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Current Pharmaceutical Design

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ISSN (Print): 1381-6128
ISSN (Online): 1873-4286

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General Research Article

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

Author(s): Saumya Choudhary, Dibyabhaba Pradhan*, Noor S. Khan, Harpreet Singh, George Thomas and Arun K. Jain*

Volume 26, Issue 29, 2020

Page: [3619 - 3630] Pages: 12

DOI: 10.2174/1381612826666200311130133

Price: $65

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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.

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

« Previous
[1]
Jia J, Li C, Yang J, Wang X, Li R, Luo S, et al. Yes-associated protein promotes the abnormal proliferation of psoriatic keratinocytes via an amphiregulin dependent pathway. Sci Rep 2018; 158(1): 14513.
[http://dx.doi.org/10.1038/s41598-018-32522-y]
[2]
Egeberg A, Thyssen JP. Factors associated with patient-reported importance of skin clearance among adults with psoriasis and atopic dermatitis. J Am Acad Dermatol 2019; 81(4): 943-9.
[http://dx.doi.org/10.1016/j.jaad.2019.06.018] [PMID: 31202869]
[3]
Zhang Y-J, Sun Y-Z, Gao X-H, Qi R-Q. Integrated bioinformatic analysis of differentially expressed genes and signaling pathways in plaque psoriasis. Mol Med Rep 2019; 20(1): 225-35.
[http://dx.doi.org/10.3892/mmr.2019.10241] [PMID: 31115544]
[4]
Melero JL, Andrades S, Arola L, Romeu A. Deciphering psoriasis. A bioinformatic approach. J Dermatol Sci 2018; 89(2): 120-6.
[http://dx.doi.org/10.1016/j.jdermsci.2017.11.010] [PMID: 29239787]
[5]
Huang Y-H, Kuo C-F, Huang L-H, Hsieh M-Y. Familial Aggregation of Psoriasis and Co-Aggregation of Autoimmune Diseases in Affected Families. J Clin Med 2019; 8(1) E115
[http://dx.doi.org/10.3390/jcm8010115] [PMID: 30669308]
[6]
Aggarwal S, Nayek A, Pradhan D, et al. dbGAPs: A comprehensive database of genes and genetic markers associated with psoriasis and its subtypes. Genomics 2017; S0888-7543(17): 30115-5. [PMID: 29031638]
[7]
Singh S, Pradhan D, Puri P, et al. Genomic alterations driving psoriasis pathogenesis. Gene 2019; 683: 61-71.
[http://dx.doi.org/10.1016/j.gene.2018.09.042] [PMID: 30287254]
[8]
Ainali C, Valeyev N, Perera G, et al. Transcriptome classification reveals molecular subtypes in psoriasis. BMC Genomics 2012; 13: 472.
[http://dx.doi.org/10.1186/1471-2164-13-472] [PMID: 22971201]
[9]
Swindell WR, Johnston A, Carbajal S, et al. Genome-wide expression profiling of five mouse models identifies similarities and differences with human psoriasis. PLoS One 2011; 6(4) e18266
[http://dx.doi.org/10.1371/journal.pone.0018266] [PMID: 21483750]
[10]
Yao Y, Richman L, Morehouse C, et al. Type I interferon: potential therapeutic target for psoriasis? PLoS One 2008; 3(7) e2737
[http://dx.doi.org/10.1371/journal.pone.0002737] [PMID: 18648529]
[11]
Gautier L, Cope L, Bolstad BM, Irizarry RA. affy-analysis of Affymetrix GeneChip data at the probe level. Bioinformatics 2004; 20(3): 307-15.
[http://dx.doi.org/10.1093/bioinformatics/btg405] [PMID: 14960456]
[12]
Sun C, Yuan Q, Wu D, Meng X, Wang B. Identification of core genes and outcome in gastric cancer using bioinformatics analysis. Oncotarget 2017; 8(41): 70271-80.
[http://dx.doi.org/10.18632/oncotarget.20082] [PMID: 29050278]
[13]
Wang Y, Zheng T. Screening of hub genes and pathways in colorectal cancer with microarray technology. Pathol Oncol Res 2014; 20(3): 611-8.
[http://dx.doi.org/10.1007/s12253-013-9739-5] [PMID: 24504536]
[14]
Yu G, Wang L-G, Han Y, He Q-Y. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS 2012; 16(5): 284-7.
[http://dx.doi.org/10.1089/omi.2011.0118] [PMID: 22455463]
[15]
Kanehisa M, Furumichi M, Tanabe M, Sato Y, Morishima K. KEGG: new perspectives on genomes, pathways, diseases and drugs. Nucleic Acids Res 2017; 45(D1): D353-61.
[http://dx.doi.org/10.1093/nar/gkw1092] [PMID: 27899662]
[16]
Welter D, MacArthur J, Morales J, et al. The NHGRI GWAS Catalog, a curated resource of SNP-trait associations. Nucleic Acids Res 2014; 42(Database issue): D1001-6.
[http://dx.doi.org/10.1093/nar/gkt1229] [PMID: 24316577]
[17]
CJ M M, MC R, GT C, JN F, JL B. The Comparative Toxicogenomics Database (CTD): A resource for comparative toxicological studies. J Exp Zoolog A Comp Exp Biol 2006; 305(9): 689-92.
[18]
Landrum MJ, Lee JM, Riley GR, et al. ClinVar: public archive of relationships among sequence variation and human phenotype. Nucleic Acids Res 2014; 42(Database issue): D980-5.
[http://dx.doi.org/10.1093/nar/gkt1113] [PMID: 24234437]
[19]
Bairoch A, Apweiler R, Wu CH, et al. The Universal Protein Resource (UniProt). Nucleic Acids Res 2005; 33(Database issue): D154-9.
[http://dx.doi.org/10.1093/nar/gki070] [PMID: 15608167]
[20]
Piñero J, Bravo À, Queralt-Rosinach N, Gutiérrez-Sacristán A, Deu-Pons J, Centeno E, et al. DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants. Nucleic Acids Res 2017; 04;45(D1): D833-9.
[21]
Carvalho-Silva D, Pierleoni A, Pignatelli M, et al. Open Targets Platform: new developments and updates two years on. Nucleic Acids Res 2019; 47(D1): D1056-65.
[http://dx.doi.org/10.1093/nar/gky1133] [PMID: 30462303]
[22]
Szklarczyk D, Gable AL, Lyon D, et al. STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res 2019; 47(D1): D607-13.
[http://dx.doi.org/10.1093/nar/gky1131] [PMID: 30476243]
[23]
Shannon P, Markiel A, Ozier O, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 2003; 13(11): 2498-504.
[http://dx.doi.org/10.1101/gr.1239303] [PMID: 14597658]
[24]
Yang Y, Zhong Z, Ding Y, Zhang W, Ma Y, Zhou L. Bioinformatic identification of key genes and pathways that may be involved in the pathogenesis of HBV-associated acute liver failure. Genes Dis 2018; 5(4): 349-57.
[http://dx.doi.org/10.1016/j.gendis.2018.02.005] [PMID: 30591937]
[25]
Nayak S, Pradhan D, Singh H, Reddy MS. Computational screening of potential drug targets for pathogens causing bacterial pneumonia. Microb Pathog 2019; 130: 271-82.
[http://dx.doi.org/10.1016/j.micpath.2019.03.024] [PMID: 30914386]
[26]
Guo P, Luo Y, Mai G, et al. Gene expression profile based classification models of psoriasis. Genomics 2014; 103(1): 48-55.
[http://dx.doi.org/10.1016/j.ygeno.2013.11.001] [PMID: 24239985]
[27]
Chen C, Wu N, Duan Q, et al. C10orf99 contributes to the development of psoriasis by promoting the proliferation of keratinocytes. Sci Rep 2018; 8(1): 8590.
[http://dx.doi.org/10.1038/s41598-018-26996-z] [PMID: 29872130]
[28]
Águeda-Pinto A, Castro LFC, Esteves PJ. The evolution of S100A7: an unusual gene expansion in Myotis bats. BMC Evol Biol 2019; 19(1): 102.
[http://dx.doi.org/10.1186/s12862-019-1433-0] [PMID: 31088346]
[29]
Ekman A-K, Vegfors J, Eding CB, Enerbäck C. Overexpression of psoriasin (S100A7) contributes to dysregulated differentiation in psoriasis. Acta Derm Venereol 2017; 97(4): 441-8.
[http://dx.doi.org/10.2340/00015555-2596] [PMID: 27958610]
[30]
Sun L, Cao Y, He N, et al. Association between LCE gene polymorphisms and psoriasis vulgaris among mongolians from inner mongolia. Arch Dermatol Res 2018; 310(4): 321-7.
[http://dx.doi.org/10.1007/s00403-018-1813-0] [PMID: 29397434]
[31]
Bergboer JGM, Tjabringa GS, Kamsteeg M, et al. Psoriasis risk genes of the late cornified envelope-3 group are distinctly expressed compared with genes of other LCE groups. Am J Pathol 2011; 178(4): 1470-7.
[http://dx.doi.org/10.1016/j.ajpath.2010.12.017] [PMID: 21435436]
[32]
Sevimoglu T, Arga KY. Computational Systems Biology of Psoriasis: Are We Ready for the Age of Omics and Systems Biomarkers? OMICS 2015; 19(11): 669-87.
[http://dx.doi.org/10.1089/omi.2015.0096] [PMID: 26480058]
[33]
Suárez-Fariñas M, Lowes MA, Zaba LC, Krueger JG. Evaluation of the psoriasis transcriptome across different studies by gene set enrichment analysis (GSEA). PLoS One 2010; 5(4) e10247
[http://dx.doi.org/10.1371/journal.pone.0010247] [PMID: 20422035]
[34]
Buerger C. Epidermal mTORC1 Signaling Contributes to the Pathogenesis of Psoriasis and Could Serve as a Therapeutic Target. Front Immunol 2018; 9: 2786.
[35]
Benhadou F, Mintoff D, Del Marmol V. Psoriasis: Keratinocytes or immune cells - which is the trigger? Dermatology (Basel) 2019; 235(2): 91-100.
[http://dx.doi.org/10.1159/000495291] [PMID: 30566935]
[36]
Pasquali L, Srivastava A, Meisgen F, et al. The keratinocyte transcriptome in psoriasis: pathways related to immune responses, cell cycle and keratinization. Acta Derm Venereol 2019; 99(2): 196-205.
[http://dx.doi.org/10.2340/00015555-3066] [PMID: 30320872]
[37]
Neve A, Cantatore FP, Maruotti N, Corrado A, Ribatti D. Extracellular matrix modulates angiogenesis in physiological and pathological conditions. BioMed Res Int 2014; 2014756078
[http://dx.doi.org/10.1155/2014/756078] [PMID: 24949467]
[38]
Georgescu S-R, Tampa M, Caruntu C, et al. Advances in understanding the immunological pathways in psoriasis. Int J Mol Sci 2019; 20(3) E739
[http://dx.doi.org/10.3390/ijms20030739] [PMID: 30744173]
[39]
Pfaff CM, Marquardt Y, Fietkau K, Baron JM, Lüscher B. The psoriasis-associated IL-17A induces and cooperates with IL-36 cytokines to control keratinocyte differentiation and function. Sci Rep 2017; 7(1): 15631.
[http://dx.doi.org/10.1038/s41598-017-15892-7] [PMID: 29142248]
[40]
Nedoszytko B, Sokołowska-Wojdyło M, Ruckemann-Dziurdzińska K, Roszkiewicz J, Nowicki RJ. Chemokines and cytokines network in the pathogenesis of the inflammatory skin diseases: atopic dermatitis, psoriasis and skin mastocytosis. Postepy Dermatol Alergol 2014; 31(2): 84-91.
[http://dx.doi.org/10.5114/pdia.2014.40920] [PMID: 25097473]
[41]
Swindell WR, Johnston A, Voorhees JJ, Elder JT, Gudjonsson JE. Dissecting the psoriasis transcriptome: inflammatory- and cytokine-driven gene expression in lesions from 163 patients. BMC Genomics 2013; 14: 527.
[http://dx.doi.org/10.1186/1471-2164-14-527] [PMID: 23915137]
[42]
Kim HJ, Lebwohl MG. Biologics and psoriasis: the beat goes on. Dermatol Clin 2019; 37(1): 29-36.
[http://dx.doi.org/10.1016/j.det.2018.07.004] [PMID: 30466686]
[43]
Miracco C, Pellegrino M, Flori ML, Vatti R, Materno M, Andreassi L. Cyclin D1, B and A expression and cell turnover in psoriatic skin lesions before and after cyclosporin treatment. Br J Dermatol 2000; 143(5): 950-6.
[http://dx.doi.org/10.1046/j.1365-2133.2000.03826.x] [PMID: 11069501]
[44]
Albanesi C, Madonna S, Gisondi P, Girolomoni G. The Interplay Between Keratinocytes and Immune Cells in the Pathogenesis of Psoriasis. Front Immunol 2018; 9: 1549.
[http://dx.doi.org/10.3389/fimmu.2018.01549] [PMID: 30034395]
[45]
Bai F, Zheng W, Dong Y, et al. Serum levels of adipokines and cytokines in psoriasis patients: a systematic review and meta-analysis. Oncotarget 2017; 9(1): 1266-78.
[http://dx.doi.org/10.18632%2Foncotarget.22260] [PMID: 29416693]
[46]
Swindell WR, Sarkar MK, Liang Y, Xing X, Baliwag J, Elder JT, et al. RNA-seq identifies a diminished differentiation gene signature in primary monolayer keratinocytes grown from lesional and uninvolved psoriatic skin. Sci Rep 2017; 7(1): 18045.
[http://dx.doi.org/10.1038/s41598-017-18404-9] [PMID: 29273799]
[47]
Muromoto R, Hirao T, Tawa K, et al. IL-17A plays a central role in the expression of psoriasis signature genes through the induction of IκB-ζ in keratinocytes. Int Immunol 2016; 28(9): 443-52.
[http://dx.doi.org/10.1093/intimm/dxw011] [PMID: 26944069]

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