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Identification and Verification of Ferroptosis-Related Genes in Keratoconus Using Bioinformatics Analysis.

Authors :
Gao, Jing-Fan
Dong, Yue-Yan
Jin, Xin
Dai, Li-Jun
Wang, Jing-Rao
Zhang, Hong
Source :
Journal of Inflammation Research; Apr2024, Vol. 17, p2383-2397, 15p
Publication Year :
2024

Abstract

Keratoconus is a commonly progressive and blinding corneal disorder. Iron metabolism and oxidative stress play crucial roles in both keratoconus and ferroptosis. However, the association between keratoconus and ferroptosis is currently unclear. This study aimed to analyze and verify the role of ferroptosis-related genes (FRGs) in the pathogenesis of keratoconus through bioinformatics. Methods: We first obtained keratoconus-related datasets and FRGs. Then, the differentially expressed FRGs (DE-FRGs) associated with keratoconus were screened through analysis, followed by analysis of their biological functions. Subsequently, the LASSO and SVM-RFE algorithms were used to screen for diagnostic biomarkers. GSEA was performed to explore the potential functions of the marker genes. Finally, the associations between these biomarkers and immune cells were analyzed. qRT‒PCR was used to detect the expression of these biomarkers in corneal tissues. Results: A total of 39 DE-FRGs were screened, and functional enrichment analysis revealed that the DE-FRGs were closely related to apoptosis, oxidative stress, and the immune response. Then, using multiple algorithms, 6 diagnostic biomarkers were selected, and the ROC curve was used to verify their risk prediction ability. In addition, based on CIBERSORT analysis, alterations in the immune microenvironment of keratoconus patients might be associated with H19, GCH1, CHAC1, and CDKN1A. Finally, qRT‒PCR confirmed that the expression of H19 and CHAC1 was elevated in the keratoconus group. Conclusion: This study identified 6 DE-FRGs, 4 of which were associated with immune infiltrating cells, and established a diagnostic model with predictive value for keratoconus. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
11787031
Volume :
17
Database :
Complementary Index
Journal :
Journal of Inflammation Research
Publication Type :
Academic Journal
Accession number :
177990014
Full Text :
https://doi.org/10.2147/JIR.S455337