Abstract
Schizophrenia (SCZ) is a serious psychiatric condition with a 1% lifetime risk. SCZ is one of the top ten global causes of disabilities. Despite numerous attempts to understand the function of genetic factors in SCZ development, genetic components in SCZ pathophysiology remain unknown. The competing endogenous RNA (ceRNA) network has been demonstrated to be involved in the development of many kinds of diseases. The ceRNA hypothesis states that cross-talks between coding and non-coding RNAs, including long non-coding RNAs (lncRNAs), via miRNA complementary sequences known as miRNA response elements, creates a large regulatory network across the transcriptome. In the present study, we developed a lncRNA-related ceRNA network to elucidate molecular regulatory mechanisms involved in SCZ. Microarray datasets associated with brain regions (GSE53987) and lymphoblasts (LBs) derived from peripheral blood (sample set B from GSE73129) of SCZ patients and control subjects containing information about both mRNAs and lncRNAs were downloaded from the Gene Expression Omnibus database. The GSE53987 comprised 48 brain samples taken from SCZ patients (15 HPC: hippocampus, 15 BA46: Brodmann area 46, 18 STR: striatum) and 55 brain samples taken from control subjects (18 HPC, 19 BA46, 18 STR). The sample set B of GSE73129 comprised 30 LB samples (15 patients with SCZ and 15 controls). Differentially expressed mRNAs (DEmRNAs) and lncRNAs (DElncRNAs) were identified using the limma package of the R software. Using DIANA-LncBase, Human MicroRNA Disease Database (HMDD), and miRTarBase, the lncRNA- associated ceRNA network was generated. Pathway enrichment of DEmRNAs was performed using the Enrichr tool. We developed a protein–protein interaction network of DEmRNAs and identified the top five hub genes by the use of STRING and Cytoscape, respectively. Eventually, the hub genes, DElncRNAs, and predictive miRNAs were chosen to reconstruct the subceRNA networks. Our bioinformatics analysis showed that twelve key DEmRNAs, including BDNF, VEGFA, FGF2, FOS, CD44, SOX2, NRAS, SPARC, ZFP36, FGG, ELAVL1, and STARD13, participate in the ceRNA network in SCZ. We also identified DLX6-AS1, NEAT1, MINCR, LINC01094, DLGAP1-AS1, BABAM2-AS1, PAX8-AS1, ZFHX4-AS1, XIST, and MALAT1 as key DElncRNAs regulating the genes mentioned above. Furthermore, expression of 15 DEmRNAs (e.g., ADM and HLA-DRB1) and one DElncRNA (XIST) were changed in both the brain and LB, suggesting that they could be regarded as candidates for future biomarker studies. The study indicated that ceRNAs could be research candidates for investigating SCZ molecular pathways.
Highlights
Schizophrenia (SCZ) is a severe psychotic disorder with a lifetime risk of almost 1%
A recent postmortem transcriptional profiling study shows a considerable burden of differentially expressed genes (DEGs) across hippocampus (HPC), Brodmann area 46 (BA46), and striatum (STR) regions and reveals that multiple signaling and inflammatory pathways are dysregulated in all three regions in SCZ7
It was suggested that cross-talk between both coding and non-coding RNAs such as long non-coding RNAs (lncRNAs), circular RNAs, and pseudogenes via miRNA response elements (MREs), as miRNA complementary sequences, leads to the formation of a large-scale regulatory network in diverse parts of the t ranscriptome[22]
Summary
Schizophrenia (SCZ) is a severe psychotic disorder with a lifetime risk of almost 1%. A growing body of evidence has indicated that the brain is linked to the periphery via the circulatory system containing hormones and other secreted regulatory molecules produced in the diffuse neuroendocrine system which impact the gene expression pattern of the peripheral m arkers[8,9] These findings are confirmatory evidence that SCZ is a systemic disorder and support the notion that investigation of the SCZ can be through studying the biomarkers in the peripheral samples such as whole blood, peripheral blood mononuclear cells (PBMCs), lymphoblasts (LBs), and olfactory e pithelium[10,11,12,13]. Numerous studies demonstrated alterations in non-coding RNA (ncRNA) in people with S CZ14 These findings provided information concerning the underlying mechanisms of dysregulation in gene expression and protein production. Given that SCZ is one of the ten most prevalent causes of disability globally and since the nature of the genetic component in SCZ pathophysiology is not fully understood, we performed a bioinformatics analysis to elucidate the lncRNA-associated ceRNA network to clarify molecular regulatory mechanisms involved in SCZ
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