Optimization of a breath analysis methodology to potentially diagnose transplanted kidney rejection

Abstract

Chronic kidney disease may result in end stage renal disorder and increased mortality rate. Up to date, kidney transplantation represents the only definitive treatment to restore normal life expectancy. Nevertheless, there is a high risk of organ rejection in the short-medium term after surgery. This paper proposes a new ReCIVA®-GC-MS technology to potentially predict the rejection of the transplanted kidney during the first year after surgery by analyzing human breath. Twenty VOCs, recognized by literature as targets or as representative of the major classes of molecules essential to the identification of chronic kidney disease affected patients and/or healthy subjects, were selected and employed for this methodology optimization. The breath profile of healthy subjects was considered as target in case of restored kidney function after transplantation. Calibration curves, linearity concentration range, limit of detection and quantification of selected molecules were estimated as well as the intra-day and inter-day reproducibility of the method. To test the applicability of the GC-MS developed methodology, the breath of healthy subjects and chronic kidney disease affected patients was ReCIVA® sampled, and then analyzed. Sixty-seven molecules were identified, and between these, thirteen of twenty selected compounds were quantified, confirming the robustness of the optimized protocol.