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润燥止痒方治疗特应性皮炎关键基因的鉴定与验证：联合RNA测序、生物信息学分析及实验研究

Authentication and validation of key genes in the treatment of atopic dermatitis with Runfuzhiyang powder: combined RNA-seq, bioinformatics analysis, and experimental research.

作者信息

Lin Yan, Xiong Guangyi, Xia Xiansong, Yin Zhiping, Zou Xuhui, Zhang Xu, Zhang Chenghao, Ye Jianzhou

机构信息

Department of Dermatology, The No.1 Affiliated Hospital of Yunnan University of CM, Kunming, China.

Biology and Medical Statistic Unit, Basic Medical Science School, Yunnan University of CM, Kunming, China.

出版信息

Front Genet. 2024 Aug 1;15:1335093. doi: 10.3389/fgene.2024.1335093. eCollection 2024.

DOI:10.3389/fgene.2024.1335093
PMID:39149589
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11324508/
Abstract

BACKGROUND

Atopic dermatitis (AD) is inflammatory disease. So far, therapeutic mechanism of Runfuzhiyang powder on AD remains to be studied. This study aimed to mine key biomarkers to explore potential molecular mechanism for AD incidence and Runfuzhiyang powder treatment.

METHODS

The control group, AD group, treat group (AD mice treated with Runfuzhiyang powder were utilized for studying. Differentially expressed AD-related genes were acquired by intersecting of key module genes related to control group, AD group and treatment group which were screened by WGCNA and AD-related differentially expressed genes (DEGs). KEGG and GO analyses were further carried out. Next, LASSO regression analysis was utilized to screen feature genes. The ROC curves were applied to validate the diagnostic ability of feature genes to obtain AD-related biomarkers. Then protein-protein interaction (PPI) network, immune infiltration analysis and single-gene gene set enrichment analysis (GSEA) were presented. Finally, TF-mRNA-lncRNA and drug-gene networks of biomarkers were constructed.

RESULTS

4 AD-related biomarkers (Ddit4, Sbf2, Senp8 and Zfp777) were identified in AD groups compared with control group and treat group by LASSO regression analysis. The ROC curves revealed that four biomarkers had good distinguishing ability between AD group and control group, as well as AD group and treatment group. Next, GSEA revealed that pathways of E2F targets, KRAS signaling up and inflammatory response were associated with 4 biomarkers. Then, we found that Ddit4, Sbf2 and Zfp777 were significantly positively correlated with M0 Macrophage, and were significantly negatively relevant to Resting NK. Senp8 was the opposite. Finally, a TF-mRNA-lncRNA network including 200 nodes and 592 edges was generated, and 20 drugs targeting SENP8 were predicted.

CONCLUSION

4 AD-related and Runfuzhiyang powder treatment-related biomarkers (Ddit4, Sbf2, Senp8 and Zfp777) were identified, which could provide a new idea for targeted treatment and diagnosis of AD.

摘要

背景

特应性皮炎（AD）是一种炎症性疾病。迄今为止，润肤止痒散治疗AD的作用机制尚待研究。本研究旨在挖掘关键生物标志物，以探索AD发病及润肤止痒散治疗的潜在分子机制。

方法

采用对照组、AD组、治疗组（用润肤止痒散治疗的AD小鼠）进行研究。通过对加权基因共表达网络分析（WGCNA）筛选出的对照组、AD组和治疗组相关关键模块基因与AD相关差异表达基因（DEGs）进行交集分析，获得AD相关差异表达基因。进一步进行KEGG和GO分析。然后，利用LASSO回归分析筛选特征基因。应用ROC曲线验证特征基因对AD的诊断能力，以获得AD相关生物标志物。接着构建蛋白质-蛋白质相互作用（PPI）网络、免疫浸润分析和单基因基因集富集分析（GSEA）。最后，构建生物标志物的转录因子-信使核糖核酸-长链非编码核糖核酸（TF-mRNA-lncRNA）和药物-基因网络。

结果

通过LASSO回归分析，在AD组中与对照组和治疗组相比，鉴定出4个AD相关生物标志物（Ddit4、Sbf2、Senp8和Zfp777）。ROC曲线显示，这4个生物标志物在AD组与对照组以及AD组与治疗组之间具有良好的区分能力。接下来，GSEA显示E2F靶点、KRAS信号上调和炎症反应通路与这4个生物标志物相关。然后，我们发现Ddit4、Sbf2和Zfp777与M0巨噬细胞显著正相关，与静息自然杀伤细胞显著负相关。Senp8则相反。最后，生成了一个包含200个节点和592条边的TF-mRNA-lncRNA网络，并预测了20种靶向SENP8的药物。

结论

鉴定出4个与AD及润肤止痒散治疗相关的生物标志物（Ddit4、Sbf2、Senp8和Zfp777），可为AD的靶向治疗和诊断提供新思路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fbfc/11324508/f13cdafa2dbd/fgene-15-1335093-g010.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fbfc/11324508/e366fc7c8594/fgene-15-1335093-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fbfc/11324508/a58b2e23aae8/fgene-15-1335093-g007.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fbfc/11324508/f13cdafa2dbd/fgene-15-1335093-g010.jpg

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