Humanities
Skip to main content Skip to main navigation menu Skip to site footer
  • Register
  • Login
  • Menu
  • Home
  • Current
  • Archives
  • Announcements
  • About
    • About the Journal
    • Submissions
    • Editorial Team
    • Privacy Statement
    • Contact
  • Register
  • Login

Journal of Education, Health and Sport

Differentially Expressed Genes in Atopic Dermatitis: Bioinformatics analysis of pooled microarray gene expression datasets in Gene Expression Omnibus
  • Home
  • /
  • Differentially Expressed Genes in Atopic Dermatitis: Bioinformatics analysis of pooled microarray gene expression datasets in Gene Expression Omnibus
  1. Home /
  2. Archives /
  3. Vol. 63 (2024) /
  4. Medical Sciences

Differentially Expressed Genes in Atopic Dermatitis: Bioinformatics analysis of pooled microarray gene expression datasets in Gene Expression Omnibus

Authors

  • Danna Jia Washington Institute for Health Sciences https://orcid.org/0009-0009-7964-985X
  • Wenqiang Chen Georgetown University Medical Center https://orcid.org/0009-0006-6864-9932
  • Bin Li Washington Institute for Health Sciences https://orcid.org/0000-0002-1051-801X

DOI:

https://doi.org/10.12775/JEHS.2024.63.014

Keywords

atopic dermatitis, GEO database, bioinformatics, study comparison

Abstract

Introduction:

Atopic dermatitis (AD) is a chronic and refractory inflammatory skin disease characterized by relapsing eczematous and pruritic skin lesions. Understanding the specific gene expression patterns associated with AD is crucial for advancing diagnosis and targeted treatment development. Using bioinformatics methods, candidate genes and biological pathways involved in AD pathogenesis were identified based on gene expression profiles in the Gene Expression Omnibus (GEO) database.

Materials and Methods:

A comprehensive analysis of four pooled transcriptomic datasets obtained from the Gene Expression Omnibus (GEO) database were conducted. Differential gene expression analysis was performed using the GEO2R. The differentially expressed genes (DEGs) between lesion skin of AD patients and normal skin of individuals were analyzed using the Gene Ontology (GO) term enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and protein-protein interaction (PPI) network to explore the functional roles of these genes.

Results:

Among the patient-level gene expression datasets, we identified 133 shared DEGs, consisting of 48 upregulated genes and 85 downregulated genes. GO analyses revealed these DEGs to be significantly enriched in biological processes including inflammatory responses, cytokine-mediated signaling pathway. These DEGs were also enriched in the KEGG pathway, including viral protein interaction with cytokine and cytokine receptor, C-type lectin receptor signaling pathway, cytokine-cytokine receptor interaction, JAK-STAT signaling pathway, and Adipocytokine signaling pathway.

Conclusion:

By comparing with other studies using the same method, we found that in addition to the already confirmed pathways such as inflammatory response, different studies have found changes in different hub genes and metabolic pathways, which prompts us to develop individualized treatments for AD.

References

Kapur S, Watson W, Carr S. 2018. Atopic dermatitis. Allergy Asthma Clin Immunol 14:52 DOI 10.1186/s13223-018-0281-6.

Laughter MR, Maymone MBC, Mashayekhi S, Arents BW M, Karimkhani C, Langan SM, Dellavalle RP, Flohr C. 2021. The global burden of atopic dermatitis: lessons from the Global Burden of Disease Study 1990-2017. The British journal of dermatology 184: 304–309 DOI 10.1111/bjd.19580

Patrick GJ, Archer NK, Miller LS. 2021. Which Way Do We Go? Complex Interactions in Atopic Dermatitis Pathogenesis. J Invest Dermatol 141:274-284 DOI 10.1016/j.jid.2020.07.006.

Sroka-Tomaszewska J, Trzeciak M. 2021. Molecular Mechanisms of Atopic Dermatitis Pathogenesis. Int J Mol Sci 22:4130 DOI 10.3390/ijms22084130.

Bieber T. 2008. Atopic dermatitis. N Engl J Med 358:1483-1494 DOI 10.1056/NEJMra074081.

Trier AM, Kim BS. 2023. Insights into atopic dermatitis pathogenesis lead to newly approved systemic therapies. Br J Dermatol 188:698-708 DOI 10.1093/bjd/ljac016.

Schultz Larsen F. Atopic dermatitis: a genetic-epidemiologic study in a population-based twin sample. J Am Acad Dermatol 1993; 28: 719–723.

Brown SJ, Elias MS, Bradley M. 2020. Genetics in Atopic Dermatitis: Historical Perspective and Future Prospects. Acta Derm Venereol 100:adv00163 DOI 10.2340/00015555-3513.

Ghosh D, Bernstein JA, Khurana Hershey GK, Rothenberg ME, Mersha TB. 2018. Leveraging Multilayered "Omics" Data for Atopic Dermatitis: A Road Map to Precision Medicine. Front Immunol 9:2727 DOI 10.3389/fimmu.2018.02727.

Nedoszytko B, Reszka E, Gutowska-Owsiak D, et al. 2020. Genetic and Epigenetic Aspects of Atopic Dermatitis. Int J Mol Sci 21:6484 DOI 10.3390/ijms21186484.

Barrett T, Wilhite SE, Ledoux P, et al. 2013. NCBI GEO: archive for functional genomics data sets--update. Nucleic Acids Res 41:D991-D995 DOI 10.1093/nar/gks1193.

Huang DW, Sherman BT, Tan Q, et al. 2007. DAVID Bioinformatics Resources: expanded annotation database and novel algorithms to better extract biology from large gene lists. Nucleic Acids Res 35:W169-W175 DOI 10.1093/nar/gkm415.

Szklarczyk D, Franceschini A, Wyder S, et al. 2015. STRING v10: protein-protein interaction networks, integrated over the tree of life. Nucleic Acids Res 43:D447-D452 DOI 10.1093/nar/gku1003.

Su G, Morris JH, Demchak B, Bader GD. 2014. Biological network exploration with Cytoscape 3. Curr Protoc Bioinformatics 47:8.13.1-8.13.24 DOI 10.1002/0471250953.bi0813s47.

Chen G, Yan J. 2022. Integrated bioinformatics-based identification of potential diagnostic biomarkers associated with atopic dermatitis. Postepy Dermatol Alergol. 39:1059-1068 DOI 10.5114/ada.2022.114899

Yu YW, Li YF, Jiang M, Zhao JJ. 2021. SPRR2C, DEFB4A, WIF1, CRY2, and KRT19 are correlated with the development of atopic eczema. Eur Rev Med Pharmacol Sci 25:1436-1446 doi 10.26355/eurrev_202102_24851.

Peng S, Chen M, Yin M, Feng H. 2021. Identifying the Potential Therapeutic Targets for Atopic Dermatitis Through the Immune Infiltration Analysis and Construction of a ceRNA Network. Clin Cosmet Investig Dermatol 14:437-453 DOI 10.2147/CCID.S310426.

Yin H, Wang S, Gu C. 2020. Identification of Molecular Signatures in Mild Intrinsic Atopic Dermatitis by Bioinformatics Analysis. Ann Dermatol 32:130-140 DOI 10.5021/ad.2020.32.2.130.

Li HM, Xiao YJ, Min ZS, Tan C. 2019. Identification and interaction analysis of key genes and microRNAs in atopic dermatitis by bioinformatics analysis. Clin Exp Dermatol 44:257-264 DOI 10.1111/ced.13691.

Ding Y, Shao X, Li X, et al. 2016. Identification of candidate genes in atopic dermatitis based on bioinformatic methods. Int J Dermatol 55:791-800 DOI 10.1111/ijd.13291.

Zhang ZK, Yang Y, Bai SR, et al. 2014. Screening for key genes associated with atopic dermatitis with DNA microarrays. Mol Med Rep 9:1049-1055 DOI 10.3892/mmr.2014.1908

Downloads

  • PDF

Published

2024-03-08

How to Cite

1.
JIA, Danna, CHEN, Wenqiang and LI, Bin. Differentially Expressed Genes in Atopic Dermatitis: Bioinformatics analysis of pooled microarray gene expression datasets in Gene Expression Omnibus. Journal of Education, Health and Sport. Online. 8 March 2024. Vol. 63, pp. 182-202. [Accessed 28 June 2025]. DOI 10.12775/JEHS.2024.63.014.
  • ISO 690
  • ACM
  • ACS
  • APA
  • ABNT
  • Chicago
  • Harvard
  • IEEE
  • MLA
  • Turabian
  • Vancouver
Download Citation
  • Endnote/Zotero/Mendeley (RIS)
  • BibTeX

Issue

Vol. 63 (2024)

Section

Medical Sciences

License

Copyright (c) 2024 Danna Jia, Wenqiang Chen, Bin Li

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

The periodical offers access to content in the Open Access system under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0

Stats

Number of views and downloads: 590
Number of citations: 0

Search

Search

Browse

  • Browse Author Index
  • Issue archive

User

User

Current Issue

  • Atom logo
  • RSS2 logo
  • RSS1 logo

Information

  • For Readers
  • For Authors
  • For Librarians

Newsletter

Subscribe Unsubscribe

Tags

Search using one of provided tags:

atopic dermatitis, GEO database, bioinformatics, study comparison
Up

Akademicka Platforma Czasopism

Najlepsze czasopisma naukowe i akademickie w jednym miejscu

apcz.umk.pl

Partners

  • Akademia Ignatianum w Krakowie
  • Akademickie Towarzystwo Andragogiczne
  • Fundacja Copernicus na rzecz Rozwoju Badań Naukowych
  • Instytut Historii im. Tadeusza Manteuffla Polskiej Akademii Nauk
  • Instytut Kultur Śródziemnomorskich i Orientalnych PAN
  • Instytut Tomistyczny
  • Karmelitański Instytut Duchowości w Krakowie
  • Ministerstwo Kultury i Dziedzictwa Narodowego
  • Państwowa Akademia Nauk Stosowanych w Krośnie
  • Państwowa Akademia Nauk Stosowanych we Włocławku
  • Państwowa Wyższa Szkoła Zawodowa im. Stanisława Pigonia w Krośnie
  • Polska Fundacja Przemysłu Kosmicznego
  • Polskie Towarzystwo Ekonomiczne
  • Polskie Towarzystwo Ludoznawcze
  • Towarzystwo Miłośników Torunia
  • Towarzystwo Naukowe w Toruniu
  • Uniwersytet im. Adama Mickiewicza w Poznaniu
  • Uniwersytet Komisji Edukacji Narodowej w Krakowie
  • Uniwersytet Mikołaja Kopernika
  • Uniwersytet w Białymstoku
  • Uniwersytet Warszawski
  • Wojewódzka Biblioteka Publiczna - Książnica Kopernikańska
  • Wyższe Seminarium Duchowne w Pelplinie / Wydawnictwo Diecezjalne „Bernardinum" w Pelplinie

© 2021- Nicolaus Copernicus University Accessibility statement Shop