Computational Prediction of Biomarkers, Pathways, and New Target Drugs in the Pathogenesis of Immune-Based Diseases Regarding Kidney Transplantation Rejection

Computational Prediction of Biomarkers, Pathways, and New Target Drugs in the Pathogenesis of Immune-Based Diseases Regarding Kidney Transplantation Rejection

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Introduction

The intensity and prevalence of rejection in kidney transplant (KT) recipients are influenced by a variety of factors that influence the size and character of immune responses. Understanding how genetic and molecular variables influence immune cell effector activities and donor-specific antibodies (DSA) can assist clinicians better stratify patients based on their immunological risk and make proper judgments to avoid adverse outcomes. High-throughput technologies such as next-generation sequencing (NGS) and microarrays have been developed in the recent two decades. Parallel to this, international public data repositories have been built, such as the National Center for Biotechnology Information’s (NCBI) GEO (Gene Expression Omnibus) database and the Institute European Bioinformatics’ (EBI) Array Express database, to store and share data.

The histological characteristics of biopsy samples are used to diagnose graft rejection in kidney transplantation (KT) patients. The expansion of omics sciences and bioinformatics approaches has aided in the discovery and prediction of biomarkers, pathways, and new target medications, allowing for more precise and minimally intrusive diagnosis. The goal was to find differentially expressed genes (DEGs) in patients with and without antibody-mediated rejection (AMR), as well as to identify essential cells involved in AMR, new target drugs, and protein-protein interactions (PPI), as well as to understand their functional and biological analysis.

Materials and Methods

Four GEO databases of kidney biopsies of kidney transplantation with/without AMR were analyzed. The infiltrating leukocyte populations in the graft, new target drugs, protein-protein interactions (PPI), functional and biological analysis were studied by different bioinformatics tools.

Results

Our results show DEGs and the infiltrating leukocyte populations in the graft. There is an increase in the expression of genes related to different stages of the activation of the immune system, antigenic presentation such as antibody-mediated cytotoxicity, or leukocyte migration during AMR. The importance of the IRF/STAT1 pathways of response to IFN in controlling the expression of genes related to humoral rejection.

The genes of this biological pathway were postulated as potential therapeutic targets and biomarkers of AMR. These biological processes correlated showed the infiltration of NK cells and monocytes towards the allograft. Besides the increase in dendritic cell maturation, it plays a central role in mediating the damage suffered by the graft during AMR. Computational approaches to the search for new therapeutic uses of approved target drugs also showed that imatinib might theoretically be helpful in KT for the prevention and/or treatment of AMR.

Conclusion

Our results suggest the importance of the IRF/STAT1 pathways in humoral kidney rejection. NK cells and monocytes in graft damage have an essential role during rejection, and imatinib improves KT outcomes.

Our results will have to be validated for the potential use of overexpressed genes as rejection biomarkers that can be used as diagnostic and prognostic markers and as therapeutic targets to avoid graft rejection in patients.

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