ArticleIndian journal of dermatology
Pathogenesis of Alopecia Areata Based on Bioinformatics Analysis.
Article in Indian journal of dermatology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 8 citations in OpenAlex.
- Meta-Analysis of Gene Expression Reveals the Core Transcriptomic Profile of Lesional Scalp in Alopecia Areata.Dermatology and therapy · 2025Review
- Identification of SLC40A1, LCN2, CREB5, and SLC7A11 as ferroptosis-related biomarkers in alopecia areata through machine learning.Scientific reports · 2024Article
- Hair Follicle-Related MicroRNA-34a Serum Expression and rs2666433A/G Variant in Patients with Alopecia: A Cross-Sectional Analysis.Biomolecules · 2022Article
- Article
- Perinatal Exposure to Nicotine Alters Sperm RNA Profiles in Rats.Frontiers in endocrinology · 2022Article
- CTLA4 +49AG (rs231775) and CT60 (rs3087243) gene variants are not associated with alopecia areata in a Mexican population from Monterrey Mexico.Anais brasileiros de dermatologiaArticle
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAlopecia 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.
aimTo explore the possible mechanisms of AA and to provide a basis for the early diagnosis and treatment of AA.
methodsGene 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.
resultsThe 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.
conclusionsThe 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.
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