Key result
Four metabolism-related genes (AMDHD1, FMO1, LPL, and P4HA1) were identified as diagnostic biomarkers for nonalcoholic fatty liver disease, demonstrating good diagnostic accuracy with AUC values > 0.8.
Observational (n=101)
Effect estimate: AUC > 0.8
Bioinformatics analysis identified AMDHD1, FMO1, LPL, and P4HA1 as potential metabolism-related biomarkers for diagnosing and treating NAFLD.
Requires prospective validation before NAFLD diagnostic use; leaves open clinical utility of these gene biomarkers.
Background: Nonalcoholic fatty liver disease (NAFLD) is a metabolic syndrome of the liver. Metabolism-related genes significantly influence the onset and progression of the disease. Hence, it is necessary to screen metabolism-related biomarkers for diagnosing and treating patients with NAFLD. Methods: First, the transcriptomic data of patients with NAFLD were screened to identify differentially expressed genes (DEGs). Next, Venn Diagram was used to identify metabolism-related DEGs (MR-DEGs). Further, a protein-protein interaction network was developed to show the interaction between MR-DEGs. Subsequently, the “Least absolute shrinkage and selection operator regression” and “Random Forest” algorithms were used to screen metabolism-related genes in patients with NAFLD. Next, immune cell infiltration and gene set enrichment analyses were performed on these metabolism-related genes. Finally, metabolism-related gene expression was determined at the transcription level. Results: First, 129 DEGs related to NAFLD development were identified among patients with nonalcoholic steatohepatitis (NASH) and healthy control. Next, 18 MR-DEGs were identified using the Venn diagram. Subsequently, four genes, including AMDHD1, FMO1, LPL, and P4HA1,were identified using machine learning. Moreover, a regulatory network consisting of four genes, 25 miRNAs, and 41 transcription factors was constructed. Finally, a significant increase in FMO1 and LPLexpression levels and a decrease in AMDHD1 and P4HA1 expression levels were observed in patients in the NASH group compared to the healthy control group. Conclusion: Metabolism-related genes associated with NAFLD, such as AMDHD1, FMO1, LPL, and P4HA1, were identified which provide insights into diagnosing and treating patients with NAFLD.
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Jiang et al. (2023) conducted an observational in Nonalcoholic fatty liver disease (NAFLD) (n=101). Metabolism-related genes (AMDHD1, FMO1, LPL, P4HA1) vs. Healthy controls was evaluated on Diagnostic accuracy of metabolism-related biomarkers (AUC > 0.8). Four metabolism-related genes (AMDHD1, FMO1, LPL, and P4HA1) were identified as diagnostic biomarkers for nonalcoholic fatty liver disease, demonstrating good diagnostic accuracy with AUC values > 0.8.
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