Identification of a Novel Three-immunogene Diagnostic Signature for Alopecia Areata
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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 immu- nogenes in AA patients using bioinformatic methods. Methods: Five AA scalp gene expression profiles were obtained from the Gene Expression Omni- bus database. Differentially-expressed genes (DEGs) between AA and control groups were iden- tified. An immune-related gene diagnostic signature (IRGDS) was established by protein-pro- tein 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 pre- sented 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 estab- lished, and biological alterations were deciphered in AA. The IRGDS may be used as an auxiliary diagnostic marker for AA.
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 immu- nogenes in AA patients using bioinformatic methods. Methods: Five AA scalp gene expression profiles were obtained from the Gene Expression Omni- bus database. Differentially-expressed genes (DEGs) between AA and control groups were iden- tified. An immune-related gene diagnostic signature (IRGDS) was established by protein-pro- tein 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 pre- sented 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 estab- lished, and biological alterations were deciphered in AA. The IRGDS may be used as an auxiliary diagnostic marker for AA.