Pathogenesis of alopecia areata based on bioinformatics analysis - Zhigang Zhang; Xiaoli Wang; Rongqiang Zhang (Wolters Kluwer Medknow Publications, 2019)
Background: Alopecia areata (AA) describes a sudden localized patchy alopecia. The cause of AA is not completely clear and its incidence may be related to genetic, autoimmune, and environmental factors. Aim: To explore the possible mechanisms of AA and to provide a basis for the early diagnosis and treatment of AA. Methods: Gene microarray data from 122 scalp skin biopsy tissue samples from patients with AA or healthy controls from the Gene-Cloud of Biotechnology Information database were analyzed using bioinformatics analysis methods. Molecular network analysis of the differentially expressed genes (DEGs) was conducted by Cytocluster using the Molecular Complex Detection (MCODE) algorithm. Results: The gene expression profile of skin lesions from patients with AA was significantly altered, with 111 DEGs found in the skin lesions of AA, compared with that of the healthy skin. The DEGs were mainly related to biological processes such as the development of the epidermis and inflammatory reaction. The protein-protein interaction network analysis of DEGs revealed bone morphogenetic protein 2 (BMP2) as a core protein interaction network. BMP2 acted not only via the inflammatory response but also via the signaling pathways in epithelial cell development and epidermal cell differentiation to affect the epidermal development. MCODE analysis further showed that keratins (KRTs) and keratin-associated proteins (KRTAPs) can affect the epidermal development via the epidermal development pathway. Conclusions: The abnormal development of the epidermis and inflammatory reactions in skin tissue play important roles in the pathogenesis of AA and are closely related to BMP2, KRTs, and KRTAPs genes. Limitations: Our study was limited by experimental verification.