A comprehensive analysis of type 1 interferon gene signatures in systematic lupus erythematosus and prediction of the crucial susceptible factor for Sjögren syndrome.

Abstract

This study aimed to determine the role of IFN-1 gene signatures in SLE and their association with Sjögren syndrome (SS). Publicly available data from the Gene Expression Omnibus database were used to construct the models. The random forest tree model was used to screen key IFN-1 gene signatures, and consensus clustering algorithms were used for unsupervised cluster analysis of these signatures. CIBERSORT and gene set variation analyses were used to evaluate the relative immune cell infiltration and enriched molecular pathways of the samples, respectively. Weighted gene co-expression network analysis was used to identify the co-expression modules and hub genes. Finally, univariate and multivariate logistic regression models were used to evaluate differences in clinical and laboratory characteristics between the different groups. The role of IFN-1 gene signatures in SLE was comprehensively assessed, which revealed an IFN-1 gene signature including six genes that could easily distinguish SLE patients and healthy individuals and identified two distinct IFN-1 subtypes exhibiting significant differences in clinical characteristics, immune microenvironment, and biological functional pathways. The SLE disease activity index, lower lymphocyte count, nucleotide oligomerization domain (NOD)-like receptor signaling pathway, and dendritic cell activation were strongly correlated with the IFN-1 gene signatures. In addition, we found that IFN-1 gene signatures in SLE may be an important susceptibility factor for SS, and the NOD-like receptor signaling pathway was identified as a common pathway. This study provides a comprehensive evaluation of the IFN-1 gene signatures, which may provide a new direction for the understanding of SLE and SS and help in the selection of optimal strategies for personalized immunotherapy.