Nucleus pulposus (NP) is the core substance to maintain the homeostasis of intervertebral disc and stability of biomechanics. The insufficient supply of nutrition (especially glucose) is an important factor that leads to the degeneration of NP cells. circRNAs play an important role in the process of intervertebral disc degeneration (IDD) by regulating the functions of NP cells. However, glucose deprivation-related circRNAs and their functions in IDD have not been reported. In this study, the differentially expressed circRNAs in NP cells after 0, 6, 12, and 24 h of glucose deprivation culture were detected by a microarray assay. Besides, time series clustering analysis by STEM software obtained the differentially up- and downregulated circRNAs during glucose deficiency. Then, the main functions and pathways of up- and downregulated circRNAs were predicted by the functional enrichment analysis. By constructing the circRNA-miRNA regulatory network, the potential mechanisms of the most differentially expressed circRNAs were predicted. In addition, according to in vitro validation, circ_0075062 was upregulated in degenerating NP tissues and glucose deprivation-induced NP cell degeneration. Based on Sanger sequencing and RNase tolerance assay, circ_0075062 was the circular transcript. Interfering with circ_0075062 expression could potentially alleviate the imbalance of extracellular matrix (ECM) synthesis and degradation in the NP cells induced by glucose deprivation. Together, these findings help us gain a comprehensive understanding of the underlying mechanisms of IDD, and circ_0075062 may be a promising therapeutic target of IDD.
Intervertebral disc degeneration (IDD), a major cause of lower back pain, has multiple contributing factors including genetics, environment, age, and loading history. Bioinformatics analysis has been extensively used to identify diagnostic biomarkers and therapeutic targets for IDD diagnosis and treatment. However, multiple microarray dataset analysis and machine learning methods have not been integrated. In this study, we downloaded the mRNA, microRNA (miRNA), long noncoding RNA (lncRNA), and circular RNA (circRNA) expression profiles (GSE34095, GSE15227, GSE63492
GSE116726, GSE56081 and GSE67566) associated with IDD from the GEO database. Using differential expression analysis and recursive feature elimination, we extracted four optimal feature genes. We then used the support vector machine (SVM) to make a classification model with the four optimal feature genes. The ROC curve was used to evaluate the model’s performance, and the expression profiles (GSE63492, GSE116726, GSE56081, and GSE67566) were used to construct a competitive endogenous RNA (ceRNA) regulatory network and explore the underlying mechanisms of the feature genes. We found that three miRNAs (hsa-miR-4728-5p, hsa-miR-5196-5p, and hsa-miR-185-5p) and three circRNAs (hsa_circRNA_100723, hsa_circRNA_104471, and hsa_circRNA_100750) were important regulators with more interactions than the other RNAs across the whole network. The expression level analysis of the three datasets revealed that BCAS4 and SCRG1 were key genes involved in IDD development. Ultimately, our study proposes a novel approach to determining reliable and effective targets in IDD diagnosis and treatment.
Micro RNAs (miRNAs) are widely recognized to play an essential role via target genes in the development of intervertebral disc degeneration( IDD), but the molecular mechanisms remain unclear. To identify the key microRNAs and potential targets during IDD, the Gene Expression Omnibus datasets (GSE19943, GSE63492, and GSE116726) were downloaded.An R package was used to identify differentially expressed miRNAs (DEMs) and four online tools(TargetScan, miRDB, miRTarBase, and DIANA-TarBase) were performed to predict their target genes. Functional enrichment analysis revealed that DEMs gene targets were highly enriched in cell development, cell differentiation, and the p53 and Wnt signaling pathways. we identified 13 hub genes with node degree≥10 through established a protein-protein interaction (PPI) network. Among them,MAPK8, BMP4, and GSK3B were top 3 highest degree. After constructing the miRNA-target gene-functional analysis network, we found that most hub genes could be regulated by miR-557 and were mainly enriched in cell development, cell differentiation, and Wnt signaling pathway. Further in vitro experiment by qRT-PCR confirmed that miR-577 was significantly downregulated than the control,whereas miR-516-3p was significantly upregulated. Together, the key microRNA and their target genes identified in this study help us understand the underlying pathogenesis mechanisms in the development of IDD, and provide diagnostic biomarkers and new therapeutic strategies for the treatment of IDD.
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