Abstract
BackgroundMetabolic dysfunction-associated steatotic liver disease (MASLD) is an independent risk factor for type 2 diabetes mellitus (T2DM), and its early identification and intervention offer opportunities for reversing diabetes mellitus.MethodsIn this study, we identified biomarkers for the MASLD dataset (GSE33814, GSE48452) and the T2DM dataset (GSE76895 and GSE89120) by bioinformatics analysis. Next, we constructed weighted gene co-expression network (WGCNA) for disease module analysis to screen out shared genes strongly associated with diseases. We also analyzed the enriched pathways of shared genes using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Next, hub gene validation was performed using the least absolute shrinkage and selection operator (LASSO) and receiver operating characteristic (ROC) curves. Finally, we used RT-qPCR, immunofluorescence, Western blotting and Elisa to validate hub gene expression in MASLD and T2DM mouse models.ResultsThis analysis identified 20 genes shared by MASLD and T2DM that were enriched in the bile secretion, phototransduction, cancer, carbohydrate digestion and absorption, cholesterol/glycerol metabolism, and retinol metabolism. The LASSO algorithm and ROC curve identified Retinol Dehydrogenase 10 (RDH10) as the best diagnostic gene for MASLD and T2DM. Immunofluorescence and Western blot showed that RDH10 expression was reduced in the liver and pancreatic islets of MASLD and T2DM model mice. Similarly, serum levels of RDH10 were significantly lower in MASLD and T2DM model mice and humans than in controls.ConclusionOur study suggests that RDH10 is a common diagnostic marker for MASLD and T2DM and provides new research directions for the prevention and treatment of MASLD and T2DM.
Published Version
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