Bioinformatics Analysis Identifies Potential Diagnostic Biomarkers of Sarcoidosis
Keywords:
Sarcoidosis, Differentially expressed genes, Diagnostic markers, Immune infiltrationAbstract
Background and aim: Sarcoidosis is a complex inflammatory disorder characterized by the formation of non-caseating granulomas, which can affect multiple systems, with a predominant impact on the lungs and thoracic lymph nodes. The aim of the study is to identify potential diagnostic markers and explore the infiltration of immune cells associated with sarcoidosis.
Methods: The datasets of GSE19314, GSE83456, and GSE37912 were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were screened by comparing sarcoidosis samples to healthy controls in GSE19314 and GSE83456. Functional enrichment analyses and protein-protein interactions (PPIs) network construction were performed to elucidate the functional roles of the DEGs. Hub genes were identified through PPI network analysis. The GSE37912 dataset was used as validation set. Immune cell infiltration in patients diagnosed with sarcoidosis was investigated. Furthermore, the trehalose 6,6′-dimycolate-granuloma (TDM)-induced granuloma experimental model was employed to resemble human sarcoid granulomas, and the expression of hub genes in lung tissues was detected by qRT-PCR.
Results: A total of 71 common DEGs, including 53 upregulated DEGs and 18 downregulated DEGs, was identified between sarcoidosis individuals and controls. The genes signal transducer and activator of transcription 1 (STAT1), C-X-C motif chemokine ligand 10 (CXCL10) and basic leucine zipper ATF-like transcription factor 2 (BATF2) were considered hub genes and showed potential diagnostic capabilities of sarcoidosis. Immune infiltration analysis showed that compared with the control group, activated NK cells, monocytes, macrophage, activated dendritic cells and resting mast cell were higher infiltrated in sarcoidosis. In TDM-induced lung granuloma model, expression of STAT1, CXCL10 and BATF2 was increased in sarcoidosis lung tissue.
Conclusions: Bioinformatics analysis indicated that STAT1, CXCL10 and BATF2 may become new candidate biomarkers for sarcoidosis diagnosis.
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