currently affect about 1% of children. Significant genetic factors and mechanisms underline the causation of ASD. Indeed, many affected individuals are diagnosed with chromosomal abnormalities, submicroscopic deletions or duplications, single-gene disorders or variants. However, a range of metabolic abnormalities has been highlighted in many patients, by identifying biofluid metabolome and proteome profiles potentially usable as ASD biomarkers. Indeed, next-generation sequencing and other omics platforms, including proteomics and metabolomics, have uncovered early age disease biomarkers which may lead to novel diagnostic tools and treatment targets that may vary from patient to patient depending on the specific genomic and other omics findings. The progressive identification of new proteins and metabolites acting as biomarker candidates, combined with patient genetic and clinical data and environmental factors, including microbiota, would bring us towards advanced clinical decision support systems (CDSSs) assisted by machine learning models for advanced ASD-personalized medicine. Herein, we will discuss novel computational solutions to evaluate new proteome and metabolome ASD biomarker candidates, in terms of their recurrence in the reviewed literature and laboratory medicine feasibility. Moreover, the way to exploit CDSS, performed by artificial intelligence, is presented as an effective tool to integrate omics data to electronic health/medical records (EHR/EMR), hopefully acting as added value in the near future for the clinical management of ASD.

Neuronal α2δ proteins and brain disorders

α2δ proteins are membrane-anchored extracellular glycoproteins which are abundantly expressed in the brain and the peripheral nervous system. They serve as regulatory subunits of voltage-gated calcium channels and, particularly in nerve cells, regulate presynaptic and postsynaptic functions independently from their role as channel subunits. α2δ proteins are the targets of the widely prescribed anti-epileptic and anti-allodynic drugs gabapentin and pregabalin, particularly for the treatment of neuropathic pain conditions. Recently, the human genes (CACNA2D1-4) encoding for the four known α2δ proteins (isoforms α2δ-1 to α2δ-4) have been linked to a large variety of neurological and neuropsychiatric disorders including epilepsy, autism spectrum disorders, bipolar disorders, schizophrenia, and depressive disorders. Here, we provide an overview of the hitherto identified disease associations of all known α2δ genes, hypothesize on the pathophysiological mechanisms considering their known physiological roles, and discuss the most immanent future research questions. Elucidating their specific physiological and pathophysiological mechanisms may open the way for developing entirely novel therapeutic paradigms for treating brain disorders.

Genetic associations between voltage-gated calcium channels and autism spectrum disorder: a systematic review

OBJECTIVES

The present review systematically summarized existing publications regarding the genetic associations between voltage-gated calcium channels (VGCCs) and autism spectrum disorder (ASD).

METHODS

A comprehensive literature search was conducted to gather pertinent studies in three online databases. Two authors independently screened the included records based on the selection criteria. Discrepancies in each step were settled through discussions.

RESULTS

From 1163 resulting searched articles, 28 were identified for inclusion. The most prominent among the VGCCs variants found in ASD were those falling within loci encoding the α subunits, CACNA1A, CACNA1B, CACNA1C, CACNA1D, CACNA1E, CACNA1F, CACNA1G, CACNA1H, and CACNA1I as well as those of their accessory subunits CACNB2, CACNA2D3, and CACNA2D4. Two signaling pathways, the IP3-Ca²⁺ pathway and the MAPK pathway, were identified as scaffolds that united genetic lesions into a consensus etiology of ASD.

CONCLUSIONS

Evidence generated from this review supports the role of VGCC genetic variants in the pathogenesis of ASD, making it a promising therapeutic target. Future research should focus on the specific mechanism that connects VGCC genetic variants to the complex ASD phenotype.

Elevated basal transcription can underlie timothy channel association with autism related disorders

Timothy syndrome (TS) is a neurodevelopmental disorder caused by mutations in the pore-forming subunit α₁1.2 of the L-type voltage-gated Ca²⁺-channel Cav1.2, at positions G406R or G402S. Although both mutations cause cardiac arrhythmias, only Cav1.2^G406R is associated with the autism-spectrum-disorder (ASD). We show that transcriptional activation by Cav1.2^G406R and Cav1.2^G402S is driven by membrane depolarization through the Ras/ERK/CREB pathway in a process called excitation-transcription (ET) coupling, as previously shown for wt Cav1.2. This process requires the presence of the intracellular β-subunit of the channel. We found that only the autism-associated mutant Cav1.2^G406R, as opposed to the non-autistic mutated channel Cav1.2^G402S, exhibits a depolarization-independent CREB phosphorylation, and spontaneous transcription of cFos and MeCP2. A leftward voltage-shift typical of Cav1.2^G406R activation, increases channel opening at subthreshold potentials, resulting in an enhanced channel activity, as opposed to a rightward shift in Cav1.2^G402S. We suggest that the enhanced spontaneous Cav1.2^G406R activity accounts for the increase in basal transcriptional activation. This uncontroled transcriptional activation may result in the manifestation of long-term dysregulations such as autism. Thus, gating changes provide a mechanistic framework for understanding the molecular events underlying the autistic phenomena caused by the G406R Timothy mutation. They might clarify whether a constitutive transcriptional activation accompanies other VGCC that exhibit a leftward voltage-shift of activation and are also associated with long-term cognitive disorders.

Emerging biomarkers in autism spectrum disorder: a systematic review

Autism spectrum disorder (ASD) affects approximately 2% of children in the United States (US) yet its etiology is unclear and effective treatments are lacking. Therapeutic interventions are most effective if started early in life, yet diagnosis often remains delayed, partly because the diagnosis of ASD is based on identifying abnormal behaviors that may not emerge until the disorder is well established. Biomarkers that identify children at risk during the pre-symptomatic period, assist with early diagnosis, confirm behavioral observations, stratify patients into subgroups, and predict therapeutic response would be a great advance. Here we underwent a systematic review of the literature on ASD to identify promising biomarkers and rated the biomarkers in regards to a Level of Evidence and Grade of Recommendation using the Oxford Centre for Evidence-Based Medicine scale. Biomarkers identified by our review included physiological biomarkers that identify neuroimmune and metabolic abnormalities, neurological biomarkers including abnormalities in brain structure, function and neurophysiology, subtle behavioral biomarkers including atypical development of visual attention, genetic biomarkers and gastrointestinal biomarkers. Biomarkers of ASD may be found prior to birth and after diagnosis and some may predict response to specific treatments. Many promising biomarkers have been developed for ASD. However, many biomarkers are preliminary and need to be validated and their role in the diagnosis and treatment of ASD needs to be defined. It is likely that biomarkers will need to be combined to be effective to identify ASD early and guide treatment.

Genetic Associations between Voltage-Gated Calcium Channels and Psychiatric Disorders

Psychiatric disorders are mental, behavioral or emotional disorders. These conditions are prevalent, one in four adults suffer from any type of psychiatric disorders world-wide. It has always been observed that psychiatric disorders have a genetic component, however, new methods to sequence full genomes of large cohorts have identified with high precision genetic risk loci for these conditions. Psychiatric disorders include, but are not limited to, bipolar disorder, schizophrenia, autism spectrum disorder, anxiety disorders, major depressive disorder, and attention-deficit and hyperactivity disorder. Several risk loci for psychiatric disorders fall within genes that encode for voltage-gated calcium channels (CaVs). Calcium entering through CaVs is crucial for multiple neuronal processes. In this review, we will summarize recent findings that link CaVs and their auxiliary subunits to psychiatric disorders. First, we will provide a general overview of CaVs structure, classification, function, expression and pharmacology. Next, we will summarize tools to study risk loci associated with psychiatric disorders. We will examine functional studies of risk variations in CaV genes when available. Finally, we will review pharmacological evidence of the use of CaV modulators to treat psychiatric disorders. Our review will be of interest for those studying pathophysiological aspects of CaVs.

Comparative Phosphoproteomic Profiling of Type III Adenylyl Cyclase Knockout and Control, Male, and Female Mice

Type III adenylyl cyclase (AC3, ADCY3) is predominantly enriched in neuronal primary cilia throughout the central nervous system (CNS). Genome-wide association studies in humans have associated ADCY3 with major depressive disorder and autistic spectrum disorder, both of which exhibit sexual dimorphism. To date, it is unclear how AC3 affects protein phosphorylation and signal networks in central neurons, and what causes the sexual dimorphism of autism. We employed a mass spectrometry (MS)-based phosphoproteomic approach to quantitatively profile differences in phosphorylation between inducible AC3 knockout (KO) and wild type (WT), male and female mice. In total, we identified 4,655 phosphopeptides from 1,756 proteins, among which 565 phosphopeptides from 322 proteins were repetitively detected in all samples. Over 46% phosphopeptides were identified in at least three out of eight biological replicas. Comparison of AC3 KO and WT datasets revealed that phosphopeptides with motifs matching proline-directed kinases' recognition sites had a lower abundance in the KO dataset than in WTs. We detected 14 phosphopeptides restricted to WT dataset (i.e., Rabl6, Spast and Ppp1r14a) and 35 exclusively in KOs (i.e., Sptan1, Arhgap20, Arhgap44, and Pde1b). Moreover, 95 phosphopeptides (out of 90 proteins) were identified only in female dataset and 26 only in males. Label-free MS spectrum quantification using Skyline further identified phosphopeptides that had higher abundance in each sample group. In total, 204 proteins had sex-biased phosphorylation and 167 of them had increased expression in females relative to males. Interestingly, among the 204 gender-biased phosphoproteins, 31% were found to be associated with autism, including Dlg1, Dlgap2, Syn1, Syngap1, Ctnna1, Ctnnd1, Ctnnd2, Pkp4, and Arvcf. Therefore, this study also provides the first phosphoproteomics evidence suggesting that gender-biased post-translational phosphorylation may be implicated in the sexual dimorphism of autism.

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.

From bedside to bench and back: Translating ASD models

Autism spectrum disorders (ASD) represent a heterogeneous group of disorders defined by deficits in social interaction/communication and restricted interests, behaviors, or activities. Models of ASD, developed based on clinical data and observations, are used in basic science, the "bench," to better understand the pathophysiology of ASD and provide therapeutic options for patients in the clinic, the "bedside." Translational medicine creates a bridge between the bench and bedside that allows for clinical and basic science discoveries to challenge one another to improve the opportunities to bring novel therapies to patients. From the clinical side, biomarker work is expanding our understanding of possible mechanisms of ASD through measures of behavior, genetics, imaging modalities, and serum markers. These biomarkers could help to subclassify patients with ASD in order to better target treatments to a more homogeneous groups of patients most likely to respond to a candidate therapy. In turn, basic science has been responding to developments in clinical evaluation by improving bench models to mechanistically and phenotypically recapitulate the ASD phenotypes observed in clinic. While genetic models are identifying novel therapeutics targets at the bench, the clinical efforts are making progress by defining better outcome measures that are most representative of meaningful patient responses. In this review, we discuss some of these challenges in translational research in ASD and strategies for the bench and bedside to bridge the gap to achieve better benefits to patients.

Neuronal and astrocytic primary cilia in the mature brain

Primary cilia are tiny microtubule-based signaling devices that regulate a variety of physiological functions, including metabolism and cell division. Defects in primary cilia lead to a myriad of diseases in humans such as obesity and cancers. In the mature brain, both neurons and astrocytes contain a single primary cilium. Although neuronal primary cilia are not directly involved in synaptic communication, their pathophysiological impacts on obesity and mental disorders are well recognized. In contrast, research on astrocytic primary cilia lags far behind. Currently, little is known about their functions and molecular pathways in the mature brain. Unlike neurons, postnatal astrocytes retain the capacity of cell division and can become reactive and proliferate in response to various brain insults such as epilepsy, ischemia, traumatic brain injury, and neurodegenerative β-amyloid plaques. Since primary cilia derive from the mother centrioles, astrocyte proliferation must occur in coordination with the dismantling and ciliogenesis of astrocyte cilia. In this regard, the functions, signal pathways, and structural dynamics of neuronal and astrocytic primary cilia are fundamentally different. Here we discuss and compare the current understanding of neuronal and astrocytic primary cilia.

Autism-related behaviors in the cyclooxygenase-2-deficient mouse model

Prostaglandin E2 (PGE2) is an endogenous lipid molecule involved in normal brain development. Cyclooxygenase-2 (COX2) is the main regulator of PGE2 synthesis. Emerging clinical and molecular research provides compelling evidence that abnormal COX2/PGE2 signaling is associated with autism spectrum disorder (ASD). We previously found that COX2 knockout mice had dysregulated expression of many ASD genes belonging to important biological pathways for neurodevelopment. The present study is the first to show the connection between irregular COX2/PGE2 signaling and autism-related behaviors in male and female COX2-deficient knockin, (COX)-2^- , mice at young (4-6 weeks) or adult (8-11 weeks) ages. Autism-related behaviors were prominent in male (COX)-2^- mice for most behavioral tests. In the open field test, (COX)-2^- mice traveled more than controls and adult male (COX)-2^- mice spent less time in the center indicating elevated hyperactive and anxiety-linked behaviors. (COX)-2^- mice also buried more marbles, with males burying more than females, suggesting increased anxiety and repetitive behaviors. Young male (COX)-2^- mice fell more frequently in the inverted screen test revealing motor deficits. The three-chamber sociability test found that adult female (COX)-2^- mice spent less time in the novel mouse chamber indicative of social abnormalities. In addition, male (COX)-2^- mice showed altered expression of several autism-linked genes: Wnt2, Glo1, Grm5 and Mmp9. Overall, our findings offer new insight into the involvement of disrupted COX2/PGE2 signaling in ASD pathology with age-related differences and greater impact on males. We propose that (COX)-2^- mice might serve as a novel model system to study specific types of autism.

Autism throughout genetics: Perusal of the implication of ion channels

BACKGROUND

Autism spectrum disorder (ASD) comprises a group of neurodevelopmental psychiatric disorders characterized by deficits in social interactions, interpersonal communication, repetitive and stereotyped behaviors and may be associated with intellectual disabilities. The description of ASD as a synaptopathology highlights the importance of the synapse and the implication of ion channels in the etiology of these disorders.

METHODS

A narrative and critical review of the relevant papers from 1982 to 2017 known by the authors was conducted.

RESULTS

Genome-wide linkages, association studies, and genetic analyses of patients with ASD have led to the identification of several candidate genes and mutations linked to ASD. Many of the candidate genes encode for proteins involved in neuronal development and regulation of synaptic function including ion channels and actors implicated in synapse formation. The involvement of ion channels in ASD is of great interest as they represent attractive therapeutic targets. In agreement with this view, recent findings have shown that drugs modulating ion channel function are effective for the treatment of certain types of patients with ASD.

CONCLUSION

This review describes the genetic aspects of ASD with a focus on genes encoding ion channels and highlights the therapeutic implications of ion channels in the treatment of ASD.

Genetic testing and autism: Tutorial for communication sciences and disorders

This tutorial provides professionals in communication sciences and disorders with an overview of the molecular basis and parental perceptions of genetic testing as associated with autism. The introduction notes the prominence of genetic testing within present-day medical practices and highlights related limitations and concerns through the lens of disability critique. The body of the tutorial provides an overview of four different forms of genetic variation, highlighting the potential associations with autism and available genetic testing. In sum, most autism cases cannot be associated directly with specified forms of genetic variation but are attributed instead to multiple genetic and environmental influences working in concert. Finally, the discussion focuses on parental perceptions of the genetic testing associated with autism, both the potential benefits and harms, and emphasizes the need to integrate first-person perspectives from autistic individuals.

Polygenic Risk Scores in Clinical Psychology: Bridging Genomic Risk to Individual Differences

Genomewide association studies (GWASs) across psychiatric phenotypes have shown that common genetic variants generally confer risk with small effect sizes (odds ratio < 1.1) that additively contribute to polygenic risk. Summary statistics derived from large discovery GWASs can be used to generate polygenic risk scores (PRS) in independent, target data sets to examine correlates of polygenic disorder liability (e.g., does genetic liability to schizophrenia predict cognition?). The intuitive appeal and generalizability of PRS have led to their widespread use and new insights into mechanisms of polygenic liability. However, when currently applied across traits they account for small amounts of variance (<3%), are relatively uninformative for clinical treatment, and, in isolation, provide no insight into molecular mechanisms. Larger GWASs are needed to increase the precision of PRS, and novel approaches integrating various data sources (e.g., multitrait analysis of GWASs) may improve the utility of current PRS.

Genetics and epigenetics of autism: A Review

Autism is a developmental disorder that starts before age 3 years, and children with autism have impairment in both social interaction and communication, and have restricted, repetitive, and stereotyped patterns of behavior, interests, and activities. There is a strong heritable component of autism and autism spectrum disorder (ASD) as studies have shown that parents who have a child with ASD have a 2-18% chance of having a second child with ASD. The prevalence of autism and ASD have been increasing during the last 3 decades and much research has been carried out to understand the etiology, so as to develop novel preventive and treatment strategies. This review aims at summarizing the latest research studies related to autism and ASD, focusing not only on the genetics but also some epigenetic findings of autism/ASD. Some promising areas of research using transgenic/knockout animals and some ideas related to potential novel treatment and prevention strategies will be discussed.

iTRAQ-Based Proteomic Analysis Reveals Protein Profile in Plasma from Children with Autism

PURPOSE

Autism is a childhood neurological disorder with poorly understood etiology and pathology. This study is designed to identify differentially expressed proteins that might serve as potential biomarkers for autism.

EXPERIMENTAL DESIGN

We perform iTRAQ (isobaric tags for relative and absolute quantitation) analysis for normal and autistic children's plasma of the same age group.

RESULTS

The results show that 24 differentially expressed proteins were identified between autistic subjects and controls. For the first time, differential expression of complement C5 (C5) and fermitin family homolog 3 (FERMT3) are related to autism. Five proteins, that is, complement C3 (C3), C5, integrin alpha-IIb (ITGA2B), talin-1 (TLN1), and vitamin D-binding protein (GC) were validated via enzyme-linked immunosorbent assay (ELISA). By ROC (receiver operating characteristic) analysis, combinations of these five proteins C3, C5, GC, ITGA2B, and TLN1 distinguished autistic children from healthy controls with a high AUC (area under the ROC curve) value (0.982, 95% CI, 0.957-1.000, p < 0.000).

CONCLUSION

These above described proteins are found involved in different pathways that have previously been linked to the pathophysiology of autism spectrum disorders (ASDs). The results strongly support that focal adhesions, acting cytoskeleton, cell adhesion, motility and migration, synaptogenesis, and complement system are involved in the pathogenesis of autism, and highlight the important role of platelet function in the pathophysiology of autism.

Replicative genetic association study between functional polymorphisms in AVPR1A and social behavior scales of autism spectrum disorder in the Korean population

Background

Arginine vasopressin has been shown to affect social and emotional behaviors, which is mediated by the arginine vasopressin receptor (AVPR1A). Genetic polymorphisms in the AVPR1A promoter region have been identified to be associated with susceptibility to social deficits in autism spectrum disorder (ASD). We hypothesize that alleles of polymorphisms in the promoter region of AVPR1A may differentially interact with certain transcriptional factors, which in turn affect quantitative traits, such as sociality, in children with autism.

Methods

We performed an association study between ASD and polymorphisms in the AVPR1A promoter region in the Korean population using a family-based association test (FBAT). We evaluated the correlation between genotypes and the quantitative traits that are related to sociality in children with autism. We also performed a promoter assay in T98G cells and evaluated the binding affinities of transcription factors to alleles of rs7294536.

Results

The polymorphisms—RS1, RS3, rs7294536, and rs10877969—were analyzed. Under the dominant model, RS1–310, the shorter allele, was preferentially transmitted. The FBAT showed that the rs7294536 A allele was also preferentially transmitted in an additive and dominant model under the bi-allelic mode. When quantitative traits were used in the FBAT, rs7294536 and rs10877969 were statistically significant in all genotype models and modes. Luciferase and electrophoretic mobility-shift assays suggest that the rs7294536 A/G allele results in a Nf-κB binding site that exhibits differential binding affinities depending on the allele.

Conclusion

These results demonstrate that polymorphisms in the AVPR1A promoter region might be involved in pathophysiology of ASD and in functional regulation of the expression of AVPR1A.

Electronic supplementary material

The online version of this article (doi:10.1186/s13229-017-0161-9) contains supplementary material, which is available to authorized users.

Bio-collections in autism research

Autism spectrum disorder (ASD) is a group of complex neurodevelopmental disorders with diverse clinical manifestations and symptoms. In the last 10 years, there have been significant advances in understanding the genetic basis for ASD, critically supported through the establishment of ASD bio-collections and application in research. Here, we summarise a selection of major ASD bio-collections and their associated findings. Collectively, these include mapping ASD candidate genes, assessing the nature and frequency of gene mutations and their association with ASD clinical subgroups, insights into related molecular pathways such as the synapses, chromatin remodelling, transcription and ASD-related brain regions. We also briefly review emerging studies on the use of induced pluripotent stem cells (iPSCs) to potentially model ASD in culture. These provide deeper insight into ASD progression during development and could generate human cell models for drug screening. Finally, we provide perspectives concerning the utilities of ASD bio-collections and limitations, and highlight considerations in setting up a new bio-collection for ASD research.