ArticleFrontiers in endocrinology2023
Identification of biomarkers for the diagnosis of chronic kidney disease (CKD) with non-alcoholic fatty liver disease (NAFLD) by bioinformatics analysis and machine learning.
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 22 papers, 1 of them a synthesis that pooled it.
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22 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Advanced applications in chronic disease monitoring using IoT mobile sensing device data, machine learning algorithms and frame theory: a systematic review.Frontiers in public health · 2025Pooled it
- Identification of shared diagnostic biomarkers and molecular pathways between chronic kidney disease and renal cell carcinoma using transcriptomics and machine learning.Translational cancer research · 2026Article
- Emerging Urinary Biomarkers and Innovative Technologies for the Early Detection and Personalized Management of Chronic Kidney Disease.International journal of molecular sciences · 2026Review
- Vitamin D and Metabolic Dysfunction-Associated Steatotic Liver Disease: Molecular Mechanisms and Clinical Implications-A Narrative Review.International journal of molecular sciences · 2026Review
- A comprehensive cancer analysis investigating the oncogenic role of zinc finger protein 36 (ZFP36) in human tumors.Scientific reports · 2026Article
- Identification of Ferroptosis-Related Hub Genes and Immune Infiltration Landscape in Chronic Kidney Disease via Bioinformatics and Experimental Verification.Immunity, inflammation and disease · 2026Article
- Integrated bioinformatics and machine learning identify early diagnostic biomarkers for MAFLD with comorbid psoriasis.Frontiers in immunology · 2026Article
- Keratin 20 Suppresses Exosomal Secretion of Peroxiredoxin 2 and Ferroptosis in Acute Kidney Injury.Journal of the American Society of Nephrology : JASN · 2026Article
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- Orphan Nuclear Receptors in Metabolic Dysfunction-associated Steatotic Liver Disease Development.Journal of clinical and translational hepatology · 2025Review
- Screening of biomarkers for diagnosing chronic kidney disease and heart failure with preserved ejection fraction through bioinformatics analysis.Biochemistry and biophysics reports · 2025Article
- Global burden of MAFLD, MAFLD related cirrhosis and MASH related liver cancer from 1990 to 2021.Scientific reports · 2025Article
- Are we ready to integrate advanced artificial intelligence models in clinical laboratory?Biochemia medica · 2025Review
- An insight on the additive impact of type 2 diabetes mellitus and nonalcoholic fatty liver disease on cardiovascular consequences.Molecular biology reports · 2025Review
- Machine learning applications in healthcare clinical practice and research.World journal of clinical cases · 2025Article
- Uncovering biomarkers and molecular pathways linking NAFLD and AIS: Insights from bioinformatic analysis and experiment.PloS one · 2025Article
- The hepatocellular model of fatty liver disease: from current imaging diagnostics to innovative proteomics technologies.Frontiers in medicine · 2025Review
- Unveiling functionality and conducting two-sample mendelian randomization on WGCNA-identified oxidative stress-related hub genes in metabolic dysfunction-associated fatty liver disease.Biochemistry and biophysics reports · 2024Article
- Machine learning-based comparison of factors influencing estimated glomerular filtration rate in Chinese women with or without non-alcoholic fatty liver.World journal of clinical cases · 2024Article
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Abstract
Background: Chronic kidney disease (CKD) and non-alcoholic fatty liver disease (NAFLD) are closely related to immune and inflammatory pathways. This study aimed to explore the diagnostic markers for CKD patients with NAFLD. Methods: CKD and NAFLD microarray data sets were screened from the GEO database and analyzed the differentially expressed genes (DEGs) in GSE10495 of CKD date set. Weighted Gene Co-Expression Network Analysis (WGCNA) method was used to construct gene coexpression networks and identify functional modules of NAFLD in GSE89632 date set. Then obtaining NAFLD-related share genes by intersecting DEGs of CKD and modular genes of NAFLD. Then functional enrichment analysis of NAFLD-related share genes was performed. The NAFLD-related hub genes come from intersection of cytoscape software and machine learning. ROC curves were used to examine the diagnostic value of NAFLD related hub genes in the CKD data sets and GSE89632 date set of NAFLD. CIBERSORTx was also used to explore the immune landscape in GSE104954, and the correlation between immune infiltration and hub genes expression was investigated. Results: A total of 45 NAFLD-related share genes were obtained, and 4 were NAFLD-related hub genes. Enrichment analysis showed that the NAFLD-related share genes were significantly enriched in immune-related pathways, programmed cell death, and inflammatory response. ROC curve confirmed 4 NAFLD-related hub genes in CKD training set GSE104954 and other validation sets. Then they were used as diagnostic markers for CKD. Interestingly, these 4 diagnostic markers of CKD also showed good diagnostic value in the NAFLD date set GSE89632, so these genes may be important targets of NAFLD in the development of CKD. The expression levels of the 4 diagnostic markers for CKD were significantly correlated with the infiltration of immune cells. Conclusion: 4 NAFLD-related genes (DUSP1, NR4A1, FOSB, ZFP36) were identified as diagnostic markers in CKD patients with NAFLD. Our study may provide diagnostic markers and therapeutic targets for CKD patients with NAFLD.
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