Torque teno virus viremia and QuantiFERON®-CMV assay in prediction of cytomegalovirus reactivation in R+ kidney transplant recipients.

Introduction: Cytomegalovirus (CMV) is the most frequent infectious complication following solid organ transplantation. Torque teno viruses (TTV) viremia has been proposed as a biomarker of functional immunity in the management of kidney transplant recipients (KTR). The QuantiFERON®-CMV (QF-CMV) is a commercially available assay that allows the assessment of CD8+ T-cell responses in routine diagnostic laboratories. Methods: In a prospective national multicenter cohort of 64 CMV-seropositive (R+) KTR, we analyzed the value of TTV load and the two markers of the QF-CMV assay [QF-Ag (CMV-specific T-cell responses) and QF-Mg (overall T-cell responses)], alone and in combination, in prediction of CMV reactivation (≥3 log10 IU/ ml) in the first post-transplant year. We compared previously published cut-offs and specific cut-offs optimized from ROC curves for our population. Results: Using the conventional cut-off (3.45 log10 copies/ml), TTV load at D0 [inclusion visit on the day of transplantation before induction (D0)], or at M1 (1-month post-transplant visit) perform better in predicting CMV viremia control than CMV reactivation. Survival analyses suggest a better performance of our optimized TTV cut-offs (3.78 log10 copies/ml at D0 and 4.23 log10 copies/ml at M1) for risk stratification of CMV reactivation in our R+ KTR cohort. The QF-CMV (QF-Ag = 0.2 IU/ml, and QF-Mg = 0.5 IU/ml) also appears to better predict CMV viremia control than CMV reactivation. Moreover, survival analyses suggest that the QF-Mg would perform better than the QF-Ag in stratifying the risk of CMV reactivation. The use of our optimized QF-Mg cut-off (1.27 IU/ml) at M1 further improved risk stratification of CMV reactivation. Using conventional cut-offs, the combination of TTV load and QF-Ag or TTV load and QF-Mg did not improve prediction of CMV viremia control compared to separate analysis of each marker but resulted in an increase of positive predictive values. The use of our cut-offs slightly improved risk prediction of CMV reactivation. Conclusion: The combination of TTV load and QF-Ag or TTV load and QF-Mg could be useful in stratifying the risk of CMV reactivation in R+ KTR during the first post-transplant year and thereby have an impact on the duration of prophylaxis in these patients. Clinical trial registration: ClinicalTrials.gov registry, identifier NCT02064699.

A Lack of Significant Effect of POR*28 Allelic Variant on Tacrolimus Exposure in Kidney Transplant Recipients.

BACKGROUND: POR*28 is a recently newly described allelic variant of the cytochrome P450 oxidoreductase (POR), which might be associated with an increased metabolic activity of P450 cytochromes (CYP) 3A5 and 3A4. Consequently, carriers of at least 1 allele of this polymorphism could require increased calcineurin inhibitors doses to reach the target residual concentrations (C0). The objective of this study was to test whether the allelic variant of POR, which is associated with an increased metabolic activity of CYP3A, impacts tacrolimus (Tac) pharmacokinetics. METHODS: We tested this hypothesis in a population of 229 kidney transplant recipients (KTR) from a large, multicenter, prospective and randomized study. We have analyzed the association between POR*28 genotype and the proportion of individuals reaching the target Tac residual concentration (Tac C0) 10 days after transplantation. We have also measured the association between POR*28 and the Tac C0, and adjusted Tac C0 (Tac C0/Tac dose) over time using generalized mixed linear models. RESULTS: Ten days after transplantation, there was no difference of frequencies of KTR within the target range of Tac C0 (C0 10-15 ng/mL) according to the POR*28 genotype (P = 0.8). The mean Tac C0 at day 10 in the POR*1/*1 group was 15.3 ± 9.7 ng/mL compared with 15.7 ± 7.8 ng/mL in the POR*1/*28 group and 14.2 ± 6.8 ng/mL, in the POR*28/*28 group, P = 0.8. The adjusted Tac C0 was not associated with POR*28 genotype over time (random effects model, P = 0.9). When restricted to KTR expressing CYP3A5, POR*28 genotype did not impact the proportion of individuals within the Tac C0 target range neither the adjusted Tac C0 (random effects model, P = 0.1). CONCLUSIONS: POR*28 does not significantly influence Tac pharmacokinetic parameters in a large cohort of KTR. This study does not confirm recent findings indicating that POR*28 carriers require more Tac to reach target C0.

Assessment of body protein: energy status in chronic kidney disease.

The prevalence of protein-energy malnutrition progressively increases during the evolution of chronic kidney disease (CKD). As a consequence, it has been reported that 40% of patients present with symptoms of undernutrition at the entrance to chronic dialysis treatment. In patients established on maintenance hemodialysis, the prevalence of malnutrition varies from 20% to 60% according to which indicators of nutritional status are used. Protein-energy malnutrition is associated with an increase in overall and cardiovascular death risks both in CKD patients not yet on dialysis and in dialysis patients. Given the impact of protein-energy wasting on the outcome of CKD patients, screening malnutrition and monitoring protein-energy status appear of primary importance. Therefore, scientific and professional societies or foundations have developed guidelines for the assessment of nutritional status as well as for the treatment of malnourished CKD patients. Recently, an expert panel recommended the term protein-energy wasting for loss of body protein mass and fuel reserves. According to these recommendations, protein-energy wasting should be diagnosed if 3 characteristics are present (low serum levels of albumin, transthyretin, or cholesterol), reduced body mass (low or reduced body mass or fat mass or weight loss with reduced intake of protein and energy), and reduced muscle mass (muscle wasting or sarcopenia, reduced mid-arm-muscle circumference). The present article addresses the methods for assessing protein-energy status, their specificities regarding the CKD staging, and the criteria for choosing among these methods when managing the follow-up evaluation of CKD patients. The practical implications of nutritional parameters for the management of CKD patients are illustrated by a case presentation.