Bioinformatics analysis identifies candidate biomarkers associated with sarcoidosis

Linling Jin; Chunfeng Pan; Yujie Sun; Jiayi Zhang; Weiping Xie; Mengyu He

doi:10.36141/svdld.v42i4.17074

Authors

Linling Jin Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital with Nanjing Medical University, Nanjing, Jiangsu, China
Chunfeng Pan Department of Thoracic Surgery, The First Affiliated Hospital with Nanjing Medical University, Nanjing, Jiangsu, China
Yujie Sun Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital with Nanjing Medical University, Nanjing, Jiangsu, China
Jiayi Zhang Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital with Nanjing Medical University, Nanjing, Jiangsu, China
Weiping Xie Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital with Nanjing Medical University, Nanjing, Jiangsu, China
Mengyu He Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital with Nanjing Medical University, Nanjing, Jiangsu, China

Keywords:

Sarcoidosis, Differentially expressed genes, biomarkers, Immune infiltration

Abstract

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 biomarkers 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 a validation set. Immune cell infiltration in sarcoidosis patients 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, were identified between sarcoidosis patients and controls. The 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 as hub genes, showing promising diagnostic potential for sarcoidosis. Immune infiltration analysis indicated that compared with the controls, sarcoidosis samples exhibited increased infiltration of activated NK cells, monocytes, macrophage, activated dendritic cells and resting mast cells. In the TDM-induced lung granuloma model, STAT1, CXCL10 and BATF2 expression was upregulated in sarcoidosis lung tissue.

Conclusions: Bioinformatics analysis indicated that STAT1, CXCL10 and BATF2 may as candidate biomarkers associated with sarcoidosis.

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