Construction of ceRNA network mediated by circRNAs screening from microarray and identification of novel biomarkers for myasthenia gravis

Author:

Kong Xiaotong1ORCID,Wu Tao2,Chen Zhimin1,Cai Hanlu1,Wang Yu1,He Ping3,Liu Peifang1,Li Lei1,Peng Shanshan1,Tian Kuo1,Wang Jianjian1,Zhang Huixue1,Wang Lihua1ORCID

Affiliation:

1. Second Affiliated Hospital of Harbin Medical University

2. Xuanwu Hospital Capital Medical University

3. Harbin City First Hospital

Abstract

Abstract Background: Recent studies have revealed that circRNA can serve as ceRNA to participate in the development of multiple autoimmune diseases. However, the ceRNA regulatory mechanism mediated by circRNA in myasthenia gravis is not yet investigated in detail. Our study aims to explore the key circRNA as ceRNA and biomarker for the progression of MG. Methods: We used circRNA microarray to explore DECs from MG compared with control. Then we predicted the target miRNA asscociated with DECs and screened miRNAs by the algorithm of random walk with restart. DECM network was constructed to present the relationship of miRNA and circRNA. Based on the miRNAs in DECM, we predicted the target genes from different database. Next, we constructed the circRNA-miRNA-mRNA ceRNA regulated network (CMMC) to identify the hub objects. Protein–protein interaction (PPI) network analysis and module analysis were performed using the genes from CMMC. The GO and KEGG pathway enrichment analysis were carried out to analyze the function of the circRNA via targeting genes. Hypergeometric test was calculated to identify the significant circRNA-gene pairs. Following, we detected the expression of hub-circRNAs by RT-PCR. Results: 5 up-regulated circRNAs and 16 down-regulated circRNAs were obtained from microarray. 16 circRNAs and 184 miRNAs were screening by RWR algorithm and used to construct DECM. Then, 16 DECs, 184 miRNAs and 127 genes were integrated to construct the CMMC network. Based on CMMC, we identified 5 hub circRNA (hsa_circ_0004183; hsa_circ_0089153; hsa_circ_0035381; hsa_circ_0046669 and hsa_circ_0048764). We found that the expression level of hsa_circ_0004183 and hsa_circ_0035381 were upregulated and hsa_circ_0089153 had the low expression level in MG compared with control. In the end, we considerd that hsa_circ_0004183 or hsa_circ_0089153 may play key roles in the occurence of MG through miR-145-5p/SMAD4 axis. Conclusions: We found that hsa_circ_0004183, hsa_circ_0035381 and hsa_circ_0089153 can be seen as the valuable potential novel biomarker for MG. hsa_circ_0004183 or hsa_circ_008915 may participate the pathology of MG via miR-145-5p/SMAD4 axis.

Publisher

Research Square Platform LLC

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