Integrative genomic analyses for identification and prioritization of long non-coding RNAs associated with autism

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.

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.

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.

Signalling pathways in autism spectrum disorder: mechanisms and therapeutic implications

Autism spectrum disorder (ASD) is a prevalent and complex neurodevelopmental disorder which has strong genetic basis. Despite the rapidly rising incidence of autism, little is known about its aetiology, risk factors, and disease progression. There are currently neither validated biomarkers for diagnostic screening nor specific medication for autism. Over the last two decades, there have been remarkable advances in genetics, with hundreds of genes identified and validated as being associated with a high risk for autism. The convergence of neuroscience methods is becoming more widely recognized for its significance in elucidating the pathological mechanisms of autism. Efforts have been devoted to exploring the behavioural functions, key pathological mechanisms and potential treatments of autism. Here, as we highlight in this review, emerging evidence shows that signal transduction molecular events are involved in pathological processes such as transcription, translation, synaptic transmission, epigenetics and immunoinflammatory responses. This involvement has important implications for the discovery of precise molecular targets for autism. Moreover, we review recent insights into the mechanisms and clinical implications of signal transduction in autism from molecular, cellular, neural circuit, and neurobehavioural aspects. Finally, the challenges and future perspectives are discussed with regard to novel strategies predicated on the biological features of autism.

Recent Major Transcriptomics and Epitranscriptomics Contributions toward Personalized and Precision Medicine

With the advent of genome-wide screening methods-beginning with microarray technologies and moving onto next generation sequencing methods-the era of precision and personalized medicine was born. Genomics led the way, and its contributions are well recognized. However, "other-omics" fields have rapidly emerged and are becoming as important toward defining disease causes and exploring therapeutic benefits. In this review, we focus on the impacts of transcriptomics, and its extension-epitranscriptomics-on personalized and precision medicine efforts. There has been an explosion of transcriptomic studies particularly in the last decade, along with a growing number of recent epitranscriptomic studies in several disease areas. Here, we summarize and overview major efforts for cancer, cardiovascular disease, and neurodevelopmental disorders (including autism spectrum disorder and intellectual disability) for transcriptomics/epitranscriptomics in precision and personalized medicine. We show that leading advances are being made in both diagnostics, and in investigative and landscaping disease pathophysiological studies. As transcriptomics/epitranscriptomics screens become more widespread, it is certain that they will yield vital and transformative precision and personalized medicine contributions in ways that will significantly further genomics gains.

Brain-immune interactions in neuropsychiatric disorders: Lessons from transcriptome studies for molecular targeting

Understanding the pathophysiological mechanisms of neuropsychiatric disorders has been a challenging quest for neurobiologists. Recent years have witnessed enormous technological advances in the field of neuroimmunology, blurring boundaries between the central nervous system and the periphery. Consequently, the discipline has expanded to cover interactions between the nervous and immune systems in health and diseases. The complex interplay between the peripheral and central immune pathways in neuropsychiatric disorders has recently been documented in various studies, but the genetic determinants remain elusive. Recent transcriptome studies have identified dysregulated genes involved in peripheral immune cell activation, blood-brain barrier integrity, glial cell activation, and synaptic plasticity in major depressive disorder, bipolar disorder, autism spectrum disorder, and schizophrenia. Herein, the key transcriptomic techniques applied in investigating differentially expressed genes and pathways responsible for altered brain-immune interactions in neuropsychiatric disorders are discussed. The application of transcriptomics that can aid in identifying molecular targets in various neuropsychiatric disorders is highlighted.

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.

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

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

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.

Diverse lncRNA mechanisms in brain development and disease

Long noncoding RNAs (lncRNAs) are a diverse and pervasive class of genes. Recent studies in the mammalian brain have uncovered several novel mechanisms. LncRNA loci are often located in proximity to developmental transcriptional factors. The lncRNA product may act like a transcription factor to control distantly located genes, or in other instances, the lncRNA loci contain DNA regulatory elements that act locally on neighboring genes. Circular RNAs are covalently closed single-stranded RNAs that can control neuronal function by acting as microRNA sponges and additional mechanisms. LncRNAs can also engage in target-directed microRNA degradation to shape the pool of microRNAs and translation. Thus, diverse mechanisms allow lncRNAs to act in the nucleus and cytoplasm to control neuronal fate and function.

Genomics, transcriptomics, proteomics and big data analysis in the discovery of new diagnostic markers and targets for therapy development

Highly complex endophenotypes and underlying molecular mechanisms have prevented effective diagnosis and treatment of autism spectrum disorder. Despite extensive studies to identify relevant biosignatures, no biomarker and therapeutic targets are available in the current clinical practice. While our current knowledge is still largely incomplete, -omics technology and machine learning-based big data analysis have provided novel insights on the etiology of autism spectrum disorders, elucidating systemic impairments that can be translated into biomarker and therapy target candidates. However, more integrated and sophisticated approaches are vital to realize molecular stratification and individualized treatment strategy. Ultimately, systemic approaches based on -omics and big data analysis will significantly contribute to more effective biomarker and therapy development for autism spectrum disorder.

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.

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.

Epigenetic Regulation of the Social Brain

Social behavior, a highly adaptive and crucial component of mammalian life, is regulated by particularly sensitive regulatory brain mechanisms. Substantial evidence implicates classical epigenetic mechanisms including histone modifications, DNA methylation, and nucleosome remodeling as well as nonclassical mechanisms mediated by noncoding RNA in the regulation of social behavior. These mechanisms collectively form the 'epigenetic network' that orchestrates genomic integration of salient and transient social experiences. Consequently, its dysregulation has been linked to behavioral deficits and psychopathologies. This review focuses on the role of the epigenetic network in regulating the enduring effects of social experiences during early-life, adolescence, and adulthood. We discuss research in animal models, primarily rodents, and associations between dysregulation of epigenetic mechanisms and human psychopathologies, specifically autism spectrum disorder (ASD) and schizophrenia.

Long noncoding RNA C21orf121/bone morphogenetic protein 2/microRNA-140-5p gene network promotes directed differentiation of stem cells from human exfoliated deciduous teeth to neuronal cells

Previous studies have revealed that long noncoding RNA (lncRNA) and microRNA play a crucial role in autism, which is a childhood neurodevelopmental disorder with complicated genetic origins. Hence, the study concerns whether lncRNA C21orf121/bone morphogenetic proteins 2 (BMP2)/miR-140-5p gene network affects directed differentiation of stem cells from human exfoliated deciduous teeth (SHED) to neuronal cells in rats with autism. Autism models were successfully established. The neuron cells that differentiated from SHED cell were identified. The expression of lncRNA C21orf121, miR-140-5p, BMP2, Nestin, βIII-tubulin, and microtubule-associated protein 2 (MAP2) and the expression of neuron-specific enolase (NSE) were examined. Besides, the gap junction (GJ) function of SHED, the intracellular free Ca ²⁺ concentration, and the social behavior and repetitive stereotyped movements of rats in autism were detected. The target relationship between lncRNA C21orf121 and miR-140-5p and that between miR-140-5p and BMP2 were also verified. Firstly, we successfully isolated SHED and identified the differentiated neurons of SHED. Besides, the expression of BMP2, MAP2, Nestin, βIII-tubulin, NSE positive rate, GJ function, and intracellular free Ca ²⁺ concentration were increased with the upregulation of C21orf121 and downregulation of miR-140-5p, and accumulated time of repetitive stereotyped movements decreased and the frequency of social behavior increased. The results indicate that lncRNA C21orf121 as a competing endogenous RNA competes with BMP2 binding to miR-140-5p, thereby promoting SHED to differentiate into neuronal cells via upregulating BMP2 expression.

Nonprotein-coding RNAs in Fetal Alcohol Spectrum Disorders

Early developmental exposure to ethanol, a known teratogen, can result in a range of neurodevelopmental disorders, collectively referred to as Fetal Alcohol Spectrum Disorders (FASDs). Changes in the environment, including exposure to teratogens, can result in long term alterations to the epigenetic landscape of a cell, thereby altering gene expression. Noncoding RNAs (ncRNAs) can affect transcription and translation of networks of genes. ncRNAs are dynamically expressed during development and have been identified as a target of alcohol. ncRNAs therefore make for attractive targets for novel therapeutics to address the developmental deficits associated with FASDs.