A Method to Exchange Recombinant Differentially Phosphorylated Rhodamine-Labeled Cardiac RLC into Permeabilized Cardiac Trabeculae

Cyclosporine, everolimus, and tacrolimus are the cornerstone of immunosuppressive therapy in renal transplantation. These drugs are characterized by narrow therapeutic windows, highly variable pharmacokinetics (PK), and metabolism by CYP3A enzymes. Recently, the decreased activity allele, CYP3A4*22, was described as a potential predictive marker for CYP3A4 activity. This study investigated the effect of CYP3A4*22, CYP3A5*3, and CYP3A combined genotypes on cyclosporine, everolimus, and tacrolimus PK in renal transplant patients. CYP3A4*22 carriers showed a significant lower clearance for cyclosporine (−15%), and a trend was observed for everolimus (−7%) and tacrolimus (−16%). Patients carrying at least one CYP3A5*1 allele had 1.5-fold higher tacrolimus clearance compared with noncarriers; however, CYP3A5*3 appeared to be nonpredictive for everolimus and cyclosporine. CYP3A combined genotype did not significantly improve prediction of clearance compared with CYP3A5*3 or CYP3A4*22 alone. These data suggest that dose individualization of cyclosporine, everolimus, or tacrolimus therapy based on CYP3A4*22 is not indicated

A population pharmacokinetic model to predict the individual starting dose of tacrolimus in adult renal transplant recipients

Aims: The aims of this study were to describe the pharmacokinetics of tacrolimus immediately after kidney transplantation, and to develop a clinical tool for selecting the best starting dose for each patient. Methods: Data on tacrolimus exposure were collected for the first 3 months following renal transplantation. A population pharmacokinetic analysis was conducted using nonlinear mixed-effects modelling. Demographic, clinical and genetic parameters were evaluated as covariates. Results: A total of 4527 tacrolimus blood samples collected from 337 kidney transplant recipients were available. Data were best described using a two-compartment model. The mean absorption rate was 3.6 h-1 , clearance was 23.0 l h-1 (39% interindividual variability, IIV), central volume of distribution was 692 l (49% IIV) and the peripheral volume of distribution 5340 l (53% IIV). Interoccasion variability was added to clearance (14%). Higher body surface area (BSA), lower serum creatinine, younger age, higher albumin and lower haematocrit levels were identified as covariates enhancing tacrolimus clearance. Cytochrome P450 (CYP) 3A5 expressers had a significantly higher tacrolimus clearance (160%), whereas CYP3A4*22 carriers had a significantly lower clearance (80%). From these significant covariates, age, BSA, CYP3A4 and CYP3A5 genotype were incorporated in a second model to individualize the tacrolimus starting dose: [Formula: see text] Both models were successfully internally and externally validated. A clinical trial was simulated to demonstrate the added value of the starting dose model. Conclusions: For a good prediction of tacrolimus pharmacokinetics, age, BSA, CYP3A4 and CYP3A5 genotype are important covariates. These covariates explained 30% of the variability in CL/F. The model proved effective in calculating the optimal tacrolimus dose based on these parameters and can be used to individualize the tacrolimus dose in the early period after transplantation

Salt, but not protein intake, is associated with accelerated disease progression in autosomal dominant polycystic kidney disease

In autosomal dominant polycystic kidney disease (ADPKD), there are only scarce data on the effect of salt and protein intake on disease progression. Here we studied association of these dietary factors with the rate of disease progression in ADPKD, and what the mediating factors are by analyzing an observational cohort of 589 patients with ADPKD. Salt and protein intake were estimated from 24-hour urine samples and the plasma copeptin concentration measured as a surrogate for vasopressin. The association of dietary intake with annual change in the estimated glomerular filtration rate (eGFR) and height adjusted total kidney volume (htTKV) growth was analyzed with mixed models. In case of significant associations, mediation analyses were performed to elucidate potential mechanisms. These patients (59% female) had a mean baseline age of 47, eGFR 64 mL/min/1.73m2 and the median htTKV was 880 mL. The mean estimated salt intake was 9.1 g/day and protein intake 84 g/day. During a median follow-up of 4.0 years, eGFR was assessed a median of six times and 24-hour urine was collected a median of five times. Salt intake was significantly associated with annual change in eGFR of -0.11 (95% confidence interval (0.20 - - 0.02) mL/min/1.73m2 per gram of salt, whereas protein intake was not (-0.00001 (-0.01 - 0.01) mL/min/1.73m2 per gram of protein. The effect of salt intake on eGFR slope was significantly mediated by plasma copeptin (crude analysis: 77% mediation, and, adjusted analysis: 45% mediation), but not by systolic blood pressure. Thus, higher salt, but not higher protein intake may be detrimental in ADPKD. The substantial mediation by plasma copeptin suggests that this effect is primarily a consequence of a salt-induced rise in vasopressin

AUC-guided dosing of tacrolimus prevents progressive systemic overexposure in renal transplant recipients

AUC-guided dosing of tacrolimus prevents progressive systemic overexposure in renal transplant recipients.BackgroundTacrolimus has a narrow therapeutic window, and bioavailability is known to vary considerably between renal transplant recipients. Most centers still rely on measurement of trough levels, but there are conflicting reports on the correlation between tacrolimus trough levels and systemic exposure, as measured by the area-under-the-concentration-over-time curve (AUC(0-12h)).MethodsWe developed and validated a two-compartmental population-based pharmacokinetic model with Bayesian estimation of tacrolimus systemic exposure. Subsequently, we used this model to apply prospectively AUC-guided dosing of tacrolimus in 15 consecutive renal transplant recipients. The main objective was to study intrapatient variability in the course of time.ResultsBayesian forecasting with a two-point sampling strategy, a trough level, and a second sample obtained between two and four hours post-dose significantly improved the squared correlation with the AUC(0-12h) (r2= 0.94). Compared with trough level monitoring only, this approach reduced the 95%-prediction interval by 50%. The Bayesian approach proved to be feasible in clinical practice, and provided accurate information about systemic tacrolimus exposure in individual patients. In the AUC-guided dosing cohort the apparent clearance of tacrolimus decreased gradually over time, which was not reflected in corresponding trough levels.ConclusionThis simple, flexible method provides the opportunity to tailor immunosuppression, and should help minimize tacrolimus-related toxicity, such as nephrotoxicity and post-transplant diabetes mellitus

Serum Potassium and Risk of Death or Kidney Replacement Therapy in Older People With CKD Stages 4-5: Eight-Year Follow-up

Rationale & objective: Hypokalemia may accelerate kidney function decline. Both hypo- and hyperkalemia can cause sudden cardiac death. However, little is known about the relationship between serum potassium and death or the occurrence of kidney failure requiring replacement therapy (KRT). We investigated this relationship in older people with chronic kidney disease (CKD) stage 4-5. Study design: Prospective observational cohort study. Setting & participants: We followed 1,714 patients (≥65 years old) from the European Quality (EQUAL) study for 8 years from their first estimated glomerular filtration rate (eGFR)<20mL/min/1.73m2 measurement. Exposure: Serum potassium was measured every 3 to 6 months and categorized as≤3.5,>3.5-≤4.0,>4.0-≤4.5,>4.5-≤5.0 (reference),>5.0-≤5.5, >5.5-≤6.0, and>6.0mmol/L. Outcome: The combined outcome death before KRT or start of KRT. Analytical approach: The association between categorical and continuous time-varying potassium and death or KRT start was examined using Cox proportional hazards and restricted cubic spline analyses, adjusted for age, sex, diabetes, cardiovascular disease, renin-angiotensin-aldosterone system (RAAS) inhibition, eGFR, and subjective global assessment (SGA). Results: At baseline, 66% of participants were men, 42% had diabetes, 47% cardiovascular disease, and 54% used RAAS inhibitors. Their mean age was 76±7 (SD) years, mean eGFR was 17±5 (SD) mL/min/1.73m2, and mean SGA was 6.0±1.0 (SD). Over 8 years, 414 (24%) died before starting KRT, and 595 (35%) started KRT. Adjusted hazard ratios for death or KRT according to the potassium categories were 1.6 (95% CI, 1.1-2.3), 1.4 (95% CI, 1.1-1.7), 1.1 (95% CI, 1.0-1.4), 1 (reference), 1.1 (95% CI, 0.9-1.4), 1.8 (95% CI, 1.4-2.3), and 2.2 (95% CI, 1.5-3.3). Hazard ratios were lowest at a potassium of about 4.9mmol/L. Limitations: Shorter intervals between potassium measurements would have allowed for more precise estimations. Conclusions: We observed a U-shaped relationship between serum potassium and death or KRT start among patients with incident CKD 4-5, with a nadir risk at a potassium level of 4.9mmol/L. These findings underscore the potential importance of preventing both high and low potassium in patients with CKD 4-5. Plain-language summary: Abnormal potassium blood levels may increase the risk of death or kidney function decline, especially in older people with chronic kidney disease (CKD). We studied 1,714 patients aged≥65 years with advanced CKD from the European Quality (EQUAL) study and followed them for 8 years. We found that both low and high levels of potassium were associated with an increased risk of death or start of kidney replacement therapy, with the lowest risk observed at a potassium level of 4.9 mmol/L. In patients with CKD, the focus is often on preventing high blood potassium. However, this relatively high optimum potassium level stresses the potential importance of also preventing low potassium levels in older patients with advanced CKD