Then, the serum levels of these markers in different groups of AA patients were detected to validate the results of bioinformatics analysis. Results: We identified four key genes that significantly increased ( CD8A, PRF1, and XCL1) or decreased ( BMP2) in AA tissues, especially in the subtypes of AT and AU. Moreover, 40 serum samples of healthy children from the Department of Health Care, Wuhan Children’s Hospital were used for healthy control. And the serum level of proteins coded by key genes were quantitatively detected by ELISA. Clinical information and serum samples were collected before and after treatment. Then, 80 AA children were enrolled at the Department of Dermatology, Wuhan Children’s Hospital between January 2020 to December 2020. Methods: In this study, we conducted weighted gene co-expression network analysis (WGCNA) and functional annotation analysis to identify key genes that correlated to the severity of AA. Therefore, identifying clinically available biomarkers that predict the risk of AA recurrence could improve the prognosis for AA patients. When they progress to the subtypes of alopecia totalis (AT) or alopecia universalis (AU), the outcome is unfavorable. The outcome of AA patients varies greatly.
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