AUTHOR=Ma Xiaoxia , Zhang Huan , Li Jiana 

TITLE=CLEC4E as a molecular biomarker in systemic lupus erythematosus: integrating bioinformatics and clinical data to assess its prognostic value

JOURNAL=Frontiers in Immunology

VOLUME=Volume 16 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2025.1617878

DOI=10.3389/fimmu.2025.1617878

ISSN=1664-3224

ABSTRACT=ObjectiveThis study explores the prognostic value of the CLEC4E gene in systemic lupus erythematosus (SLE) through bioinformatics analysis and evaluates its role in disease diagnosis and progression.MethodsGene expression datasets related to SLE (GSE17755, GSE50772, and GSE61635) were obtained from the GEO (Gene Expression Omnibus) database. Intersection analysis was performed using the Jvenn tool with a screening threshold of |log2FC| > 1 and P< 0.05 to identify differentially expressed genes (DEGs). The resulting DEGs were then cross-referenced with immune-related genes in the GeneCards database (relevance score > 8) to further prioritize candidates with immunological relevance. Peripheral blood from 360 SLE patients and 360 healthy controls was collected for CLEC4E expression analysis via RT-qPCR. Disease activity was evaluated using the SLEDAI score, and patients were grouped accordingly. Pearson and Spearman correlation analysis to investigate the relationship between CLEC4E and immune indicators. Logistic regression and ROC analyses were conducted to assess diagnostic and prognostic value. Kaplan-Meier analysis evaluated survival outcomes.ResultsBioinformatics analysis identified six SLE-related DEGs, namely ISG15, HERC5, TNFAIP6, IFIT3, OASL, and CLEC4E. Further intersection with immune-related genes from the GeneCards database (relevance score > 8) ultimately highlighted CLEC4E as the key gene for clinical validation. The expression level of CLEC4E was significantly higher in SLE patients compared with healthy controls. ROC analysis showed good diagnostic performance (AUC = 0.7744). CLEC4E expression was higher in active SLE, and multivariate analysis identified CLEC4E, C3, C4, ANA, and anti-dsDNA as independent predictors of disease activity. CLEC4E demonstrated moderate diagnostic value for distinguishing active from inactive disease (AUC = 0.6360). Higher CLEC4E expression was associated with worse prognosis (P = 0.0002). The combined diagnostic performance with other biomarkers (C3, C4, ANA, anti-dsDNA) showed a remarkable AUC of 0.9407.ConclusionCLEC4E is a potential biomarker for SLE diagnosis, disease activity assessment, and prognosis evaluation.