ArticleMolecular medicine reports2020
Identification of hub genes and key pathways of dietary advanced glycation end products‑induced non‑alcoholic fatty liver disease by bioinformatics analysis and animal experiments.
Article in Molecular medicine reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.
- Rodent model of metabolic dysfunction-associated fatty liver disease: a systematic review.Journal of gastroenterology and hepatology · 2025Pooled it
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- Mechanistic Insight into Phenolic Compounds in Mitigating Diabetic Complications Induced by Advanced Glycation End Products.Current issues in molecular biology · 2025Review
- Construction and evaluation of a diagnostic model for metabolic dysfunction-associated steatotic liver disease based on advanced glycation end products and their receptors.Frontiers in medicine · 2025Article
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- Inhibition of UHRF1 Improves Motor Function in Mice with Spinal Cord Injury.Cellular and molecular neurobiology · 2024Article
- Associations of dietary advanced glycation end products with liver steatosis via vibration controlled transient elastography in the United States: a nationwide cross-sectional study.European journal of nutrition · 2024Article
- The identification of metabolites from gut microbiota in NAFLD via network pharmacology.Scientific reports · 2023Article
- A novel lnc-LAMC2-1:1 SNP promotes colon adenocarcinoma progression by targeting miR-216a-3p/HMGB3.Heliyon · 2022Article
- Bioinformatics analysis identification ofExperimental and therapeutic medicine · 2022Article
- Update cognition of nonalcoholic fatty liver disease/metabolism-associated fatty liver disease.Chronic diseases and translational medicine · 2022Article
- Identification of Hub Genes Associated With Non-alcoholic Steatohepatitis Using Integrated Bioinformatics Analysis.Frontiers in genetics · 2022Article
- Article
- Identification of a novel circRNA, hsa_circ_0065898, that regulates tumor growth in cervical squamous cell carcinoma.Translational cancer research · 2021Article
- Dysregulated circulating SOCS3 and haptoglobin expression associated with stable coronary artery disease and acute coronary syndrome: An integrated study based on bioinformatics analysis and case-control validation.Anatolian journal of cardiology · 2020Article
- Allopurinol ameliorates liver injury in type 1 diabetic rats through activating Nrf2.International journal of immunopathology and pharmacologyArticle
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Non‑alcoholic fatty liver disease (NAFLD) is a common chronic liver disease. Advanced glycation end products (AGEs) negatively affect the liver and accelerate NAFLD progression; however, the underlying mechanisms remain unclear. The present study aimed to examine the effect and mechanism of dietary AGEs on the mouse liver using bioinformatics and in vivo experimental approaches. Gene expression datasets associated with NAFLD were obtained from the Gene Expression Omnibus and differentially expressed genes (DEGs) were identified using GEO2R. Functional enrichment analyses were performed using the Database for Annotation, Visualization and Integrated Discovery and a protein‑protein interaction network for the DEGs was constructed using the Search Tool for the Retrieval of Interacting Genes database. MCODE, a Cytoscape plugin, was subsequently used to identify the most significant module. The key genes involved were verified in a dietary AGE‑induced non‑alcoholic steatohepatitis (NASH) mouse model using reverse transcription‑quantitative PCR (RT‑qPCR). The 462 DEGs associated with NAFLD in the two datasets, of which 34 overlapping genes were found in two microarray datasets. Functional analysis demonstrated that the 34 DEGs were enriched in the 'PPAR signaling pathway', 'central carbon metabolism in cancer', and 'cell adhesion molecules (CAMs)'. Moreover, four hub genes (cell death‑inducing DFFA‑like effector a, cell death‑inducing DFFA‑like effector c, fatty acid‑binding protein 4 and perilipin 4) were identified from a protein‑protein interaction network and were verified using RT‑qPCR in a mouse model of NASH. The results suggested that AGEs and their receptor axis may be involved in NAFLD onset and/or progression. This integrative analysis identified candidate genes and pathways in NAFLD, as well as DEGs and hub genes related to NAFLD progression in silico and in vivo.
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