Analysis of Key Genes Related to Systemic Lupus Erythematosus and COVID-19

Author:

Guan Rui1,Yu Jing2,Zheng Jiannan2,Zhao Yeyu2,Zhang Bolun1,Wang Min1,Gao Mingli2

Affiliation:

1. Liaoning University Of Traditional Chinese Medicine, Shenyang, China

2. Rheumatology Department, The Affiliated Hospital Of Liaoning University Of Traditional Chinese Medicine, Shenyang, China

Abstract

Background: Systemic Lupus Erythematosus (SLE) is a multifactorial and complex immune disease; however, the relevance of COVID-19 infection in SLE patients remains uncertain. Aim: This study aims to explore the key candidate genes and pathways in patients with SLE. It also seeks to employ bioinformatics analysis to unravel the molecular signatures inherent in both SLE and COVID-19 patients. The ultimate aim is to identify potential targets and markers specifically relevant to SLE patients who contract SARS-CoV-2. Methods: Datasets (GSE12374, GSE20864, GSE61635, GSE81622, and GSE144390) from the Gene Expression Omnibus (GEO) database were analyzed using Robust Rank Aggregation (RRA) method to identify differential expression genes (DEGs) in SLE patients compared to healthy individuals. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, tissue-specific gene analysis, and Protein-protein interaction (PPI) network were performed. Finally, the Venn diagram was employed to identify the intersections of COVID-19 genes, serving as potential targets for SLE patients with COVID-19 infection. Results: A total of 154 DEGs were discovered, with GO enrichment indicating a predominant involvement in the defense response against the virus (P<0.001). KEGG pathway analysis showed enrichment in the NOD-like receptor signaling pathway and coronavirus disease, specifically COVID-19 (P<0.001). Tissue-specific genes related to the hematological and immune systems were emphasized (74%). The PPI network highlighted 22 genes, and 5 key genes, namely, IFIT1, IFIT3, MX1, MX2, and OAS3, which were identified after intersecting with COVID-19 patients’ data. Conclusion: IFIT1, IFIT3, MX1, MX2, and OAS3 exhibiting differential expression, as well as the pathways associated with COVID-19, could potentially function as biomarkers and therapeutic targets for individuals with SLE infected with COVID-19.

Publisher

Bentham Science Publishers Ltd.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3