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

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

JOURNAL=Frontiers in Genetics

VOLUME=Volume 15 - 2024

YEAR=2024

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2024.1335093

DOI=10.3389/fgene.2024.1335093

ISSN=1664-8021

ABSTRACT=Atopic dermatitis (AD) is a prevalent chronic inflammatory skin disease characterized by frequent relapses. This study aims to mineidentify key biomarkers toand explore the potential molecular mechanism formechanisms underlying AD incidence. It also investigates, as well as to investigate the therapeutic mechanismeffects of Runfuzhiyang powder on AD. Differentially expressed AD-related genes were acquiredidentified by intersecting key module genes related to thefrom control group, AD group, and treatment group, which were groups and screened bythrough weighted correlation network analysis. Four AD-related biomarkers (-Ddit4, Sbf2, Senp8, and Zfp777) -were identified through thepinpointed using the least absolute shrinkage and selection operator regression analysis. The receiverReceiver operating characteristic curves revealeddemonstrated that these four biomarkers can be employed toeffectively distinguish between the AD group and control group andgroups, as well as between the AD group and treatment groupgroups. Gene set enrichment analysis revealed that these four biomarkers are linked these biomarkers to the pathways ofinvolving E2F targets, KRAS signaling upregulation, and inflammatory response. In additionresponses. Additionally, Ddit4, Sbf2, and Zfp777 were significantly positively correlatedshowed significant positive correlations with M0 macrophages and significantly negatively correlatedsignificant negative correlations with resting NK cells, while it wasSenp8 exhibited the opposite for Senp8. Finallypattern. Furthermore, a transcription factor-mRNA-long noncoding RNA network includingcomprising 200 nodes and 592 edges was generated, andconstructed, predicting 20 drugs targeting SENP8 were predicted. We believe that our study results. These findings may help design facilitate the development of novel strategies for the targeted diagnosis and treatment of AD.