Biomarkers Identification of Early Rheumatoid Arthritis via Bioinformatics Approach and Experimental Verification.

IF 1.1 4区医学 Q4 MEDICAL LABORATORY TECHNOLOGY

Annals of clinical and laboratory science Pub Date : 2024-09-01

Caifang Shen, Bin Gu, Maodan Tang, Ke Ma, Kaili Du, Jianping Wu, Youlong Xiong, Dong Zhan

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引用次数: 0

Abstract

Objective: To screen and identify potential biomarker for early rheumatoid arthritis (RA) by bioinformatic analysis and experimental investigation.

Methods: Transcriptome data of RA synovium was downloaded from GEO. Differentially expressed genes (DEGs), gene ontology (GO) functional annotation, and KEGG pathway were analyzed to inspect significative target genes. The protein-protein interaction was constructed using STRING database and Cytoscape to screen hub genes with least absolute shrinkage and selection operator (LASSO). The diagnostic effectivity of screened hub genes was analyzed with receiver operating characteristic (ROC). RA synovial fibroblast (SF) was treated with TNF-α (20ng/mL for 24h). RT-qPCR and Western blotting were used to measure mRNA and protein for screened hub gene.

Results: A total of 271 DEGs were found in GEO dataset. GO analysis indicated that DEGs mainly involved in phagocytosis, recognition and complement activation, etc. KEGG analysis suggested that DEGs were mostly enriched in the cytokine-cytokine receptor interaction, regulation of lipolysis in adipocytes, PPAR signaling pathway. LASSO regression and ROC curve indicated that ADIPOQ, CIDEA, FABP4, AQP7, LOC102723407, PLIN4, LIPE, CIDEC, PLIN1, and LEP had excellent diagnostic value. The area under ROC was 0.734. The level of ADIPOQ, LEP, LIPE, PLIN1, and PLIN4 were lower in RA group rather than that of control group (p<0.01). The higher expressions of CIDEC and FABP4 were found in RA group comparing to control group (p<0.001).

Conclusions: Identified hub genes might be valuable biomarkers for early RA diagnosis to promote precise and personal therapy.

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通过生物信息学方法和实验验证鉴定早期类风湿关节炎的生物标记物

目的通过生物信息学分析和实验研究，筛选并确定早期类风湿性关节炎（RA）的潜在生物标志物：方法：从 GEO 下载 RA 滑膜的转录组数据。方法：从 GEO 下载 RA 滑膜转录组数据，分析差异表达基因（DEGs）、基因本体论（GO）功能注释和 KEGG 通路，以检测重要的靶基因。利用 STRING 数据库和 Cytoscape 构建蛋白质-蛋白质相互作用，并使用最小绝对收缩和选择算子（LASSO）筛选枢纽基因。用接收器操作特征（ROC）分析了筛选出的中心基因的诊断效果。用 TNF-α（20ng/mL，24 小时）处理 RA 滑膜成纤维细胞（SF）。采用 RT-qPCR 和 Western 印迹法测定筛选出的枢纽基因的 mRNA 和蛋白质：结果：在 GEO 数据集中共发现 271 个 DEGs。GO分析表明，DEGs主要参与吞噬、识别和补体激活等。KEGG分析表明，DEGs主要富集于细胞因子-细胞因子受体相互作用、脂肪细胞脂肪分解调控、PPAR信号通路。LASSO回归和ROC曲线表明，ADIPOQ、CIDEA、FABP4、AQP7、LOC102723407、PLIN4、LIPE、CIDEC、PLIN1和LEP具有很好的诊断价值。ROC 下面积为 0.734。与对照组相比，RA 组的 ADIPOQ、LEP、LIPE、PLIN1 和 PLIN4 水平较低：所发现的枢纽基因可能是早期诊断 RA 的有价值的生物标志物，可促进精确的个性化治疗。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Annals of clinical and laboratory science 医学-医学实验技术

CiteScore

1.60

自引率

0.00%

发文量

112

审稿时长

6-12 weeks

期刊介绍： The Annals of Clinical & Laboratory Science welcomes manuscripts that report research in clinical science, including pathology, clinical chemistry, biotechnology, molecular biology, cytogenetics, microbiology, immunology, hematology, transfusion medicine, organ and tissue transplantation, therapeutics, toxicology, and clinical informatics.