Proteomics for Biomarker Discovery for Diagnosis and Prognosis of Kidney Transplantation Rejection

Proteomes. 2022 Jul 2;10(3):24. doi: 10.3390/proteomes10030024.

Abstract

Renal transplantation is currently the treatment of choice for end-stage kidney disease, enabling a quality of life superior to dialysis. Despite this, all transplanted patients are at risk of allograft rejection processes. The gold-standard diagnosis of graft rejection, based on histological analysis of kidney biopsy, is prone to sampling errors and carries high costs and risks associated with such invasive procedures. Furthermore, the routine clinical monitoring, based on urine volume, proteinuria, and serum creatinine, usually only detects alterations after graft histologic damage and does not differentiate between the diverse etiologies. Therefore, there is an urgent need for new biomarkers enabling to predict, with high sensitivity and specificity, the rejection processes and the underlying mechanisms obtained from minimally invasive procedures to be implemented in routine clinical surveillance. These new biomarkers should also detect the rejection processes as early as possible, ideally before the 78 clinical outputs, while enabling balanced immunotherapy in order to minimize rejections and reducing the high toxicities associated with these drugs. Proteomics of biofluids, collected through non-invasive or minimally invasive analysis, e.g., blood or urine, present inherent characteristics that may provide biomarker candidates. The current manuscript reviews biofluids proteomics toward biomarkers discovery that specifically identify subclinical, acute, and chronic immune rejection processes while allowing for the discrimination between cell-mediated or antibody-mediated processes. In time, these biomarkers will lead to patient risk stratification, monitoring, and personalized and more efficient immunotherapies toward higher graft survival and patient quality of life.

Keywords: biofluids; biomarker; exosomes; kidney allograft; proteomics; rejection.

Publication types

  • Review

Grants and funding

This research was funded by project grant DSAIPA/DS/0117/2020 supported by Fundação para a Ciência e a Tecnologia, Portugal, and by the project grant NeproMD/ISEL/2020 financed by Instituto Politécnico de Lisboa. The present work was conducted in the Engineering & Health Laboratory, that resulted from a collaboration protocol established between Universidade Católica Portuguesa and Instituto Politécnico de Lisboa.