Preprint Article Version 1 This version is not peer-reviewed

Identification of Hub Genes and Key Pathways Associated with Atopic Dermatitis via Integrated Bioinformatics

Version 1 : Received: 28 June 2019 / Approved: 1 July 2019 / Online: 1 July 2019 (12:47:49 CEST)

How to cite: Sun, Y.; Yang, A.W.; Lenon, G.B.. Identification of Hub Genes and Key Pathways Associated with Atopic Dermatitis via Integrated Bioinformatics. Preprints 2019, 2019070018 (doi: 10.20944/preprints201907.0018.v1). Sun, Y.; Yang, A.W.; Lenon, G.B.. Identification of Hub Genes and Key Pathways Associated with Atopic Dermatitis via Integrated Bioinformatics. Preprints 2019, 2019070018 (doi: 10.20944/preprints201907.0018.v1).

Abstract

The exploration and identification of targets and pathways for Atopic dermatitis (AD) treatment and diagnosis are critical for AD control. The conventional target exploration approach such as the literature review is not satisfying in terms of efficiency and accuracy. Recently, the bioinformatic approach is drawing attention for its unique advantage of high-volume data analysis for target and pathway exploration; Open Targets Platform is the targets source for this study to extract top 200 high-rank proteins from 3122 AD associated proteins. STRING, Cytoscape, CytoHubba, ClueGo, and CluePedia function had been applied for data analysis. The KEGG Mapper search & colour pathway was the pathway map resource for identified pathways; 23 key hub genes (VDR, KIT, BCL2L11, NFKBIA, KRAS, IL13, JAK2, STAT3, IL21, IL4R, REL, PDGFRB, FOXP3, RARA, RELB, EGFR, IL21R, MYC, CREBBP, NR3C1, IL2, JAK1, and KITLG). Additionally, 8 correlated pathways and the biological process had been identified; Through this study, a viable approach for target and pathway exploration had been presented. The identified AD targets and pathways will be tested for upcoming research for traditional Chinese medicinal herb interactions

Subject Areas

atopic dermatitis; AD; dermatology; target identification; pathway identification; bioinformatics; protein-protein networks

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