Abstract
BACKGROUND: Autoimmune mechanisms have important roles in the pathogenesis of alopecia areata (AA). OBJECTIVE: This study aimed to evaluate the exact biological and clinical importance of immunogenes in AA patients using bioinformatic methods. METHODS: Five AA scalp gene expression profiles were obtained from the Gene Expression Omnibus database. Differentially-expressed genes (DEGs) between AA and control groups were identified. An immune-related gene diagnostic signature (IRGDS) was established by protein-protein interaction network analysis, least absolute shrinkage and selection operator and logistic regression analysis. RESULTS: A total of 102 immune-related DEGs were identified. We developed an IRGDS composed of CD8A, CSF1R and CXCL10 for AA molecular pathological assessment and diagnosis (area under the receiver operating characteristic curve [AUC]=0.962). We also validated the diagnostic value of the IRGDS in an external cohort (AUC=0.955). Patients with high IRGDS scores presented with a higher abundance of immune cell infiltration and expression of genes associated with immune recruitment and immune activation, suggesting adverse biological alterations. CONCLUSION: In our study, an IRGDS model with accurately diagnostic capacity for AA was established, and biological alterations were deciphered in AA. The IRGDS may be used as an auxiliary diagnostic marker for AA.