ArticleFrontiers in immunology2023
Identification and validation of potential diagnostic signature and immune cell infiltration for NAFLD based on cuproptosis-related genes by bioinformatics analysis and machine learning.
Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 23 citations in OpenAlex.
- Copper Dyshomeostasis, Redox Buffering and Immune Aging Converge on Cuproptosis in Age-Related Diseases.Antioxidants (Basel, Switzerland) · 2026Review
- Cuproptosis: Biomarkers, Mechanisms and Treatments in Diseases.Molecules (Basel, Switzerland) · 2026Review
- Integrated bioinformatics and machine learning identify early diagnostic biomarkers for MAFLD with comorbid psoriasis.Frontiers in immunology · 2026Article
- Review
- Cuproptosis as a Potential Therapeutic Target for Steatotic Liver Disease.Biomolecules · 2025Review
- Copper and hepatic lipid dysregulation: Mechanisms and implications.World journal of hepatology · 2025Review
- Killing hepatocellular carcinoma in the NAFLD/NASH stage: a comprehensive perspective on targeting regulated cell death.Cell death discovery · 2025Review
- Review
- Mechanisms of copper metabolism and cuproptosis: implications for liver diseases.Frontiers in immunology · 2025Review
- Identification of FDFT1 and PGRMC1 as New Biomarkers in Nonalcoholic Steatohepatitis (NASH)-Related Hepatocellular Carcinoma by Deep Learning.Journal of hepatocellular carcinoma · 2025Article
- Unraveling the mechanisms underlying diabetic cataracts: insights from Mendelian randomization analysis.Redox report : communications in free radical research · 2024Article
- Review
- Article
- Examining the Pathogenesis of MAFLD and the Medicinal Properties of Natural Products from a Metabolic Perspective.Metabolites · 2024Review
- Identification and validation of cuproptosis-related genes in acetaminophen-induced liver injury using bioinformatics analysis and machine learning.Frontiers in immunology · 2024Article
- Identification and validation of potential diagnostic signature and immune cell infiltration for HIRI based on cuproptosis-related genes through bioinformatics analysis and machine learning.Frontiers in immunology · 2024Article
Corrections and comments
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Authors and funding
13 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and aims: Cuproptosis has been identified as a key player in the development of several diseases. In this study, we investigate the potential role of cuproptosis-related genes in the pathogenesis of nonalcoholic fatty liver disease (NAFLD). Method: The gene expression profiles of NAFLD were obtained from the Gene Expression Omnibus database. Differential expression of cuproptosis-related genes (CRGs) were determined between NAFLD and normal tissues. Protein-protein interaction, correlation, and function enrichment analyses were performed. Machine learning was used to identify hub genes. Immune infiltration was analyzed in both NAFLD patients and controls. Quantitative real-time PCR was employed to validate the expression of hub genes. Results: Four datasets containing 115 NAFLD and 106 control samples were included for bioinformatics analysis. Three hub CRGs (NFE2L2, DLD, and POLD1) were identified through the intersection of three machine learning algorithms. The receiver operating characteristic curve was plotted based on these three marker genes, and the area under the curve (AUC) value was 0.704. In the external GSE135251 dataset, the AUC value of the three key genes was as high as 0.970. Further nomogram, decision curve, calibration curve analyses also confirmed the diagnostic predictive efficacy. Gene set enrichment analysis and gene set variation analysis showed these three marker genes involved in multiple pathways that are related to the progression of NAFLD. CIBERSORT and single-sample gene set enrichment analysis indicated that their expression levels in macrophages, mast cells, NK cells, Treg cells, resting dendritic cells, and tumor-infiltrating lymphocytes were higher in NAFLD compared with control liver samples. The ceRNA network demonstrated a complex regulatory relationship between the three hub genes. The mRNA level of these hub genes were further confirmed in a mouse NAFLD liver samples. Conclusion: Our study comprehensively demonstrated the relationship between NAFLD and cuproptosis, developed a promising diagnostic model, and provided potential targets for NAFLD treatment and new insights for exploring the mechanism for NAFLD.
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