The Long Noncoding RNA Landscape in Amygdala Tissues from Schizophrenia Patients

MIAT LncRNA: A multifunctional key player in non-oncological pathological conditions

The discovery of non-coding RNAs (ncRNAs) has unveiled a wide range of transcripts that do not encode proteins but play key roles in several cellular and molecular processes. Long noncoding RNAs (lncRNAs) are specific class of ncRNAs that are longer than 200 nucleotides and have gained significant attention due to their diverse mechanisms of action and potential involvement in various pathological conditions. In the current review, the authors focus on the role of lncRNAs, specifically highlighting the Myocardial Infarction Associated Transcript (MIAT), in non-oncological context. MIAT is a nuclear lncRNA that has been directly linked to myocardial infarction and is reported to control post-transcriptional processes as a competitive endogenous RNA (ceRNA) molecule. It interacts with microRNAs (miRNAs), thereby limiting the translation and expression of their respective target messenger RNA (mRNA) and regulating protein expression. Yet, MIAT has been implicated in other numerous pathological conditions such as other cardiovascular diseases, autoimmune disease, neurodegenerative diseases, metabolic diseases, and many others. In this review, the authors emphasize that MIAT exhibits distinct expression patterns and functions across different pathological conditions and is emerging as potential diagnostic, prognostic, and therapeutic agent. Additionally, the authors highlight the regulatory role of MIAT and shed light on the involvement of lncRNAs and specifically MIAT in various non-oncological pathological conditions.

Unravelling the genetic basis of Schizophrenia

Neuronal development is a highly regulated mechanism that is central to organismal function in animals. In humans, disruptions to this process can lead to a range of neurodevelopmental phenotypes, including Schizophrenia (SCZ). SCZ has a significant genetic component, whereby an individual with an SCZ affected family member is eight times more likely to develop the disease than someone with no family history of SCZ. By examining a combination of genomic, transcriptomic and epigenomic datasets, large-scale 'omics' studies aim to delineate the relationship between genetic variation and abnormal cellular activity in the SCZ brain. Herein, we provide a brief overview of some of the key omics methods currently being used in SCZ research, including RNA-seq, the assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) and high-throughput chromosome conformation capture (3C) approaches (e.g., Hi-C), as well as single-cell/nuclei iterations of these methods. We also discuss how these techniques are being employed to further our understanding of the genetic basis of SCZ, and to identify associated molecular pathways, biomarkers, and candidate drug targets.

Ethanol- and PARP-Mediated Regulation of Ribosome-Associated Long Non-Coding RNA (lncRNA) in Pyramidal Neurons

Although, by definition, long noncoding RNAs (lncRNAs) are not translated, they are sometimes associated with ribosomes. In fact, some estimates suggest the existence of more than 50 K lncRNA molecules that could encode for small peptides. We examined the effects of an ethanol and Poly-ADP Ribose Polymerase (PARP) inhibitor (ABT-888) on ribosome-bound lncRNAs. Mice were administered via intraperitoneal injection (i.p.) either normal saline (CTL) or ethanol (EtOH) twice a day for four consecutive days. On the fourth day, a sub-group of mice administered with ethanol also received ABT-888 (EtOH+ABT). Ribosome-bound lncRNAs in CaMKIIα-expressing pyramidal neurons were measured using the Translating Ribosome Affinity Purification (TRAP) technique. Our findings show that EtOH altered the attachment of 107 lncRNA transcripts, while EtOH+ABT altered 60 lncRNAs. Among these 60 lncRNAs, 49 were altered by both conditions, while EtOH+ABT uniquely altered the attachment of 11 lncRNA transcripts that EtOH alone did not affect. To validate these results, we selected eight lncRNAs (Mir124-2hg, 5430416N02Rik, Snhg17, Snhg12, Snhg1, Mir9-3hg, Gas5, and 1110038B12Rik) for qRT-PCR analysis. The current study demonstrates that ethanol-induced changes in lncRNA attachment to ribosomes can be mitigated by the addition of the PARP inhibitor ABT-888.

Long non-coding RNAs in schizophrenia: Genetic variations, treatment markers and potential targeted signaling pathways

Schizophrenia (SZ), a complex and debilitating spectrum of psychiatric disorders, is now mainly attributed to multifactorial etiology that includes genetic and environmental factors. Long non-coding RNAs (lncRNAs) are gaining popularity as a way to better understand the comprehensive mechanisms beneath the clinical manifestation of SZ. Only in recent years has it been elucidated that mammalian genomes encode thousands of lncRNAs. Strikingly, roughly 30-40% of these lncRNAs are extensively expressed in different regions across the brain, which may be closely associated with SZ. The therapeutic and adverse effects of atypical antipsychotic drugs (AAPDs) are partially reflected by their role in the regulation of lncRNAs. This begs the question directly, do any lncRNAs exist as biomarkers for AAPDs treatment? Furthermore, we comprehend a range of mechanistic investigations that have revealed the regulatory roles for lncRNAs both involved in the brain and the periphery of SZ. More crucially, we also combine insights from a variety of signaling pathways to argue that lncRNAs probably play critical roles in SZ via their interactive downstream factors. This review provides a thorough understanding regarding dysregulation of lncRNAs, corresponding genetic alternations, as well as their potential regulatory roles in the pathology of SZ, which might help reveal useful therapeutic targets in SZ.

Dysregulation of Long Intergenic Non-Coding RNA Expression in the Schizophrenia Brain

BACKGROUND

Transcriptomic studies of the brains of schizophrenia (SZ) patients have produced abundant but largely inconsistent findings about the disorders pathophysiology. These inconsistencies might stem not only from the heterogeneous nature of the disorder, but also from the unbalanced focus on particular cortical regions and protein-coding genes. Compared to protein-coding transcripts, long intergenic non-coding RNA (lincRNA) display substantially greater brain region and disease response specificity, positioning them as prospective indicators of SZ-associated alterations. Further, a growing understanding of the systemic character of the disorder calls for a more systematic screening involving multiple diverse brain regions.

AIM

We aimed to identify and interpret alterations of the lincRNA expression profiles in SZ by examining the transcriptomes of 35 brain regions.

METHODS

We measured the transcriptome of 35 brain regions dissected from eight adult brain specimens, four SZ patients, and four healthy controls, using high-throughput RNA sequencing. Analysis of these data yielded 861 annotated human lincRNAs passing the detection threshold.

RESULTS

Of the 861 detected lincRNA, 135 showed significant region-dependent expression alterations in SZ (two-way ANOVA, BH-adjusted p 0.05) and 37 additionally showed significant differential expression between HC and SZ individuals in at least one region (post hoc Tukey test, p 0.05). For these 37 differentially expressed lincRNAs (DELs), 88% of the differences occurred in a cluster of brain regions containing axon-rich brain regions and cerebellum. Functional annotation of the DEL targets further revealed stark enrichment in neurons and synaptic transmission terms and pathways.

CONCLUSION

Our study highlights the utility of a systematic brain transcriptome analysis relying on the expression profiles measured across multiple brain regions and singles out white matter regions as a prospective target for further SZ research.

Current progress in understanding schizophrenia using genomics and pluripotent stem cells: A meta-analytical overview

Schizophrenia (SCZ) is a complex, heritable and polygenic neuropsychiatric disease, which disables the patients as well as decreases their life expectancy and quality of life. Common and rare variants studies on SCZ subjects have provided >100 genomic loci that hold importance in the context of SCZ pathophysiology. Transcriptomic studies from clinical samples have informed about the differentially expressed genes (DEGs) and non-coding RNAs in SCZ patients. Despite these advancements, no causative genes for SCZ were found and hence SCZ is difficult to recapitulate in animal models. In the last decade, induced Pluripotent Stem Cells (iPSCs)-based models have helped in understanding the neural phenotypes of SCZ by studying patient iPSC-derived 2D neuronal cultures and 3D brain organoids. Here, we have aimed to provide a simplistic overview of the current progress and advancements after synthesizing the enormous literature on SCZ genetics and SCZ iPSC-based models. Although further understanding of SCZ genetics and pathophysiological mechanisms using these technological advancements is required, the recent approaches have allowed to delineate important cellular mechanisms and biological pathways affected in SCZ.

Inferring miRNA sponge modules across major neuropsychiatric disorders

The role of non-coding RNAs in neuropsychiatric disorders (NPDs) is an emerging field of study. The long non-coding RNAs (lncRNAs) are shown to sponge the microRNAs (miRNAs) from interacting with their target mRNAs. Investigating the sponge activity of lncRNAs in NPDs will provide further insights into biological mechanisms and help identify disease biomarkers. In this study, a large-scale inference of the lncRNA-related miRNA sponge network of pan-neuropsychiatric disorders, including autism spectrum disorder (ASD), schizophrenia (SCZ), and bipolar disorder (BD), was carried out using brain transcriptomic (RNA-Seq) data. The candidate miRNA sponge modules were identified based on the co-expression pattern of non-coding RNAs, sharing of miRNA binding sites, and sensitivity canonical correlation. miRNA sponge modules are associated with chemical synaptic transmission, nervous system development, metabolism, immune system response, ribosomes, and pathways in cancer. The identified modules showed similar and distinct gene expression patterns depending on the neuropsychiatric condition. The preservation of miRNA sponge modules was shown in the independent brain and blood-transcriptomic datasets of NPDs. We also identified miRNA sponging lncRNAs that may be potential diagnostic biomarkers for NPDs. Our study provides a comprehensive resource on miRNA sponging in NPDs.

Two subtypes of schizophrenia identified by an individual-level atypical pattern of tensor-based morphometric measurement

Difficulties in parsing the multiaspect heterogeneity of schizophrenia (SCZ) based on current nosology highlight the need to subtype SCZ using objective biomarkers. Here, utilizing a large-scale multisite SCZ dataset, we identified and validated 2 neuroanatomical subtypes with individual-level abnormal patterns of the tensor-based morphometric measurement. Remarkably, compared with subtype 1, which showed moderate deficits of some subcortical nuclei and an enlarged striatum and cerebellum, subtype 2, which showed cerebellar atrophy and more severe subcortical nuclei atrophy, had a higher subscale score of negative symptoms, which is considered to be a core aspect of SCZ and is associated with functional outcome. Moreover, with the neuroimaging-clinic association analysis, we explored the detailed relationship between the heterogeneity of clinical symptoms and the heterogeneous abnormal neuroanatomical patterns with respect to the 2 subtypes. And the neuroimaging-transcription association analysis highlighted several potential heterogeneous biological factors that may underlie the subtypes. Our work provided an effective framework for investigating the heterogeneity of SCZ from multilevel aspects and may provide new insights for precision psychiatry.

Effects of Psychotropic Drugs on Ribosomal Genes and Protein Synthesis

Altered protein synthesis has been implicated in the pathophysiology of several neuropsychiatric disorders, particularly schizophrenia. Ribosomes are the machinery responsible for protein synthesis. However, there remains little information on whether current psychotropic drugs affect ribosomes and contribute to their therapeutic effects. We treated human neuronal-like (NT2-N) cells with amisulpride (10 µM), aripiprazole (0.1 µM), clozapine (10 µM), lamotrigine (50 µM), lithium (2.5 mM), quetiapine (50 µM), risperidone (0.1 µM), valproate (0.5 mM) or vehicle control for 24 h. Transcriptomic and gene set enrichment analysis (GSEA) identified that the ribosomal pathway was altered by these drugs. We found that three of the eight drugs tested significantly decreased ribosomal gene expression, whilst one increased it. Most changes were observed in the components of cytosolic ribosomes and not mitochondrial ribosomes. Protein synthesis assays revealed that aripiprazole, clozapine and lithium all decreased protein synthesis. Several currently prescribed psychotropic drugs seem to impact ribosomal gene expression and protein synthesis. This suggests the possibility of using protein synthesis inhibitors as novel therapeutic agents for neuropsychiatric disorders.

The Long Non-Coding RNA GOMAFU in Schizophrenia: Function, Disease Risk, and Beyond

Neuropsychiatric diseases are among the most common brain developmental disorders, represented by schizophrenia (SZ). The complex multifactorial etiology of SZ remains poorly understood, which reflects genetic vulnerabilities and environmental risks that affect numerous genes and biological pathways. Besides the dysregulation of protein-coding genes, recent discoveries demonstrate that abnormalities associated with non-coding RNAs, including microRNAs and long non-coding RNAs (lncRNAs), also contribute to the pathogenesis of SZ. lncRNAs are an actively evolving family of non-coding RNAs that harbor greater than 200 nucleotides but do not encode for proteins. In general, lncRNA genes are poorly conserved. The large number of lncRNAs specifically expressed in the human brain, together with the genetic alterations and dysregulation of lncRNA genes in the SZ brain, suggests a critical role in normal cognitive function and the pathogenesis of neuropsychiatric diseases. A particular lncRNA of interest is GOMAFU, also known as MIAT and RNCR2. Growing evidence suggests the function of GOMAFU in governing neuronal development and its potential roles as a risk factor and biomarker for SZ, which will be reviewed in this article. Moreover, we discuss the potential mechanisms through which GOMAFU regulates molecular pathways, including its subcellular localization and interaction with RNA-binding proteins, and how interruption to GOMAFU pathways may contribute to the pathogenesis of SZ.

What genes are differentially expressed in individuals with schizophrenia? A systematic review

Schizophrenia is a severe, complex mental disorder characterized by a combination of positive symptoms, negative symptoms, and impaired cognitive function. Schizophrenia is highly heritable (~80%) with multifactorial etiology and complex polygenic genetic architecture. Despite the large number of genetic variants associated with schizophrenia, few causal variants have been established. Gaining insight into the mechanistic influences of these genetic variants may facilitate our ability to apply these findings to prevention and treatment. Though there have been more than 300 studies of gene expression in schizophrenia over the past 15 years, none of the studies have yielded consistent evidence for specific genes that contribute to schizophrenia risk. The aim of this work is to conduct a systematic review and synthesis of case-control studies of genome-wide gene expression in schizophrenia. Comprehensive literature searches were completed in PubMed, EmBase, and Web of Science, and after a systematic review of the studies, data were extracted from those that met the following inclusion criteria: human case-control studies comparing the genome-wide transcriptome of individuals diagnosed with schizophrenia to healthy controls published between January 1, 2000 and June 30, 2020 in the English language. Genes differentially expressed in cases were extracted from these studies, and overlapping genes were compared to previous research findings from the genome-wide association, structural variation, and tissue-expression studies. The transcriptome-wide analysis identified different genes than those previously reported in genome-wide association, exome sequencing, and structural variation studies of schizophrenia. Only one gene, GBP2, was replicated in five studies. Previous work has shown that this gene may play a role in immune function in the etiology of schizophrenia, which in turn could have implications for risk profiling, prevention, and treatment. This review highlights the methodological inconsistencies that impede valid meta-analyses and synthesis across studies. Standardization of the use of covariates, gene nomenclature, and methods for reporting results could enhance our understanding of the potential mechanisms through which genes exert their influence on the etiology of schizophrenia. Although these results are promising, collaborative efforts with harmonization of methodology will facilitate the identification of the role of genes underlying schizophrenia.

LncRNA RP5-998N21.4 promotes immune defense through upregulation of IFIT2 and IFIT3 in schizophrenia

Schizophrenia is a complex polygenic disease that is affected by genetic, developmental, and environmental factors. Accumulating evidence indicates that environmental factors such as maternal infection and excessive prenatal neuroinflammation may contribute to the onset of schizophrenia by affecting epigenetic modification. We recently identified a schizophrenia-associated upregulated long noncoding RNA (lncRNA) RP5-998N21.4 by transcriptomic analysis of monozygotic twins discordant for schizophrenia. Importantly, we found that genes coexpressed with RP5-998N21.4 were enriched in immune defense-related biological processes in twin subjects and in RP5-998N21.4-overexpressing (OE) SK-N-SH cell lines. We then identified two genes encoding an interferon-induced protein with tetratricopeptide repeat (IFIT) 2 and 3, which play an important role in immune defense, as potential targets of RP5-998N21.4 by integrative analysis of RP5-998N21.4_OE-induced differentially expressed genes (DEGs) in SK-N-SH cells and RP5-998N21.4-coexpressed schizophrenia-associated DEGs from twin subjects. We further demonstrated that RP5-998N21.4 positively regulates the transcription of IFIT2 and IFIT3 by binding to their promoter regions and affecting their histone modifications. In addition, as a general nuclear coactivator, RMB14 (encoding RNA binding motif protein 14) was identified to facilitate the regulatory role of RP5-998N21.4 in IFIT2 and IFIT3 transcription. Finally, we observed that RP5-998N21.4_OE can enhance IFIT2- and IFIT3-mediated immune defense responses through activation of signal transducer and activator of transcription 1 (STAT1) signaling pathway in U251 astrocytoma cells under treatment with the viral mimetic polyinosinic: polycytidylic acid (poly I:C). Taken together, our findings suggest that lncRNA RP5-998N21.4 is a critical regulator of immune defense, providing etiological and therapeutic implications for schizophrenia.

The emerging role of long non-coding RNAs in schizophrenia

Schizophrenia (SZ) is a severe psychiatric disorder which is contributed by both genetic and environmental factors. However, at present, its specific pathogenesis is still not very clear, and there is a lack of objective and reliable biomarkers. Accumulating evidence indicates that long non-coding RNAs (lncRNAs) are involved in the pathophysiology of several psychiatric disorders, including SZ, and hold promise as potential biomarkers and therapeutic targets for psychiatric disorders. In this review, we summarize and discuss the role of lncRNAs in the pathogenesis of SZ and their potential value as biomarkers and therapeutic targets.

Non-coding RNAs and their bioengineering applications for neurological diseases

Engineering of cellular biomolecules is an emerging landscape presenting creative therapeutic opportunities. Recently, several strategies such as biomimetic materials, drug-releasing scaffolds, stem cells, and dynamic culture systems have been developed to improve specific biological functions, however, have been confounded with fundamental and technical roadblocks. Rapidly emerging investigations on the bioengineering prospects of mammalian ribonucleic acid (RNA) is expected to result in significant biomedical advances. More specifically, the current trend focuses on devising non-coding (nc) RNAs as therapeutic candidates for complex neurological diseases. Given the pleiotropic and regulatory role, ncRNAs such as microRNAs and long non-coding RNAs are deemed as attractive therapeutic candidates. Currently, the list of non-coding RNAs in mammals is evolving, which presents the plethora of hidden possibilities including their scope in biomedicine. Herein, we critically review on the emerging repertoire of ncRNAs in neurological diseases such as Alzheimer’s disease, Parkinson’s disease, neuroinflammation and drug abuse disorders. Importantly, we present the advances in engineering of ncRNAs to improve their biocompatibility and therapeutic feasibility as well as provide key insights into the applications of bioengineered non-coding RNAs that are investigated for neurological diseases.

LncRNA-AC006129.1 reactivates a SOCS3-mediated anti-inflammatory response through DNA methylation-mediated CIC downregulation in schizophrenia

Schizophrenia is a complex genetic disorder, the non-Mendelian features of which are likely complicated by epigenetic factors yet to be elucidated. Here, we performed RNA sequencing of peripheral blood RNA from monozygotic twins discordant for schizophrenia, and identified a schizophrenia-associated upregulated long noncoding RNA (lncRNA, AC006129.1) that participates in the inflammatory response by enhancing SOCS3 and CASP1 expression in schizophrenia patients and further validated this finding in AC006129.1-overexpressing mice showing schizophrenia-related abnormal behaviors. We find that AC006129.1 binds to the promoter region of the transcriptional repressor Capicua (CIC), facilitates the interactions of DNA methyltransferases with the CIC promoter, and promotes DNA methylation-mediated CIC downregulation, thereby ameliorating CIC-induced SOCS3 and CASP1 repression. Derepression of SOCS3 enhances the anti-inflammatory response by inhibiting JAK/STAT-signaling activation. Our findings reveal an epigenetic mechanism with etiological and therapeutic implications for schizophrenia.

Neuroepigenetics of psychiatric disorders: Focus on lncRNA

Understanding the pathology of psychiatric disorders is challenging due to their complexity and multifactorial origin. However, development of high-throughput technologies has allowed for better insight into their molecular signatures. Advancement of sequencing methodologies have made it possible to study not only the protein-coding but also the noncoding genome. It is now clear that besides the genetic component, different epigenetic mechanisms play major roles in the onset and development of psychiatric disorders. Among them, examining the role of long noncoding RNAs (lncRNAs) is a relatively new field. Here, we present an overview of what is currently known about the involvement of lncRNAs in schizophrenia, major depressive and bipolar disorders, as well as suicide. The diagnosis of psychiatric disorders mainly relies on clinical evaluation without using measurable biomarkers. In this regard, lncRNA may open new opportunities for development of molecular tests. However, so far only a small set of known lncRNAs have been characterized at molecular level, which means they have a long way to go before clinical implementation. Understanding how changes in lncRNAs affect the appearance and development of psychiatric disorders may lead to a more classified and objective diagnostic system, but also open up new therapeutic targets for these patients.

A Review on the Expression Pattern of Non-coding RNAs in Patients With Schizophrenia: With a Special Focus on Peripheral Blood as a Source of Expression Analysis

Schizophrenia is a destructive neuropsychiatric disease with a median prevalence of 4.0 per 1,000 during the whole life. Genome-wide association studies have shown the role of copy number variants (generally deletions) and certain alleles of common single nucleotide polymorphisms in the pathogenesis of schizophrenia. This disorder predominantly follows the polygenic inheritance model. Schizophrenia has also been linked with various alterations in the transcript and protein content of the brain tissue. Recent studies indicate that alterations in non-coding RNAs (ncRNAs) signature underlie a proportion of this dysregulation. High throughput microarray investigations have demonstrated momentous alterations in the expression of long non-coding RNAs (lncRNA) and microRNAs (miRNAs) in the circulation or post-mortem brain tissues of patients with schizophrenia compared with control samples. While Gomafu, PINT, GAS5, TCONS_l2_00021339, IFNG-AS1, FAS-AS1, PVT1, and TUG1 are among down-regulated lncRNAs in schizophrenia, MEG3, THRIL, HOXA-AS2, Linc-ROR, SPRY4-IT1, UCA1, and MALAT1 have been up-regulated in these patients. Moreover, several miRNAs, such as miR-30e, miR-130b, hsa-miR-130b, miR-193a-3p, hsa-miR-193a-3p, hsa-miR-181b, hsa-miR-34a, hsa-miR-346, and hsa-miR-7 have been shown to be dysregulated in blood or brain samples of patients with schizophrenia. Dysregulation of these transcripts in schizophrenia not only provides insight into the pathogenic processes of this disorder, it also suggests these transcripts could serve as diagnostic markers for schizophrenia. In the present paper, we explore the changes in the expression of miRNAs and lncRNAs in patients with schizophrenia.

Exploring concomitant neuroimaging and genetic alterations in patients with and patients without auditory verbal hallucinations: A pilot study and mini review

Objective

To explore concomitant neuroimaging and genetic alterations in patients with schizophrenia with or without auditory verbal hallucinations (AVHs), and to discuss the use of pattern recognition techniques in the development of an objective index that may improve diagnostic accuracy and treatment outcomes for schizophrenia.

Methods

The pilot study included patients with schizophrenia with AVHs (SCH-AVH group) and without AVHs (SCH-no AVH group). High throughput sequencing (HTS) was performed to explore RNA networks. Global functional connectivity density (gFCD) analysis was performed to assess functional connectivity (FC) alterations of the default mode network (DMN). Quantitative long noncoding (lnc) RNA and mRNA expression data were related to peak T values of gFCDs using Pearson’s correlation coefficient analysis.

Results

Compared with the SCH-no AVH group (n = 5), patients in the SCH-AVH group (n = 5) exhibited differences in RNA expression in RNA networks that were related to AVH severity, and displayed alterations in FC (reflected by gFCD differences) within the DMN (posterior cingulate and dorsal-medial prefrontal cortex), and in the right parietal lobe, left occipital lobe, and left temporal lobe. Peak lncRNA expression values were significantly related to peak gFCD T values within the DMN.

Conclusion

Among patients with schizophrenia, there are concomitant FC and genetic expression alterations associated with AVHs. Data from pattern recognition studies may inform the development of an objective index aimed at improving early diagnostic accuracy and treatment planning for patients with schizophrenia with and without AVHs.

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.

Machine Learning Reduced Gene/Non-Coding RNA Features That Classify Schizophrenia Patients Accurately and Highlight Insightful Gene Clusters

RNA-seq has been a powerful method to detect the differentially expressed genes/long non-coding RNAs (lncRNAs) in schizophrenia (SCZ) patients; however, due to overfitting problems differentially expressed targets (DETs) cannot be used properly as biomarkers. This study used machine learning to reduce gene/non-coding RNA features. Dorsolateral prefrontal cortex (dlpfc) RNA-seq data from 254 individuals was obtained from the CommonMind consortium. The average predictive accuracy for SCZ patients was 67% based on coding genes, and 96% based on long non-coding RNAs (lncRNAs). Machine learning is a powerful algorithm to reduce functional biomarkers in SCZ patients. The lncRNAs capture the characteristics of SCZ tissue more accurately than mRNA as the former regulate every level of gene expression, not limited to mRNA levels.

On the functional relevance of spatiotemporally-specific patterns of experience-dependent long noncoding RNA expression in the brain

The majority of transcriptionally active RNA derived from the mammalian genome does not code for protein. Long noncoding RNA (lncRNA) is the most abundant form of noncoding RNA found in the brain and is involved in many aspects of cellular metabolism. Beyond their fundamental role in the nucleus as decoys for RNA-binding proteins associated with alternative splicing or as guides for the epigenetic regulation of protein-coding gene expression, recent findings indicate that activity-induced lncRNAs also regulate neural plasticity. In this review, we discuss how lncRNAs may exert molecular control over brain function beyond their known roles in the nucleus. We propose that subcellular localization is a critical feature of experience-dependent lncRNA activity in the brain, and that lncRNA-mediated control over RNA metabolism at the synapse serves to regulate local mRNA stability and translation, thereby influencing neuronal function, learning and memory.

A Potential Autophagy-Related Competing Endogenous RNA Network and Corresponding Diagnostic Efficacy in Schizophrenia

Competing endogenous RNA (ceRNA) and autophagy were related to neurological diseases. But the relationship among ceRNA, autophagy and Schizophrenia (SZ) was not clear. In this study, we obtained gene expression profile of SZ patients (GSE38484, GSE54578, and GSE16930) from Gene Expression Omnibus (GEO) database. Then we screened the autophagy-related differentially expressed lncRNA, miRNA, and mRNA (DElncRNA, DEmiRNA, and DEmRNA) combined with Gene database from The National Center for Biotechnology Information (NCBI). In addition, we performed enrichment analysis. The result showed that biological processes (BPs) mainly were associated with cellular responses to oxygen concentration. The enriched pathways mainly included ErbB, AMPK, mTOR signaling pathway and cell cycle. Furthermore, we constructed autophagy-related ceRNA network based on the TargetScan database. Moreover, we explored the diagnostic efficiency of lncRNA, miRNA and mRNA in ceRNA, through gene set variation analysis (GSVA). The result showed that the diagnostic efficiency was robust, especially miRNA (AUC = 0.884). The miRNA included hsa-miR-423-5p, hsa-miR-4532, hsa-miR-593-3p, hsa-miR-618, hsa-miR-4723-3p, hsa-miR-4640-3p, hsa-miR-296-5p, and hsa-miR-3943. The result of this study may be helpful for deepening the pathophysiology of SZ. In addition, our finding may provide a guideline for the clinical diagnosis of SZ.

nMAGMA: a network-enhanced method for inferring risk genes from GWAS summary statistics and its application to schizophrenia

MOTIVATION

Annotating genetic variants from summary statistics of genome-wide association studies (GWAS) is crucial for predicting risk genes of various disorders. The multimarker analysis of genomic annotation (MAGMA) is one of the most popular tools for this purpose, where MAGMA aggregates signals of single nucleotide polymorphisms (SNPs) to their nearby genes. In biology, SNPs may also affect genes that are far away in the genome, thus missed by MAGMA. Although different upgrades of MAGMA have been proposed to extend gene-wise variant annotations with more information (e.g. Hi-C or eQTL), the regulatory relationships among genes and the tissue specificity of signals have not been taken into account.

RESULTS

We propose a new approach, namely network-enhanced MAGMA (nMAGMA), for gene-wise annotation of variants from GWAS summary statistics. Compared with MAGMA and H-MAGMA, nMAGMA significantly extends the lists of genes that can be annotated to SNPs by integrating local signals, long-range regulation signals (i.e. interactions between distal DNA elements), and tissue-specific gene networks. When applied to schizophrenia (SCZ), nMAGMA is able to detect more risk genes (217% more than MAGMA and 57% more than H-MAGMA) that are involved in SCZ compared with MAGMA and H-MAGMA, and more of nMAGMA results can be validated with known SCZ risk genes. Some disease-related functions (e.g. the ATPase pathway in Cortex) are also uncovered in nMAGMA but not in MAGMA or H-MAGMA. Moreover, nMAGMA provides tissue-specific risk signals, which are useful for understanding disorders with multitissue origins.

Identification of Genetic Loci Shared Between Attention-Deficit/Hyperactivity Disorder, Intelligence, and Educational Attainment

BACKGROUND

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder that is consistently associated with lower levels of educational attainment. A recent large genome-wide association study identified common gene variants associated with ADHD, but most of the genetic architecture remains unknown.

METHODS

We analyzed independent genome-wide association study summary statistics for ADHD (19,099 cases and 34,194 controls), educational attainment (N = 842,499), and general intelligence (N = 269,867) using a conditional/conjunctional false discovery rate (FDR) statistical framework that increases power of discovery by conditioning the FDR on overlapping associations. The genetic variants identified were characterized in terms of function, expression, and biological processes.

RESULTS

We identified 58 linkage disequilibrium-independent ADHD-associated loci (conditional FDR < 0.01), of which 30 were shared between ADHD and educational attainment or general intelligence (conjunctional FDR < 0.01) and 46 were novel risk loci for ADHD.

CONCLUSIONS

These results expand on previous genetic and epidemiological studies and support the hypothesis of a shared genetic basis between these phenotypes. Although the clinical utility of the identified loci remains to be determined, they can be used as resources to guide future studies aiming to disentangle the complex etiologies of ADHD, educational attainment, and general intelligence.

Molecular alterations in the medial temporal lobe in schizophrenia

The medial temporal lobe (MTL) and its individual structures have been extensively implicated in schizophrenia pathophysiology, with considerable efforts aimed at identifying structural and functional differences in this brain region. The major structures of the MTL for which prominent differences have been revealed include the hippocampus, the amygdala and the superior temporal gyrus (STG). The different functions of each of these regions have been comprehensively characterized, and likely contribute differently to schizophrenia. While neuroimaging studies provide an essential framework for understanding the role of these MTL structures in various aspects of the disease, ongoing efforts have sought to employ molecular measurements in order to elucidate the biology underlying these macroscopic differences. This review provides a summary of the molecular findings in three major MTL structures, and discusses convergent findings in cellular architecture and inter-and intra-cellular networks. The findings of this effort have uncovered cell-type, network and gene-level specificity largely unique to each brain region, indicating distinct molecular origins of disease etiology. Future studies should test the functional implications of these molecular changes at the circuit level, and leverage new advances in sequencing technology to further refine our understanding of the differential contribution of MTL structures to schizophrenia.

Non-Coding RNAs in Psychiatric Disorders and Suicidal Behavior

It is well known that only a small proportion of the human genome code for proteins; the rest belong to the family of RNAs that do not code for protein and are known as non-coding RNAs (ncRNAs). ncRNAs are further divided into two subclasses based on size: 1) long non-coding RNAs (lncRNAs; >200 nucleotides) and 2) small RNAs (<200 nucleotides). Small RNAs contain various family members that include microRNAs (miRNAs), small interfering RNAs (siRNAs), piwi-interacting RNAs (piRNAs), small nucleolar RNAs (snoRNAs), and small nuclear RNAs (snRNAs). The roles of ncRNAs, especially lncRNAs and miRNAs, are well documented in brain development, homeostasis, stress responses, and neural plasticity. It has also been reported that ncRNAs can influence the development of psychiatric disorders including schizophrenia, major depressive disorder, and bipolar disorder. More recently, their roles are being investigated in suicidal behavior. In this article, we have comprehensively reviewed the findings of lncRNA and miRNA expression changes and their functions in various psychiatric disorders including suicidal behavior. We primarily focused on studies that have been done in postmortem human brain. In addition, we have briefly reviewed the role of other small RNAs (e.g. piwiRNA, siRNA, snRNA, and snoRNAs) and their expression changes in psychiatric illnesses.

Postmortem brain tissue as an underutilized resource to study the molecular pathology of neuropsychiatric disorders across different ethnic populations

In recent years, large scale meta-analysis of genome-wide association studies (GWAS) have reliably identified genetic polymorphisms associated with neuropsychiatric disorders such as schizophrenia (SCZ), bipolar disorder (BPD) and major depressive disorder (MDD). However, the majority of disease-associated single nucleotide polymorphisms (SNPs) appear within functionally ambiguous non-coding genomic regions. Recently, increased emphasis has been placed on identifying the functional relevance of disease-associated variants via correlating risk polymorphisms with gene expression levels in etiologically relevant tissues. For neuropsychiatric disorders, the etiologically relevant tissue is brain, which requires robust postmortem sample sizes from varying genetic backgrounds. While small sample sizes are of decreasing concern, postmortem brain databases are composed almost exclusively of Caucasian samples, which significantly limits study design and result interpretation. In this review, we highlight the importance of gene expression and expression quantitative loci (eQTL) studies in clinically relevant postmortem tissue while addressing the current limitations of existing postmortem brain databases. Finally, we introduce future collaborations to develop postmortem brain databases for neuropsychiatric disorders from Chinese and Asian subpopulations.

RNA-Sequencing and Bioinformatics Analysis of Long Noncoding RNAs and mRNAs in the Prefrontal Cortex of Mice Following Repeated Social Defeat Stress

Background

Repeated or continuous chronic psychological stress may induce diverse neuropsychiatric disorders; however, the underlying mechanisms remain unclear. In this study, we explored the expression profiles of long noncoding RNAs (lncRNAs) and mRNAs, along with their biological function and regulatory network, in mice after repeated social defeat (RSD) stress to explore their potential involvement in the development of anxiety-like behaviors.

Main Methods

RNA-sequencing was used to screen all differentially expressed (DE) lncRNAs and mRNAs between the RSD and control groups. Quantitative real-time polymerase chain reaction (qRT-PCR) was used for confirmation of the RNA-sequencing results. The function of DE lncRNAs was predicted by Gene Ontology (GO) enrichment and pathway analyses of target mRNAs. In addition, the functional regulatory network of the target mRNAs was constructed to reveal potential relationships between lncRNAs and their target genes with bioinformatics approaches.

Key Findings

In mice experiencing RSD, 373 and 454 lncRNAs, along with 1142 and 654, mRNAs were significantly upregulated and downregulated, respectively. The detailed regulatory network included 126 eligible lncRNA-mRNA pairs. Among them, 14 genes such as Arhgef1, Chchd2, Fam107a, Dlg1, Nova2, Dpf1, and Shank3 involved in neurite growth, neural development, and synaptic plasticity were direct targets of the DE lncRNAs. qRT-PCR of four of the DE lncRNAs and mRNAs confirmed the reliability of RNA-sequencing. GO clustering analyses showed that the top enriched biological process, cellular component, and molecular function terms were synaptic transmission, neuron spine, and glutamate receptor binding, respectively. Further, the top three significant enriched pathways were synaptic adhesion-like molecule (SALM) protein interactions at the synapses, trafficking of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors, as well as glutamate binding, activation of AMPA receptors, and synaptic plasticity.

Significance

Hundreds of lncRNAs and mRNAs are dysregulated after RSD, and many of these lncRNAs might participate in the development of anxiety-like behaviors via multiple complex mechanisms such as target regulation. Available informatics evidence highlighted the likely role of synapse dysfunction and abnormal synaptic neurotransmission in these behaviors. Thus, our findings provide potential candidate biomarkers or intervention targets for chronic psychological stress-induced neuropsychiatric disorders.