GBP2 promotes M1 macrophage polarization by activating the notch1 signaling pathway in diabetic nephropathy

Abstract

BackgroundDiabetic nephropathy (DN) is one of the most common diabetic complications, which has become the primary cause of end-stage renal disease (ESRD) globally. Macrophage infiltration has been proven vital in the occurrence and development of DN. This study was designed to investigate the hub genes involved in macrophage-mediated inflammation of DN via bioinformatics analysis and experimental validation.MethodsGene microarray datasets were obtained from the Gene Expression Omnibus (GEO) public website. Integrating the CIBERSORT, weighted gene co-expression network analysis (WGCNA) and DEGs, we screened macrophage M1-associated key genes with the highest intramodular connectivity. Subsequently, the Least Absolute Shrinkage and Selection Operator (LASSO) regression was utilized to further mine hub genes. GSE104954 acted as an external validation to predict the expression levels and diagnostic performance of these hub genes. The Nephroseq online platform was employed to evaluate the clinical implications of these hub genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed to elucidate the dominant biological functions and signal pathways. Finally, we conducted experiments to verify the role of GBP2 in M1 macrophage-mediated inflammatory response and the underlying mechanism of this role.ResultsSixteen DEGs with the highest connectivity in M1 macrophages-associated module (paleturquoise module) were determined. Subsequently, we identified four hub genes through LASSO regression analysis, including CASP1, MS4A4A, CD53, and GBP2. Consistent with the training set, expression levels of these four hub genes manifested memorably elevated and the ROC curves indicated a good diagnostic accuracy with an area under the curve of greater than 0.8. Clinically, enhanced expression of these four hub genes predicted worse outcomes of DN patients. Given the known correlation between the first three hub genes and macrophage-mediated inflammation, experiments were performed to demonstrate the effect of GBP2, which proved that GBP2 contributed to M1 polarization of macrophages by activating the notch1 signaling pathway.ConclusionOur findings detected four hub genes, namely CASP1, MS4A4A, CD53, and GBP2, may involve in the progression of DN via pro-inflammatory M1 macrophage phenotype. GBP2 could be a promising prognostic biomarker and intervention target for DN by regulating M1 polarization.

Epigenetic programming of host lipid metabolism associates with resistance to TST/IGRA conversion after exposure toMycobacterium tuberculosis

“…Cholesterol represents an important fatty acid for Mtb as it is a preferred carbon source (32, 34) and contributes to macrophage responses to Mtb including membrane lipid rafts permissive to Mtb uptake (36), modulation of cellular function, and development of foamy macrophages (32, 33, 37, 38). Hippo signaling is involved in pleiotropic activities related to cell proliferation, differentiation, and survival (25) including in macrophages (39). Among these functions, Hippo signaling regulates cholesterol levels through sterol regulatory element-binding proteins (SREBPs) (25).…”

Exploration of potential biomarkers and therapeutic targets for trauma-related acute kidney injury

“…A recent study found that increased expression of MS4A4A indicated poor prognosis in patients with diabetic nephropathy. 48 The mechanism may involve the participation of the pro-inflammatory M1 macrophage phenotype in the progression of diabetic neuropathy. However, it remains uncertain whether this mechanism has a similar effect in AKI, as current studies do not provide conclusive evidence.…”

Application of Proteomics and Machine Learning Methods to Study the Pathogenesis of Diabetic Nephropathy and Screen Urinary Biomarkers

“…In fact, these terms or pathways have also been reported in previous DN-related reviews 9,34,55 or studies of high-throughput methods. 34,56 Next, two machine learning methods were employed to screen potential diagnostic biomarkers of DN in clusters 3, 4, and 6, and five overlapping biomarker proteins (KLK1, CSPG4, PLAU, SERPINA3, and ALB) were identified as key diagnostic biomarkers of DN. The expression of four proteins (KLK1, CSPG4, SERPINA3, and ALB) was verified by ELISA assays, and the results of three proteins were in general agreement with the proteomic results, i.e., KLK1, CSPG4S, and SERPINA3.…”