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Войти в исследования International journal of general medicine · 2026
Construction and Analysis of ceRNA Regulatory Networks Reveal the Core Genes Associated with Rheumatoid Arthritis.
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Zhang Cheng, Chen Xiaomei, Yu Hongmin, Huang Meixia, Wang Yingzheng, Wang Yinghao
Аннотация
BACKGROUND: Circular RNAs (circRNAs), microRNAs (miRNAs), and transcription factors (TFs) participate in the immune dysregulation that drives rheumatoid arthritis (RA), but their integrated regulatory architecture in peripheral blood remains incompletely defined. We therefore constructed a circRNA-miRNA-TF-mRNA competing endogenous RNA (ceRNA) network and performed experimental validation in a collagen-induced arthritis (CIA) model.
METHODS: Publicly available RA datasets were retrieved from the Gene Expression Omnibus, including GSE189338 (circRNA), GSE124373 (miRNA), and GSE17755 (mRNA). Differentially expressed transcripts were identified with limma. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were used to characterize the differentially expressed mRNAs. TF-mRNA pairs were obtained from TRRUST v2, experimentally supported miRNA-target interactions were obtained from miRTarBase, and circRNA-miRNA interactions were predicted with CircBank. Candidate genes were cross-checked in the Comparative Toxicogenomics Database. Selected network components were validated by quantitative real-time PCR (RT-qPCR) using peripheral blood from CIA rats.
RESULTS: We identified 920 differentially expressed mRNAs, 282 differentially expressed miRNAs, and 980 differentially expressed circRNAs. Functional enrichment linked the mRNA signature to leukocyte adhesion, apoptosis-related processes, focal adhesion, and immune-inflammatory pathways relevant to RA. Integration of TF, miRNA, and circRNA layers yielded an initial network containing 6 circRNAs, 4 miRNAs, 4 TFs, and 24 mRNAs. For biological verification, we prioritized 6 circRNAs, 4 miRNAs, 3 TFs, and 8 mRNAs for RT-qPCR. Most candidates showed expression changes consistent with the discovery datasets, whereas miR-195-5p did not differ significantly between groups. After excluding the unsupported branch, the refined network comprised 5 circRNAs, 3 miRNAs, 3 TFs, and 8 mRNAs.
CONCLUSION: This study defines a blood-based circRNA-miRNA-TF-mRNA regulatory framework in RA and nominates a focused set of candidate biomarkers for subsequent mechanistic and clinical validation. The findings should be interpreted as hypothesis-generating rather than definitive evidence of causal ceRNA regulation.
METHODS: Publicly available RA datasets were retrieved from the Gene Expression Omnibus, including GSE189338 (circRNA), GSE124373 (miRNA), and GSE17755 (mRNA). Differentially expressed transcripts were identified with limma. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were used to characterize the differentially expressed mRNAs. TF-mRNA pairs were obtained from TRRUST v2, experimentally supported miRNA-target interactions were obtained from miRTarBase, and circRNA-miRNA interactions were predicted with CircBank. Candidate genes were cross-checked in the Comparative Toxicogenomics Database. Selected network components were validated by quantitative real-time PCR (RT-qPCR) using peripheral blood from CIA rats.
RESULTS: We identified 920 differentially expressed mRNAs, 282 differentially expressed miRNAs, and 980 differentially expressed circRNAs. Functional enrichment linked the mRNA signature to leukocyte adhesion, apoptosis-related processes, focal adhesion, and immune-inflammatory pathways relevant to RA. Integration of TF, miRNA, and circRNA layers yielded an initial network containing 6 circRNAs, 4 miRNAs, 4 TFs, and 24 mRNAs. For biological verification, we prioritized 6 circRNAs, 4 miRNAs, 3 TFs, and 8 mRNAs for RT-qPCR. Most candidates showed expression changes consistent with the discovery datasets, whereas miR-195-5p did not differ significantly between groups. After excluding the unsupported branch, the refined network comprised 5 circRNAs, 3 miRNAs, 3 TFs, and 8 mRNAs.
CONCLUSION: This study defines a blood-based circRNA-miRNA-TF-mRNA regulatory framework in RA and nominates a focused set of candidate biomarkers for subsequent mechanistic and clinical validation. The findings should be interpreted as hypothesis-generating rather than definitive evidence of causal ceRNA regulation.