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During ischemia and reperfusion injury (IRI), mitochondria may release mitochondrial DNA (mtDNA). mtDNA can serve as a propagator of further injury but in specific settings has anti-inflammatory capacities as well. Therefore, the aim of this study was to study the perioperative dynamics of plasma mtDNA during living donor kidney transplantation (LDKT) and its potential as a marker of graft outcome. Fifty-six donor-recipient couples from the Volatile Anesthetic Protection of Renal Transplants-1 (VAPOR-1) trial were included. Systemic venous, systemic arterial, and renal venous samples were taken at multiple timepoints during and after LDKT. Levels of mtDNA genes changed over time and between vascular compartments. Several donor, recipient, and transplantation-related variables significantly explained the course of mtDNA genes over time. mtDNA genes predicted 1-month and 24-month estimated glomerular filtration rate (eGFR) and acute rejection episodes in the two-year follow-up period. To conclude, mtDNA is released in plasma during the process of LDKT, either from the kidney or from the whole body in response to transplantation. While circulating mtDNA levels positively and negatively predict post-transplantation outcomes, the exact mechanisms and difference between mtDNA genes are not yet understood and need further exploration.

Early non-invasive detection and prediction of graft function after kidney transplantation is essential since interventions might prevent further deterioration. The aim of this study was to analyze the dynamics and predictive value of four urinary biomarkers: kidney injury molecule-1 (KIM-1), heart-type fatty acid binding protein (H-FABP), N-acetyl-β-D-glucosaminidase (NAG), and neutrophil gelatinase-associated lipocalin (NGAL) in a living donor kidney transplantation (LDKT) cohort. Biomarkers were measured up to 9 days after the transplantation of 57 recipients participating in the VAPOR-1 trial. Dynamics of KIM-1, NAG, NGAL, and H-FABP significantly changed over the course of 9 days after transplantation. KIM-1 at day 1 and NAG at day 2 after transplantation were significant predictors for the estimated glomerular filtration rate (eGFR) at various timepoints after transplantation with a positive estimate ( p < 0.05), whereas NGAL and NAG at day 1 after transplantation were negative significant predictors ( p < 0.05). Multivariable analysis models for eGFR outcome improved after the addition of these biomarker levels. Several donor, recipient and transplantation factors significantly affected the baseline of urinary biomarkers. In conclusion, urinary biomarkers are of added value for the prediction of graft outcome, but influencing factors such as the timing of measurement and transplantation factors need to be considered.

Background and Objective: Historically, dosing of tacrolimus is guided by therapeutic drug monitoring (TDM) of the whole blood concentration, which is strongly influenced by haematocrit. The therapeutic and adverse effects are however expected to be driven by the unbound exposure, which could be better represented by measuring plasma concentrations. Objective: We aimed to establish plasma concentration ranges reflecting whole blood concentrations within currently used target ranges. Methods: Plasma and whole blood tacrolimus concentrations were determined in samples of transplant recipients included in the TransplantLines Biobank and Cohort Study. Targeted whole blood trough concentrations are 4–6 ng/mL and 7–10 ng/mL for kidney and lung transplant recipients, respectively. A population pharmacokinetic model was developed using non-linear mixed-effects modelling. Simulations were performed to infer plasma concentration ranges corresponding to whole blood target ranges. Results: Plasma (n = 1973) and whole blood (n = 1961) tacrolimus concentrations were determined in 1060 transplant recipients. A one-compartment model with fixed first-order absorption and estimated first-order elimination characterised observed plasma concentrations. Plasma was linked to whole blood using a saturable binding equation (maximum binding 35.7 ng/mL, 95% confidence interval (CI) 31.0–40.4 ng/mL; dissociation constant 0.24 ng/mL, 95% CI 0.19–0.29 ng/mL). Model simulations indicate that patients within the whole blood target range are expected to have plasma concentrations (95% prediction interval) of 0.06–0.26 ng/mL and 0.10–0.93 ng/mL for kidney and lung transplant recipients, respectively. Conclusion: Whole blood tacrolimus target ranges, currently used to guide TDM, were translated to plasma concentration ranges of 0.06–0.26 ng/mL and 0.10–0.93 ng/mL for kidney and lung transplant recipients, respectively. [ABSTRACT FROM AUTHOR]