Chronic discoidal lupus erythematosus (CDLE) is an inflammatory skin disease characterized by localized, round, red, patchy skin lesions, which often occur on the head. Inflammatory cells often show an infiltration pattern targeting hair follicles, leading to alopecia. Our study aims to analyze the characteristics of gene expression data from hair follicle samples by bioinformatics methods, and the representative genes will be validated in data from skin samples with the same disease. The gene expression profile GSE119207 was obtained from the Gene Expression Omnibus (GEO) database as an experimental set, including microarray gene expression data of 4 healthy human hair follicles and 7 lesional and non-lesional hair follicles with CDLE. Gene profile GSE81071 included 13 healthy scalp samples and 47 scalp samples from CDLE lesions as the validation set. The experimental set was analyzed by differential gene expression analysis and WGCNA, respectively, and the intersection was taken to screen the key genes. The key genes were analyzed by GO and KEGG analysis to determine the related biological processes and pathways. The protein-protein interaction network of key genes was established by string and visualized by Cytoscape, and hub genes were obtained by cytoHubba. The acquired hub genes were used as ROC curve in the validation set to verify the consistency, and the related mirnas predicted by the hub genes were obtained by miRNet (version 2.0). Finally, cibersort was used to explore the infiltration pattern of immune cells in the hair follicles of CDLE. Through this process, we found that type I interferon response-related genes activated by the RIG-1 and IL-17 signaling pathways were significantly up-regulated, and the involved hub genes were also consistently upregulated in skin tissues. This process may involve the involvement of follicular helper T cells (Tfhs).