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Identification of ferroptosis-related genes in the progress of NASH

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BackgroundNon-alcoholic steatohepatitis (NASH) is becoming more widespread, and some similarities exist between its etiology and ferroptosis. However, there are limited investigations on which ferroptosis-related genes (FRGs) are regulated in NASH and how to regulate them. We screened and validated the pivotal genes linked to ferroptosis in NASH to comprehend the function of ferroptosis in the development of NASH.MethodsTwo mRNA expression data were obtained from the Gene Expression Omnibus (GEO) as the training set and validation set respectively. FRGs were downloaded from FerrDb. The candidate genes were obtained from the intersection between differentially expressed genes (DEGs) and FRGs, and further analyzed using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The hub genes were identified by the protein-protein interaction (PPI) network and Cytoscape. Then, FRGs closely related to the severity of NASH were identified and further confirmed using the validation set and mouse models. Ultimately, based on these genes, a diagnostic model was established to differentiate NASH from normal tissues using another data set from GEO.ResultsA total of 327 FRGs in NASH were acquired and subjected to GSEA. And 42 candidate genes were attained by overlapping the 585 FRGs with 2823 DEGs, and enrichment analysis revealed that these genes were primarily engaged in the fatty acid metabolic, inflammatory response, and oxidative stress. A total of 10 hub genes (PTGS2、IL1B、IL6、NQO1、ZFP36、SIRT1、ATF3、CDKN1A、EGR1、NOX4) were then screened by PPI network. The association between the expression of 10 hub genes and the progress of NASH was subsequently evaluated by a training set and verified by a validation set and mouse models. CDKN1A was up-regulated along with the development of NASH while SIRT1 was negatively correlated with the course of the disease. And the diagnostic model based on CDKN1A and SIRT1 successfully distinguished NASH from normal samples.ConclusionIn summary, our findings provide a new approach for the diagnosis, prognosis, and treatment of NASH based on FRGs, while advancing our understanding of ferroptosis in NASH.
Title: Identification of ferroptosis-related genes in the progress of NASH
Description:
BackgroundNon-alcoholic steatohepatitis (NASH) is becoming more widespread, and some similarities exist between its etiology and ferroptosis.
However, there are limited investigations on which ferroptosis-related genes (FRGs) are regulated in NASH and how to regulate them.
We screened and validated the pivotal genes linked to ferroptosis in NASH to comprehend the function of ferroptosis in the development of NASH.
MethodsTwo mRNA expression data were obtained from the Gene Expression Omnibus (GEO) as the training set and validation set respectively.
FRGs were downloaded from FerrDb.
The candidate genes were obtained from the intersection between differentially expressed genes (DEGs) and FRGs, and further analyzed using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG).
The hub genes were identified by the protein-protein interaction (PPI) network and Cytoscape.
Then, FRGs closely related to the severity of NASH were identified and further confirmed using the validation set and mouse models.
Ultimately, based on these genes, a diagnostic model was established to differentiate NASH from normal tissues using another data set from GEO.
ResultsA total of 327 FRGs in NASH were acquired and subjected to GSEA.
And 42 candidate genes were attained by overlapping the 585 FRGs with 2823 DEGs, and enrichment analysis revealed that these genes were primarily engaged in the fatty acid metabolic, inflammatory response, and oxidative stress.
A total of 10 hub genes (PTGS2、IL1B、IL6、NQO1、ZFP36、SIRT1、ATF3、CDKN1A、EGR1、NOX4) were then screened by PPI network.
The association between the expression of 10 hub genes and the progress of NASH was subsequently evaluated by a training set and verified by a validation set and mouse models.
CDKN1A was up-regulated along with the development of NASH while SIRT1 was negatively correlated with the course of the disease.
And the diagnostic model based on CDKN1A and SIRT1 successfully distinguished NASH from normal samples.
ConclusionIn summary, our findings provide a new approach for the diagnosis, prognosis, and treatment of NASH based on FRGs, while advancing our understanding of ferroptosis in NASH.

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