Screening key genes for preeclampsia in systemic lupus erythematosus patients based on gene expression omnibus databases
10.13602/j.cnki.jcls.2024.06.14
- VernacularTitle:基于高通量基因表达数据库筛选系统性红斑狼疮妊娠并发先兆子痫的关键基因
- Author:
Hong LI
1
;
Jiao MU
;
Hong YU
Author Information
1. 武汉市中医医院检验科,武汉 430000
- Keywords:
systemic lupus erythematosus;
pregnancy;
preeclampsia;
differentially expressed genes;
gene expression omnibus database
- From:
Chinese Journal of Clinical Laboratory Science
2024;42(6):461-465
- CountryChina
- Language:Chinese
-
Abstract:
Objective To identify the key genes associated with preeclampsia in the pregnant women with systemic lupus erythematosus(SLE)using bioinformatics methods and analyze their biological functions.Methods The gene expression dataset GSE108497 related to preeclampsia in SLE pregnancy was obtained from the Gene Expression Omnibus(GEO)database.Differentially expressed genes(DEGs)were screened using R software.Gene Ontology(GO)functional annotation and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analyses were performed on the DEGs using online analysis tools.A protein-protein interaction(PPI)network was constructed using the STRING database to identify the key genes.Receiver operating characteristic(ROC)curves were plotted to evaluate the diagnostic efficacy of the key genes for preeclampsia in SLE pregnancy.Results A total of 162 DEGs were i-dentified from the GSE 108497 dataset,including 105 upregulated and 57 downregulated genes.GO analysis revealed that the DEGs were mainly involved in T lymphocyte activation and differentiation,neutrophil-mediated immune regulation and degranulation.KEGG analysis indicated that DEGs primarily regulate pathways involved in primary immunodeficiency,glycolysis and antigen presentation.PPI network analysis identified 9 key genes:HMGN2,EEFIB2,RPL32,BTF3,MRPL11,EEFID,EEF1A1,RPL6 and RPLP1.ROC curve analysis suggested that these genes had high diagnostic value for preeclampsia in SLE pregnancy with areas under the curve(AUCROC)greater than 0.9.Conclusion This study identified 9 key genes associated with preeclampsia in SLE pregnancy using bioinformatics analysis of the GEO database.These findings provide potential biomarkers and therapeutic targets for the diagnosis and treatment of preeclampsia in SLE pregnancy.
