Dataset Information

Profiling and Bioinformatics Analysis of Differentially Expressed circRNAs in Spinal Ligament Tissues of Patients with Ankylosing Spondylitis.

ABSTRACT: Recent studies have reported that circular RNAs (circRNAs) play a crucial regulatory role in a variety of human diseases. However, the roles of circRNAs in ankylosing spondylitis (AS) remain unclear. In this study, we conducted circRNA expression profiling of the spinal ligament tissues of patients with AS by RNA sequencing (RNA-seq) and analyzed the potential functions of differentially expressed circRNA by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses to investigate the potential mechanisms associated with AS. The results showed that a total of 1,172 circRNAs were detected in the spinal ligament tissue samples, of which 123 circRNAs were significantly differentially expressed by a fold?change ? 1.5 and p value < 0.05. Among these, 57 circRNAs were upregulated, and 66 were downregulated. GO and KEGG analyses demonstrated that the differentially expressed circRNAs were mainly involved in the regulation of biological processes of peptidyl-serine phosphorylation and human immune system that may be related to AS. In addition, the circRNA/miRNA interaction networks were established to predict the potential roles of differentially expressed circRNAs by bioinformatics analysis. Taken together, these results revealed the expression profiles of circRNAs and the potential functions of the differentially expressed circRNAs in the spinal ligament tissue of patients with AS, which may provide new clues for understanding the mechanisms associated with AS, and proceed to identify novel potential molecular targets for the diagnoses and treatment of AS.

SUBMITTER: Kou J

PROVIDER: S-EPMC7313148 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Profiling and Bioinformatics Analysis of Differentially Expressed circRNAs in Spinal Ligament Tissues of Patients with Ankylosing Spondylitis.

Kou Jianqiang J Liu Guoming G Liu Xiangyun X Li Tianmi T Wei Ying Y Sun Yuanliang Y Wang Ting T Wang Yingzhen Y Zheng Xiujun X

BioMed research international 20200614

Recent studies have reported that circular RNAs (circRNAs) play a crucial regulatory role in a variety of human diseases. However, the roles of circRNAs in ankylosing spondylitis (AS) remain unclear. In this study, we conducted circRNA expression profiling of the spinal ligament tissues of patients with AS by RNA sequencing (RNA-seq) and analyzed the potential functions of differentially expressed circRNA by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses to invest ...[more]

PMID: 32626759

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Project description:Background Long non-coding RNAs (lncRNAs) are important regulators in ankylosing spondylitis (AS). Few studies have examined the lncRNA-RNA binding protein (RBP) interaction in AS. This study performed bioinformatics analysis and clinical verification to identify key lncRNAs and propose their RBP interaction. Methods Three GEO datasets of AS were analyzed by differential expression analysis. The differentially expressed lncRNAs between the AS and control groups were screened out, and the intersecting lncRNAs were regarded as target lncRNAs. Functional was performed to identify target lncRNAs by enrichment analysis, co-expressed RNA analysis, and lncRNA-RBP interaction analysis. Finally, this study analyzed the differential expression level and clinical value of lncRNAs between the AS and control groups. Results Linc00304, linc00926, and MIAT were differentially expressed and upregulated. Enrichment analysis indicated that the key KEGG terms were the T-cell receptor signaling pathway and B-cell receptor signaling pathway. The key molecular function term was protein binding, and the key biological process term was adaptive immune response. In qRT-PCR results, 44 samples were validated. linc00304 expression was positively correlated with bath ankylosing spondylitis disease activity index (BASDAI), bath ankylosing spondylitis functional index (BASFI), erythrocyte sedimentation rate (ESR), and c-reactive protein (CRP). linc00926 expression was only positively correlated with ESR, whereas MIAT expression was positively correlated with BASFI, ESR, and CRP. Logistic regression revealed that linc00304, ESR, and CRP were the independent risk factors for BASDAI activation. The area under the curve (AUC) of serum linc00304 level in the diagnosis of AS was 0.687 (cutoff value: 0.413, specificity: 0.423, sensitivity: 0.900). AUC of linc00926 was 0.664 (cutoff value: 0.299, sensitivity: 0.882, specificity: 0.417). AUC of MIAT was 0.623 (cutoff value: 0.432, specificity: 0.443, sensitivity: 0.890) (all P <0.05). Conclusion Overall, this study uncovered three novel lncRNAs, which were upregulated in AS, and proposed a new lncRNA-RBP-mRNA interaction that might regulate adaptive immune response.

Project description:ObjectiveThe aim of this study was to search for key genes in ankylosing spondylitis (AS) through comprehensive bioinformatics analysis, thus providing some theoretical support for future diagnosis and treatment of AS and further research.MethodsGene expression profiles were collected from Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo/ ) by searching for the term "ankylosing spondylitis". Ultimately, two microarray datasets (GSE73754 and GSE11886) were downloaded from the GEO database. A bioinformatic approach was used to screen differentially expressed genes and perform functional enrichment analysis to obtain biological functions and signalling pathways associated with the disease. Weighted correlation network analysis (WGCNA) was used to further obtain key genes. Immune infiltration analysis was performed using the CIBERSORT algorithm to conduct a correlation analysis of key genes with immune cells. The GWAS data of AS were analysed to identify the pathogenic regions of key genes in AS. Finally, potential therapeutic agents for AS were predicted using these key genes.ResultsA total of 7 potential biomarkers were identified: DYSF, BASP1, PYGL, SPI1, C5AR1, ANPEP and SORL1. ROC curves showed good prediction for each gene. T cell, CD4 naïve cell, and neutrophil levels were significantly higher in the disease group than in the paired normal group, and key gene expression was strongly correlated with immune cells. CMap results showed that the expression profiles of ibuprofen, forskolin, bongkrek-acid, and cimaterol showed the most significant negative correlation with the expression profiles of disease perturbations, suggesting that these drugs may play a role in AS treatment.ConclusionThe potential biomarkers of AS screened in this study are closely related to the level of immune cell infiltration and play an important role in the immune microenvironment. This may provide help in the clinical diagnosis and treatment of AS and provide new ideas for further research.

Project description:Multiple symmetric lipomatosis (MSL) is a rare disorder characterized by aberrant multiple and symmetric subcutaneous adipose tissue accumulation in the face, neck, shoulders, back, chest and abdomen, severely affecting the quality of life of patients. At present, precise MSL etiology and pathogenesis remain to be elucidated. The present study first utilized a digital gene expression technique with a next‑generation sequencing platform to profile differentially expressed genes in three cases of MSL vs. normal control tissue. cDNA libraries from these tissue specimens were constructed and DNA sequenced for identification of differentially expressed genes, which underwent bioinformatic analysis using the Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) and protein‑protein interaction (PPI) network analyses. As a result, a total of 859 differentially expressed genes were identified, including 308 upregulated genes (C19orf80, Apelin, C21orf33, FAM166B and HSD11B2 were mostly upregulated 6.984‑, 4.670‑, 4.412‑, 3.693‑ and 3.561‑fold, respectively) and 551 downregulated genes [FosB proto‑oncogene, AP‑1 transcription factor subunit (FOSB), selectin (SEL) E, RAR related orphan receptor (ROR) B, salt inducible kinase (SIK)1 and epidermal growth factor‑like protein (EGFL)6 were mostly downregulated ‑9.845, ‑8.243, ‑8.123, ‑7.702 and ‑7.664 fold, respectively). The GO functional enrichment analysis demonstrated these differentially expressed genes were predominantly involved in biological processes and cellular components, while the KEGG pathway enrichment analysis demonstrated that ribosome, non‑alcoholic fatty liver disease, human T‑lymphotropic virus type 1 (HTLV‑I) infection and Alzheimer's disease pathways were altered in MSL. The PPI network data demonstrated ubiquitin C (UBC), translocator protein (TSPO), Jun Proto‑Oncogene, AP‑1 Transcription Factor (JUN) and FOS were among these differentially expressed genes that participated in regulation of adipocyte differentiation, although no previous study has linked them to MSL. In conclusion, the present study profiled differentially expressed genes in MSL and identified gene pathways that may be associated with MSL development and progression.

Dataset Information

Profiling and Bioinformatics Analysis of Differentially Expressed circRNAs in Spinal Ligament Tissues of Patients with Ankylosing Spondylitis.

Publications

Profiling and Bioinformatics Analysis of Differentially Expressed circRNAs in Spinal Ligament Tissues of Patients with Ankylosing Spondylitis.

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