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ArticleCombinatorial chemistry & high throughput screening2025

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

Rui Guan, Jing Yu, Jiannan Zheng, Yeyu Zhao, Bolun Zhang, Min Wang, Mingli Gao

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Article in Combinatorial chemistry & high throughput screening, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

7 authors.

Rui GuanLiaoning University of Traditional Chinese Medicine, Shenyang, China.
Jing YuDepartment of Rheumatology, The Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang, China.
Jiannan ZhengDepartment of Rheumatology, The Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang, China.
Yeyu ZhaoDepartment of Rheumatology, The Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang, China.
Bolun ZhangLiaoning University of Traditional Chinese Medicine, Shenyang, China.
Min WangLiaoning University of Traditional Chinese Medicine, Shenyang, China.
Mingli GaoDepartment of Rheumatology, The Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSystemic Lupus Erythematosus (SLE) is a multifactorial and complex immune disease; however, the relevance of COVID-19 infection in SLE patients remains uncertain.

aimThis 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.

methodsDatasets (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.

resultsA 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.

conclusionIFIT1, 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.

Indexed as

COVID-19Lupus Erythematosus, SystemicComputational BiologyDatabases, GeneticGene Expression ProfilingGene OntologyGene Regulatory NetworksHumansProtein Interaction MapsSARS-CoV-2bioinformatics analysisCOVID-19differential expression genesprotein-protein interaction (PPI).Systemic lupus erythematosus

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.