P0653THE USE OF URINARY EPIDERMAL GROWTH FACTOR FOR EVALUATION OF KIDNEY GRAFT FUNCTION

Abstract

Abstract Background and Aims Follow-up after kidney transplantation requires repeated, reliable glomerular filtration rate (GFR) measurements. Measured GFR (mGFR), using urinary or plasma clearance of an exogenous filtration marker such as iohexol, provides precise measurements but are expensive and time consuming. Instead, estimated GFR (eGFR) based on serum creatinine is most commonly used in clinical practice. Epidermal growth factor is produced in the kidney and promotes tubular cell regeneration and recovery of kidney function after injury. Low levels of urinary epidermal growth factor (uEGF) are linked to progression of chronic kidney disease and increased risk of kidney graft failure. The aim of this study was to investigate uEGF as an additional marker to evaluate graft function in kidney transplant recipients (KTRs). Method Participants in the Omega-3 fatty acids in Renal Transplantation (ORENTRA) trial were examined with mGFR by iohexol clearance at 1 year after kidney transplantation. The concentration of iohexol in serum was measured 3 and 4 hours after iv injection. On the same day, fasting blood and urine samples were obtained in the morning. Serum creatinine was measured and eGFR calculated with the MDRD formula. uEGF and a pre-specified selection of inflammation and fibrosis markers were measured with multiplex immunoassay technique and normalized with urinary creatinine. Principal component analysis (PCA) was used to explore clustering of markers. Correlations were calculated with Pearson’s correlation coefficient R. Results Fifty-nine participants had complete measurements of mGFR (57.2 ± 15.2 mL/min/1.73m2), eGFR (68.6 ± 23.0 mL/min/1.73m2) and uEGF. The correlation between mGFR and eGFR was strong (R=0.783, P<0.001). Measurements of uEGF had a coefficient of variation below 10% for all participants, with a mean value of 22.0 ± 12.1 μg/g creatinine. There was a significant correlation between mGFR and uEGF (R=0.678, P<0.001). The component score of uEGF and eGFR calculated with PCA (74% of variance) had the strongest correlation with mGFR (R=0.845, P<0.001). Conclusion Combining uEGF with eGFR into one component score by PCA gives a greater correlation with mGFR compared to eGFR alone in this cohort of KTRs. These findings need to be validated in other patient populations.