Literature DB >> 32160841

Decoding Psoriasis: Integrated Bioinformatics Approach to Understand Hub Genes and Involved Pathways.

Saumya Choudhary1, Dibyabhaba Pradhan2, Noor S Khan3, Harpreet Singh2, George Thomas1, Arun K Jain3.   

Abstract

BACKGROUND: Psoriasis is a chronic immune mediated skin disorder with global prevalence of 0.2- 11.4%. Despite rare mortality, the severity of the disease could be understood by the accompanying comorbidities, that has even led to psychological problems among several patients. The cause and the disease mechanism still remain elusive.
OBJECTIVE: To identify potential therapeutic targets and affecting pathways for better insight of the disease pathogenesis.
METHOD: The gene expression profile GSE13355 and GSE14905 were retrieved from NCBI, Gene Expression Omnibus database. The GEO profiles were integrated and the DEGs of lesional and non-lesional psoriasis skin were identified using the affy package in R software. The Kyoto Encyclopaedia of Genes and Genomes pathways of the DEGs were analyzed using clusterProfiler. Cytoscape, V3.7.1 was utilized to construct protein interaction network and analyze the interactome map of candidate proteins encoded in DEGs. Functionally relevant clusters were detected through Cytohubba and MCODE.
RESULTS: A total of 1013 genes were differentially expressed in lesional skin of which 557 were upregulated and 456 were downregulated. Seven dysregulated genes were extracted in non-lesional skin. The disease gene network of these DEGs revealed 75 newly identified differentially expressed gene that might have a role in development and progression of the disease. GO analysis revealed keratinocyte differentiation and positive regulation of cytokine production to be the most enriched biological process and molecular function. Cytokines -cytokine receptor was the most enriched pathways. Among 1013 identified DEGs in lesional group, 36 DEGs were found to have altered genetic signature including IL1B and STAT3 which are also reported as hub genes. CCNB1, CCNA2, CDK1, IL1B, CXCL8, MKI 67, ESR1, UBE2C, STAT1 and STAT3 were top 10 hub gene.
CONCLUSION: The hub genes, genomic altered DEGs and other newly identified differentially dysregulated genes would improve our understanding of psoriasis pathogenesis, moreover, the hub genes could be explored as potential therapeutic targets for psoriasis. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.

Entities:  

Keywords:  Psoriasis; bioinformatic approaches; differentially expressed genes; hub gene; network analysis; pathogenesis

Year:  2020        PMID: 32160841     DOI: 10.2174/1381612826666200311130133

Source DB:  PubMed          Journal:  Curr Pharm Des        ISSN: 1381-6128            Impact factor:   3.116


  5 in total

1.  Multi-omics-based identification of atopic dermatitis target genes and their potential associations with metabolites and miRNAs.

Authors:  Animesh Acharjee; Elizaveta Gribaleva; Subia Bano; Georgios V Gkoutos
Journal:  Am J Transl Res       Date:  2021-12-15       Impact factor: 4.060

2.  Based on Gene Expression Analysis: Low-Density Neutrophil Expression Is a Characteristic of the Fast Responders Treated With Guselkumab for Psoriasis.

Authors:  Jiajing Lu; Yu Wang; Ying Li; Xiaoyuan Zhong; Yu Gong; Yangfeng Ding; Ning Yu; Yuling Shi
Journal:  Front Immunol       Date:  2022-05-26       Impact factor: 8.786

3.  CXCL10 and its related key genes as potential biomarkers for psoriasis: Evidence from bioinformatics and real-time quantitative polymerase chain reaction.

Authors:  Ailing Zou; Qichao Jian
Journal:  Medicine (Baltimore)       Date:  2021-09-24       Impact factor: 1.817

4.  Identification of Genes Potentially Associated with Melanoma Tumorigenesis Through Co-Expression Network Analysis.

Authors:  Xiuyun Xuan; Yuqi Wang; Yanhong Sun; Changzheng Huang
Journal:  Int J Gen Med       Date:  2021-11-19

5.  Identification of key apoptosis-related genes and immune infiltration in the pathogenesis of psoriasis.

Authors:  Ailing Zou; Qingtao Kong; Hong Sang
Journal:  Hereditas       Date:  2022-06-22       Impact factor: 2.595

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.