Abstract : Objective To identify the key genes associated with preclampsia in the pregnant women with systemic lupus erythematosus(SLE)using bioinformatics methods and analyze their biological finctioms. MethodsT'he gene expression dataset CSE108497 relatedto preeclampsia in SLE pregnancy was obtained from the Gene Expression Omnilus ( CEO）) database. Differentially expressexl genes( DECs) were screened using R software. Cene Ontology (CO) functional annotation and Kyoto Encyclopedia of Cenes and Cenomes(KECC) pathway enrichment analyses were peformed on the DECs 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 wereploted 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 CSE108497 dataset， including 105 upregulated and 57 downregulated genes. CO analysis revealed that the DECswere mainly involved in T lymphocyte activation and differentiation，neutrophil-mediated immune regulation and degranulation.KECGanalysis indicaterl that DECs primarily regulate pathways involved in pmrimary immunodeficiency， glyeolysis and antigen presentation.PPI network analysis identified 9 key genes:HMGN2，EEFIB2，RPL32,BTF3，MRPL1l, EEFID，EEFlAl，RPL6 and RPLP1.ROC curve analysis suggested that these genes had high diagnostic value for preeclampsia in SLE pregnancy with areas under the curve(AUCRE) greater than 0.9.ConclusionThis stutly identified 9 key genes associated with preclampsia in SLE pregnancy usingbioinformatics analysis of the CEO datalase. These findings provide potential biomarkers and therapeutic targets for the diagnosis andtreatment of preeclampsia in SLE pregnancy.