Literature DB >> 32353685

Identification and verification of EOMEs regulated network in Alopecia areata.

Xin Yuan1, Yan Tang1, Zhixiang Zhao1, Fangfen Liu1, Wei Shi1, Yiya Zhang2, Ji Li3.   

Abstract

Alopecia areata (AA) is a common alopecia characterized by non-scarring hair loss with the dysregulated immunity. However, the pathogenesis of AA remains to be elucidated. In this study, we identified gene signatures and then analyzed transcription factor-immune regulatory network in AA using integrated bioinformatics methods. Finally, we verified potential target genes in lesions of AA patients using qPCR and immunohistochemistry. Here, 74 differentially expressed genes (DEGs) were identified in AA, which were enriched in immune-related signaling pathway. The immune analysis revealed the infiltration of γδT cells and Macrophages M1 in AA lesion. Next, the expression correlation analysis and ChIP-seq results revealed a transcription factor (EOMEs) regulated network. We found that EOMEs, a T-box transcription factor, may be involved in the immunoregulation in AA via targeting CD8A and BMP2, and it may affect keratinocytes function via regulating GZMK, LYPD6, RNF182, KRTAP5-9 and KRT73 expression. Finally, the mRNA expression of these network genes in AA lesions was confirmed using qPCR. And the increase expression of EOMEs was identified at inflammatory cells at the periphery of hair follicles and partial keratinocytes in AA tissue using immunohistochemistry. In conclusions, our research demonstrated that EOMEs may play a key role in the progression of AA via regulating immune cell infiltration and keratinocytes function, indicating EOMEs as a promising therapeutic target of AA.
Copyright © 2020 Elsevier B.V. All rights reserved.

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Keywords:  Alopecia areata; Bioinformatics analysis; EOMEs; Immunoregulation; Keratinocytes function; Transcription factor

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Year:  2020        PMID: 32353685     DOI: 10.1016/j.intimp.2020.106544

Source DB:  PubMed          Journal:  Int Immunopharmacol        ISSN: 1567-5769            Impact factor:   4.932


  1 in total

1.  CHAC1 as a novel biomarker for distinguishing alopecia from other dermatological diseases and determining its severity.

Authors:  Hassan Karami; Samira Nomiri; Mohammad Ghasemigol; Niloufar Mehrvarzian; Afshin Derakhshani; Mohammad Fereidouni; Masoud Miri-Moghaddam; Hossein Safarpour
Journal:  IET Syst Biol       Date:  2022-08-18       Impact factor: 1.468

  1 in total

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