ArticleFrontiers in endocrinology2023
Identification of ferroptosis-related genes in the progress of NASH.
Article in Frontiers in endocrinology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 13 citations in OpenAlex.
- Proanthocyanidin and mitoglitazone suppress lipogenesis by targeting ferroptosis in metabolic dysfunction-associated steatohepatitis.Naunyn-Schmiedeberg's archives of pharmacology · 2025Article
- Potential role of SIRT1 in cell ferroptosis.Frontiers in cell and developmental biology · 2025Review
- Machine learning-based integration identifies the ferroptosis hub genes in nonalcoholic steatohepatitis.Lipids in health and disease · 2024Article
- Abnormalities in the SIRT1-SIRT3 axis promote myocardial ischemia-reperfusion injury through ferroptosis caused by silencing the PINK1/Parkin signaling pathway.BMC cardiovascular disorders · 2023Article
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Non-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. Methods: Two 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. Results: A 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 ( Conclusion: In 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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