Intergenic variants may predispose to major depression disorder through regulation of long non-coding RNA expression

The role of ncRNAs in depression

Depressive disorders have a significant impact on public health, and depression have an unsatisfactory recurrence rate and are challenging to treat. Non-coding RNAs (ncRNAs) are RNAs that do not code protein, which have been shown to be crucial for transcriptional regulation. NcRNAs are important to the onset, progress and treatment of depression because they regulate various physiological functions. This makes them distinctively useful as biomarkers for diagnosing and tracking responses to therapy among individuals with depression. It is important to seek out and summarize the research findings on the impact of ncRNAs on depression since significant advancements have been made in this area recently. Hence, we methodically outlined the findings of published researches on ncRNAs and depression, focusing on microRNAs. Above all, this review aims to improve our understanding of ncRNAs and provide new insights of the diagnosis and treatment of depression.

Integrating mitoepigenetics into research in mood disorders: a state-of-the-art review

Mood disorders, including major depressive disorder and bipolar disorder, are highly prevalent and stand among the leading causes of disability. Despite the largely elusive nature of the molecular mechanisms underpinning these disorders, two pivotal contributors-mitochondrial dysfunctions and epigenetic alterations-have emerged as significant players in their pathogenesis. This state-of-the-art review aims to present existing data on epigenetic alterations in the mitochondrial genome in mood disorders, laying the groundwork for future research into their pathogenesis. Associations between abnormalities in mitochondrial function and mood disorders have been observed, with evidence pointing to notable changes in mitochondrial DNA (mtDNA). These changes encompass variations in copy number and oxidative damage. However, information on additional epigenetic alterations in the mitochondrial genome remains limited. Recent studies have delved into alterations in mtDNA and regulations in the mitochondrial genome, giving rise to the burgeoning field of mitochondrial epigenetics. Mitochondrial epigenetics encompasses three main categories of modifications: mtDNA methylation/hydroxymethylation, modifications of mitochondrial nucleoids, and mitochondrial RNA alterations. The epigenetic modulation of mitochondrial nucleoids, lacking histones, may impact mtDNA function. Additionally, mitochondrial RNAs, including non-coding RNAs, present a complex landscape influencing interactions between the mitochondria and the nucleus. The exploration of mitochondrial epigenetics offers valuable perspectives on how these alterations impact neurodegenerative diseases, presenting an intriguing avenue for research on mood disorders. Investigations into post-translational modifications and the role of mitochondrial non-coding RNAs hold promise to unravel the dynamics of mitoepigenetics in mood disorders, providing crucial insights for future therapeutic interventions.

A cross talk on the role of contemporary biomarkers in depression

Introduction: Biomarkers can be used to identify determinants of response to various treatments of mental disorders. Evidence to date demonstrates that markers of inflammatory, neurotransmitter, neurotrophic, neuroendocrine, and metabolic function can predict the psychological and physical consequences of depression in individuals, allowing for the development of new therapeutic targets with fewer side effects. Extensive research has included hundreds of potential biomarkers of depression, but their roles in depression, abnormal patients, and how bioinformatics can be used to improve diagnosis, treatment, and prognosis have not been determined or defined. To determine which biomarkers can and cannot be used to predict treatment response, classify patients for specific treatments, and develop targets for new interventions, proprietary strategies, and current research projects need to be tailored.Material and Methods: This review article focuses on - biomarker systems that would help in the further development and expansion of newer targets - which holds great promise for reducing the burden of depression.Results and Discussion: Further, this review point to the inflammatory response, metabolic marker, and microribonucleic acids, long non-coding RNAs, HPA axis which are - related to depression and can serve as future targets.

Epigenetic regulation in major depression and other stress-related disorders: molecular mechanisms, clinical relevance and therapeutic potential

Major depressive disorder (MDD) is a chronic, generally episodic and debilitating disease that affects an estimated 300 million people worldwide, but its pathogenesis is poorly understood. The heritability estimate of MDD is 30-40%, suggesting that genetics alone do not account for most of the risk of major depression. Another factor known to associate with MDD involves environmental stressors such as childhood adversity and recent life stress. Recent studies have emerged to show that the biological impact of environmental factors in MDD and other stress-related disorders is mediated by a variety of epigenetic modifications. These epigenetic modification alterations contribute to abnormal neuroendocrine responses, neuroplasticity impairment, neurotransmission and neuroglia dysfunction, which are involved in the pathophysiology of MDD. Furthermore, epigenetic marks have been associated with the diagnosis and treatment of MDD. The evaluation of epigenetic modifications holds promise for further understanding of the heterogeneous etiology and complex phenotypes of MDD, and may identify new therapeutic targets. Here, we review preclinical and clinical epigenetic findings, including DNA methylation, histone modification, noncoding RNA, RNA modification, and chromatin remodeling factor in MDD. In addition, we elaborate on the contribution of these epigenetic mechanisms to the pathological trait variability in depression and discuss how such mechanisms can be exploited for therapeutic purposes.

The emerging role of long noncoding RNA in depression and its implications in diagnostics and therapeutic responses

Depression is one of the most common mental illnesses, affecting more than 350 million people worldwide. However, the occurrence of depression is a complex process involving genetic, physiological, psychological, and social factors, and the underlying mechanisms of its pathogenesis remain unclear. With advances in sequencing technology and epigenetic studies, increasing research evidence suggests that long noncoding RNAs (lncRNAs) play nonnegligible roles in the development of depression and may be involved in the pathogenesis of depression through multiple pathways, including regulating neurotrophic factors and other growth factors and affecting synaptic function. In addition, significant alterations in lncRNA expression profiles in peripheral blood and different brain regions of patients and model animals with depression suggest that lncRNAs may function as biomarkers for the differential diagnosis of depression and other psychiatric disorders and may also be potential therapeutic targets. In this paper, the biological functions of lncRNAs are briefly described, and the functional roles and abnormal expression of lncRNAs in the development, diagnosis and treatment of depression are reviewed.

Weighted Gene Co-Expression Network Analysis (WGCNA) Discovered Novel Long Non-Coding RNAs for Polycystic Ovary Syndrome

Polycystic ovary syndrome (PCOS) affects reproductive-age women. This condition causes infertility, insulin resistance, obesity, and heart difficulties. The molecular basis and mechanism of PCOS might potentially generate effective treatments. Long non-coding RNAs (lncRNAs) show control over multifactorial disorders' growth and incidence. Numerous studies have emphasized its significance and alterations in PCOS. We used bioinformatic methods to find novel dysregulated lncRNAs in PCOS. To achieve this objective, the gene expression profile of GSE48301, comprising PCOS patients and normal control tissue samples, was evaluated using the R limma package with the following cut-off criterion: p-value < 0.05. Firstly, weighted gene co-expression network analysis (WGCNA) was used to determine the co-expression genes of lncRNAs; subsequently, hub gene identification and pathway enrichment analysis were used. With the defined criteria, nine novel dysregulated lncRNAs were identified. In WGCNA, different colors represent different modules. In the current study, WGCNA resulted in turquoise, gray, blue, and black co-expression modules with dysregulated lncRNAs. The pathway enrichment analysis of these co-expressed modules revealed enrichment in PCOS-associated pathways, including gene expression, signal transduction, metabolism, and apoptosis. In addition, CCT7, EFTUD2, ESR1, JUN, NDUFAB1, CTTNB1, GRB2, and CTNNB1 were identified as hub genes, and some of them have been investigated in PCOS. This study uncovered nine novel PCOS-related lncRNAs. To confirm how these lncRNAs control translational modification in PCOS, functional studies are required.

A novel inflammation-related lncRNAs prognostic signature identifies LINC00346 in promoting proliferation, migration, and immune infiltration of glioma

In this study, a total of 13 inflammation-related lncRNAs with a high prognostic value were identified with univariate, multivariate Cox regression analysis, and LASSO analysis. LINC00346, which is one of the 13 lncRNAs identified, was positively associated with type 2 macrophage activation and the malignant degree of glioma. Fluorescence in situ hybridization (FISH) and immunohistochemical staining showed that LINC00346 was highly expressed in high-grade glioma, while type 2 macrophages key transcription factor STAT3 and surface marker CD204 were also highly expressed simultaneously. LINC00346 high-expression gliomas were more sensitive to the anti–PD-1 and anti-CTLA-4 therapy. LINC00346 was also associated with tumor proliferation and tumor migration validated by EdU, cell colony, formation CCK8, and transwell assays. These findings reveal novel biomarkers for predicting glioma prognosis and outline relationships between lncRNAs inflammation, and glioma, as well as possible immune checkpoint targets for glioma.

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.

LncRNA-84277 is involved in chronic pain-related depressive behaviors through miR-128-3p/SIRT1 axis in central amygdala

Long-term chronic pain can lead to depression. However, the mechanism underlying chronic pain-related depression remains unclear. Sirtuin 1 (SIRT1) is a nicotinamide adenine dinucleotide (NAD+)-dependent histone deacetylase (HDAC). Our previous studies have demonstrated that SIRT1 in the central nucleus of the amygdala (CeA) is involved in the development of chronic pain-related depression. In addition, increasing studies have indicated that long non-coding RNAs (lncRNAs) play a vital role in the pathogenesis of pain or depression. However, whether lncRNAs are involved in SIRT1-mediated chronic pain-related depression remains largely unknown. In this study, we identified that a novel lncRNA-84277 in CeA was the upstream molecule to regulate SIRT1 expression. Functionally, lncRNA-84277 overexpression in CeA significantly alleviated the depression-like behaviors in spared nerve injury (SNI)-induced chronic pain rats, whereas lncRNA-84277 knockdown in CeA induced the depression-like behaviors in naïve rats. Mechanically, lncRNA-84277 acted as a competing endogenous RNA (ceRNA) to upregulate SIRT1 expression by competitively sponging miR-128-3p, and therefore improved chronic pain-related depression-like behaviors. Our findings reveal the critical role of lncRNA-84277 in CeA specifically in guarding against chronic pain-related depression via a ceRNA mechanism and provide a potential therapeutic target for chronic pain-related depression.

Long noncoding RNA HOTAIR polymorphisms and susceptibility to bipolar disorder: a preliminary case-control study

Recent studies have shown that long noncoding RNAs contribute to the pathogenesis of bipolar disorder (BD). In this study, we genotyped four HOX Transcript Antisense Intergenic RNA (HOTAIR) gene polymorphisms to investigate if these variations could affect the risk of BD and its clinical subtypes. A total of 357 subjects, comprised of 194 BD patients and 163 age-matched healthy controls, were enrolled. Genotyping was carried out using PCR-RFLP and ARMS-PCR methods. We detected significant associations between the HOTAIR gene rs1899663 G/T, rs12826786 C/T, rs4759314 A/G, and rs920778 C/T polymorphism and the risk of BD under allelic, recessive, dominant, and codominant contrasted genetic models. The CT genotype of rs920778 C/T, GT genotype of rs1899663 G/T, and CT genotype of rs12826786 C/T polymorphisms enhanced the risk of BD type II (BDII). In contrast, the GG genotype of rs4759314 A/G polymorphism significantly diminished BDII risk by 83%. A positive association was noticed between CTTA and CTCG haplotypes of rs920778/rs1899663/rs12826786/rs4759314 and BD risk. Our findings reveal an interactive effect of HOTAIR polymorphisms on the development of BD and its subtypes. Further functional studies are needed to elucidate the role of these variations on HOTAIR expression and epigenetic status.

Emerging roles of long non-coding RNA in depression

Depression is the second most common psychiatric disorder, affecting more than 340 million people of all ages worldwide. However, the mechanisms underlying the development of depression remain unclear, and existing antidepressants may cause clinical dependence and toxic side effects. Recently, emerging evidence from the fields of neuroscience, genetics, and genomics supports the modulatory role of long non-coding RNA (lncRNA) in depression. LncRNAs may mediate the pathogenesis of depression through multiple pathways, including regulating neurotransmitters and neurotrophic factors, affecting synaptic conduction, and regulating the ventriculo-olfactory neurogenic system. In addition, relying on genome-wide association study and molecular biological experiment, the possibility of lncRNA as a potential biomarker for the differential diagnosis of depression and other mental illnesses, including schizophrenia and anxiety disorders, is gradually being revealed. Thus, it is important to explore whether lncRNAs are potential therapeutic targets and diagnostic biomarkers for depression. Here, we summarize the genesis and function of lncRNAs and discuss the aberrant expression and functional roles of lncRNAs in the development, diagnosis, and therapy of depression, as well as the deficiencies and limitations of these studies. Moreover, we established a lncRNA-miRNA-mRNA-pathway-drug network of depression through bioinformatics analysis methods to deepen our understanding of the relationship between lncRNA and depression, promoting the clinical application of epigenetic research.

Non-coding RNAs in depression: Promising diagnostic and therapeutic biomarkers

Non-coding RNAs (ncRNAs), including microRNAs, circular RNAs, and long non-coding RNAs, are important regulators of normal biological processes and their abnormal expression may be involved in the pathogenesis of human diseases including depression. Multiple studies have demonstrated a significantly increased or reduced ncRNAs expression in depressed patients compared with healthy subjects and that antidepressant therapy can alter the aberrant expression of ncRNAs in depressed patients. Although the existing evidence is important, it is also mixed and a comprehensive review to guide an effective clinical translation is lacking. Focused on human research, this review summarizes clinical findings of ncRNAs in depression, including those in brain tissues and peripheral samples. We outlined the characteristics and functions of ncRNAs and highlighted their performance in the diagnosis and treatment of depression. Although their precise roles in depression remain uncertain, ncRNAs have shown potential value as biomarkers for diagnosis and therapy in depressed patients.

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.

Bioinformatics analysis of a TF-miRNA-lncRNA regulatory network in major depressive disorder

Major depressive disorder (MDD) is a highly prevalent disease and one of the main causes of disability worldwide. Although many studies have partially revealed the occurrence and development process of MDD, the pathogeny and molecular mechanisms are not fully understood. Weighted gene coexpression network analysis (WGCNA) was used to explore the co-expression modules and hub genes in MDD. A protein-protein interaction (PPI) network of the most significant module and a TF-miRNA-lncRNA regulatory network of MDD were constructed using bioinformatics analysis tools. A KEGG pathway and gene ontology (GO) functional enrichment analysis of the genes in the significant module was performed using DAVID. Five hub genes in the PPI network and 10 genes in the TF-miRNA-lncRNA regulatory network with high degree values were identified, which may provide new insights for the investigation of key pathways, diagnostic bio-markers, and therapeutic targets of MDD. This study brings a novel perspective and provides valuable information to explore the molecular mechanism of MDD.

Identification of hub lncRNA ceRNAs in multiple sclerosis based on ceRNA mechanisms

Multiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system, and the pathogenesis is influenced by genetic susceptibility. Accumulating evidence has demonstrated that long non-coding RNAs (lncRNAs) play essential roles in complex diseases, including acting as competing endogenous RNAs (ceRNAs). However, the functional roles and regulatory mechanisms of lncRNAs acting as ceRNAs in MS are still unclear. In this study, we identified hub lncRNA ceRNAs in MS based on ceRNA mechanisms and annotated their functions. The lncRNA-associated ceRNA network (LACN) was constructed by integrating the expression profiles of lncRNA/mRNA and miRNA in MS and normal samples, and the experimentally validated interactions of lncRNA-miRNA and mRNA-miRNA. We found three hub lncRNA ceRNAs (XIST, OIP5-AS1, and CTB-89H12.4) using the network analysis and obtained 96 lncRNA-mediated competing triplets (LCTs, lncRNA-miRNA-mRNA) with the hub lncRNA ceRNAs, which constituted 3 hub ceRNA modules. The functional analysis identified 12 pathways enriched by the 3 hub lncRNA ceRNAs, of which 6 were confirmed to be related to MS. For example, XIST was enriched in the 'spliceosome' and 'RNA transport' related to the typing of MS, and CTB-89H12.4 was enriched in the 'mTOR signaling pathway,' a potential therapeutic target for MS. We dissected the expression patterns of the 96 LCTs in MS individually. LCT XIST-miR-326-HNRNPA1, for which the expression pattern in MS revealed that XIST and HNRNPA1 were up-regulated and miR-326 was down-regulated, consisted of risk RNAs for MS that were validated by other research. Therefore, XIST-miR-326-HNRNPA1 might play a central role in the pathogenesis of MS. These results will contribute to the discovery of novel biomarkers and the development of new therapeutic methods for MS.

LncRNA LINC00998 inhibits the malignant glioma phenotype via the CBX3-mediated c-Met/Akt/mTOR axis

Long noncoding RNAs (lncRNAs), once considered to be nonfunctional relics of evolution, are emerging as essential genes in tumor progression. However, the function and underlying mechanisms of lncRNAs in glioma remain unclear. This study aimed to investigate the role of LINC00998 in glioma progression. Through screening using TCGA database, we found that LINC00998 was downregulated in glioblastoma tissues and that low expression of LINC00998 was associated with poor prognosis. Overexpression of LINC00998 inhibited glioma cell proliferation in vitro and in vivo and blocked the G1/S cell cycle transition, which exerted a tumor-suppressive effect on glioma progression. Mechanistically, RNA pull-down and mass spectrometry results showed an interaction between LINC00998 and CBX3. IP assays demonstrated that LINC00998 could stabilize CBX3 and prevent its ubiquitination degradation. GSEA indicated that LINC00998 could regulate the c-Met/Akt/mTOR signaling pathway, which was further confirmed by a rescue assay using siRNA-mediated knockdown of CBX3 and the Akt inhibitor MK2206. In addition, dual-luciferase assays showed that miR-34c-5p could directly bind to LINC00998 and downregulate its expression. Our results identified LINC00998 as a novel tumor suppressor in glioma, and LINC00998 could be a novel prognostic biomarker, providing a strategy for precision therapy in glioma patients.

Immune-related lncRNAs as predictors of survival in breast cancer: a prognostic signature

Background

Breast cancer is a highly heterogeneous disease, this poses challenges for classification and management. Long non-coding RNAs play acrucial role in the breast cancersdevelopment and progression, especially in tumor-related immune processes which have become the most rapidly investigated area. Therefore, we aimed at developing an immune-related lncRNA signature to improve the prognosis prediction of breast cancer.

Methods

We obtained breast cancer patient samples and corresponding clinical data from The Cancer Genome Atlas (TCGA) database. Immune-related lncRNAs were screened by co-expression analysis of immune-related genes which were downloaded from the Immunology Database and Analysis Portal (ImmPort). Clinical patient samples were randomly separated into training and testing sets. In the training set, univariate Cox regression analysis and LASSO regression were utilized to build a prognostic immune-related lncRNA signature. The signature was validated in the training set, testing set, and whole cohorts by the Kaplan–Meier log-rank test, time-dependent ROC curve analysis, principal component analysis, univariate andmultivariate Cox regression analyses.

Results

A total of 937 immune- related lncRNAs were identified, 15 candidate immune-related lncRNAs were significantly associated with overall survival (OS). Eight of these lncRNAs (OTUD6B-AS1, AL122010.1, AC136475.2, AL161646.1, AC245297.3, LINC00578, LINC01871, AP000442.2) were selected for establishment of the risk prediction model. The OS of patients in the low-risk group was higher than that of patients in the high-risk group (p = 1.215e − 06 in the training set; p = 0.0069 in the validation set; p = 1.233e − 07 in whole cohort). The time-dependent ROC curve analysis revealed that the AUCs for OS in the first, eighth, and tenth year were 0.812, 0.81, and 0.857, respectively, in the training set, 0.615, 0.68, 0.655 in the validation set, and 0.725, 0.742, 0.741 in the total cohort. Multivariate Cox regression analysis indicated the model was a reliable and independent indicator for the prognosis of breast cancer in the training set (HR = 1.432; 95% CI 1.204–1.702, p < 0.001), validation set (HR = 1.162; 95% CI 1.004–1.345, p = 0.044), and whole set (HR = 1.240; 95% CI 1.128–1.362, p < 0.001). GSEA analysis revealed a strong connection between the signature and immune-related biological processes and pathways.

Conclusions

We constructed and verified a robust signature of 8 immune-related lncRNAs for the prediction of breast cancer patient survival.

Screening and evaluation of key genes in contributing to pathogenesis of hepatic fibrosis based on microarray data

BACKGROUND

Hepatic fibrosis (HF), which is characterized by the excessive accumulation of extracellular matrix (ECM) in the liver, usually progresses to liver cirrhosis and then death. To screen differentially expressed (DE) long non-coding RNAs (lncRNAs) and mRNAs, explore their potential functions to elucidate the underlying mechanisms of HF.

METHODS

The microarray of GSE80601 was downloaded from the Gene Expression Omnibus database, which is based on the GPL1355 platform. Screening for the differentially expressed LncRNAs and mRNAs was conducted between the control and model groups. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to analyze the biological functions and pathways of the DE mRNAs. Additionally, the protein-protein interaction (PPI) network was delineated. In addition, utilizing the Weighted Gene Co-expression Network Analysis (WGCNA) package and Cytoscape software, we constructed lncRNA-mRNA weighted co-expression networks.

RESULTS

A total of 254 significantly differentially expressed lncRNAs and 472 mRNAs were identified. GO and KEGG analyses revealed that DE mRNAs regulated HF by participating in the GO terms of metabolic process, inflammatory response, response to wounding and oxidation-reduction. DE mRNAs were also significantly enriched in the pathways of ECM-receptor interaction, PI3K-Akt signaling pathway, focal adhesion (FA), retinol metabolism and metabolic pathways. Moreover, 24 lncRNAs associated with 40 differentially expressed genes were observed in the modules of lncRNA-mRNA weighted co-expression network.

CONCLUSIONS

This study revealed crucial information on the molecular mechanisms of HF and laid a foundation for subsequent genes validation and functional studies, which could contribute to the development of novel diagnostic markers and provide new therapeutic targets for the clinical treatment of HF.

Sex-Specific Role for the Long Non-coding RNA LINC00473 in Depression

Depression is a common disorder that affects women at twice the rate of men. Here, we report that long non-coding RNAs (lncRNAs), a recently discovered class of regulatory transcripts, represent about one-third of the differentially expressed genes in the brains of depressed humans and display complex region- and sex-specific patterns of regulation. We identified the primate-specific, neuronal-enriched gene LINC00473 as downregulated in prefrontal cortex (PFC) of depressed females but not males. Using viral-mediated gene transfer to express LINC00473 in adult mouse PFC neurons, we mirrored the human sex-specific phenotype by inducing stress resilience solely in female mice. This sex-specific phenotype was accompanied by changes in synaptic function and gene expression selectively in female mice and, along with studies of human neuron-like cells in culture, implicates LINC00473 as a CREB effector. Together, our studies identify LINC00473 as a female-specific driver of stress resilience that is aberrant in female depression.

Altered expression of long noncoding RNAs in patients with major depressive disorder

Although major depressive disorder (MDD) is a leading cause of disability worldwide, its pathophysiology is poorly understood. Increasing evidence suggests that aberrant regulation of transcription plays a key role in the pathophysiology of MDD. Recently, long noncoding RNAs (lncRNAs) have been recognized for their important functions in chromatin structure, gene expression, and the subsequent manifestation of various biological processes in the central nervous system. However, it is unclear whether the aberrant expression and function of lncRNAs are associated with the pathophysiology of MDD. In this study, we sought to evaluate the expression of lncRNAs in peripheral blood leukocytes as potential biomarkers for MDD. We measured the expression levels of 83 lncRNAs in the peripheral blood leukocytes of 29 MDD patients and 29 age- and gender-matched healthy controls using quantitative reverse transcription PCR (RT-qPCR) analysis. We found that MDD patients exhibited distinct expression signatures. Specifically, the expression level of one lncRNA (RMRP) was lower while the levels of four (Y5, MER11C, PCAT1, and PCAT29) were higher in MDD patients compared to healthy controls. The expression level of RMRP was correlated with depression severity as measured by the Hamilton Depression Rating Scale (HAM-D). Moreover, RMRP expression was lower in a mouse model of depression, corroborating the observation from MDD patients. Taken together, our data suggest that lower RMRP levels may serve as a potential biomarker for MDD.

Effect of astragalosides on long non-coding RNA expression profiles in rats with adjuvant-induced arthritis

Rheumatoid arthritis (RA) is an autoimmune disease of unknown etiology, which occurs in ~1.0% of the general population. Increasing studies have suggested that long non-coding RNAs (lncRNAs) may serve important roles in various biological processes and may be associated with the pathogenesis of different types of disease, including RA. Astragalosides (AST) has been used as a traditional Chinese medicine for the treatment of RA. However, the mechanism underlying its therapeutic effect has remained unclear to date. Thus, there is an urgent need to elucidate the possible mechanism of AST in the treatment of RA from the perspective of lncRNAs. In the present study, the lncRNAs and mRNAs of a vehicle group, animal model group and AST treatment (control) group were determined by Arraystar Rat lncRNA/mRNA microarray. The differentially expressed genes with a fold change >1.5 and P<0.05 were selected and analyzed. Gene Ontology (GO) and pathway analysis was performed using the Database for Annotation, Visualization and Integration Discovery, and the coding-non-coding gene co-expression network was drawn based on the correlation analysis between the differentially expressed lncRNAs and mRNAs. Based on node degree and the correlation between bioinformatics analysis and RA, the critical differentially expressed lncRNAs were selected, analyzed and verified by reverse transcription-quantitative PCR (RT-qPCR) analysis. The results showed that, following AST treatment, up to 75 lncRNAs and 247 mRNAs were found to be differentially expressed among the three groups. GO and pathway analysis manifested that 135 GO terms and 17 pathways were enriched by differentially expressed genes. Four lncRNAs (MRAK012530, MRAK132628, MRAK003448 and XR_006457) were selected as the critical lncRNAs and their trend in expression showed consistency between the RT-qPCR and microarray data. In conclusion, AST had a regulatory effect on differentially expressed lncRNAs during the development of RA, and four lncRNAs could be selected as critical therapeutic targets of AST.

Long Non-Coding RNAs in Multifactorial Diseases: Another Layer of Complexity

Multifactorial diseases such as cancer, cardiovascular conditions and neurological, immunological and metabolic disorders are a group of diseases caused by the combination of genetic and environmental factors. High-throughput RNA sequencing (RNA-seq) technologies have revealed that less than 2% of the genome corresponds to protein-coding genes, although most of the human genome is transcribed. The other transcripts include a large variety of non-coding RNAs (ncRNAs), and the continuous generation of RNA-seq data shows that ncRNAs are strongly deregulated and may be important players in pathological processes. A specific class of ncRNAs, the long non-coding RNAs (lncRNAs), has been intensively studied in human diseases. For clinical purposes, lncRNAs may have advantages mainly because of their specificity and differential expression patterns, as well as their ideal qualities for diagnosis and therapeutics. Multifactorial diseases are the major cause of death worldwide and many aspects of their development are not fully understood. Recent data about lncRNAs has improved our knowledge and helped risk assessment and prognosis of these pathologies. This review summarizes the involvement of some lncRNAs in the most common multifactorial diseases, with a focus on those with published functional data.

Using Human iPSC-Derived Neurons to Uncover Activity-Dependent Non-Coding RNAs

Humans are arguably the most complex organisms present on Earth with their ability to imagine, create, and problem solve. As underlying mechanisms enabling these capacities reside in the brain, it is not surprising that the brain has undergone an extraordinary increase in size and complexity within the last few million years. Human induced pluripotent stem cells (hiPSCs) can be differentiated into many cell types that were virtually inaccessible historically, such as neurons. Here, we used hiPSC-derived neurons to investigate the cellular response to activation at the transcript level. Neuronal activation was performed with potassium chloride (KCl) and its effects were assessed by RNA sequencing. Our results revealed the involvement of long non-coding RNAs and human-specific genetic variants in response to neuronal activation and help validate hiPSCs as a valuable resource for the study of human neuronal networks. In summary, we find that genes affected by KCl-triggered activation are implicated in pathways that drive cell proliferation, differentiation, and the emergence of specialized morphological features. Interestingly, non-coding RNAs of various classes are amongst the most highly expressed genes in activated hiPSC-derived neurons, thus suggesting these play crucial roles in neural pathways and may significantly contribute to the unique functioning of the human brain.

The functions and unique features of long intergenic non-coding RNA

Long intergenic non-coding RNA (lincRNA) genes have diverse features that distinguish them from mRNA-encoding genes and exercise functions such as remodelling chromatin and genome architecture, RNA stabilization and transcription regulation, including enhancer-associated activity. Some genes currently annotated as encoding lincRNAs include small open reading frames (smORFs) and encode functional peptides and thus may be more properly classified as coding RNAs. lincRNAs may broadly serve to fine-tune the expression of neighbouring genes with remarkable tissue specificity through a diversity of mechanisms, highlighting our rapidly evolving understanding of the non-coding genome.

The association of rs710886 in lncRNA PCAT1 with bladder cancer risk in a Chinese population

OBJECTIVE

The long noncoding RNA PCAT1 is an important gene involved in urinary tumors. In this study, we aimed to explore the association between polymorphisms in PCAT1 and bladder cancer susceptibility.

METHODS

A two-stage case-control study was conducted to assess the association between four tagging SNPs (i.e., rs4871771, rs1902432, rs16901904 and rs710886) and bladder cancer risk. Odds ratios (ORs) and their 95% confidence intervals (CIs) were calculated with unconditional univariate and multivariate logistic regression.

RESULTS

At the first stage of discovery, we identified that SNP rs710886A>G was significantly associated with bladder cancer risk (OR=0.86, 95% CI=0.74-0.99, P=0.046). At the following stage of validation, individuals with GG genotype were found to have a significant reduction in bladder cancer risk compared with those carrying AA genotype (adjusted OR=0.83, 95% CI=0.74-0.93, P=0.001). Furthermore, stratified analyses showed that protective effect of rs710886 was more pronounced in subgroup of age>60 and never smoking, and had little to do with sex. Besides, rs710886 was identified as an eQTL for PCAT1. G allele was consistent with lower PCAT1 expression.

CONCLUSION

This study indicates that genetic variants in lncRNA PCAT1 were associated with bladder cancer susceptibility and the SNP rs710886 may act as a potential biomarker for bladder cancer risk.

Reconstruction and analysis of the lncRNA–miRNA–mRNA network based on competitive endogenous RNA reveal functional lncRNAs in rheumatoid arthritis

Rheumatoid arthritis (RA) is an autoimmune disease with an unknown etiology, occurring in approximately 1.0% of general population.