ABSTRACT
Keratoconjunctivitis sicca (KCS) is an ocular condition characterized by insufficient tear production and inflammatory irritation, with Sjögren's syndrome (SS) being a major causative factor. This study aimed to extract patient transcriptomic data from the GEO database to identify signature genes associated with the diagnosis and treatment of KCS and the expression of three key genes were experimentally verified. We performed a difference analysis on the SS patient dataset and performed a Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis on the resulting genes. Additionally, a Weighted Gene Co-expression Network Analysis (WGCNA) was constructed. Machine learning techniques were employed to analyze the most strongly correlated gene modules with SS traits. These findings were further validated using KCS immune-correlation microarrays as a validation set. The correlation of the three identified genes with 22 immune cells was assessed through immune infiltration analysis. Subsequently, a rat model of desiccated keratoconjunctivitis was established, and the modeling situation and expression of characteristic genes were analyzed at the morphological, tissue, and molecular levels. Bioinformatic prediction revealed that the expression of JAK1, SKI, ZBTB16 not only differed in the machine learning validation set, but also correlated with some immune cells in the immune infiltration analysis. The results of animal experiments showed that the transcription and expression levels of these three genes were significantly different in rat KCS tissues and normal tissues, and there were also differences in the expression of JAK1 and SKI in rat peripheral blood, as well as significant up-regulation of the expression of related inflammatory factors in KCS tissues. Through bioinformatics prediction and animal experimental validation, this study identified three differentially expressed genes in SS mediated KCS patients, which provide new potential biological targets for the diagnosis and treatment of KCS.
