Identification and Clinical Correlation Analysis of IFI44 in Systemic Lupus Erythematosus Combined with Bioinformatics and Immune Infiltration Analysis

Yuan Wang; Chengfeng Ma; Zhanbing Ma; Mengyi Yang; Jing Pu; Xiuhui Ma; Xi Wu; Liang Peng; Zhenghao Huo; Jie Dang

doi:10.2147/JIR.S419880

Identification and Clinical Correlation Analysis of IFI44 in Systemic Lupus Erythematosus Combined with Bioinformatics and Immune Infiltration Analysis

J Inflamm Res. 2023 Aug 1:16:3219-3231. doi: 10.2147/JIR.S419880. eCollection 2023.

Authors

Yuan Wang^{1

2

3}, Chengfeng Ma^{1

2}, Zhanbing Ma^{1

2}, Mengyi Yang^{1

2}, Jing Pu^{1

2}, Xiuhui Ma^{1

2}, Xi Wu^{1

2}, Liang Peng^{1

2}, Zhenghao Huo^#^{1

2}, Jie Dang^#^{1

2}

Affiliations

¹ School of Basic Medicine, Ningxia Medical University, Yinchuan, Ningxia, People's Republic of China.
² Key Laboratory of Fertility Preservation and Maintenance of the Ministry of Education, Ningxia Medical University, Yinchuan, Ningxia, People's Republic of China.
³ Department of Dermatology, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, People's Republic of China.

^# Contributed equally.

Abstract

Purpose: Systemic lupus erythematosus (SLE) is a chronic autoimmune disease that can cause systemic damage to multiple organs. This study aims to analyze the value and function of IFI44 in the diagnosis and pathology of SLE by bioinformatics and immune infiltration analysis.

Patients and methods: GSE49454 and GSE65391 of SLE were obtained from the GEO dataset, and R software was employed to identify DEGs and investigate their functions. The PPI network was utilized to identify hub genes associated with SLE. CIBERSORT was used to assess differences in immune cell infiltration in SLE patients and controls. ROC curve analysis was performed to evaluate the diagnostic value of IFI44 in SLE. The expression of IFI44 in PBMCs was detected by RT-qPCR, and the correlation between IFI44 expression and SLE-related clinical indicators was analyzed.

Results: A total of 65 DEGs were identified from the GSE49454 and GSE65391 databases. Through PPI analysis, IFI44 and RSAD2 were identified as significantly aberrantly expressed in SLE patients. SLE patients and controls showed a significant difference in the proportion of immune cell infiltration. IFI44 expression was positively correlated with activated DCs, monocytes, PCs, neutrophils, and activated memory CD4⁺T cells, while negatively correlated with M0 and CD8⁺T cells. The expression of IFI44 was significantly higher in SLE patients (P<0.01), especially in male patients (P=0.0376). ROC curve analysis demonstrated that IFI44 had a high diagnostic value for SLE. Correlation analysis indicated that IFI44 expression was correlated with levels of RBC, HGB, HCT, IgA, ESR, UPRO, C3, C4, and ENA in SLE patients.

Conclusion: IFI44 may play a role in the pathogenesis of SLE by influencing the immune microenvironment of SLE patients, and thus has the potential to serve as a diagnostic marker and therapeutic target for SLE.

Keywords: IFI44; bioinformatics; immune cell infiltration; sexual dimorphism; systemic lupus erythematosus.