Adverse effects of mycophenolic acid in renal transplant recipients: gender differences

Representation of Women in Contemporary Kidney Transplant Trials

Women are often underrepresented in clinical trials. It is unclear if this applies to trials in kidney transplant (KT) and whether the intervention or trial focus influences this. In this study, the weighted participation-to-prevalence ratio (PPR) for women enrollees in KT trials was determined for leading medical transplant or kidney journals between 2018 and 2023 using meta-regression overall and in three sensitivity analyses by: 1) Whether the intervention involved immunosuppression; 2) Area of trial focus; rejection, cardiometabolic, infection, lifestyle, surgical; 3) Whether the intervention was medical/surgical or social/behavioral. Overall, 33.7% of participants in 24 trials were women. The overall pooled PPR for the included trials was 0.80, 95% CI 0.76-0.85, with significant heterogeneity between trials (I ² 56.6%, p-value < 0.001). Women had a lower PPR when the trial involved immunosuppression (PPR 0.77, 95% CI 0.72-0.82) than when it did not (PPR 0.86, 95% CI 0.80-0.94) and were less likely to participate in trials with a medical/surgical versus behavioral intervention; the lowest PPR for women was in studies examining rejection risk (PPR 0.75, 95% CI 0.70-0.81). There is better representation of women in KT trials compared to other medical disciplines, however women remain underrepresented in transplant trials examining immunosuppression and rejection.

Utility of salivary mycophenolic acid concentration monitoring: Modeling and Monte Carlo validation approach

The results of the previous studies demonstrated an association between mycophenolic acid (MPA) exposure, serum albumin level (ALB), and adverse effects in kidney transplant patients. The aim was the identification of mathematical correlation and association between both, total and unbound MPA concentration in relation to ALB, body mass (BM), age and estimated glomerular filtration rate (eGFR) in stable kidney transplant recipients. Furthermore, investigation was conducted with the aim to clarify the role of salivary concentration (CSAL ) of MPA in adverse effect profile. In order to analyze the association between total and salivary concentration of MPA in relation to ALB, BM, age and eGFR, a least squares method for determining the correlation between these parameters was performed. In addition, derived mathematical model based on experimental data can also be performed and simulated through the Monte Carlo (MC) approach. Adverse effects were grouped according to the nature of symptoms and scored by a previously published validated system. Numerically calculated values of CSAL from the models [CSAL  = f(ALB, BM, age, eGFR, CP ) = a00  + a10 *(ALB, BM, age, eGFR) + a01 *CP ] were then compared with those from validation set of patients, where the best fitting model was for ALB [CSAL  = 54.96-1.64*ALB +13.4*CP ]. Adverse effects estimation showed the difference in esthetic score, positively correlated with CSAL in the lower ALB group (145.41 ± 219.02 vs. 354.08 ± 262.19; with statistical significance p = .014) and almost significant for gastrointestinal score (167.69 ± 174.79 vs. 347.55 ± 320.95; p = .247). The study showed that CSAL MPA may contribute to management of adverse effects, but these findings require confirmation of clinical utility.

Microbiota, renal disease and renal transplantation

Aim of this frontier review has been to highlight the role of microbiota in healthy subjects and in patients affected by renal diseases with particular reference to renal transplantation. The microbiota has a relevant role in conditioning the healthy status and the diseases. In particular gut microbiota is essential in the metabolism of food and has a relevant role for its relationship with the immune system. The indigenous microbiota in patients with chronic renal failure is completely different than that of the healthy subjects and pathobionts appear. This abnormality in microbiota composition is called dysbiosis and may cause a rapid deterioration of the renal function both for activating the immune system and producing large quantity of uremic toxins. Similarly, after renal trans-plantation the microbiota changes with the appearance of pathobionts, principally in the first period because of the assumption of immunosuppressive drugs and antibiotics. These changes may deeply interfere with the graft outcome causing acute rejection, renal infections, diarrhea, and renal interstitial fibrosis. In addition, change in the microbiota may modify the metabolism of immuno-suppressive drugs causing in some patients the need of modifying the immunosuppressant dosing. The restoration of the indigenous microbiota after transplantation is important, either to avoiding the complications that impair the normal renal graft, and because recent studies have documented the role of an indigenous microbiota in inducing tolerance towards the graft. The use of prebiotics, probiotics, smart bacteria and diet modification may restore the indigenous microbiota, but these studies are just at their beginning and more data are needed to draw definitive conclusions.

Assessment of pharmacokinetic mycophenolic acid clearance models using Monte Carlo numerical analysis

Previously, we performed population pharmacokinetic analysis and indicated age, mycophenolate mofetil (MMF)/mycophenolic acid (MPA) daily dose, and presence of nifedipine in patient therapy as significant predictors of MPA apparent clearance (CL/F) variability. This study aimed to determine the reliability of previously published population pharmacokinetic models derived from similar studies. Furthermore, this study investigated correspondence between chosen population models from the literature.By means of the Monte Carlo simulation method, pharmacokinetic models from different studies are simulated and analysed in the range of standard deviations of measured system parameters as well as the range of observed model parameters taken from the comparison studies.The 1000 numerical simulations were performed for every analysed model in order to calculate the most possible MPA CL/F values according to the expected values from the performed experiment. Fitting our results with other models showed how the presence of nifedipine makes difference in MPA CL/F values.By testing the data from selected studies into our model, a similar range of expected CL/F values was obtained, which may confirm the validity of our model. The results of our population pharmacokinetic study are partially applicable in models by other researchers.

Characteristics and Dysbiosis of the Gut Microbiome in Renal Transplant Recipients

Renal transplantation is life-changing in many aspects. This includes changes to the gut microbiome likely due to exposure to immunosuppressive drugs and antibiotics. As a consequence, renal transplant recipients (RTRs) might suffer from intestinal dysbiosis. We aimed to investigate the gut microbiome of RTRs and compare it with healthy controls and to identify determinants of the gut microbiome of RTRs. Therefore, RTRs and healthy controls participating in the TransplantLines Biobank and Cohort Study (NCT03272841) were included. We analyzed the gut microbiome using 16S rRNA sequencing and compared the composition of the gut microbiome of RTRs to healthy controls using multivariate association with linear models (MaAsLin). Fecal samples of 139 RTRs (50% male, mean age: 58.3 ± 12.8 years) and 105 healthy controls (57% male, mean age: 59.2 ± 10.6 years) were collected. Median time after transplantation of RTRs was 6.0 (1.5-12.5)years. The microbiome composition of RTRs was significantly different from that of healthy controls, and RTRs had a lower diversity of the gut microbiome (p < 0.01). Proton-pump inhibitors, mycophenolate mofetil, and estimated glomerular filtration rate (eGFR) are significant determinants of the gut microbiome of RTRs (p < 0.05). Use of mycophenolate mofetil correlated to a lower diversity (p < 0.01). Moreover, significant alterations were found in multiple bacterial taxa between RTRs and healthy controls. The gut microbiome of RTRs contained more Proteobacteria and less Actinobacteria, and there was a loss of butyrate-producing bacteria in the gut microbiome of RTRs. By comparing the gut microbiome of RTRs to healthy controls we have shown that RTRs suffer from dysbiosis, a disruption in the balance of the gut microbiome.