Tacrolimus (TAC) has a narrow therapeutic window and patient-specific pharmacokinetic variability. In our study, we analyzed the association between TAC exposure, metabolism, and kidney graft outcomes (function, rejection, and histological lesions). TAC trough (C₀), coefficient of variation (TAC CV), concentration/dose ratio (C/D), and biomarkers related to kidney injury molecule-1 (KIM-1) and neutrophil gelatinase lipocalin (NGAL) were analyzed. We examined 174 patients who were subjected to a triple immunosuppressive regimen and underwent kidney transplantation between 2017 and 2022. Surveillance biopsies were performed at the time of kidney implantation and at three and twelve months after transplantation. We classified patients based on their Tac C/D ratios, classifying them as fast (C/D ratio < 1.05 ng/mL × 1/mg) or slow (C/D ratio ≥ 1.05 ng/mL × 1/mg) metabolizers. TAC exposure/metabolism did not significantly correlate with interstitial fibrosis/tubular atrophy (IF/TA) progression during the first year after kidney transplantation. TAC CV third tertile was associated with a higher chronicity score at one-year biopsy. TAC C/D ratio at three months and Tac C₀ at six months were associated with rejection during the first year after transplantation. A fast TAC metabolism at six months was associated with reduced kidney graft function one year (OR: 2.141, 95% CI: 1.044–4.389, p = 0.038) and two years after transplantation (OR: 4.654, 95% CI: 1.197–18.097, p = 0.026), and TAC CV was associated with reduced eGFR at three years. uNGAL correlated with IF/TA and chronicity scores at three months and negatively correlated with TAC C₀ and C/D at three months and one year. Conclusion: Calculating the C/D ratio at three and six months after transplantation may help to identify patients at risk of suffering acute rejection and deterioration of graft function.

With an increasing number of marginal donors, additional methods for the evaluation of cadaveric kidney quality are required. This study aimed to evaluate pretransplant deceased donor serum (s) and urine (u) biomarkers, including neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1), interleukin-18, and C-X-C motif chemokine 10 (CXCL10) for predicting early and late graft function. In total, 43 deceased kidney donors and 76 corresponding recipients were enrolled. Delayed graft function (DGF) occurred in 27.6% of cases. sIL-18, sKIM-1, uNGAL, and uKIM-1 were predictors of DGF. A model incorporating sIL-18, uKIM-1, and clinical factors was developed to predict DGF (AUROC 0.863). Univariate analysis showed a negative association between uKIM and graft eGFR at 6, 12, 24, and 36 months, but this was not confirmed in the multivariate analysis. In conclusion, we report a superior performance of donor biomarkers for predicting DGF and later graft function over serum creatinine. Higher levels of donor sIL-18 and uKIM in conjunction with expanded-criteria donors and longer cold ischemia times predicted DGF. With no renal tubular damage in zero-time donor biopsies, higher pretransplant urine and serum NGAL levels were associated with better allograft function one year after transplantation, and sNGAL with graft function three years after transplantation.

The objective of the present study was to compare principal cell-specific aquaporin-2 (AQP2) abundances in urinary extracellular vesicles (uEVs) on the first postoperative day in deceased-donor kidney transplant recipients without and with acute kidney injury. We measured uEV markers (CD9 and CD63) and the abundances of proximal tubular sodium-glucose transporter 2, distal tubular sodium/chloride cotransporter, and principal cell-specific aquaporin-2 using Western blotting of urine. uEV-AQP2 levels were normalized to living donor controls. The validation cohort consisted of 82 deceased-donor kidney transplant recipients who had a median age of 50 years (IQR 43 to 57 years). A total of 32% of recipients had acute kidney injury. The median uEV-AQP2 was significantly higher in recipients with acute kidney injury compared to immediate allograft function (2.05; IQR 0.87 to 2.83; vs. 0.81; IQR 0.44 to 1.78; p < 0.01). The Youden index indicated a uEV-AQP2 threshold of 2.00. Stratifying uEV-AQP2 into quartiles showed that recipients with higher uEV-AQP2 levels had higher rates of acute kidney injury (Cochran–Armitage, p = 0.001). The discovery cohort showed elevated CD9, CD63, and uEV-AQP2 levels in urine from recipients with acute kidney injury compared to immediate allograft function. We were able to quantify the damage of principal cells after kidney transplant to predict acute kidney injury using uEV-AQP2.