ArticleFrontiers in cell and developmental biology2026
Significance of fatty acid metabolism regulators in the diagnosis and subtype classification in non-alcoholic fatty liver disease.
Article in Frontiers in cell and developmental biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Introduction: Non - alcoholic fatty liver disease (NAFLD) is currently the most common steatosis of the liver among Chinese. Nevertheless, a large proportion of individuals go undiagnosed and receive no treatment because of the absence of dependable and efficient diagnostic methods. Given the vital part that fatty acid metabolism (FAM) dysregulation plays in the development of NAFLD, this research aimed to assess the possible worth of FAM regulators as diagnostic biomarkers for NAFLD. Methods: GSE89632 (24 normal liver tissue samples and 39 NAFLD liver tissue samples) was utilized as the training cohort. FAM regulators were extracted from the Molecular Signatures Database. The four most crucial FAM regulators, demonstrating the highest significance (FABP4, CPOX, TLR2, and OXT), as identified by the RF model, were used to develop the diagnostic nomogram. To validate the nomogram, analyses of the calibration curve, decision curve (DCA), and clinical impact curve were carried out. FAM subtypes were categorized according to crucial FAM regulators, and genes with differential expression (DEGs) associated with FAM were pinpointed between the subtypes. Further division of gene subtypes was based on FAM-related DEGs. Results: Results: The RF model achieved a higher area under the curve (AUC) than the SVM model in diagnostic ROC analysis. FAM subtype B exhibited higher macrophage infiltration, and gene subtype B consistently exhibited higher infiltration levels of immune cells. FAM scores were also remarkably elevated in FAM subtype B and gene subtype B compared with corresponding FAM subtype A and gene subtype A. Discussion: The aforementioned genes were then validated by external datasets (GSE48452, GSE66676, and GSE135251). Finally, the expression of key genes was verified in the HepG2 cells and mice. In summary, these findings support the feasibility of using FAM regulators to predict NAFLD occurrence.
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