Significant increasing of DISC2 long non-coding RNA expression as a potential biomarker in bipolar disorder

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.

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.

RNA Biomarkers in Bipolar Disorder and Response to Mood Stabilizers

Bipolar disorder (BD) is a severe chronic disorder that represents one of the main causes of disability among young people. To date, no reliable biomarkers are available to inform the diagnosis of BD or clinical response to pharmacological treatment. Studies focused on coding and noncoding transcripts may provide information complementary to genome-wide association studies, allowing to correlate the dynamic evolution of different types of RNAs based on specific cell types and developmental stage with disease development or clinical course. In this narrative review, we summarize findings from human studies that evaluated the potential utility of messenger RNAs and noncoding transcripts, such as microRNAs, circular RNAs and long noncoding RNAs, as peripheral markers of BD and/or response to lithium and other mood stabilizers. The majority of available studies investigated specific targets or pathways, with large heterogeneity in the included type of cells or biofluids. However, a growing number of studies are using hypothesis-free designs, with some studies also integrating data on coding and noncoding RNAs measured in the same participants. Finally, studies conducted in neurons derived from induced-pluripotent stem cells or in brain organoids provide promising preliminary findings supporting the power and utility of these cellular models to investigate the molecular determinants of BD and clinical response.

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.

Downregulation of long non-coding RNAs in patients with bipolar disorder

The abnormal function of signaling cascades is currently a candidate in the pathophysiology of bipolar disorder (BD). One of the factors involved in activating these signals is oxidative stress. Some long non-coding RNAs (lncRNA) are involved in the oxidative stress. In this study, we compared expression levels of lincRNA-p21, lincRNA-ROR, and lincRNA-PINT in the peripheral blood mononuclear cells (PBMC) from BD patients (n = 50) and healthy individuals (n = 50). Expression levels of lincRNA-p21, lincRNA-ROR, and lincRNA-PINT were significantly reduced in patients with BD compared to controls. In sex-based analyses, down-regulation of these lncRNAs was revealed only in male BD patients compared to male healthy subjects. Also, in BD patients, all three lncRNAs showed a significant pairwise positive correlation in expression level. The area under curve values for lincRNA-p21, lincRNA-ROR, and lincRNA-PINT was 0.66, 0.75, and 0.66, respectively. Thus, the ROC curve analysis showed that lncRNA-ROR might serve as a diagnostic biomarker for distinguishing between BD patients and controls. Altogether, the current study proposes a role for lincRNA-p21, lincRNA-ROR, and lincRNA-PINT in the pathogenesis of bipolar disorder. Moreover, the peripheral expression of these lncRNAs might be useful as potential biomarkers for BD.

Significant reduction of long non-coding RNAs expression in bipolar disorder

Long non-coding RNAs (lncRNAs) have been recently emerged as critical modulators of oxidative stress pathway. Likewise, rising evidence currently highlights dysfunction of oxidative stress pathways in bipolar disorder (BD) patients.In the current study, we evaluated the expression levels of H19, SCAL1 (LUCAT1), RMST, MEG3 and MT1DP lncRNAs in the PBMC from 50 patients with BD and 50 control subjects (male/female ratio in each group: 70%/30%). Expression levels of SCAL1, RMST and MEG3 but not H19 and MT1DP were considerably decreased in BD patients compared with healthy individuals. Such significant decrease in the expression of MEG3, RMST and SCAL1 was only reported in male BD patients compared with male controls. Substantial pairwise correlations were observed between expression levels of these lncRNAs in BD subjects. The area under curve values for RMST, MEG3 and SCAL1 were 0.70, 0.63 and 0.61 respectively. On the basis of this finding, RMST had the best efficiency in the discrimination of disease status between BD patients and controls. Taken together, the current results suggest a role for MEG3, RMST and SCAL1 lncRNAs in the pathogenesis of BD. In addition, peripheral expression levels of these lncRNAs might serve as potential peripheral markers for BD.

A preliminary analysis of LncRNA biomarkers for schizophrenia

Aim: The aim of this study was to identify the long noncoding RNAs (lncRNAs) associated with schizophrenia (SZ) and the relationships among their expression, antipsychotic efficacy and SZ severity. Method: The diagnostic and predictive value of nine lncRNAs, Gomafu, DISC2, PSZA11, AK096174, AK123097, DB340248, uc011dma.1, ENST00000509804-1 and ENST00000509804-2, was investigated in 48 patients with SZ before and after antipsychotic treatment. Results: Gomafu, AK096174, AK123097, DB340248, uc011dma.1, ENST00000509804-1 and ENST00000509804-2 were individually and collectively associated with, and predictive of, SZ pathogenesis. Moreover, increased expression of plasma AK123097, uc011dma.1 and ENST00000509804-1 levels was reversed after 12 weeks of antipsychotic treatment, which was associated with SZ severity. Conclusion: Seven lncRNAs serve as novel biomarkers for SZ diagnosis and prognosis and three lncRNAs are potential therapeutic targets.

DNA methylation signature as a biomarker of major neuropsychiatric disorders

DNA methylation is a broadly-investigated epigenetic modification that has been considered as a heritable and reversible change. Previous findings have indicated that DNA methylation regulates gene expression in the central nervous system (CNS). Also, disturbance of DNA methylation patterns has been associated with destructive consequences that lead to human brain diseases such as neuropsychiatric disorders (NPDs). In this review, we comprehensively discuss the mechanism and function of DNA methylation and its most recent associations with the pathology of NPDs-including major depressive disorder (MDD), schizophrenia (SZ), autism spectrum disorder (ASD), bipolar disorder (BD), and attention/deficit hyperactivity disorder (ADHD). We also discuss how heterogeneous findings demand further investigations. Finally, based on the recent studies we conclude that DNA methylation status may have implications in clinical diagnostics and therapeutics as a potential epigenetic biomarker of NPDs.

Identification of lncRNA NR_028138.1 as a biomarker and construction of a ceRNA network for bipolar disorder

The pathogenesis of bipolar disorder (BD), a chronic mood disorder, is largely unknown. Noncoding RNAs play important roles in the pathogenesis of BD. However, little is known about the correlations of long noncoding RNAs (lncRNAs) with BD. Illumina high-throughput sequencing in BD patients and normal controls was used to identify differentially expressed (DE) genes. Two-step real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to validate DE-RNAs in the first cohort (50 BD and 50 control subjects). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and lncRNA-mRNA coexpression and lncRNA-microRNA (miRNA)-messenger RNA (mRNA) competing endogenous RNA (ceRNA) network analyses were used to predict the functions of DE-RNAs. Receiver operating characteristic (ROC) curve analysis and logistic regression were applied to evaluate diagnostic performance in an additional testing group (80 BD and 66 control subjects). A total of 576 significantly DE-lncRNAs and 262 DE-mRNAs were identified in BD patients, and 95 lncRNA-miRNA-mRNA interactions were used to construct a ceRNA regulatory network. Analysis of the first cohort showed that six RNAs (NR_028138.1, TCONS_00018621, TCONS_00002186, TNF, PID1, and SDK1) were differentially expressed in the BD group (P < 0.01). NR_028138.1 was used to establish a BD diagnostic model (area under the ROC curve 0.923, P < 0.004, 95% CI: 0.830-0.999). Verification in the second cohort revealed uniformly significant differences in NR_028138.1 (P < 0.0001). This study constructed a ceRNA regulatory network and provided a hypothesis for the pathogenesis of BD. NR_028138.1 was identified as a central element involved in the transcriptional regulation in BD and a potential biomarker.

Long non-coding RNAs and their involvement in bipolar disorders

Non-coding RNAs (nc-RNAs) can be defined as RNA molecules that are not translated into proteins. Although the functional meaning of many nc-RNAs remains still to be verified, several of these molecules have a clear biological importance, which goes from translation of mRNAs to DNA replication. Indeed, regulatory nc-RNAs can be classified into two groups: short non-coding RNAs (sncRNAs) and long-non coding RNAs (lncRNAs). In the last years, lncRNAs have gained increasing importance in the study of gene regulation, helping authors understand the molecular mechanisms underlying cellular physiology and pathology. LncRNAs are greater than 200 bp and accumulate in nucleus, cytoplasm and exosomes with high tissue specificity, acting in cis or in trans in order to exert enhancer or silencer modulation on gene expression. Such regulatory features, which are widespread in human cells and tissues, can be disrupted in several morbid states. Recent evidences may suggest a disruption of lncRNAs in bipolar disorders, a cluster of severe, chronic and disabling psychiatric diseases, which are characterized by major depressive states cyclically alternating with manic episodes. Here, the authors reviewed genes, classification, biogenesis, structures, functions and databases regarding lncRNAs, and also focused on bipolar disorders, in which some lncRNAs, especially those involved in inflammation and neuronal development, has reported to be dysregulated.

Altered expression of lncRNAs in autism spectrum disorder

Long non-coding RNAs (lncRNAs) have been recognized as an important epigenetic factor in the evolution of neuropsychiatric conditions. We have selected five lncRNAs (DISC2, PRKAR2A-AS1, LOC105375675, LRRC2-AS1, and LOC101928237) to measure their expression in blood samples of children with autism spectrum disorder (ASD) versus children with normal development. Expressions of DISC2, PRKAR2A-AS1 and LOC101928237 have been enhanced in ASD cases compared with healthy children (Posterior Beta = 2.508, P value<0.0001; Posterior Beta = 2.793, P value = 0.014 and Posterior Beta = 1.646, P value <0.0001, respectively). On the other hand, expression of LRRC2-AS1 has been lower in ASD patients compared with controls (Posterior Beta = -3.781, P value<0.0001). Remarkably, expression of DISC2 and PRKAR2A-AS1 have been lower in girls compared with boys (Posterior Beta = -0.982, P value<0.0001 and Posterior Beta = -0.135, P value<0.0001, respectively). In addition, expression of DISC2 has been lower in ASD cases aged more than 6 compared with those aged less than 6 years (Posterior Beta = -0.876, P value = 0.003). DISC2, LOC101928237, LRRC2-AS1, and PRKAR2A-AS1 had the area under curve (AUC) values of 0.76, 0.90, 0.92, and 0.79 in distinguishing between ASD and healthy children. Expression levels of none of DISC2, LOC101928237, LOC105375675, LRRC2-AS1, and PRKAR2A-AS1 were correlated with age of ASD cases or healthy controls. A significant correlation was detected between expressions of DISC2 and PRKAR2A-AS1. There were inverse correlations between the following pairs of lncRNAs: DISC2/LRRC2-AS1, DISC2/LOC101928237, LRRC2-AS1/PRKAR2A-AS1, LOC101928237/LRRC2-AS1, and LOC101928237 /LOC105375675. We conclude that DISC2, LOC101928237, LRRC2-AS1, and PRKAR2A-AS1 might be used as potential markers for this condition.

A Comprehensive Review on the Role of Non-Coding RNAs in the Pathophysiology of Bipolar Disorder

Aim: Bipolar disorder is a multifactorial disorder being linked with dysregulation of several genes. Among the recently acknowledged factors in the pathophysiology of bipolar disorder are non-coding RNAs (ncRNAs). Methods: We searched PubMed and Google Scholar databases to find studies that assessed the expression profile of miRNAs, lncRNAs and circRNAs in bipolar disorder. Results: Dysregulated ncRNAs in bipolar patients have been enriched in several neuron-related pathways such as GABAergic and glutamatergic synapses, morphine addiction pathway and redox modulation. Conclusion: Altered expression of these transcripts in bipolar disorder provides clues for identification of the pathogenesis of this disorder and design of targeted therapies for the treatment of patients.

Molecular landscape of long noncoding RNAs in brain disorders

According to current paradigms, various risk factors, such as genetic mutations, oxidative stress, neural network dysfunction, and abnormal protein degradation, contribute to the progression of brain disorders. Through the cooperation of gene transcripts in biological processes, the study of noncoding RNAs can lead to insights into the cause and treatment of brain disorders. Recently, long noncoding RNAs (lncRNAs) which are longer than 200 nucleotides in length have been suggested as key factors in various brain disorders. Accumulating evidence suggests the potential of lncRNAs as diagnostic or prognostic biomarkers and therapeutic targets. High-throughput screening-based sequencing has been instrumental in identification of lncRNAs that demand new approaches to understanding the progression of brain disorders. In this review, we discuss the recent progress in the study of lncRNAs, and addresses the pathogenesis of brain disorders that involve lncRNAs and describes the associations of lncRNAs with neurodegenerative disorders such as Alzheimer disease (AD), Parkinson disease (PD), and neurodevelopmental disorders. We also discuss potential targets of lncRNAs and their promise as novel therapeutics and biomarkers in brain disorders.

Changes in Non-Coding RNA in Depression and Bipolar Disorder: Can They Be Used as Diagnostic or Theranostic Biomarkers?

The similarities between the depressive symptoms of Major Depressive Disorders (MDD) and Bipolar Disorders (BD) suggest these disorders have some commonality in their molecular pathophysiologies, which is not apparent from the risk genes shared between MDD and BD. This is significant, given the growing literature suggesting that changes in non-coding RNA may be important in both MDD and BD, because they are causing dysfunctions in the control of biochemical pathways that are affected in both disorders. Therefore, understanding the changes in non-coding RNA in MDD and BD will lead to a better understanding of how and why these disorders develop. Furthermore, as a significant number of individuals suffering with MDD and BD do not respond to medication, identifying non-coding RNA that are altered by the drugs used to treat these disorders offer the potential to identify biomarkers that could predict medication response. Such biomarkers offer the potential to quickly identify patients who are unlikely to respond to traditional medications so clinicians can refocus treatment strategies to ensure more effective outcomes for the patient. This review will focus on the evidence supporting the involvement of non-coding RNA in MDD and BD and their potential use as biomarkers for treatment response.

Current challenges and possible future developments in personalized psychiatry with an emphasis on psychotic disorders

A personalized medicine approach seems to be particularly applicable to psychiatry. Indeed, considering mental illness as deregulation, unique to each patient, of molecular pathways, governing the development and functioning of the brain, seems to be the most justified way to understand and treat disorders of this medical category. In order to extract correct information about the implicated molecular pathways, data can be drawn from sampling phenotypic and genetic biomarkers and then analyzed by a machine learning algorithm. This review describes current difficulties in the field of personalized psychiatry and gives several examples of possibly actionable biomarkers of psychotic and other psychiatric disorders, including several examples of genetic studies relevant to personalized psychiatry. Most of these biomarkers are not yet ready to be introduced in clinical practice. In a next step, a perspective on the path personalized psychiatry may take in the future is given, paying particular attention to machine learning algorithms that can be used with the goal of handling multidimensional datasets.