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斑秃新型三免疫基因诊断标志物的鉴定

Identification of a Novel Three-immunogene Diagnostic Signature for Alopecia Areata.

作者信息

Chen Xiuwen, Liang Wenzi, Lin Changmin, Lin Yike

机构信息

Department of Neurology, The First Affiliated Hospital of Shantou University Medical College, Shantou, China.

Department of Histology and Embryology, Shantou University Medical College, Shantou, China.

出版信息

Ann Dermatol. 2025 Feb;37(1):22-31. doi: 10.5021/ad.24.053.

Abstract

BACKGROUND

Autoimmune mechanisms have important roles in the pathogenesis of alopecia areata (AA).

OBJECTIVE

This study aimed to evaluate the exact biological and clinical importance of immunogenes in AA patients using bioinformatic methods.

METHODS

Five AA scalp gene expression profiles were obtained from the Gene Expression Omnibus database. Differentially-expressed genes (DEGs) between AA and control groups were identified. An immune-related gene diagnostic signature (IRGDS) was established by protein-protein interaction network analysis, least absolute shrinkage and selection operator and logistic regression analysis.

RESULTS

A total of 102 immune-related DEGs were identified. We developed an IRGDS composed of CD8A, CSF1R and CXCL10 for AA molecular pathological assessment and diagnosis (area under the receiver operating characteristic curve [AUC]=0.962). We also validated the diagnostic value of the IRGDS in an external cohort (AUC=0.955). Patients with high IRGDS scores presented with a higher abundance of immune cell infiltration and expression of genes associated with immune recruitment and immune activation, suggesting adverse biological alterations.

CONCLUSION

In our study, an IRGDS model with accurately diagnostic capacity for AA was established, and biological alterations were deciphered in AA. The IRGDS may be used as an auxiliary diagnostic marker for AA.

摘要

背景

自身免疫机制在斑秃(AA)的发病机制中起重要作用。

目的

本研究旨在使用生物信息学方法评估免疫基因在AA患者中的确切生物学和临床重要性。

方法

从基因表达综合数据库中获取五个AA头皮基因表达谱。鉴定AA组和对照组之间的差异表达基因(DEG)。通过蛋白质-蛋白质相互作用网络分析、最小绝对收缩和选择算子以及逻辑回归分析建立免疫相关基因诊断特征(IRGDS)。

结果

共鉴定出102个免疫相关DEG。我们开发了一种由CD8A、CSF1R和CXCL10组成的IRGDS,用于AA的分子病理评估和诊断(受试者操作特征曲线下面积[AUC]=0.962)。我们还在外部队列中验证了IRGDS的诊断价值(AUC=0.955)。IRGDS评分高的患者表现出更高丰度的免疫细胞浸润以及与免疫募集和免疫激活相关基因的表达,提示不良生物学改变。

结论

在我们的研究中,建立了一种对AA具有准确诊断能力的IRGDS模型,并解读了AA中的生物学改变。IRGDS可作为AA的辅助诊断标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5678/11791023/1aa87adc45fc/ad-37-22-g001.jpg

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