Identification of Unique Transcriptomic Signatures and Hub Genes Through RNA Sequencing and Integrated WGCNA and PPI Network Analysis in Nonerosive Reflux Disease

通过RNA测序和整合WGCNA和PPI网络分析鉴定非糜烂性反流病中独特的转录组特征和枢纽基因

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Abstract

PURPOSE: Transcriptomic studies on gastroesophageal reflux disease are scarce, and gene expression signatures in nonerosive reflux disease (NERD) remain elusive. The aim of the study was to identify gene expression profiles and potential hub genes in NERD. PATIENTS AND METHODS: We performed RNA sequencing on biopsy samples from nine consecutive patients with NERD and six healthy controls. Differentially expressed genes (DEGs) were analysed with the DESeq2 R package. A DEG-based protein-protein interaction (PPI) network was constructed to filter hub genes using Cytoscape. Weighted gene coexpression network analysis (WGCNA) was conducted to identify the coexpression relationships of all modules and explore the relationship between gene sets and clinical traits. RESULTS: In total, 1195 DEGs were identified, including 649 upregulated and 546 downregulated genes involved in regulating the inflammatory response and epithelial cell differentiation. Overlap of the PPI and WGCNA networks identified five shared genes, namely, THY1, BMP2, LOX, KDR and MMP9, as candidate hub genes in NERD. Quantitative PCR analysis of the expression of these five genes confirmed the sequencing results. Receiver operating characteristic analyses indicated that these hub genes had diagnostic potential for NERD patients. Gene set enrichment analysis confirmed that each hub gene was closely associated with the pathophysiological processes of NERD. In addition, a regulatory network comprising 42 transcription factors (TFs), 28 miRNAs and 5 hub genes was established. CONCLUSION: The five core genes may be promising biomarkers of NERD. The TF/miRNA/hub gene network can improve the understanding of the molecular mechanisms underlying disease progression.

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