Evidence map›Paper›PMID 38830963›Full record

ArticleScientific reports2024

Bioinformatics analysis of signature genes related to cell death in keratoconus.

Jinghua Liu, Juan Gao, Shulei Xing, Yarong Yan, Xinlin Yan, Yapeng Jing, Xuan Li

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Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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6 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Jinghua Liu *School of Medicine, Nankai University, Tianjin, 300071, China.
Juan Gao *Tianjin Eye Hospital, Tianjin Key Lab of Ophthalmology and Vision Science, Tianjin Eye Institute, Tianjin, 300020, China.
Shulei XingClinical College of Ophthalmology, Tianjin Medical University, Tianjin, 300020, China.
Yarong YanClinical College of Ophthalmology, Tianjin Medical University, Tianjin, 300020, China.
Xinlin YanSchool of Medicine, Nankai University, Tianjin, 300071, China.
Yapeng JingSchool of Medicine, Nankai University, Tianjin, 300071, China.
Xuan LiSchool of Medicine, Nankai University, Tianjin, 300071, China. xuanli08@yahoo.com.

Funding

the National Natural Science Foundation of China 82171024the Tianjin Health Research Project TJWJ2023QN080the Tianjin Key Medical Discipline (Specialty) Construction Project TJYXZDXK-016Athe Tianjin Science&Technology Foundation 20JCYBJC01450
6 · The paper itself

Abstract

Keratoconus is corneal disease in which the progression of conical dilation of cornea leads to reduced visual acuity and even corneal perforation. However, the etiology mechanism of keratoconus is still unclear. This study aims to identify the signature genes related to cell death in keratoconus and examine the function of these genes. A dataset of keratoconus from the GEO database was analysed to identify the differentially expressed genes (DEGs). A total of 3558 DEGs were screened from GSE151631. The results of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that they mainly involved in response to hypoxia, cell-cell adhesion, and IL-17 signaling pathway. Then, the cell death-related genes datasets were intersected with the above 3558 DEGs to obtain 70 ferroptosis-related DEGs (FDEGs), 32 autophagy-related DEGs (ADEGs), six pyroptosis-related DEGs (PDEGs), four disulfidptosis-related DEGs (DDEGs), and one cuproptosis-related DEGs (CDEGs). After using Least absolute shrinkage and selection operator (LASSO), Random Forest analysis, and receiver operating characteristic (ROC) curve analysis, one ferroptosis-related gene (TNFAIP3) and five autophagy-related genes (CDKN1A, HSPA5, MAPK8IP1, PPP1R15A, and VEGFA) were screened out. The expressions of the above six genes were significantly decreased in keratoconus and the area under the curve (AUC) values of these genes was 0.944, 0.893, 0.797, 0.726, 0.882 and 0.779 respectively. GSEA analysis showed that the above six genes mainly play an important role in allograft rejection, asthma, and circadian rhythm etc. In conclusion, the results of this study suggested that focusing on these genes and autoimmune diseases will be a beneficial perspective for the keratoconus etiology research.

Indexed as

Computational BiologyGene Expression ProfilingKeratoconusCell DeathDatabases, GeneticFerroptosisGene OntologyGene Regulatory NetworksHumansProtein Interaction MapsTranscriptome

Identifiers

PMID38830963
PMCPMC11148072

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