BATF2 and PDK4 as diagnostic molecular markers of sarcoidosis and their relationship with immune infiltration.

Background: Sarcoidosis (SA) is an immune disorder disease featuring granulomas formation with a controversial etiopathogenesis. We aimed to uncover potential markers for SA diagnosis and explore how immune cell infiltration contributes to the pathogenesis of SA. Methods: Sarcoidosis GSE83456 samples and GSE42834 from Gene Expression Omnibus (GEO) were analyzed as the training and external validation sets, respectively. Firstly, R statistical software was employed to uncover the differentially expressed genes (DEGs) of GSE83456. Weighted gene co-expression network analysis (WGCNA) was used to reveal the key module of DEGs. Secondly, the genes of the key module were used to analyze functional correlations. Thirdly, support vector machine (SVM) algorithms and least absolute shrinkage and selection operator (LASSO) logistic regression were applied for screening and verification of the diagnostic markers for key module genes. Finally, the infiltration of immune cells in SA patients' blood samples was assessed by Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT), after which correlations of diagnostic markers immune cell and infiltration were explored. Serum samples collected from human research participants were used for confirmatory analysis of bioinformatics. A receiver operating characteristic (ROC) curve was used to evaluate the diagnostic value of Results: In total, 580 DEGs were identified from the key module. The genes PDK4 [area under the curve (AUC) =0.942] and Conclusions: The genes