ArticleFrontiers in genetics2024
Identification of novel targets associated with cholesterol metabolism in nonalcoholic fatty liver disease: a comprehensive study using Mendelian randomization combined with transcriptome analysis.
Article in Frontiers in genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.
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Who cites it
7 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Biomarker discovery in NAFLD: insights from metabolomics and vote counting meta-analysis.Metabolomics : Official journal of the Metabolomic Society · 2025Pooled it
- Druggable genome-wide Mendelian randomization identifies therapeutic targets for metabolic dysfunction-associated steatotic liver disease.Lipids in health and disease · 2025Pooled it
- Exercise-associated epigenetic remodeling and TCR repertoire dynamics in Lynch syndrome carriers.iScience · 2026Article
- Prolonged high-dose prenatal caffeine exposure induces organ-specific developmental toxicity: renal p53 downregulation and hepatic caspase-3 upregulation in neonatal mice, supported with in silico studies.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Article
- Research Trends and Hotspots in Mendelian Randomization Studies of Liver Diseases: A Bibliometric and Visualization Analysis.Hepatic medicine : evidence and research · 2026Review
- Crosstalk Between Metabolic Biomarkers and Pulse Wave Analysis in Hypertensive Patients.Biomedicines · 2025Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: There is limited research on cholesterol metabolism-related genes (CM-RGs) in non-alcoholic fatty liver disease (NAFLD), despite hypercholesterolemia being a recognized risk factor. The role of CM-RGs in NAFLD remains unclear. Methods: The differentially expressed genes (DEGs) between NAFLD and control were acquired by differential expression analysis. The differentially expressed genes associated with cholesterol metabolism (DE-CM-RGs) were identified and functional enrichment analyses were performed. Protein-protein interaction network analysis and a two-sample Mendelian randomization study were utilized for identifying hub genes. Nomogram model, competing endogenous RNA and messenger RNA-drug networks were established. In addition, immunoinfiltration analysis was performed. Results: We identified four hub genes (MVK, HMGCS1, TM7SF2, and FDPS) linked to NAFLD risk. MVK and TM7SF2 were protective factors, HMGCS1 and FDPS were risk factors for NAFLD. The area under the curve values of nomograms in GSE135251 and GSE126848 were 0.79 and 0.848, respectively. The gene set enrichment analysis indicated that hub genes participated in calcium signaling pathways and biosynthesis of unsaturated fatty acids. NAFLD patients showed increased CD56 Conclusion: Our study has linked cholesterol metabolism genes (MVK, HMGCS1, TM7SF2, and FDPS) to NAFLD, providing a promising diagnostic framework, identifying treatment targets, and offering novel perspectives into its mechanisms.
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