Identification of glycosyltransferase genes for diagnosis of T-cell mediated rejection and prediction of graft loss in kidney transplantation

Abstract

Background

Glycosylation is a complex and fundamental metabolic biosynthetic process orchestrated by multiple glycosyltransferases (GT) and glycosidases enzymes. Functions of GT have been extensively examined in multiple human diseases. Our study investigated the potential role of GT genes in T-cell mediated rejection (TCMR) and possible prediction of graft loss of kidney transplantation.

Methods

We downloaded the microarray datasets and GT genes from the GEO and the HUGO Gene Nomenclature Committee (HGNC) databases, respectively. Differentially expressed GT genes (DE-GTGs) were obtained by differential expression and Venn analysis. A TCMR diagnostic model was developed based on the hub DE-GTGs using LASSO regression and XGboost machine learning algorithms. In addition, a predictive model for graft survival was constructed by univariate Cox and LASSO Cox regression analysis.

Results

We have obtained 15 DE-GTGs. Both GO and KEGG analyses showed that the DE-GTGs were mainly involved in the glycoprotein biosynthetic process. The TCMR diagnostic model exhibited high diagnostic potential with generally highly correlated accuracies [aera under the curve (AUC) of 0.83]. The immune characteristics analysis revealed that higher levels of immune cell infiltration and immune responses were observed in the high-risk group than in the low-risk group. In particular, the Kaplan-Meier survival analysis revealed that renal grafts in the high-risk group have poor prognostic outcomes than the low-risk group. The predictive AUC values of 1-, 2- and 3-year graft survival were 0.76, 0.81, and 0.70, respectively.

Conclusion

Our results indicated that GT genes could be used for diagnosis of TCMR and prediction of graft loss in kidney transplantation. These results provide new perspectives and tools for diagnosing, treating and predicting kidney transplant-related diseases.