Aberrant expression of long noncoding RNAs in autistic brain

Hidden regulators: the emerging roles of lncRNAs in brain development and disease

Long non-coding RNAs (lncRNAs) have emerged as critical players in brain development and disease. These non-coding transcripts, which once considered as "transcriptional junk," are now known for their regulatory roles in gene expression. In brain development, lncRNAs participate in many processes, including neurogenesis, neuronal differentiation, and synaptogenesis. They employ their effect through a wide variety of transcriptional and post-transcriptional regulatory mechanisms through interactions with chromatin modifiers, transcription factors, and other regulatory molecules. Dysregulation of lncRNAs has been associated with certain brain diseases, including Alzheimer's disease, Parkinson's disease, cancer, and neurodevelopmental disorders. Altered expression and function of specific lncRNAs have been implicated with disrupted neuronal connectivity, impaired synaptic plasticity, and aberrant gene expression pattern, highlighting the functional importance of this subclass of brain-enriched RNAs. Moreover, lncRNAs have been identified as potential biomarkers and therapeutic targets for neurological diseases. Here, we give a comprehensive review of the existing knowledge of lncRNAs. Our aim is to provide a better understanding of the diversity of lncRNA structure and functions in brain development and disease. This holds promise for unravelling the complexity of neurodevelopmental and neurodegenerative disorders, paving the way for the development of novel biomarkers and therapeutic targets for improved diagnosis and treatment.

Epigenetic mechanisms linking early-life adversities and mental health

Early-life adversities, whether prenatal or postnatal exposure, have been linked to adverse mental health outcomes later in life increasing the risk of several psychiatric disorders. Research on its neurobiological consequences demonstrated an association between exposure to adversities and persistent alterations in the structure, function, and connectivity of the brain. Consistent evidence supports the idea that regulation of gene expression through epigenetic mechanisms are involved in embedding the impact of early-life experiences in the genome and mediate between social environments and later behavioral phenotypes. In addition, studies from rodent models and humans suggest that these experiences and the acquired risk factors can be transmitted through epigenetic mechanisms to offspring and the following generations potentially contributing to a cycle of disease or disease risk. However, one of the important aspects of epigenetic mechanisms, unlike genetic sequences that are fixed and unchangeable, is that although the epigenetic markings are long-lasting, they are nevertheless potentially reversible. In this review, we summarize our current understanding of the epigenetic mechanisms involved in the mental health consequences derived from early-life exposure to malnutrition, maltreatment and poverty, adversities with huge and pervasive impact on mental health. We also discuss the evidence about transgenerational epigenetic inheritance in mammals and experimental data suggesting that suitable social and pharmacological interventions could reverse adverse epigenetic modifications induced by early-life negative social experiences. In this regard, these studies must be accompanied by efforts to determine the causes that promote these adversities and that result in health inequity in the population.

Role of regulatory non-coding RNAs in traumatic brain injury

Traumatic brain injury (TBI) is a potentially fatal health event that cannot be predicted in advance. After TBI occurs, it can have enduring consequences within both familial and social spheres. Yet, despite extensive efforts to improve medical interventions and tailor healthcare services, TBI still remains a major contributor to global disability and mortality rates. The prompt and accurate diagnosis of TBI in clinical contexts, coupled with the implementation of effective therapeutic strategies, remains an arduous challenge. However, a deeper understanding of changes in gene expression and the underlying molecular regulatory processes may alleviate this pressing issue. In recent years, the study of regulatory non-coding RNAs (ncRNAs), a diverse class of RNA molecules with regulatory functions, has been a potential game changer in TBI research. Notably, the identification of microRNAs (miRNAs), long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), and other ncRNAs has revealed their potential as novel diagnostic biomarkers and therapeutic targets for TBI, owing to their ability to regulate the expression of numerous genes. In this review, we seek to provide a comprehensive overview of the functions of regulatory ncRNAs in TBI. We also summarize regulatory ncRNAs used for treatment in animal models, as well as miRNAs, lncRNAs, and circRNAs that served as biomarkers for TBI diagnosis and prognosis. Finally, we discuss future challenges and prospects in diagnosing and treating TBI patients in the clinical settings.

Integrative analysis of long noncoding RNAs dysregulation and synapse-associated ceRNA regulatory axes in autism

Autism spectrum disorder (ASD) is a complex disorder of neurodevelopment, the function of long noncoding RNA (lncRNA) in ASD remains essentially unknown. In the present study, gene networks were used to explore the ASD disease mechanisms integrating multiple data types (for example, RNA expression, whole-exome sequencing signals, weighted gene co-expression network analysis, and protein-protein interaction) and datasets (five human postmortem datasets). A total of 388 lncRNAs and five co-expression modules were found to be altered in ASD. The downregulated co-expression M4 module was significantly correlated with ASD, enriched with autism susceptibility genes and synaptic signaling. Integrating lncRNAs from the M4 module and microRNA (miRNA) dysregulation data from the literature identified competing endogenous RNA (ceRNA) network. We identified the downregulated mRNAs that interact with miRNAs by the miRTarBase, miRDB, and TargetScan databases. Our analysis reveals that MIR600HG was downregulated in multiple brain tissue datasets and was closely associated with 9 autism-susceptible miRNAs in the ceRNA network. MIR600HG and target mRNAs (EPHA4, MOAP1, MAP3K9, STXBP1, PRKCE, and SCAMP5) were downregulated in the peripheral blood by quantitative reverse transcription polymerase chain reaction analysis (false discovery rate <0.05). Subsequently, we assessed the role of lncRNA dysregulation in altered mRNA levels. Experimental verification showed that some synapse-associated mRNAs were downregulated after the MIR600HG knockdown. BrainSpan project showed that the expression patterns of MIR600HG (primate-specific lncRNA) and synapse-associated mRNA were similar in different human brain regions and at different stages of development. A combination of support vector machine and random forest machine learning algorithms retrieved the marker gene for ASD in the ceRNA network, and the area under the curve of the diagnostic nomogram was 0.851. In conclusion, dysregulation of MIR600HG, a novel specific lncRNA associated with ASD, is responsible for the ASD-associated miRNA-mRNA axes, thereby potentially regulating synaptogenesis.

Anti-apoptotic capacity of MALAT1 on hippocampal neurons correlates with CASP3 DNA methylation in a mouse model of autism

Prior evidence has suggested the alleviatory effect of metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) on neuroinflammation in neurodegenerative diseases. This study primarily investigates the underlying mechanism of how the long non-coding RNA MALAT1 affects neuronal apoptosis in the hippocampus of mice with autism spectrum disorder (ASD). The findings demonstrate that CASP3 is highly expressed while MALAT1 is downregulated in the hippocampal neurons of autistic mice. MALAT1 mainly localizes within the cell nucleus and recruits DNA methyltransferases (including DNMT1, DNMT3a, and DNMT3b) to the promoter region of CASP3, promoting its methylation and further inhibiting its expression. In vitro experiments reveal that reducing MALAT1 expression promotes the expression of CASP3 and Bax while suppressing Bcl-2 expression, thereby enhancing cellular apoptosis. Conversely, increasing MALAT1 expression yields the opposite effect. Consequently, these results further confirm the role of MALAT1 in suppressing neuronal apoptosis in the hippocampus of mice with ASD through the regulation of CASP3 promoter methylation. Thus, this research unveils the significant roles of MALAT1 and CASP3 in the pathogenesis of ASD, offering new possibilities for future therapeutic interventions.

Study of lncRNAs in Pediatric Neurological Diseases: Methods, Analysis of the State-of-Art and Possible Therapeutic Implications

Long non-coding RNAs (lncRNAs) have emerged as crucial regulators in various cellular processes, and their roles in pediatric neurological diseases are increasingly being explored. This review provides an overview of lncRNA implications in the central nervous system, both in its physiological state and when a pathological condition is present. We describe the role of lncRNAs in neural development, highlighting their significance in processes such as neural stem cell proliferation, differentiation, and synaptogenesis. Dysregulation of specific lncRNAs is associated with multiple pediatric neurological diseases, such as neurodevelopmental or neurodegenerative disorders and brain tumors. The collected evidence indicates that there is a need for further research to uncover the full spectrum of lncRNA involvement in pediatric neurological diseases and brain tumors. While challenges exist, ongoing advancements in technology and our understanding of lncRNA biology offer hope for future breakthroughs in the field of pediatric neurology, leveraging lncRNAs as potential therapeutic targets and biomarkers.

Investigation of LncRNA PVT1 and MiR-21-5p Expression as Promising Novel Biomarkers for Autism Spectrum Disorder

The characteristics of ncRNA in children with autism spectrum disorder (ASD) were observed to disclose a theoretical basis for further research on molecular markers for early warning of ASD. Children with ASD and normal control children were recruited to collect peripheral blood RNA samples. The concentration of PVT1 and miR-21-5p was quantitatively analyzed by qRT-PCR. Pearson correlation coefficient method was used to evaluate the link between PVT1 level and miR-21-5p level of the children. Receiver operating characteristic (ROC) curves were applied to reckon the predictive value of PVT1, miR-21-5p, and their combination in ASD. The interconnection of PVT1 with miR-21-5p was represented by luciferase reporter assay. The targeted genes of miR-21-5p were predicted. The enrichment and protein interaction analysis of these genes was carried out to find the important core genes and analyze their value in ASD. In the disease group, the level of PVT1 was downregulated, while the content of miR-21-5p was upregulated. The expression level of serum miR-21-5p was negatively correlated with the level of PVT1. Luciferase reporter gene assay documented that PVT1 directly targeted miR-21-5p. ROC curve showed that PVT1, miR-21-5p, and their combination showed clinical value for disease diagnosis. The functional enrichment analysis showed that the targets of miR-21-5p participated in ASD by regulating related functions and pathways. Reduced expression of PVT1 and raised miR-21-5p were good diagnostic markers for ASD, which would provide a basis for effective prevention, early diagnosis, and early intervention of ASD.

Emerging concepts involving inhibitory and activating RNA functionalization towards the understanding of microcephaly phenotypes and brain diseases in humans

Microcephaly is characterized as a small head circumference, and is often accompanied by developmental disorders. Several candidate risk genes for this disease have been described, and mutations in non-coding regions are occasionally found in patients with microcephaly. Various non-coding RNAs (ncRNAs), such as microRNAs (miRNAs), SINEUPs, telomerase RNA component (TERC), and promoter-associated lncRNAs (pancRNAs) are now being characterized. These ncRNAs regulate gene expression, enzyme activity, telomere length, and chromatin structure through RNA binding proteins (RBPs)-RNA interaction. Elucidating the potential roles of ncRNA-protein coordination in microcephaly pathogenesis might contribute to its prevention or recovery. Here, we introduce several syndromes whose clinical features include microcephaly. In particular, we focus on syndromes for which ncRNAs or genes that interact with ncRNAs may play roles. We discuss the possibility that the huge ncRNA field will provide possible new therapeutic approaches for microcephaly and also reveal clues about the factors enabling the evolutionary acquisition of the human-specific "large brain."

The non-coding genome in Autism Spectrum Disorders

Autism Spectrum Disorders (ASD) are a group of neurodevelopmental disorders (NDDs) characterized by difficulties in social interaction and communication, repetitive behavior, and restricted interests. While ASD have been proven to have a strong genetic component, current research largely focuses on coding regions of the genome. However, non-coding DNA, which makes up for ∼99% of the human genome, has recently been recognized as an important contributor to the high heritability of ASD, and novel sequencing technologies have been a milestone in opening up new directions for the study of the gene regulatory networks embedded within the non-coding regions. Here, we summarize current progress on the contribution of non-coding alterations to the pathogenesis of ASD and provide an overview of existing methods allowing for the study of their functional relevance, discussing potential ways of unraveling ASD's "missing heritability".

Combining multi-omics approaches to prioritize the variant-regulated functional long non-coding RNAs in autism spectrum disorder

OBJECTIVE

Rising evidence has indicated that long non-coding RNA (lncRNA) may play an essential role in the development of autism spectrum disorder (ASD). However, identifying the lncRNAs associated with ASD and the risk loci on them remains a major challenge. This study aims to identify potential causative variants and explore the related mechanisms.

METHODS

By leveraging differential expression analysis, WGCNA analysis and cis-expression quantitative analysis, our study mined functional SNPs with the regulated long non-coding RNA genes in brain tissues. We recruited 611 ASD children and 645 healthy children in the case-control study.

RESULTS

Total 68 different expressed lncRNAs were validated by calculating the brain tissue-specific expression using RNA-seq data. By the WGCNA method, 9 functional lncRNAs classified as e-lncRNA were found to interact with 976 ASD risk genes. Furthermore, we mined functional SNPs regulated long non-coding RNAs in brain tissues. We analyzed the association between candidate SNPs and ASD risks in Chinese children, which showed BDNF-AS rs1565228 allele G to C reduced the risk of ASD (OR = 0.81, 95%CI: 0.66-0.98). Further bioinformatics analysis showed that the variant rs1565228 C>G with the low binding affinity of transcription factor SRF caused the decreased expression of lncRNA BDNF-AS. Our study revealed that rs2295412 in the non-coding sequence of the lncRNA gene region was significantly associated with the risk of ASD.

DISCUSSION

These findings suggested that the SNPs in the non-coding region of lncRNA may play important roles in the genetic susceptibility of ASD, which may facilitate the early screening of ASD.

Autism Spectrum Disorder: Neurodevelopmental Risk Factors, Biological Mechanism, and Precision Therapy

Autism spectrum disorder (ASD) is a heterogeneous, behaviorally defined neurodevelopmental disorder. Over the past two decades, the prevalence of autism spectrum disorders has progressively increased, however, no clear diagnostic markers and specifically targeted medications for autism have emerged. As a result, neurobehavioral abnormalities, neurobiological alterations in ASD, and the development of novel ASD pharmacological therapy necessitate multidisciplinary collaboration. In this review, we discuss the development of multiple animal models of ASD to contribute to the disease mechanisms of ASD, as well as new studies from multiple disciplines to assess the behavioral pathology of ASD. In addition, we summarize and highlight the mechanistic advances regarding gene transcription, RNA and non-coding RNA translation, abnormal synaptic signaling pathways, epigenetic post-translational modifications, brain-gut axis, immune inflammation and neural loop abnormalities in autism to provide a theoretical basis for the next step of precision therapy. Furthermore, we review existing autism therapy tactics and limits and present challenges and opportunities for translating multidisciplinary knowledge of ASD into clinical practice.

Inferring cell developmental stage-specific lncRNA regulation in the developing human neocortex with CDSlncR

Noncoding RNAs (ncRNAs) occupy ~98% of the transcriptome in human, and are usually not translated into proteins. Among ncRNAs, long non-coding RNAs (lncRNAs, >200 nucleotides) are important regulators to modulate gene expression, and are involved in many biological processes (e.g., cell development). To study lncRNA regulation, many computational approaches or tools have been proposed by using bulk transcriptomics data. Nevertheless, previous bulk data-driven methods are mostly limited to explore the lncRNA regulation regarding all of cells, instead of the lncRNA regulation specific to cell developmental stages. Fortunately, recent advance in single-cell sequencing data has provided a way to investigate cell developmental stage-specific lncRNA regulation. In this work, we present a novel computational method, CDSlncR (Cell Developmental Stage-specific lncRNA regulation), which combines putative lncRNA-target binding information with single-cell transcriptomics data to infer cell developmental stage-specific lncRNA regulation. For each cell developmental stage, CDSlncR constructs a cell developmental stage-specific lncRNA regulatory network in the cell developmental stage. To illustrate the effectiveness of CDSlncR, we apply CDSlncR into single-cell transcriptomics data of the developing human neocortex for exploring lncRNA regulation across different human neocortex developmental stages. Network analysis shows that the lncRNA regulation is unique in each developmental stage of human neocortex. As a case study, we also perform particular analysis on the cell developmental stage-specific lncRNA regulation related to 18 known lncRNA biomarkers in autism spectrum disorder. Finally, the comparison result indicates that CDSlncR is an effective method for predicting cell developmental stage-specific lncRNA targets. CDSlncR is available at https://github.com/linxi159/CDSlncR.

Construction of an immune-related ceRNA network to screen for potential diagnostic markers for autism spectrum disorder

Purpose: The diagnosis of autism spectrum disorder (ASD) is reliant on evaluation of patients' behavior. We screened the potential diagnostic and therapeutic targets of ASD through bioinformatics analysis. Methods: Four ASD-related datasets were downloaded from the Gene Expression Omnibus database. The "limma" package was employed to analyze differentially expressed messenger (m)RNAs, long non-coding (lnc)RNAs, and micro (mi)RNAs between ASD patients and healthy volunteers (HVs). We constructed a competing endogenous-RNA (ceRNA) network. Enrichment analyses of key genes were undertaken using the Gene Ontology database and Kyoto Encyclopedia of Genes and Genomes database. The ImmucellAI database was used to analyze differences in immune-cell infiltration (ICI) in ASD and HV samples. Synthetic analyses of the ceRNA network and ICI was done to obtain a diagnostic model using LASSO regression analysis. Analyses of receiver operating characteristic (ROC) curves were done for model verification. Results: The ceRNA network comprised 49 lncRNAs, 30 miRNAs, and 236 mRNAs. mRNAs were associated with 41 cellular components, 208 biological processes, 39 molecular functions, and 35 regulatory signaling pathways. Significant differences in the abundance of 10 immune-cell species between ASD patients and HVs were noted. Using the ceRNA network and ICI results, we constructed a diagnostic model comprising five immune cell-associated genes: adenosine triphosphate-binding cassette transporter A1 (ABCA1), DiGeorge syndrome critical region 2 (DGCR2), glucose-fructose oxidoreductase structural domain gene 1 (GFOD1), glutaredoxin (GLRX), and SEC16 homolog A (SEC16A). The diagnostic performance of our model was revealed by an area under the ROC curve of 0.923. Model verification was done using the validation dataset and serum samples of patients. Conclusion: ABCA1, DGCR2, GFOD1, GLRX, and SEC16A could be diagnostic biomarkers and therapeutic targets for ASD.

LncRNAs in neuropsychiatric disorders and computational insights for their prediction

Long non-coding RNAs (lncRNAs) are 200 nucleotide extended transcripts that do not encode proteins or possess limited coding ability. LncRNAs epigenetically control several biological functions such as gene regulation, transcription, mRNA splicing, protein interaction, and genomic imprinting. Over the years, drastic progress in understanding the role of lncRNAs in diverse biological processes has been made. LncRNAs are reported to show tissue-specific expression patterns suggesting their potential as novel candidate biomarkers for diseases. Among all other non-coding RNAs, lncRNAs are highly expressed within the brain-enriched or brain-specific regions of the neural tissues. They are abundantly expressed in the neocortex and pre-mature frontal regions of the brain. LncRNAs are co-expressed with the protein-coding genes and have a significant role in the evolution of functions of the brain. Any deregulation in the lncRNAs contributes to disruptions in normal brain functions resulting in multiple neurological disorders. Neuropsychiatric disorders such as schizophrenia, bipolar disease, autism spectrum disorders, and anxiety are associated with the abnormal expression and regulation of lncRNAs. This review aims to highlight the understanding of lncRNAs concerning normal brain functions and their deregulation associated with neuropsychiatric disorders. We have also provided a survey on the available computational tools for the prediction of lncRNAs, their protein coding potentials, and sub-cellular locations, along with a section on existing online databases with known lncRNAs, and their interactions with other molecules.

Focus on your locus with a massively parallel reporter assay

A growing number of variants associated with risk for neurodevelopmental disorders have been identified by genome-wide association and whole genome sequencing studies. As common risk variants often fall within large haplotype blocks covering long stretches of the noncoding genome, the causal variants within an associated locus are often unknown. Similarly, the effect of rare noncoding risk variants identified by whole genome sequencing on molecular traits is seldom known without functional assays. A massively parallel reporter assay (MPRA) is an assay that can functionally validate thousands of regulatory elements simultaneously using high-throughput sequencing and barcode technology. MPRA has been adapted to various experimental designs that measure gene regulatory effects of genetic variants within cis- and trans-regulatory elements as well as posttranscriptional processes. This review discusses different MPRA designs that have been or could be used in the future to experimentally validate genetic variants associated with neurodevelopmental disorders. Though MPRA has limitations such as it does not model genomic context, this assay can help narrow down the underlying genetic causes of neurodevelopmental disorders by screening thousands of sequences in one experiment. We conclude by describing future directions of this technique such as applications of MPRA for gene-by-environment interactions and pharmacogenetics.

LncRNA MEG3 activates CDH2 expression by recruitment of EP300 in valproic acid-induced autism spectrum disorder

LncRNAs partake in the biological processes contributing to development of autism spectrum disorder (ASD). The aim of the present study is to investigate the effects of lncRNA maternally expressed gene 3 (MEG3) on viability and apoptosis of hippocampal neurons from ASD rats. Rats with ASD were induced using valproic acid (VPA) with normal saline (NS) as control. We performed microarray analysis on hippocampal tissues of NS rats and ASD rats to screen the differentially expressed lncRNAs. MEG3 loss in rats alleviated the impairment of learning and memory abilities induced by VPA, and promoted neuronal viability and inhibited apoptosis. MEG3 could recruit the transcription factor E1A binding protein p300 (EP300) in the nucleus and promote the cadherin 2 (CDH2) expression. CDH2 depletion in rats ameliorated the impairment of learning and memory capacities in ASD rats. After upregulation of CDH2 in neurons with sh-MEG3, we found diminished viability and increased apoptosis in hippocampal neurons of ASD rats. Taken together, MEG3 supports activation of CDH2 via EP300, thus repressing the viability of hippocampal neurons. Therefore, MEG3 upregulation may be partially responsible for the pathogenesis of ASD.

The Role of Genetics, Epigenetics, and the Environment in ASD: A Mini Review

According to recent findings, variances in autism spectrum disorder (ASD) risk factors might be determined by several factors, including molecular genetic variants. Accumulated evidence has also revealed the important role of biological and chemical pathways in ASD aetiology. In this paper, we assess several reviews with regard to their quality of evidence and provide a brief outline of the presumed mechanisms of the genetic, epigenetic, and environmental risk factors of ASD. We also review some of the critical literature, which supports the basis of each factor in the underlying and specific risk patterns of ASD. Finally, we consider some of the implications of recent research regarding potential molecular targets for future investigations.

The Emerging Roles of Long Non-Coding RNAs in Intellectual Disability and Related Neurodevelopmental Disorders

In the human brain, long non-coding RNAs (lncRNAs) are widely expressed in an exquisitely temporally and spatially regulated manner, thus suggesting their contribution to normal brain development and their probable involvement in the molecular pathology of neurodevelopmental disorders (NDD). Bypassing the classic protein-centric conception of disease mechanisms, some studies have been conducted to identify and characterize the putative roles of non-coding sequences in the genetic pathogenesis and diagnosis of complex diseases. However, their involvement in NDD, and more specifically in intellectual disability (ID), is still poorly documented and only a few genomic alterations affecting the lncRNAs function and/or expression have been causally linked to the disease endophenotype. Considering that a significant fraction of patients still lacks a genetic or molecular explanation, we expect that a deeper investigation of the non-coding genome will unravel novel pathogenic mechanisms, opening new translational opportunities. Here, we present evidence of the possible involvement of many lncRNAs in the etiology of different forms of ID and NDD, grouping the candidate disease-genes in the most frequently affected cellular processes in which ID-risk genes were previously collected. We also illustrate new approaches for the identification and prioritization of NDD-risk lncRNAs, together with the current strategies to exploit them in diagnosis.

Vitamin A supplementation ameliorates prenatal valproic acid-induced autism-like behaviors in rats

INTRODUCTION

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by social deficits and repetitive stereotyped behaviors. Prenatal exposure to the anticonvulsant drug valproic acid (VPA) is reported to induce ASD in human and ASD-like phenotypes in rodents. Unfortunately, the etiology and pathogenesis of ASD remains unclear.

METHODS

Pregnant rats received an intraperitoneal injection of 600 mg/kg VPA on E12.5 to construct the ASD rat model in offspring. The different expression of long non-coding RNA (lncRNA) and mRNA profiles in the hippocampus were determined by RNA sequencing to investigate potential mechanisms of VPA-induced ASD. Gene Ontology (GO) and pathway enrichment analysis were performed to predict the function of dysregulated lncRNAs. Co-expression network and real-time polymerase chain reaction (RT-PCR) analysis were conducted to validate the potential regulatory lncRNA-mRNA network.

RESULTS

VPA increased the total distance, time spent in the central zone and self-grooming (open field test) in rats. Meanwhile, VPA induced social impairment (three-chamber sociability test) and repetitive behaviors (marble burying test). A total of 238 lncRNAs and 354 mRNAs were differentially expressed in the VPA group. In addition, the dysregulated lncRNAs were involved in neural function and developmental processes of ASD. 5 lncRNAs and 7 mRNAs were differently expressed and included in the lncRNA-mRNA co-expression network. RT-PCR confirmed the upregulation of 4 lncRNAs and 6 mRNAs, and identified a potential regulatory network of NONRATT021475.2 (lncRNA) and Desert hedgehog (Dhh). Moreover, VPA decreased the serum vitamin A (VA) levels in offspring rats on postnatal day (PND) 21 and 49. Importantly, VA supplementation significantly restored VPA-induced autism-related behaviors and upregulation of NONRATT021475.2 and Dhh in the hippocampus of ASD rats.

CONCLUSION

This study not only contributed to understand the importance of lncRNAs and mRNAs in the progression of ASD, but also identified VA as a potential therapy for the condition.

DATA AVAILABILITY

The data that support the findings of this study are available from the corresponding author with reasonable request.

Bringing machine learning to research on intellectual and developmental disabilities: taking inspiration from neurological diseases

Intellectual and Developmental Disabilities (IDDs), such as Down syndrome, Fragile X syndrome, Rett syndrome, and autism spectrum disorder, usually manifest at birth or early childhood. IDDs are characterized by significant impairment in intellectual and adaptive functioning, and both genetic and environmental factors underpin IDD biology. Molecular and genetic stratification of IDDs remain challenging mainly due to overlapping factors and comorbidity. Advances in high throughput sequencing, imaging, and tools to record behavioral data at scale have greatly enhanced our understanding of the molecular, cellular, structural, and environmental basis of some IDDs. Fueled by the "big data" revolution, artificial intelligence (AI) and machine learning (ML) technologies have brought a whole new paradigm shift in computational biology. Evidently, the ML-driven approach to clinical diagnoses has the potential to augment classical methods that use symptoms and external observations, hoping to push the personalized treatment plan forward. Therefore, integrative analyses and applications of ML technology have a direct bearing on discoveries in IDDs. The application of ML to IDDs can potentially improve screening and early diagnosis, advance our understanding of the complexity of comorbidity, and accelerate the identification of biomarkers for clinical research and drug development. For more than five decades, the IDDRC network has supported a nexus of investigators at centers across the USA, all striving to understand the interplay between various factors underlying IDDs. In this review, we introduced fast-increasing multi-modal data types, highlighted example studies that employed ML technologies to illuminate factors and biological mechanisms underlying IDDs, as well as recent advances in ML technologies and their applications to IDDs and other neurological diseases. We discussed various molecular, clinical, and environmental data collection modes, including genetic, imaging, phenotypical, and behavioral data types, along with multiple repositories that store and share such data. Furthermore, we outlined some fundamental concepts of machine learning algorithms and presented our opinion on specific gaps that will need to be filled to accomplish, for example, reliable implementation of ML-based diagnosis technology in IDD clinics. We anticipate that this review will guide researchers to formulate AI and ML-based approaches to investigate IDDs and related conditions.

Natural SINEUP RNAs in Autism Spectrum Disorders: RAB11B-AS1 Dysregulation in a Neuronal CHD8 Suppression Model Leads to RAB11B Protein Increase

CHD8 represents one of the highest confidence genetic risk factors implied in Autism Spectrum Disorders, with most mutations leading to CHD8 haploinsufficiency and the insurgence of specific phenotypes, such as macrocephaly, facial dysmorphisms, intellectual disability, and gastrointestinal complaints. While extensive studies have been conducted on the possible consequences of CHD8 suppression and protein coding RNAs dysregulation during neuronal development, the effects of transcriptional changes of long non-coding RNAs (lncRNAs) remain unclear. In this study, we focused on a peculiar class of natural antisense lncRNAs, SINEUPs, that enhance translation of a target mRNA through the activity of two RNA domains, an embedded transposable element sequence and an antisense region. By looking at dysregulated transcripts following CHD8 knock down (KD), we first identified RAB11B-AS1 as a potential SINEUP RNA for its domain configuration. Then we demonstrated that such lncRNA is able to increase endogenous RAB11B protein amounts without affecting its transcriptional levels. RAB11B has a pivotal role in vesicular trafficking, and mutations on this gene correlate with intellectual disability and microcephaly. Thus, our study discloses an additional layer of molecular regulation which is altered by CHD8 suppression. This represents the first experimental confirmation that naturally occurring SINEUP could be involved in ASD pathogenesis and underscores the importance of dysregulation of functional lncRNAs in neurodevelopment.

MEG3 lncRNA is over-expressed in autism spectrum disorder

Long non-coding RNAs (lncRNAs) comprise a group of regulatory transcripts which partake in the biological processes leading to development of neuropsychiatric disorders such as autism spectrum disorder (ASD). We measured circulatory levels of MEG3, GAS5, CYTOR, UCA1 lncRNAs and CRYBG3 gene in children with ASD and controls. Expression of MEG3 was remarkably higher in children with ASD when compared with controls (Posterior Beta = 2.919, SE = 0.51, P value < 0.0001). This difference was significant among male subgroups (Posterior Beta = 2.913, SE = 0.56, P value < 0.0001) as well as female subgroups (95% CrI for Beta = [0.29, 2.4], SE = 0.53, P value < 0.0001). Expression levels of other lncRNAs or CRYBG3 were not different between children with ASD and controls. Among children with ASD, the most robust correlations were found between GAS5/CYTOR, CYTOR/UCA1 and GAS5/UCA1 with correlation coefficients of 0.83, 0.83 and 0.73, respectively. Among controls, GAS5/UCA1, MEG3/UCA1 and GAS5/MEG3 pairs had the highest correlation coefficients (0.89, 0.84 and 0.80, respectively). ROC curve analysis revealed that MEG3 can distinguish children with ASD from controls with diagnostic power of 0.792 (P value < 0.0001). This value was higher among male subgroups (AUC = 0.84, P value < 0.0001) compared with female subgroups (AUC = 0.727, P value = 0.0727). The current research highlights the role of MEG3 in ASD and provides clues for depiction of an lncRNA network with possible contribution in the pathogenesis of ASD.

Sex- and tissue-specific effects of binge-level prenatal alcohol consumption on DNA methylation at birth

Background: Binge-level prenatal alcohol exposure (PAE) causes developmental abnormalities, which may be mediated in part by epigenetic mechanisms. Despite this, few studies have characterised the association of binge PAE with DNA methylation in offspring. Methods: We investigated the association between binge PAE and genome-wide DNA methylation profiles in a sex-specific manner in neonatal buccal and placental samples. Results: We identified no differentially methylated CpGs or differentially methylated regions (DMRs) at false discovery rate <0.05. However, using a sum-of-ranks approach, we identified a DMR in each tissue of female offspring. The DMR identified in buccal samples is located near regions with previously-reported associations to fetal alcohol spectrum disorder (FASD) and binge PAE. Conclusion: Our findings warrant further replication and highlight a potential epigenetic link between binge PAE and FASD.

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.

Emerging Role of Non-coding RNAs in Autism Spectrum Disorder

Autism spectrum disorders (ASD) embrace a diverse set of neurodevelopmental diseases with a multifaceted genetic basis. Non-coding RNAs (ncRNAs) are among putative loci with critical participation in the development of ASD. Expression of some lncRNAs, namely RP11-466P24.2, SYP-AS1, STXBP5-AS1, and IFNG-AS1 has been decreased in ASD, while AK128569, CTD-2516F10.2, MSNP1AS, RPS10P2-AS1, LINC00693, LINC00689, NEAT1, TUG1, and Shank2-AS lncRNAs have been over-expressed in ASD. Expression of several miRNAs which are implicated in the immunological developmental, immune responses, and protein synthesis as well as those participating in the regulation of PI3K/Akt/mTOR and EGFR signaling pathways is dysregulated in the context of ASD. In the present article, we describe investigations which appraised the role of lncRNAs, miRNAs, and circRNAs in the pathobiology of ASD.

The Epigenome in Neurodevelopmental Disorders

Neurodevelopmental diseases (NDDs), such as autism spectrum disorders, epilepsy, and schizophrenia, are characterized by diverse facets of neurological and psychiatric symptoms, differing in etiology, onset and severity. Such symptoms include mental delay, cognitive and language impairments, or restrictions to adaptive and social behavior. Nevertheless, all have in common that critical milestones of brain development are disrupted, leading to functional deficits of the central nervous system and clinical manifestation in child- or adulthood. To approach how the different development-associated neuropathologies can occur and which risk factors or critical processes are involved in provoking higher susceptibility for such diseases, a detailed understanding of the mechanisms underlying proper brain formation is required. NDDs rely on deficits in neuronal identity, proportion or function, whereby a defective development of the cerebral cortex, the seat of higher cognitive functions, is implicated in numerous disorders. Such deficits can be provoked by genetic and environmental factors during corticogenesis. Thereby, epigenetic mechanisms can act as an interface between external stimuli and the genome, since they are known to be responsive to external stimuli also in cortical neurons. In line with that, DNA methylation, histone modifications/variants, ATP-dependent chromatin remodeling, as well as regulatory non-coding RNAs regulate diverse aspects of neuronal development, and alterations in epigenomic marks have been associated with NDDs of varying phenotypes. Here, we provide an overview of essential steps of mammalian corticogenesis, and discuss the role of epigenetic mechanisms assumed to contribute to pathophysiological aspects of NDDs, when being disrupted.

Genetic contributions to autism spectrum disorder

Autism spectrum disorder (autism) is a heterogeneous group of neurodevelopmental conditions characterized by early childhood-onset impairments in communication and social interaction alongside restricted and repetitive behaviors and interests. This review summarizes recent developments in human genetics research in autism, complemented by epigenetic and transcriptomic findings. The clinical heterogeneity of autism is mirrored by a complex genetic architecture involving several types of common and rare variants, ranging from point mutations to large copy number variants, and either inherited or spontaneous (de novo). More than 100 risk genes have been implicated by rare, often de novo, potentially damaging mutations in highly constrained genes. These account for substantial individual risk but a small proportion of the population risk. In contrast, most of the genetic risk is attributable to common inherited variants acting en masse, each individually with small effects. Studies have identified a handful of robustly associated common variants. Different risk genes converge on the same mechanisms, such as gene regulation and synaptic connectivity. These mechanisms are also implicated by genes that are epigenetically and transcriptionally dysregulated in autism. Major challenges to understanding the biological mechanisms include substantial phenotypic heterogeneity, large locus heterogeneity, variable penetrance, and widespread pleiotropy. Considerable increases in sample sizes are needed to better understand the hundreds or thousands of common and rare genetic variants involved. Future research should integrate common and rare variant research, multi-omics data including genomics, epigenomics, and transcriptomics, and refined phenotype assessment with multidimensional and longitudinal measures.

Regulatory role of long non coding RNAs (lncRNAs) in neurological disorders: From novel biomarkers to promising therapeutic strategies

Long non coding RNAs (lncRNAs) are non-protein or low-protein coding transcripts that contain more than 200 nucleotides. They representing a large share of the cell's transcriptional output, demonstrate functional attributes viz. tissue-specific expression, determination of cell fate, controlled expression, RNA processing and editing, dosage compensation, genomic imprinting, conserved evolutionary traits etc. These long non coding variants are well associated with pathogenicity of various diseases including the neurological disorders like Alzheimer's disease, schizophrenia, Huntington's disease, Parkinson's disease etc. Neurological disorders are widespread and there knowing the underlying mechanisms become crucial. The lncRNAs take part in the pathogenesis by a plethora of mechanisms like decoy, scaffold, mi-RNA sequestrator, histone modifiers and in transcriptional interference. Detailed knowledge of the role of lncRNAs can help to use them further as novel biomarkers for therapeutic aspects. Here, in this review we discuss regulation and functional roles of lncRNAs in eight neurological diseases and psychiatric disorders, and the mechanisms by which they act. With these, we try to establish their roles as potential markers and viable diagnostic tools in these disorders.

Molecular Dysregulation in Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) comprises a heterogeneous group of neurodevelopmental disorders with a strong heritable genetic component. At present, ASD is diagnosed solely by behavioral criteria. Advances in genomic analysis have contributed to numerous candidate genes for the risk of ASD, where rare mutations and s common variants contribute to its susceptibility. Moreover, studies show rare de novo variants, copy number variation and single nucleotide polymorphisms (SNPs) also impact neurodevelopment signaling. Exploration of rare and common variants involved in common dysregulated pathways can provide new diagnostic and therapeutic strategies for ASD. Contributions of current innovative molecular strategies to understand etiology of ASD will be explored which are focused on whole exome sequencing (WES), whole genome sequencing (WGS), microRNA, long non-coding RNAs and CRISPR/Cas9 models. Some promising areas of pharmacogenomic and endophenotype directed therapies as novel personalized treatment and prevention will be discussed.

Systematic analysis of Long non-coding RNAs reveals diagnostic biomarkers and potential therapeutic drugs for intervertebral disc degeneration

Long non-coding RNAs (lncRNAs) are related to a variety of human diseases. However, little is known about the role of lncRNA in intervertebral disc degeneration (IDD). LncRNA expression profile of human IDD were downloaded from Gene Expression Omnibus (GEO) database. Potential biomarkers and therapeutic drugs for IDD were analyzed by weighted gene co-expression network analysis (WGCNA), R software package Limma, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). We identified 1455 differentially expressed genes and 423 differentially expressed lncRNAs. Twenty-six co-expression modules were obtained, among them, the tan, brown, and turquoise modules were most closely related to IDD. The turquoise module contained a large number of differential expressed lncRNAs and genes, these genes were mainly enriched in the MAPK signaling pathway, TGF-beta signaling pathway. Furthermore, we obtained 11,857 LmiRM-Degenerated, these lncRNAs and genes showed higher differential expression multiples and higher expression correlation. After constructing a disease-gene interaction network, 25 disease-specific genes and 9 disease-specific lncRNAs were identified. Combined with the drug-target gene interaction network, three drugs, namely, Calcium citrate, Calcium Phosphate, and Calcium phosphate dihydrate, which may have curative effects on IDD, were determined. Finally, a genetic diagnosis model and lncRNA diagnosis model with 100% diagnostic performance in both the training data set and the validation data set were established based on these genes and lncRNA. This study provided new diagnostic features for IDD and could help design personalized treatment of IDD.

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

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

Long Non-Coding RNA (lncRNA) Roles in Cell Biology, Neurodevelopment and Neurological Disorders

Development is a complex process regulated both by genetic and epigenetic and environmental clues. Recently, long non-coding RNAs (lncRNAs) have emerged as key regulators of gene expression in several tissues including the brain. Altered expression of lncRNAs has been linked to several neurodegenerative, neurodevelopmental and mental disorders. The identification and characterization of lncRNAs that are deregulated or mutated in neurodevelopmental and mental health diseases are fundamental to understanding the complex transcriptional processes in brain function. Crucially, lncRNAs can be exploited as a novel target for treating neurological disorders. In our review, we first summarize the recent advances in our understanding of lncRNA functions in the context of cell biology and then discussing their association with selected neuronal development and neurological disorders.

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.

Long Noncoding RNAs-Crucial Players Organizing the Landscape of the Neuronal Nucleus

The ability to regulate chromatin organization is particularly important in neurons, which dynamically respond to external stimuli. Accumulating evidence shows that lncRNAs play important architectural roles in organizing different nuclear domains like inactive chromosome X, splicing speckles, paraspeckles, and Gomafu nuclear bodies. LncRNAs are abundantly expressed in the nervous system where they may play important roles in compartmentalization of the cell nucleus. In this review we will describe the architectural role of lncRNAs in the nuclei of neuronal cells.

Non-Syndromic Intellectual Disability and Its Pathways: A Long Noncoding RNA Perspective

Non-syndromic intellectual disability (NS-ID or idiopathic) is a complex neurodevelopmental disorder that represents a global health issue. Although many efforts have been made to characterize it and distinguish it from syndromic intellectual disability (S-ID), the highly heterogeneous aspect of this disorder makes it difficult to understand its etiology. Long noncoding RNAs (lncRNAs) comprise a large group of transcripts that can act through various mechanisms and be involved in important neurodevelopmental processes. In this sense, comprehending the roles they play in this intricate context is a valuable way of getting new insights about how NS-ID can arise and develop. In this review, we attempt to bring together knowledge available in the literature about lncRNAs involved with molecular and cellular pathways already described in intellectual disability and neural function, to better understand their relevance in NS-ID and the regulatory complexity of this disorder.

Impaired expression of the COSMOC/MOCOS gene unit in ASD patient stem cells

Autism spectrum disorders (ASD) are complex neurodevelopmental disorders with a very large number of risk loci detected in the genome. However, at best, each of them explains rare cases, the majority being idiopathic. Genomic data on ASD derive mostly from post-mortem brain analyses or cell lines derived from blood or patient-specific induced pluripotent stem cells (iPSCS). Therefore, the transcriptional and regulatory architecture of the nervous system, particularly during early developmental periods, remains highly incomplete. To access the critical disturbances that may have occurred during pregnancy or early childhood, we recently isolated stem cells from the nasal cavity of anesthetized patients diagnosed for ASD and compared them to stem cells from gender-matched control individuals without neuropsychiatric disorders. This allowed us to discover MOCOS, a non-mutated molybdenum cofactor sulfurase-coding gene that was under-expressed in the stem cells of most ASD patients of our cohort, disturbing redox homeostasis and synaptogenesis. We now report that a divergent transcription upstream of MOCOS generates an antisense long noncoding RNA, to which we coined the name COSMOC. Surprisingly, COSMOC is strongly under-expressed in all ASD patients of our cohort with the exception of a patient affected by Asperger syndrome. Knockdown studies indicate that loss of COSMOC reduces MOCOS expression, destabilizes lipid and energy metabolisms of stem cells, but also affects neuronal maturation and splicing of synaptic genes. Impaired expression of the COSMOC/MOCOS bidirectional unit might shed new lights on the origins of ASD that could be of importance for future translational studies.

Genome-wide identification of novel long non-coding RNAs and their possible roles in hypoxic zebrafish brain

Long non-coding RNAs (lncRNAs) are the master regulators of numerous biological processes. Hypoxia causes oxidative stress with severe and detrimental effects on brain function and acts as a critical initiating factor in the pathogenesis of Alzheimer's disease (AD). From the RNA-Seq in the forebrain (Fb), midbrain (Mb), and hindbrain (Hb) regions of hypoxic and normoxic zebrafish, we identified novel lncRNAs, whose potential cis targets showed involvement in neuronal development and differentiation pathways. Under hypoxia, several lncRNAs and mRNAs were differentially expressed. Co-expression studies indicated that the Fb and Hb regions' potential lncRNA target genes were involved in the AD pathogenesis. In contrast, those in Mb (cry1b, per1a, cipca) was responsible for regulating circadian rhythm. We identified specific lncRNAs present in the syntenic regions between zebrafish and humans, possibly functionally conserved. We thus identified several conserved lncRNAs as the probable regulators of AD genes (adrb3b, cav1, stat3, bace2, apoeb, psen1, s100b).

LINC00473 as an Immediate Early Gene under the Control of the EGR1 Transcription Factor

Immediate early genes play an essential role in cellular responses to different stimuli. Many of them are transcription factors that regulate the secondary response gene expression. Non-coding RNAs may also be involved in this regulatory cascade. In fact, they are emerging as key actors of gene expression regulation, and evidence suggests that their dysregulation may underly pathological states. We previously took a snapshot of both coding and long non-coding RNAs differentially expressed in neuronal cells after brain-derived neurotrophic factor stimulation. Among these, the transcription factor EGR1 (a well-known immediate early gene) and LINC00473 (a primate-specific long non-coding RNA) that has emerged as an interesting RNA candidate involved in neuronal function and in cancer. In this work, we demonstrated that LINC00473 gene expression kinetics resembled that of immediate early genes in SH-SY5Y and HEK293T cells under different cell stimulation conditions. Moreover, we showed that the expression of LINC00473 is under the control of the transcription factor EGR1, providing evidence for an interesting functional relationship in neuron function.

Prediction and prioritization of autism-associated long non-coding RNAs using gene expression and sequence features

Background

Autism spectrum disorders (ASD) refer to a range of neurodevelopmental conditions, which are genetically complex and heterogeneous with most of the genetic risk factors also found in the unaffected general population. Although all the currently known ASD risk genes code for proteins, long non-coding RNAs (lncRNAs) as essential regulators of gene expression have been implicated in ASD. Some lncRNAs show altered expression levels in autistic brains, but their roles in ASD pathogenesis are still unclear.

Results

In this study, we have developed a new machine learning approach to predict candidate lncRNAs associated with ASD. Particularly, the knowledge learnt from protein-coding ASD risk genes was transferred to the prediction and prioritization of ASD-associated lncRNAs. Both developmental brain gene expression data and transcript sequence were found to contain relevant information for ASD risk gene prediction. During the pre-training phase of model construction, an autoencoder network was implemented for a representation learning of the gene expression data, and a random-forest-based feature selection was applied to the transcript-sequence-derived k-mers. Our models, including logistic regression, support vector machine and random forest, showed robust performance based on tenfold cross-validations as well as candidate prioritization with hypothetical loci. We then utilized the models to predict and prioritize a list of candidate lncRNAs, including some reported to be cis-regulators of known ASD risk genes, for further investigation.

Conclusions

Our results suggest that ASD risk genes can be accurately predicted using developmental brain gene expression data and transcript sequence features, and the models may provide useful information for functional characterization of the candidate lncRNAs associated with ASD.

Critical regulation of a NDIME/MEF2C axis in embryonic stem cell neural differentiation and autism

A microdeletion within human chromosome 5q14.3 has been associated with the occurrence of neurodevelopmental disorders, such as autism and intellectual disability, and MEF2C haploinsufficiency was identified as main cause. Here, we report that a brain-enriched long non-coding RNA, NDIME, is located near the MEF2C locus and is required for normal neural differentiation of mouse embryonic stem cells (mESCs). NDIME interacts with EZH2, the major component of polycomb repressive complex 2 (PRC2), and blocks EZH2-mediated trimethylation of histone H3 lysine 27 (H3K27me3) at the Mef2c promoter, promoting MEF2C transcription. Moreover, the expression levels of both NDIME and MEF2C were strongly downregulated in the hippocampus of a mouse model of autism, and the adeno-associated virus (AAV)-mediated expression of NDIME in the hippocampus of these mice significantly increased MEF2C expression and ameliorated autism-like behaviors. The results of this study reveal an epigenetic mechanism by which NDIME regulates MEF2C transcription and neural differentiation and suggest potential effects and therapeutic approaches of the NDIME/MEF2C axis in autism.

Interpreting the impact of noncoding structural variation in neurodevelopmental disorders

The emergence of novel sequencing technologies has greatly improved the identification of structural variation, revealing that a human genome harbors tens of thousands of structural variants (SVs). Since these SVs primarily impact noncoding DNA sequences, the next challenge is one of interpretation, not least to improve our understanding of human disease etiology. However, this task is severely complicated by the intricacy of the gene regulatory landscapes embedded within these noncoding regions, their incomplete annotation, as well as their dependence on the three-dimensional (3D) conformation of the genome. Also in the context of neurodevelopmental disorders (NDDs), reports of putatively causal, noncoding SVs are accumulating and understanding their impact on transcriptional regulation is presenting itself as the next step toward improved genetic diagnosis.

Biological embedding of experience: A primer on epigenetics

Biological embedding occurs when life experience alters biological processes to affect later life health and well-being. Although extensive correlative data exist supporting the notion that epigenetic mechanisms such as DNA methylation underlie biological embedding, causal data are lacking. We describe specific epigenetic mechanisms and their potential roles in the biological embedding of experience. We also consider the nuanced relationships between the genome, the epigenome, and gene expression. Our ability to connect biological embedding to the epigenetic landscape in its complexity is challenging and complicated by the influence of multiple factors. These include cell type, age, the timing of experience, sex, and DNA sequence. Recent advances in molecular profiling and epigenome editing, combined with the use of comparative animal and human longitudinal studies, should enable this field to transition from correlative to causal analyses.

Identification and Functional Analysis of Long Non-coding RNAs in Autism Spectrum Disorders

Genetic and environmental factors, alone or in combination, contribute to the pathogenesis of autism spectrum disorder (ASD). Although many protein-coding genes have now been identified as disease risk genes for ASD, a detailed illustration of long non-coding RNAs (lncRNAs) associated with ASD remains elusive. In this study, we first identified ASD-related lncRNAs based on genomic variant data of individuals with ASD from a twin study. In total, 532 ASD-related lncRNAs were identified, and 86.7% of these ASD-related lncRNAs were further validated by an independent copy number variant (CNV) dataset. Then, the functions and associated biological pathways of ASD-related lncRNAs were explored by enrichment analysis of their three different types of functional neighbor genes (i.e., genomic neighbors, competing endogenous RNA (ceRNA) neighbors, and gene co-expression neighbors in the cortex). The results have shown that most of the functional neighbor genes of ASD-related lncRNAs were enriched in nervous system development, inflammatory responses, and transcriptional regulation. Moreover, we explored the differential functions of ASD-related lncRNAs in distinct brain regions by using gene co-expression network analysis based on tissue-specific gene expression profiles. As a set, ASD-related lncRNAs were mainly associated with nervous system development and dopaminergic synapse in the cortex, but associated with transcriptional regulation in the cerebellum. In addition, a functional network analysis was conducted for the highly reliable functional neighbor genes of ASD-related lncRNAs. We found that all the highly reliable functional neighbor genes were connected in a single functional network, which provided additional clues for the action mechanisms of ASD-related lncRNAs. Finally, we predicted several potential drugs based on the enrichment of drug-induced pathway sets in the ASD-altered biological pathway list. Among these drugs, several (e.g., amoxapine, piperine, and diflunisal) were partly supported by the previous reports. In conclusion, ASD-related lncRNAs participated in the pathogenesis of ASD through various known biological pathways, which may be differential in distinct brain regions. Detailed investigation into ASD-related lncRNAs can provide clues for developing potential ASD diagnosis biomarkers and therapy.

Computational models for lncRNA function prediction and functional similarity calculation

From transcriptional noise to dark matter of biology, the rapidly changing view of long non-coding RNA (lncRNA) leads to deep understanding of human complex diseases induced by abnormal expression of lncRNAs. There is urgent need to discern potential functional roles of lncRNAs for further study of pathology, diagnosis, therapy, prognosis, prevention of human complex disease and disease biomarker detection at lncRNA level. Computational models are anticipated to be an effective way to combine current related databases for predicting most potential lncRNA functions and calculating lncRNA functional similarity on the large scale. In this review, we firstly illustrated the biological function of lncRNAs from five biological processes and briefly depicted the relationship between mutations or dysfunctions of lncRNAs and human complex diseases involving cancers, nervous system disorders and others. Then, 17 publicly available lncRNA function-related databases containing four types of functional information content were introduced. Based on these databases, dozens of developed computational models are emerging to help characterize the functional roles of lncRNAs. We therefore systematically described and classified both 16 lncRNA function prediction models and 9 lncRNA functional similarity calculation models into 8 types for highlighting their core algorithm and process. Finally, we concluded with discussions about the advantages and limitations of these computational models and future directions of lncRNA function prediction and functional similarity calculation. We believe that constructing systematic functional annotation systems is essential to strengthen the prediction accuracy of computational models, which will accelerate the identification process of novel lncRNA functions in the future.

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

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

Profiling of lincRNAs in human pluripotent stem cell derived forebrain neural progenitor cells

Human embryonic stem cells (hESCs) and induced pluripotent stem cells (iPSCs) can be differentiated into many different cell types of the central nervous system. One challenge when using pluripotent stem cells is to develop robust and efficient differentiation protocols that result in homogenous cultures of the desired cell type. Here, we have utilized the SMAD-inhibitors SB431542 and Noggin in a fully defined monolayer culture model to differentiate human pluripotent cells into homogenous forebrain neural progenitors. Temporal fate analysis revealed that this protocol results in forebrain-patterned neural progenitor cells that start to express early neuronal markers after two weeks of differentiation, allowing for the analysis of gene expression changes during neurogenesis. Using this system, we were able to identify many previously uncharacterized long intergenic non-coding RNAs that display dynamic expression during human forebrain neurogenesis.

Genomic data mining for functional annotation of human long noncoding RNAs

Life may have begun in an RNA world, which is supported by increasing evidence of the vital role that RNAs perform in biological systems. In the human genome, most genes actually do not encode proteins; they are noncoding RNA genes. The largest class of noncoding genes is known as long noncoding RNAs (lncRNAs), which are transcripts greater in length than 200 nucleotides, but with no protein-coding capacity. While some lncRNAs have been demonstrated to be key regulators of gene expression and 3D genome organization, most lncRNAs are still uncharacterized. We thus propose several data mining and machine learning approaches for the functional annotation of human lncRNAs by leveraging the vast amount of data from genetic and genomic studies. Recent results from our studies and those of other groups indicate that genomic data mining can give insights into lncRNA functions and provide valuable information for experimental studies of candidate lncRNAs associated with human disease.

Expression Analysis of BDNF, BACE1, and Their Natural Occurring Antisenses in Autistic Patients

Autism spectrum disorder (ASD) as a multifaceted neurological syndrome affects many aspects of neuropsychologic functions. Dysregulated expressions of several genes have been documented in ASD patients. The current project aimed at comparison of transcript levels of brain derived neurotrophic factor (BDNF), beta-site amyloid precursor protein cleaving enzyme 1 (BACE1), and their natural occurring antisenses in the peripheral blood of ASD individuals (n = 50, male/female = 38/12, age (mean ± standard deviation (SD)): 6 ± 1.4, age range: 3-8) and matched healthy persons (n = 50, male/female = 37/13, age (mean ± SD): 6 ± 1.74, age range: 3-8). We demonstrated remarkable higher levels of these genes in ASD patients. BACE1 transcript levels were correlated with transcript levels of BACE1-AS in all study participants. However, BACE1 transcript levels were not correlated with participants' age. BACE1-AS and BDNF transcript levels were correlated with age in female participants. Significant correlations were detected between transcript levels of BDNF and those of other genes in all study groups. The current results render further indications for contribution of BDNF, BACE1, and their antisenses in the course of ASD and suggested expression levels of these transcripts as putative markers for this neurobehavioral disorder. Such results might be applied in clinical setting for diagnosis of complicated ASD cases.