A perturbed gene network containing PI3K-AKT, RAS-ERK and WNT-β-catenin pathways in leukocytes is linked to ASD genetics and symptom severity

Embryonic origin of two ASD subtypes of social symptom severity: the larger the brain cortical organoid size, the more severe the social symptoms

BACKGROUND

Social affective and communication symptoms are central to autism spectrum disorder (ASD), yet their severity differs across toddlers: Some toddlers with ASD display improving abilities across early ages and develop good social and language skills, while others with "profound" autism have persistently low social, language and cognitive skills and require lifelong care. The biological origins of these opposite ASD social severity subtypes and developmental trajectories are not known.

METHODS

Because ASD involves early brain overgrowth and excess neurons, we measured size and growth in 4910 embryonic-stage brain cortical organoids (BCOs) from a total of 10 toddlers with ASD and 6 controls (averaging 196 individual BCOs measured/subject). In a 2021 batch, we measured BCOs from 10 ASD and 5 controls. In a 2022 batch, we  tested replicability of BCO size and growth effects by generating and measuring an independent batch of BCOs from 6 ASD and 4 control subjects. BCO size was analyzed within the context of our large, one-of-a-kind social symptom, social attention, social brain and social and language psychometric normative datasets ranging from N = 266 to N = 1902 toddlers. BCO growth rates were examined by measuring size changes between 1- and 2-months of organoid development. Neurogenesis markers at 2-months were examined at the cellular level. At the molecular level, we measured activity and expression of Ndel1; Ndel1 is a prime target for cell cycle-activated kinases; known to regulate cell cycle, proliferation, neurogenesis, and growth; and known to be involved in neuropsychiatric conditions.

RESULTS

At the BCO level, analyses showed BCO size was significantly enlarged by 39% and 41% in ASD in the 2021 and 2022 batches. The larger the embryonic BCO size, the more severe the ASD social symptoms. Correlations between BCO size and social symptoms were r = 0.719 in the 2021 batch and r = 0. 873 in the replication 2022 batch. ASD BCOs grew at an accelerated rate nearly 3 times faster than controls. At the cell level, the two largest ASD BCOs had accelerated neurogenesis. At the molecular level, Ndel1 activity was highly correlated with the growth rate and size of BCOs. Two BCO subtypes were found in ASD toddlers: Those in one subtype had very enlarged BCO size with accelerated rate of growth and neurogenesis; a profound autism clinical phenotype displaying severe social symptoms, reduced social attention, reduced cognitive, very low language and social IQ; and substantially altered growth in specific cortical social, language and sensory regions. Those in a second subtype had milder BCO enlargement and milder social, attention, cognitive, language and cortical differences.

LIMITATIONS

Larger samples of ASD toddler-derived BCO and clinical phenotypes may reveal additional ASD embryonic subtypes.

CONCLUSIONS

By embryogenesis, the biological bases of two subtypes of ASD social and brain development-profound autism and mild autism-are already present and measurable and involve dysregulated cell proliferation and accelerated neurogenesis and growth. The larger the embryonic BCO size in ASD, the more severe the toddler's social symptoms and the more reduced the social attention, language ability, and IQ, and the more atypical the growth of social and language brain regions.

Shank3 deficiency elicits autistic-like behaviors by activating p38α in hypothalamic AgRP neurons

BACKGROUND

SH3 and multiple ankyrin repeat domains protein 3 (SHANK3) monogenic mutations or deficiency leads to excessive stereotypic behavior and impaired sociability, which frequently occur in autism cases. To date, the underlying mechanisms by which Shank3 mutation or deletion causes autism and the part of the brain in which Shank3 mutation leads to the autistic phenotypes are understudied. The hypothalamus is associated with stereotypic behavior and sociability. p38α, a mediator of inflammatory responses in the brain, has been postulated as a potential gene for certain cases of autism occurrence. However, it is unclear whether hypothalamus and p38α are involved in the development of autism caused by Shank3 mutations or deficiency.

METHODS

Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and immunoblotting were used to assess alternated signaling pathways in the hypothalamus of Shank3 knockout (Shank3-/-) mice. Home-Cage real-time monitoring test was performed to record stereotypic behavior and three-chamber test was used to monitor the sociability of mice. Adeno-associated viruses 9 (AAV9) were used to express p38α in the arcuate nucleus (ARC) or agouti-related peptide (AgRP) neurons. D176A and F327S mutations expressed constitutively active p38α. T180A and Y182F mutations expressed inactive p38α.

RESULTS

We found that Shank3 controls stereotypic behavior and sociability by regulating p38α activity in AgRP neurons. Phosphorylated p38 level in hypothalamus is significantly enhanced in Shank3-/- mice. Consistently, overexpression of p38α in ARC or AgRP neurons elicits excessive stereotypic behavior and impairs sociability in wild-type (WT) mice. Notably, activated p38α in AgRP neurons increases stereotypic behavior and impairs sociability. Conversely, inactivated p38α in AgRP neurons significantly ameliorates autistic behaviors of Shank3-/- mice. In contrast, activated p38α in pro-opiomelanocortin (POMC) neurons does not affect stereotypic behavior and sociability in mice.

LIMITATIONS

We demonstrated that SHANK3 regulates the phosphorylated p38 level in the hypothalamus and inactivated p38α in AgRP neurons significantly ameliorates autistic behaviors of Shank3-/- mice. However, we did not clarify the biochemical mechanism of SHANK3 inhibiting p38α in AgRP neurons.

CONCLUSIONS

These results demonstrate that the Shank3 deficiency caused autistic-like behaviors by activating p38α signaling in AgRP neurons, suggesting that p38α signaling in AgRP neurons is a potential therapeutic target for Shank3 mutant-related autism.

IL-6 Enhances the Activation of PI3K-AKT/mTOR-GSK-3β by Upregulating GRPR in Hippocampal Neurons of Autistic Mice

Autism spectrum disorder (ASD) is a neurological disorder associated with brain inflammation. The underlying mechanisms could be attributed to the activation of PI3K signaling in the inflamed brain of ASD. Multiple studies highlight the role of GRPR in regulating ASD like abnormal behavior and enhancing the PI3K signaling. However, the molecular mechanism by which GRPR regulates PI3K signaling in neurons of individuals with ASD is still unclear. In this study, we utilized a maternal immune activation model to investigate the effects of GRPR on PI3K signaling in the inflamed brain of ASD mice. We used HT22 cells with and without GRPR to examine the impact of GRP-GRPR on the PI3K-AKT pathway with IL-6 treatment. We analyzed a dataset of hippocampus samples from ASD mice to identify hub genes. Our results demonstrated increased expression of IL-6, GRPR, and PI3K-AKT signaling in the hippocampus of ASD mice. Additionally, we observed increased GRPR expression and PI3K-AKT/mTOR activation in HT22 cells after IL-6 treatment, but decreased expression in HT22 cells with GRPR knockdown. NetworkAnalyst identified GSK-3β as the most crucial gene in the PI3K-AKT/mTOR pathway in the hippocampus of ASD. Furthermore, we found that IL-6 upregulated the expression of GSK-3β in HT22 cells by upregulating GRP-GRPR. Our findings suggest that IL-6 can enhance the activation of PI3K-AKT/mTOR-GSK-3β in hippocampal neurons of ASD mice by upregulating GRPR.

Resource allocation in mammalian systems

Cells execute biological functions to support phenotypes such as growth, migration, and secretion. Complementarily, each function of a cell has resource costs that constrain phenotype. Resource allocation by a cell allows it to manage these costs and optimize their phenotypes. In fact, the management of resource constraints (e.g., nutrient availability, bioenergetic capacity, and macromolecular machinery production) shape activity and ultimately impact phenotype. In mammalian systems, quantification of resource allocation provides important insights into higher-order multicellular functions; it shapes intercellular interactions and relays environmental cues for tissues to coordinate individual cells to overcome resource constraints and achieve population-level behavior. Furthermore, these constraints, objectives, and phenotypes are context-dependent, with cells adapting their behavior according to their microenvironment, resulting in distinct steady-states. This review will highlight the biological insights gained from probing resource allocation in mammalian cells and tissues.

Autism spectrum disorder: pathogenesis, biomarker, and intervention therapy

Autism spectrum disorder (ASD) has become a common neurodevelopmental disorder. The heterogeneity of ASD poses great challenges for its research and clinical translation. On the basis of reviewing the heterogeneity of ASD, this review systematically summarized the current status and progress of pathogenesis, diagnostic markers, and interventions for ASD. We provided an overview of the ASD molecular mechanisms identified by multi-omics studies and convergent mechanism in different genetic backgrounds. The comorbidities, mechanisms associated with important physiological and metabolic abnormalities (i.e., inflammation, immunity, oxidative stress, and mitochondrial dysfunction), and gut microbial disorder in ASD were reviewed. The non-targeted omics and targeting studies of diagnostic markers for ASD were also reviewed. Moreover, we summarized the progress and methods of behavioral and educational interventions, intervention methods related to technological devices, and research on medical interventions and potential drug targets. This review highlighted the application of high-throughput omics methods in ASD research and emphasized the importance of seeking homogeneity from heterogeneity and exploring the convergence of disease mechanisms, biomarkers, and intervention approaches, and proposes that taking into account individuality and commonality may be the key to achieve accurate diagnosis and treatment of ASD.

Metabolic dynamics in astrocytes and microglia during post-natal development and their implications for autism spectrum disorders

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition characterized by elusive underlying mechanisms. Recent attention has focused on the involvement of astrocytes and microglia in ASD pathology. These glial cells play pivotal roles in maintaining neuronal homeostasis, including the regulation of metabolism. Emerging evidence suggests a potential association between ASD and inborn errors of metabolism. Therefore, gaining a comprehensive understanding of the functions of microglia and astrocytes in ASD is crucial for the development of effective therapeutic interventions. This review aims to provide a summary of the metabolism of astrocytes and microglia during post-natal development and the evidence of disrupted metabolic pathways in ASD, with particular emphasis on those potentially important for the regulation of neuronal post-natal maturation by astrocytes and microglia.

Restoration of nNOS Expression Rescues Autistic-Like Phenotypes Through Normalization of AMPA Receptor-Mediated Neurotransmission

Autism spectrum disorder (ASD) is associated with a range of abnormalities characterized by deficits in socialization, communication, repetitive behaviors, and restricted interests. We have recently shown that neuronal nitric oxide synthase (nNOS) expression was decreased in the basolateral amygdala (BLA) of mice after postnatal valproic acid exposure. Neuronal activity-regulated pentraxin (Narp) could contribute to the regulation of the GluA4 2-amino-3-(5-methyl-3-oxo-1,2-oxazol-4-yl) propanoic acid (AMPA) subunits which are predominantly expressed in interneurons. However, the specific role of nNOS re-expression on excitatory neurotransmitter with relevance to ASD core symptoms in VPA-treated animals remains to be elucidated. Herein, nNOS overexpression using a lentiviral vector and L-arginine-activating PI3K-Akt-mTOR signaling can restore nNOS expression in the BLA induced by VPA. Restoration of nNOS expression in these mice was sufficient to reduce the severity of ASD-like behavioral patterns such that animals exhibited decreases in abnormal social interactions and communication, stereotyped/repetitive behaviors, and anxiety-like traits. Most strikingly, re-expression of nNOS upregulated surface expression of Narp and GluA4 in nNOS-positive interneuron as shown by immunoprecipitation and Western blotting. Whole-cell patch-clamp recordings demonstrated that restoration of nNOS had a significant enhancing effect on AMPA receptor-mediated excitatory glutamatergic synaptic neurotransmission, which was inhibited by disturbing the interaction between Narp and GluA4 in acutely dissociated BLA slices. Overall, these data offer a scientific basis for the additional study of nNOS re-expression as a promising therapeutic target by correcting AMPA receptor-mediated synaptic function in ASD and related neurodevelopmental disorders.

Genomic insights and advanced machine learning: characterizing autism spectrum disorder biomarkers and genetic interactions

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition characterized by altered brain connectivity and function. In this study, we employed advanced bioinformatics and explainable AI to analyze gene expression associated with ASD, using data from five GEO datasets. Among 351 neurotypical controls and 358 individuals with autism, we identified 3,339 Differentially Expressed Genes (DEGs) with an adjusted p-value (≤ 0.05). A subsequent meta-analysis pinpointed 342 DEGs (adjusted p-value ≤ 0.001), including 19 upregulated and 10 down-regulated genes across all datasets. Shared genes, pathogenic single nucleotide polymorphisms (SNPs), chromosomal positions, and their impact on biological pathways were examined. We identified potential biomarkers (HOXB3, NR2F2, MAPK8IP3, PIGT, SEMA4D, and SSH1) through text mining, meriting further investigation. Additionally, ‎we shed light on the roles of RPS4Y1 and KDM5D genes in neurogenesis and neurodevelopment. Our analysis detected 1,286 SNPs linked to ASD-related conditions, of which 14 high-risk SNPs were located on chromosomes 10 and X. We highlighted potential missense SNPs associated with FGFR inhibitors, suggesting that it may serve as a promising biomarker for responsiveness to targeted therapies. Our explainable AI model identified the MID2 gene as a potential ASD biomarker. This research unveils vital genes and potential biomarkers, providing a foundation for novel gene discovery in complex diseases.

Artificial intelligence and bioinformatics analyze markers of children's transcriptional genome to predict autism spectrum disorder

Introduction

Autism spectrum disorder (ASD), characterized by difficulties in social interaction and communication as well as restricted interests and repetitive behaviors, is extremely challenging to diagnose in toddlers. Early diagnosis and intervention are crucial however.

Methods

In this study, we developed a machine learning classification model based on mRNA expression data from the peripheral blood of 128 toddlers with ASD and 126 controls. Differentially expressed genes (DEGs) between ASD and controls were identified.

Results

We identified genes such as UBE4B, SPATA2 and RBM3 as DEGs, mainly involved in immune-related pathways. 21 genes were screened as key biomarkers using LASSO regression, yielding an accuracy of 86%. A neural network model based on these 21 genes achieved an AUC of 0.88.

Discussion

Our findings suggest that the identified neurotransmitters and 21 immune-related biomarkers may facilitate the early diagnosis of ASD. The mRNA expression profile sheds light on the biological underpinnings of ASD in toddlers and potential biomarkers for early identification. Nevertheless, larger samples are needed to validate these biomarkers.

Dysregulation of immune and metabolism pathways in maternal immune activation induces an increased risk of autism spectrum disorders

AIMS

Maternal immune activation (MIA) via infection during pregnancy is known to be an environmental risk factor for neurodevelopmental disorders and the development of autism spectrum disorders (ASD) in the offspring, but it still remains elusive that the molecular relevance between infection-induced abnormal neurodevelopmental events and an increased risk for ASD development.

MAIN METHODS

Fully considering the extremely high genetic heterogeneity of ASD and the universality of risk-gene with minimal effect-sizes, the gene and pathway-based association analysis was performed with the transcriptomic and DNA methylation landscapes of temporal human embryonic brain development and ASD, and the time-course transcriptional profiling of MIA. We conducted the transcriptional profiling of mouse abnormal neurodevelopment two days following induced MIA via LPS injection at E10.5.

KEY FINDINGS

A novel evidence was proved that illustrated altering four immune and metabolism-related risk pathways, including starch and sucrose metabolism, ribosome, protein processing in endoplasmic reticulum, and retrograde endocannabinoid signaling pathway, which were prominent involvement in the process of MIA regulating abnormal fetal brain development to induce an increased risk of ASD. Here, we have observed that almost all key genes within these risk pathways are significantly differentially expressed at embryonic days (E) 10.5-12.5, which is considered to be the optimal coincidence window of mouse embryonic brain development to study the intimate association between MIA and ASD using mouse animal models.

SIGNIFICANCE

There search establishes that MIA causes dysregulation of immune and metabolic pathways, which leads to abnormal embryonic neurodevelopment, thus promoting development of ASD symptoms in offspring.

Methodology to identify a gene expression signature by merging microarray datasets

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

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.

Language, Social, and Face Regions Are Affected in Toddlers with Autism and Predictive of Language Outcome

Identifying prognostic early brain alterations is crucial for autism spectrum disorder (ASD). Leveraging structural MRI data from 166 ASD and 109 typical developing (TD) toddlers and controlling for brain size, we found that, compared to TD, ASD toddlers showed larger or thicker lateral temporal regions; smaller or thinner frontal lobe and midline structures; larger callosal subregion volume; and smaller cerebellum. Most of these differences were replicated in an independent cohort of 38 ASD and 37 TD toddlers. Moreover, the identified brain alterations were related to ASD symptom severity and cognitive impairments at intake, and, remarkably, they improved the accuracy for predicting later language outcome beyond intake clinical and demographic variables. In summary, brain regions involved in language, social, and face processing were altered in ASD toddlers. These early-age brain alterations may be the result of dysregulation in multiple neural processes and stages and are promising prognostic biomarkers for future language ability.

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

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

Gut Microbiota Analysis and In Silico Biomarker Detection of Children with Autism Spectrum Disorder across Cohorts

The study of human gut microbiota has attracted increasing interest in the fields of life science and healthcare. However, the complicated and interconnected associations between gut microbiota and human diseases are still difficult to determine in a predictive fashion. Artificial intelligence such as machine learning (ML) and deep learning can assist in processing and interpreting biological datasets. In this study, we aggregated data from different studies based on the species composition and relative abundance of gut microbiota in children with autism spectrum disorder (ASD) and typically developed (TD) individuals and analyzed the commonalities and differences of ASD-associated microbiota across cohorts. We established a predictive model using an ML algorithm to explore the diagnostic value of the gut microbiome for the children with ASD and identify potential biomarkers for ASD diagnosis. The results indicated that the Shenzhen cohort achieved a higher area under the receiver operating characteristic curve (AUROC) value of 0.984 with 97% accuracy, while the Moscow cohort achieved an AUROC value of 0.81 with 67% accuracy. For the combination of the two cohorts, the average prediction results had an AUROC of 0.86 and 80% accuracy. The results of our cross-cohort analysis suggested that a variety of influencing factors, such as population characteristics, geographical region, and dietary habits, should be taken into consideration in microbial transplantation or dietary therapy. Collectively, our prediction strategy based on gut microbiota can serve as an enhanced strategy for the clinical diagnosis of ASD and assist in providing a more complete method to assess the risk of the disorder.

Sleep Problems in Preschoolers With Autism Spectrum Disorder Are Associated With Sensory Sensitivities and Thalamocortical Overconnectivity

BACKGROUND

Projections between the thalamus and sensory cortices are established early in development and play an important role in regulating sleep as well as in relaying sensory information to the cortex. Atypical thalamocortical functional connectivity frequently observed in children with autism spectrum disorder (ASD) might therefore be linked to sensory and sleep problems common in ASD.

METHODS

Here, we investigated the relationship between auditory-thalamic functional connectivity measured during natural sleep functional magnetic resonance imaging, sleep problems, and sound sensitivities in 70 toddlers and preschoolers (1.5-5 years old) with ASD compared with a matched group of 46 typically developing children.

RESULTS

In children with ASD, sleep problems and sensory sensitivities were positively correlated, and increased sleep latency was associated with overconnectivity between the thalamus and auditory cortex in a subsample with high-quality magnetic resonance imaging data (n = 29). In addition, auditory cortex blood oxygen level-dependent signal amplitude was elevated in children with ASD, potentially reflecting reduced sensory gating or a lack of auditory habituation during natural sleep.

CONCLUSIONS

These findings indicate that atypical thalamocortical functional connectivity can be detected early in development and may play a crucial role in sleep problems and sensory sensitivities in ASD.

Integrated analysis of endoplasmic reticulum stress regulators' expression identifies distinct subtypes of autism spectrum disorder

Endoplasmic reticulum (ER) stress has been demonstrated to play important roles in a variety of human diseases. However, their relevance to autism spectrum disorder (ASD) remains largely unknown. Herein, we aimed to investigate the expression patterns and potential roles of the ER stress regulators in ASD. The ASD expression profiles GSE111176 and GSE77103 were compiled from the Gene Expression Omnibus (GEO) database. ER stress score determined by the single sample gene set enrichment analysis (ssGSEA) was significantly higher in ASD patients. Differential analysis revealed that there were 37 ER stress regulators dysregulated in ASD. Based on their expression profile, the random forest and artificial neuron network techniques were applied to build a classifier that can effectively distinguish ASD from control samples among independent datasets. Weighted gene co-expression network analysis (WGCNA) screened out the turquoise module with 774 genes was closely related to the ER stress score. Through the overlapping results of the turquoise module and differential expression ER stress genes, hub regulators were gathered. The TF/miRNA-hub gene interaction networks were created. Furthermore, the consensus clustering algorithm was performed to cluster the ASD patients, and there were two ASD subclusters. Each subcluster has unique expression profiles, biological functions, and immunological characteristics. In ASD subcluster 1, the FAS pathway was more enriched, while subcluster 2 had a higher level of plasma cell infiltration as well as the BCR signaling pathway and interleukin receptor reaction reactivity. Finally, the Connectivity map (CMap) database was used to find prospective compounds that target various ASD subclusters. A total of 136 compounds were significantly enriched. In addition to some specific drugs which can effectively reverse the differential gene expression of each subcluster, we found that the PKC inhibitor BRD-K09991945 that targets Glycogen synthase kinase 3β (GSK3B) might have a therapeutic effect on both ASD subtypes that worth of the experimental validation. Our finding proved that ER stress plays a crucial role in the diversity and complexity of ASD, which may inform both mechanistic and therapeutic assessments of the disorder.

Dynamic changes in spatiotemporal transcriptome reveal maternal immune dysregulation of autism spectrum disorder

Maternal immune activation (MIA) during pregnancy is known to be an environmental risk factor for neurodevelopment and autism spectrum disorder (ASD). However, it is unclear at which fetal brain developmental windows and regions MIA induces ASD-related neurodevelopmental transcriptional abnormalities. The non-chasm differentially expressed genes (DEGs) involved in MIA inducing ASD during fetal brain developmental windows were identified by performing the differential expression analysis and comparing the common DEGs among MIA at four different gestational development windows, ASD with multiple brain regions from human patients and mouse models, and human and mouse embryonic brain developmental trajectory. The gene set and functional enrichment analyses were performing to identify MIA dysregulated ASD-related the fetal neurodevelopmental windows and brain regions and function annotations. Additionally, the networks were constructed using Cytoscape for visualization. MIA at E12.5 and E14.5 increased the risk of distinct brain regions for ASD. MIA-driven transcriptional alterations of non-chasm DEGs, during the coincidence brain developmental windows between human and mice, involving ASD-relevant synaptic components, as well as immune- and metabolism-related functions and pathways. Furthermore, a great number of non-chasm brain development-, immune-, and metabolism-related DEGs were overlapped in at least two existing ASD-associated databases, suggesting that the others could be considered as the candidate targets to construct the model mice for explaining the pathological changes of ASD when environmental factors (MIA) and gene mutation effects co-occur. Overall, our search supported that transcriptome-based MIA dysregulated the brain development-, immune-, and metabolism-related non-chasm DEGs at specific embryonic brain developmental window and region, leading to abnormal embryonic neurodevelopment, to induce the increasing risk of ASD.

Beyond Genes: Germline Disruption in the Etiology of Autism Spectrum Disorders

Investigations into the etiology of autism spectrum disorders have been largely confined to two realms: variations in DNA sequence and somatic developmental exposures. Here we suggest a third route-disruption of the germline epigenome induced by exogenous toxicants during a parent's gamete development. Similar to cases of germline mutation, these molecular perturbations may produce dysregulated transcription of brain-related genes during fetal and early development, resulting in abnormal neurobehavioral phenotypes in offspring. Many types of exposures may have these impacts, and here we discuss examples of anesthetic gases, tobacco components, synthetic steroids, and valproic acid. Alterations in parental germline could help explain some unsolved phenomena of autism, including increased prevalence, missing heritability, skewed sex ratio, and heterogeneity of neurobiology and behavior.

Prenatal fine particulate matter exposure associated with placental small extracellular vesicle derived microRNA and child neurodevelopmental delays

BACKGROUND AND AIMS

Prenatal fine particulate matter (PM_2.5) exposure has been linked to adverse neurodevelopment. However, epidemiological evidence remains inconclusive and little information about the effects of various PM_2.5 components on child neurodevelopment is currently known. The underlying mechanism was also not elucidated. The study aimed to evaluate the effects of PM_2.5 and components exposure on child neurodevelopmental delays and the role of placental small extracellular vesicles (sEVs)-derived miRNAs in the associations.

METHODS

We included 267 mother-child pairs in this analysis. Prenatal PM_2.5 and components (i.e. elements, water-soluble ions, and PAHs) exposure during three trimesters were monitored through personal PM_2.5 sampling. Child neurodevelopment at 2, 6, and 12 months old were evaluated by Ages and Stages Questionnaire (ASQ). We isolated sEVs from placental tissue to analyze the change of sEVs-derived miRNAs in response to PM_2.5. Associations between the PM_2.5-associated miRNAs and child neurodevelopment were evaluated using multivariate linear regression models.

RESULTS

The PM_2.5 exposure levels in the three trimesters range from 2.51 to 185.21 μg/m³. Prenatal PM_2.5 and the components of Pb, Al, V and Ti exposure in the second and third trimester were related to decreased ASQ scores communication, problem-solving and personal-social domains in children aged 2 or 6 months. RNA sequencing identified fifteen differentially expressed miRNAs. The miR-101-3p and miR-520d-5p were negatively associated with PM_2.5 and Pb component. miR-320a-3p expression was positively associated with PM_2.5 and V component. Meanwhile, the miR-320a-3p was associated with decreased ASQ scores, as reflected by ASQ-T (β: -2.154, 95 % CI: -4.313, -0.516) and problem-solving domain (β: -0.605, 95 % CI: -1.111, -0.099) in children aged 6 months.

CONCLUSION

Prenatal exposure to PM_2.5 and its Pb, Al, V & Ti component were associated with infant neurodevelopmental delays. The placenta sEVs derived miRNAs, especially miR-320a-3p, might contribute to an increased risk of neurodevelopmental delays.

Peripheral gene interactions define interpretable clusters of core ASD genes in a network-based investigation of the omnigenic theory

According to the recently proposed omnigenic theory, all expressed genes in a relevant tissue are contributing directly or indirectly to the manifestation of complex disorders such as autism. Thus, holistic approaches can be complementary in studying genetics of these complex disorders to focusing on a limited number of candidate genes. Gene interaction networks can be used for holistic studies of the omnigenic nature of autism. We used Louvain clustering on tissue-specific gene interaction networks and their subgraphs exclusively containing autism-related genes to study the effects of peripheral gene interactions. We observed that the autism gene clusters are significantly weaker connected to each other and the peripheral genes in non-neuronal tissues than in brain-related tissues. The biological functions of the brain clusters correlated well with previous findings on autism, such as synaptic signaling, regulation of DNA methylation, or regulation of lymphocyte activation, however, on the other tissues they did not enrich as significantly. Furthermore, ASD subjects with disruptive mutations in specific gene clusters show phenotypical differences compared to other disruptive variants carrying ASD individuals. Our results strengthen the omnigenic theory and can advance our understanding of the genetic background of autism.

PI3K/AKT/mTOR signalling inhibitor chrysophanol ameliorates neurobehavioural and neurochemical defects in propionic acid-induced experimental model of autism in adult rats

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder marked by social and communication deficits as well as repetitive behaviour. Several studies have found that overactivation of the PI3K/AKT/mTOR signalling pathways during brain development plays a significant role in autism pathogenesis. Overexpression of the PI3K/AKT/mTOR signalling pathway causes neurological disorders by increasing cell death, neuroinflammation, and oxidative stress. Chrysophanol, also known as chrysophanic acid, is a naturally occurring chemical obtained from the plant Rheum palmatum. This study aimed to examine the neuroprotective effect of CPH on neurobehavioral, molecular, neurochemical, and gross pathological alterations in ICV-PPA induced experimental model of autism in adult rats. The effects of ICV-PPA on PI3K/AKT/mTOR downregulation in the brain were studied in autism-like rats. Furthermore, we investigated how CPH affected myelin basic protein (MBP) levels in rat brain homogenate and apoptotic biomarkers such as caspase-3, Bax, and Bcl-2 levels in rat brain homogenate and blood plasma samples. Rats were tested for behavioural abnormalities such as neuromuscular dysfunction using an actophotometer, motor coordination using a beam crossing task (BCT), depressive behaviour using a forced swim test (FST), cognitive deficiency, and memory consolidation using a Morris water maze (MWM) task. In PPA-treated rats, prolonged oral CPH administration from day 12 to day 44 of the experimental schedule reduces autistic-like symptoms. Furthermore, in rat brain homogenates, blood plasma, and CSF samples, cellular, molecular, and cell death markers, neuroinflammatory cytokines, neurotransmitter levels, and oxidative stress indicators were investigated. The recent findings imply that CPH also restores abnormal neurochemical levels and may prevent autism-like gross pathological alterations, such as demyelination volume, in the rat brain.

Context-aware deconvolution of cell-cell communication with Tensor-cell2cell

Cell interactions determine phenotypes, and intercellular communication is shaped by cellular contexts such as disease state, organismal life stage, and tissue microenvironment. Single-cell technologies measure the molecules mediating cell–cell communication, and emerging computational tools can exploit these data to decipher intercellular communication. However, current methods either disregard cellular context or rely on simple pairwise comparisons between samples, thus limiting the ability to decipher complex cell–cell communication across multiple time points, levels of disease severity, or spatial contexts. Here we present Tensor-cell2cell, an unsupervised method using tensor decomposition, which deciphers context-driven intercellular communication by simultaneously accounting for multiple stages, states, or locations of the cells. To do so, Tensor-cell2cell uncovers context-driven patterns of communication associated with different phenotypic states and determined by unique combinations of cell types and ligand-receptor pairs. As such, Tensor-cell2cell robustly improves upon and extends the analytical capabilities of existing tools. We show Tensor-cell2cell can identify multiple modules associated with distinct communication processes (e.g., participating cell–cell and ligand-receptor pairs) linked to severities of Coronavirus Disease 2019 and to Autism Spectrum Disorder. Thus, we introduce an effective and easy-to-use strategy for understanding complex communication patterns across diverse conditions.

Cellular contexts such as disease state, organismal life stage and tissue microenvironment, shape intercellular communication, and ultimately affect an organism’s phenotypes. Here, the authors present Tensor-cell2cell, an unsupervised method for deciphering context-driven intercellular communication.

mTOR Signaling Pathway Regulates the Release of Proinflammatory Molecule CCL5 Implicated in the Pathogenesis of Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a complex pervasive neurodevelopmental disorder and neuroinflammation may contribute to the pathogenesis of ASD. However, the exact mechanisms of abnormal release of proinflammatory mediators in ASD remain poorly understood. This study reports elevated plasma levels of the proinflammatory chemokine (C-C motif) ligand 5 (CCL5) in children with ASD, suggesting an aberrant inflammatory response appearing in the development of ASD. Mining of the expression data of brain or blood tissue from individuals with ASD reveals that mTOR signaling is aberrantly activated in ASD patients. Our in vitro study shows that suppression of mTOR reduces the gene expression and release of CCL5 from human microglia, supporting that CCL5 expression is regulated by mTOR activity. Furthermore, bacterial lipopolysaccharide (LPS)-induced CCL5 expression can be counteracted by siRNA against NF-κB, suggests a determining role of NF-κB in upregulating CCL5 expression. However, a direct regulatory relationship between the NF-κB element and the mTOR signaling pathway was not observed in rapamycin-treated cells. Our results show that the phosphorylated CREB can be induced to suppress CCL5 expression by outcompeting NF-κB in binding to CREB-binding protein (CREBBP) once the mTOR signaling pathway is inhibited. We propose that the activation of mTOR signaling in ASD may induce the suppression of phosphorylation of CREB, which in turn results in the increased binding of CREBBP to NF-κB, a competitor of phosphorylated CREB to drive expression of CCL5. Our study sheds new light on the inflammatory mechanisms of ASD and paves the way for the development of therapeutic strategy for ASD.

Neural responses to affective speech, including motherese, map onto clinical and social eye tracking profiles in toddlers with ASD

Affective speech, including motherese, captures an infant's attention and enhances social, language and emotional development. Decreased behavioural response to affective speech and reduced caregiver-child interactions are early signs of autism in infants. To understand this, we measured neural responses to mild affect speech, moderate affect speech and motherese using natural sleep functional magnetic resonance imaging and behavioural preference for motherese using eye tracking in typically developing toddlers and those with autism. By combining diverse neural-clinical data using similarity network fusion, we discovered four distinct clusters of toddlers. The autism cluster with the weakest superior temporal responses to affective speech and very poor social and language abilities had reduced behavioural preference for motherese, while the typically developing cluster with the strongest superior temporal response to affective speech showed the opposite effect. We conclude that significantly reduced behavioural preference for motherese in autism is related to impaired development of temporal cortical systems that normally respond to parental affective speech.

Inhibition of miR-128 Enhances Vocal Sequence Organization in Juvenile Songbirds

The molecular mechanisms underlying learned vocal communication are not well characterized. This is a major barrier for developing treatments for conditions affecting social communication, such as autism spectrum disorder (ASD). Our group previously generated an activity-dependent gene expression network in the striatopallidal song control nucleus, Area X, in adult zebra finches to identify master regulators of learned vocal behavior. This dataset revealed that the two host genes for microRNA-128, ARPP21 and R3HDM1, are among the top genes whose expression correlates to how much birds sing. Here we examined whether miR-128 itself is behaviorally regulated in Area X and found that its levels decline with singing. We hypothesized that reducing miR-128 during the critical period for vocal plasticity would enhance vocal learning. To test this, we bilaterally injected an antisense miR-128 construct (AS miR-128) or a control scrambled sequence into Area X at post-hatch day 30 (30 d) using sibling-matched experimental and control pupils. The juveniles were then returned to their home cage and raised with their tutors. Strikingly, inhibition of miR-128 in young birds enhanced the organization of learned vocal sequences. Tutor and pupil stereotypy scores were positively correlated, though the correlation was stronger between tutors and control pupils compared to tutors and AS miR-128 pupils. This difference was driven by AS miR-128 pupils achieving higher stereotypy scores despite their tutors’ lower syntax scores. AS miR-128 birds with tutors on the higher end of the stereotypy spectrum were more likely to produce songs with faster tempos relative to sibling controls. Our results suggest that low levels of miR-128 facilitate vocal sequence stereotypy. By analogy, reducing miR-128 could enhance the capacity to learn to speak in patients with non-verbal ASD. To our knowledge, this study is the first to directly link miR-128 to learned vocal communication and provides support for miR-128 as a potential therapeutic target for ASD.

A Multi-Target and Multi-Channel Mechanism of Action for Jiawei Yinhuo Tang in the Treatment of Social Communication Disorders in Autism: Network Pharmacology and Molecular Docking Studies

Background

Autism spectrum disorder (ASD) is a highly heterogeneous neurodevelopmental disorder with complex pathogenesis. Currently, the pathogenesis of ASD is not fully understood. Moreover, current treatments do not effectively alleviate the primary symptoms of ASD social disorder (SCDA). Jiawei Yinhuo Tang (JWYHT) is an improved version of the classic prescription Yinhuo Tang. Although this medication has been shown to improve social behavior in ASD patients, the mechanism by which it works remains unknown.

Methods

In this study, network pharmacology bioinformatics analysis was used to identify the key targets, biological functions, and signal pathways of JWYHT in SCDA. Then, molecular docking and molecular dynamic simulation were used to validate the activity and stability of the active ingredient and the target protein during the binding process.

Results

The analysis identified 157 key targets and 9 core targets of JWYHT (including proto-oncogene (FOS), caspase 3 (CASP3), mitogen-activated protein kinase-3 (MAPK3), interleukin-6 (IL6), mitogen-activated protein kinase-1 (MAPK1), tumor necrosis factor (TNF), mitogen-activated protein kinase-8 (MAPK8), AKT serine/threonine kinase 1 (AKT1), and 5-hydroxytryptamine receptor 1B (5HT1B)) in SCDA. In addition, the Kyoto Encyclopedia of Gene and Genome results, as well as the staggering network analyses, revealed 20 biological processes and 20 signal pathways targeted by JWYHT in SCDA. Finally, molecular docking analysis was used to determine the binding activity of the main active components of JWYHT to the key targets. The binding activity and stability of methyl arachidonate and MAPK8 were demonstrated using molecular dynamics simulation.

Conclusion

This study demonstrates that JWYHT regulates neuronal development, synaptic transmission, intestinal and cerebral inflammatory response, and other processes in SCDA.

Blood and brain gene expression signatures of chronic intermittent ethanol consumption in mice

Alcohol Use Disorder (AUD) is a chronic, relapsing syndrome diagnosed by a heterogeneous set of behavioral signs and symptoms. There are no laboratory tests that provide direct objective evidence for diagnosis. Microarray and RNA-Seq technologies enable genome-wide transcriptome profiling at low costs and provide an opportunity to identify biomarkers to facilitate diagnosis, prognosis, and treatment of patients. However, access to brain tissue in living patients is not possible. Blood contains cellular and extracellular RNAs that provide disease-relevant information for some brain diseases. We hypothesized that blood gene expression profiles can be used to diagnose AUD. We profiled brain (prefrontal cortex, amygdala, and hypothalamus) and blood gene expression levels in C57BL/6J mice using RNA-seq one week after chronic intermittent ethanol (CIE) exposure, a mouse model of alcohol dependence. We found a high degree of preservation (rho range: [0.50, 0.67]) between blood and brain transcript levels. There was small overlap between blood and brain DEGs, and considerable overlap of gene networks perturbed after CIE related to cell-cell signaling (e.g., GABA and glutamate receptor signaling), immune responses (e.g., antigen presentation), and protein processing / mitochondrial functioning (e.g., ubiquitination, oxidative phosphorylation). Blood gene expression data were used to train classifiers (logistic regression, random forest, and partial least squares discriminant analysis), which were highly accurate at predicting alcohol dependence status (maximum AUC: 90.1%). These results suggest that gene expression profiles from peripheral blood samples contain a biological signature of alcohol dependence that can discriminate between CIE and Air subjects.

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

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

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.

A Comprehensive Evaluation of Cross-Omics Blood-Based Biomarkers for Neuropsychiatric Disorders

The identification of peripheral multi-omics biomarkers of brain disorders has long been hindered by insufficient sample size and confounder influence. This study aimed to compare biomarker potential for different molecules and diseases. We leveraged summary statistics of five blood quantitative trait loci studies (N = 1980 to 22,609) and genome-wide association studies (N = 9725 to 500,199) from 14 different brain disorders, such as Schizophrenia (SCZ) and Alzheimer's Disease (AD). We applied summary-based and two-sample Mendelian Randomization to estimate the associations between blood molecules and brain disorders. We identified 524 RNA, 807 methylation sites, 29 proteins, seven cytokines, and 22 metabolites having a significant association with at least one of 14 brain disorders. Simulation analyses indicated that a cross-omics combination of biomarkers had better performance for most disorders, and different disorders could associate with different omics. We identified an 11-methylation-site model for SCZ diagnosis (Area Under Curve, AUC = 0.74) by analyzing selected candidate markers in published datasets (total N = 6098). Moreover, we constructed an 18-methylation-sites model that could predict the prognosis of elders with mild cognitive impairment (hazard ratio = 2.32). We provided an association landscape between blood cross-omic biomarkers and 14 brain disorders as well as a suggestion guide for future clinical discovery and application.

Excess folic acid supplementation before and during pregnancy and lactation activates β-catenin in the brain of male mouse offspring

Folic acid (FA) supplementation in early pregnancy is recommended to protect against birth defects. But excess FA has exhibited neurodevelopmental toxicity. We previously reported that the mice treated with 2.5-fold the dietary requirement of FA one week before mating and throughout pregnancy and lactation displayed abnormal behaviors in the offspring. Here we found the levels of non-phosphorylated β-catenin (active) were increased in the brains of weaning and adult FA-exposed offspring. Meanwhile, demethylation of protein phosphatase 2 A catalytic subunit (PP2Ac), which suppresses its enzyme activity in regulatory subunit dependent manner, was significantly inhibited. Among the upstream regulators of β-catenin, PI3K/Akt/GSK-3β but not Wnt signaling was stimulated in FA-exposed brains only at weaning. In mouse neuroblastoma N2a cells, knockdown of PP2Ac or leucine carboxyl methyltransferase-1 (LCMT-1), or overexpression of PP2Ac methylation-deficient mutant decreased β-catenin dephosphorylation. These results suggest that excess FA may activate β-catenin via suppressing PP2Ac demethylation, providing a novel mechanism for the influence of FA on neurodevelopment.

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.

Translating the Role of mTOR- and RAS-Associated Signalopathies in Autism Spectrum Disorder: Models, Mechanisms and Treatment

Mutations affecting mTOR or RAS signaling underlie defined syndromes (the so-called mTORopathies and RASopathies) with high risk for Autism Spectrum Disorder (ASD). These syndromes show a broad variety of somatic phenotypes including cancers, skin abnormalities, heart disease and facial dysmorphisms. Less well studied are the neuropsychiatric symptoms such as ASD. Here, we assess the relevance of these signalopathies in ASD reviewing genetic, human cell model, rodent studies and clinical trials. We conclude that signalopathies have an increased liability for ASD and that, in particular, ASD individuals with dysmorphic features and intellectual disability (ID) have a higher chance for disruptive mutations in RAS- and mTOR-related genes. Studies on rodent and human cell models confirm aberrant neuronal development as the underlying pathology. Human studies further suggest that multiple hits are necessary to induce the respective phenotypes. Recent clinical trials do only report improvements for comorbid conditions such as epilepsy or cancer but not for behavioral aspects. Animal models show that treatment during early development can rescue behavioral phenotypes. Taken together, we suggest investigating the differential roles of mTOR and RAS signaling in both human and rodent models, and to test drug treatment both during and after neuronal development in the available model systems.

mTOR-related synaptic pathology causes autism spectrum disorder-associated functional hyperconnectivity

Postmortem studies have revealed increased density of excitatory synapses in the brains of individuals with autism spectrum disorder (ASD), with a putative link to aberrant mTOR-dependent synaptic pruning. ASD is also characterized by atypical macroscale functional connectivity as measured with resting-state fMRI (rsfMRI). These observations raise the question of whether excess of synapses causes aberrant functional connectivity in ASD. Using rsfMRI, electrophysiology and in silico modelling in Tsc2 haploinsufficient mice, we show that mTOR-dependent increased spine density is associated with ASD -like stereotypies and cortico-striatal hyperconnectivity. These deficits are completely rescued by pharmacological inhibition of mTOR. Notably, we further demonstrate that children with idiopathic ASD exhibit analogous cortical-striatal hyperconnectivity, and document that this connectivity fingerprint is enriched for ASD-dysregulated genes interacting with mTOR or Tsc2. Finally, we show that the identified transcriptomic signature is predominantly expressed in a subset of children with autism, thereby defining a segregable autism subtype. Our findings causally link mTOR-related synaptic pathology to large-scale network aberrations, revealing a unifying multi-scale framework that mechanistically reconciles developmental synaptopathy and functional hyperconnectivity in autism.

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.

Get SET Early to Identify and Treatment Refer Autism Spectrum Disorder at 1 Year and Discover Factors That Influence Early Diagnosis

OBJECTIVES

To examine the impact of a new approach, Get SET Early, on the rates of early autism spectrum disorder (ASD) detection and factors that influence the screen-evaluate-treat chain.

STUDY DESIGN

After attending Get SET Early training, 203 pediatricians administered 57 603 total screens using the Communication and Symbolic Behavior Scales Infant-Toddler Checklist at 12-, 18-, and 24-month well-baby examinations, and parents designated presence or absence of concern. For screen-positive toddlers, pediatricians specified if the child was being referred for evaluation, and if not, why not.

RESULTS

Collapsed across ages, toddlers were evaluated and referred for treatment at a median age of 19 months, and those screened at 12 months (59.4% of sample) by 15 months. Pediatricians referred one-third of screen-positive toddlers for evaluation, citing lack of confidence in the accuracy of screen-positive results as the primary reason for nonreferral. If a parent expressed concerns, referral probability doubled, and the rate of an ASD diagnosis increased by 37%. Of 897 toddlers evaluated, almost one-half were diagnosed as ASD, translating into an ASD prevalence of 1%.

CONCLUSIONS

The Get SET Early model was effective at detecting ASD and initiating very early treatment. Results also underscored the need for change in early identification approaches to formally operationalize and incorporate pediatrician judgment and level of parent concern into the process.

Dyrk1a Mutations Cause Undergrowth of Cortical Pyramidal Neurons via Dysregulated Growth Factor Signaling

BACKGROUND

Mutations in DYRK1A are a cause of microcephaly, autism spectrum disorder, and intellectual disability; however, the underlying cellular and molecular mechanisms are not well understood.

METHODS

We generated a conditional mouse model using Emx1-cre, including conditional heterozygous and homozygous knockouts, to investigate the necessity of Dyrk1a in the cortex during development. We used unbiased, high-throughput phosphoproteomics to identify dysregulated signaling mechanisms in the developing Dyrk1a mutant cortex as well as classic genetic modifier approaches and pharmacological therapeutic intervention to rescue microcephaly and neuronal undergrowth caused by Dyrk1a mutations.

RESULTS

We found that cortical deletion of Dyrk1a in mice causes decreased brain mass and neuronal size, structural hypoconnectivity, and autism-relevant behaviors. Using phosphoproteomic screening, we identified growth-associated signaling cascades dysregulated upon Dyrk1a deletion, including TrkB-BDNF (tyrosine receptor kinase B-brain-derived neurotrophic factor), an important regulator of ERK/MAPK (extracellular signal-regulated kinase/mitogen-activated protein kinase) and mTOR (mammalian target of rapamycin) signaling. Genetic suppression of Pten or pharmacological treatment with IGF-1 (insulin-like growth factor-1), both of which impinge on these signaling cascades, rescued microcephaly and neuronal undergrowth in neonatal mutants.

CONCLUSIONS

Altogether, these findings identify a previously unknown mechanism through which Dyrk1a mutations disrupt growth factor signaling in the developing brain, thus influencing neuronal growth and connectivity. Our results place DYRK1A as a critical regulator of a biological pathway known to be dysregulated in humans with autism spectrum disorder and intellectual disability. In addition, these data position Dyrk1a within a larger group of autism spectrum disorder/intellectual disability risk genes that impinge on growth-associated signaling cascades to regulate brain size and connectivity, suggesting a point of convergence for multiple autism etiologies.

Unveiling the Pathogenesis of Psychiatric Disorders Using Network Models

Psychiatric disorders are complex brain disorders with a high degree of genetic heterogeneity, affecting millions of people worldwide. Despite advances in psychiatric genetics, the underlying pathogenic mechanisms of psychiatric disorders are still largely elusive, which impedes the development of novel rational therapies. There has been accumulating evidence suggesting that the genetics of complex disorders can be viewed through an omnigenic lens, which involves contextualizing genes in highly interconnected networks. Thus, applying network-based multi-omics integration methods could cast new light on the pathophysiology of psychiatric disorders. In this review, we first provide an overview of the recent advances in psychiatric genetics and highlight gaps in translating molecular associations into mechanistic insights. We then present an overview of network methodologies and review previous applications of network methods in the study of psychiatric disorders. Lastly, we describe the potential of such methodologies within a multi-tissue, multi-omics approach, and summarize the future directions in adopting diverse network approaches.

Canadian Cannabis Consumption and Patterns of Congenital Anomalies: An Ecological Geospatial Analysis

OBJECTIVES

Cannabis is a known teratogen. Data availability addressing both major congenital anomalies and cannabis use allowed us to explore their geospatial relationships.

METHODS

Data for the years 1998 to 2009 from Canada Health and Statistics Canada was analyzed in R. Maps have been drawn and odds ratios, principal component analysis, correlation matrices, least squares regression and geospatial regression analyses have been conducted using the R packages base, dplyr, epiR, psych, ggplot2, colorplaner and the spml and spreml functions from package splm.

RESULTS

Mapping showed cannabis use was more common in the northern Territories of Canada in the Second National Survey of Cannabis Use 2018. Total congenital anomalies, all cardiovascular defects, orofacial clefts, Downs syndrome and gastroschisis were all found to be more common in these same regions and rose as a function of cannabis exposure. When Canada was dichotomized into high and low cannabis use zones by Provinces v Territories the Territories had a higher rate of total congenital anomalies 450.026 v 390.413 (O.R. = 1.16 95%C.I. 1.08-1.25, P = 0.000058; attributable fraction in exposed 13.25%, 95%C.I. 7.04-19.04%). In geospatial analysis in a spreml spatial error model cannabis was significant both alone as a main effect (P < 2.0 × 10) and in all its first and second order interactions with both tobacco and opioids from P < 2.0 × 10.

CONCLUSION

These results show that the northern Territories of Canada share a higher rate of cannabis use together with elevated rates of total congenital anomalies, all cardiovascular defects, Down's syndrome and gastroschisis. This is the second report of a significant association between cannabis use and both total defects and all cardiovascular anomalies and the fourth published report of a link with Downs syndrome and thereby direct major genotoxicity. The correlative relationships described in this paper are confounded by many features of social disadvantage in Canada's northern territories. However, in the context of a similar broad spectrum of defects described both in animals and in epidemiological reports from Hawaii, Colorado, USA and Australia they are cause for particular concern and indicate further research.

Modulation of Serotonin Receptors in Neurodevelopmental Disorders: Focus on 5-HT7 Receptor

Since neurodevelopmental disorders (NDDs) influence more than 3% of children worldwide, there has been intense investigation to understand the etiology of disorders and develop treatments. Although there are drugs such as aripiprazole, risperidone, and lurasidone, these medications are not cures for the disorders and can only help people feel better or alleviate their symptoms. Thus, it is required to discover therapeutic targets in order to find the ultimate treatments of neurodevelopmental disorders. It is suggested that abnormal neuronal morphology in the neurodevelopment process is a main cause of NDDs, in which the serotonergic system is emerging as playing a crucial role. From this point of view, we noticed the correlation between serotonin receptor subtype 7 (5-HT₇R) and NDDs including autism spectrum disorder (ASD), fragile X syndrome (FXS), and Rett syndrome (RTT). 5-HT₇R modulators improved altered behaviors in animal models and also affected neuronal morphology via the 5-HT₇R/G₁₂ signaling pathway. Through the investigation of recent studies, it is suggested that 5-HT₇R could be a potential therapeutic target for the treatment of NDDs.

Multiple freeze-thaw cycles lead to a loss of consistency in poly(A)-enriched RNA sequencing

Background

Both RNA-Seq and sample freeze-thaw are ubiquitous. However, knowledge about the impact of freeze-thaw on downstream analyses is limited. The lack of common quality metrics that are sufficiently sensitive to freeze-thaw and RNA degradation, e.g. the RNA Integrity Score, makes such assessments challenging.

Results

Here we quantify the impact of repeated freeze-thaw cycles on the reliability of RNA-Seq by examining poly(A)-enriched and ribosomal RNA depleted RNA-seq from frozen leukocytes drawn from a toddler Autism cohort. To do so, we estimate the relative noise, or percentage of random counts, separating technical replicates. Using this approach we measured noise associated with RIN and freeze-thaw cycles. As expected, RIN does not fully capture sample degradation due to freeze-thaw. We further examined differential expression results and found that three freeze-thaws should extinguish the differential expression reproducibility of similar experiments. Freeze-thaw also resulted in a 3′ shift in the read coverage distribution along the gene body of poly(A)-enriched samples compared to ribosomal RNA depleted samples, suggesting that library preparation may exacerbate freeze-thaw-induced sample degradation.

Conclusion

The use of poly(A)-enrichment for RNA sequencing is pervasive in library preparation of frozen tissue, and thus, it is important during experimental design and data analysis to consider the impact of repeated freeze-thaw cycles on reproducibility.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07381-z.

"The First Thousand Days" Define a Fetal/Neonatal Neurology Program

Gene-environment interactions begin at conception to influence maternal/placental/fetal triads, neonates, and children with short- and long-term effects on brain development. Life-long developmental neuroplasticity more likely results during critical/sensitive periods of brain maturation over these first 1,000 days. A fetal/neonatal program (FNNP) applying this perspective better identifies trimester-specific mechanisms affecting the maternal/placental/fetal (MPF) triad, expressed as brain malformations and destructive lesions. Maladaptive MPF triad interactions impair progenitor neuronal/glial populations within transient embryonic/fetal brain structures by processes such as maternal immune activation. Destructive fetal brain lesions later in pregnancy result from ischemic placental syndromes associated with the great obstetrical syndromes. Trimester-specific MPF triad diseases may negatively impact labor and delivery outcomes. Neonatal neurocritical care addresses the symptomatic minority who express the great neonatal neurological syndromes: encephalopathy, seizures, stroke, and encephalopathy of prematurity. The asymptomatic majority present with neurologic disorders before 2 years of age without prior detection. The developmental principle of ontogenetic adaptation helps guide the diagnostic process during the first 1,000 days to identify more phenotypes using systems-biology analyses. This strategy will foster innovative interdisciplinary diagnostic/therapeutic pathways, educational curricula, and research agenda among multiple FNNP. Effective early-life diagnostic/therapeutic programs will help reduce neurologic disease burden across the lifespan and successive generations.

Comprehensive Analysis of RNA-Seq Gene Expression Profiling of Brain Transcriptomes Reveals Novel Genes, Regulators, and Pathways in Autism Spectrum Disorder

BACKGROUND

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with deficits in social communication ability and repetitive behavior. The pathophysiological events involved in the brain of this complex disease are still unclear.

METHODS

In this study, we aimed to profile the gene expression signatures of brain cortex of ASD patients, by using two publicly available RNA-seq studies, in order to discover new ASD-related genes.

RESULTS

We detected 1567 differentially expressed genes (DEGs) by meta-analysis, where 1194 were upregulated and 373 were downregulated genes. Several ASD-related genes previously reported were also identified. Our meta-analysis identified 235 new DEGs that were not detected using the individual RNA-seq studies used. Some of those genes, including seven DEGs (PAK1, DNAH17, DOCK8, DAPP1, PCDHAC2, and ERBIN, SLC7A7), have been confirmed in previous reports to be associated with ASD. Gene Ontology (GO) and pathways analysis showed several molecular pathways enriched by the DEGs, namely, osteoclast differentiation, TNF signaling pathway, complement and coagulation cascade. Topological analysis of protein-protein interaction of the ASD brain cortex revealed proteomics hub gene signatures: MYC, TP53, HDAC1, CDK2, BAG3, CDKN1A, GABARAPL1, EZH2, VIM, and TRAF1. We also identified the transcriptional factors (TFs) regulating DEGs, namely, FOXC1, GATA2, YY1, FOXL1, USF2, NFIC, NFKB1, E2F1, TFAP2A, HINFP.

CONCLUSION

Novel core genes and molecular signatures involved with ASD were identified by our meta-analysis.

Neurodevelopmental Disorders: From Genetics to Functional Pathways

Neurodevelopmental disorders (NDDs) are a class of disorders affecting brain development and function and are characterized by wide genetic and clinical variability. In this review, we discuss the multiple factors that influence the clinical presentation of NDDs, with particular attention to gene vulnerability, mutational load, and the two-hit model. Despite the complex architecture of mutational events associated with NDDs, the various proteins involved appear to converge on common pathways, such as synaptic plasticity/function, chromatin remodelers and the mammalian target of rapamycin (mTOR) pathway. A thorough understanding of the mechanisms behind these pathways will hopefully lead to the identification of candidates that could be targeted for treatment approaches.

Prenatal Origins of ASD: The When, What, and How of ASD Development

Autism spectrum disorder (ASD) is a largely heritable, multistage prenatal disorder that impacts a child's ability to perceive and react to social information. Most ASD risk genes are expressed prenatally in many ASD-relevant brain regions and fall into two categories: broadly expressed regulatory genes that are expressed in the brain and other organs, and brain-specific genes. In trimesters one to three (Epoch-1), one set of broadly expressed (the majority) and brain-specific risk genes disrupts cell proliferation, neurogenesis, migration, and cell fate, while in trimester three and early postnatally (Epoch-2) another set (the majority being brain specific) disrupts neurite outgrowth, synaptogenesis, and the 'wiring' of the cortex. A proposed model is that upstream, highly interconnected regulatory ASD gene mutations disrupt transcriptional programs or signaling pathways resulting in dysregulation of downstream processes such as proliferation, neurogenesis, synaptogenesis, and neural activity. Dysregulation of signaling pathways is correlated with ASD social symptom severity. Since the majority of ASD risk genes are broadly expressed, many ASD individuals may benefit by being treated as having a broader medical disorder. An important future direction is the noninvasive study of ASD cell biology.

Translating insights from neuropsychiatric genetics and genomics for precision psychiatry

The primary aim of precision medicine is to tailor healthcare more closely to the needs of individual patients. This requires progress in two areas: the development of more precise treatments and the ability to identify patients or groups of patients in the clinic for whom such treatments are likely to be the most effective. There is widespread optimism that advances in genomics will facilitate both of these endeavors. It can be argued that of all medical specialties psychiatry has most to gain in these respects, given its current reliance on syndromic diagnoses, the minimal foundation of existing mechanistic knowledge, and the substantial heritability of psychiatric phenotypes. Here, we review recent advances in psychiatric genomics and assess the likely impact of these findings on attempts to develop precision psychiatry. Emerging findings indicate a high degree of polygenicity and that genetic risk maps poorly onto the diagnostic categories used in the clinic. The highly polygenic and pleiotropic nature of psychiatric genetics will impact attempts to use genomic data for prediction and risk stratification, and also poses substantial challenges for conventional approaches to gaining biological insights from genetic findings. While there are many challenges to overcome, genomics is building an empirical platform upon which psychiatry can now progress towards better understanding of disease mechanisms, better treatments, and better ways of targeting treatments to the patients most likely to benefit, thus paving the way for precision psychiatry.