End-stage kidney disease is preferably treated by kidney transplantation. The suboptimal function of the allograft often results in misbalances in kidney-controlled processes and requires long-term monitoring of allograft function and viability. As the kidneys are organs with a very high metabolomic rate, a metabolomics approach is suitable to describe systematic changes in post-transplant patients and has great potential for monitoring allograft function, which has not been described yet. In this study, we used blood plasma samples from 55 patients after primary kidney transplantation identically treated with immunosuppressants with follow-up 50 months in the mean after surgery and evaluated relative levels of basal plasma metabolites detectable by NMR spectroscopy. We were looking for the correlations between circulating metabolites levels and allograft performance and allograft rejection features. Our results imply a quantitative relationship between restricted renal function, insufficient hydroxylation of phenylalanine to tyrosine, lowered renal glutamine utilization, shifted nitrogen balance, and other alterations that are not related exclusively to the metabolism of the kidney. No link between allograft function and energy metabolism can be concluded, as no changes were found for glucose, glycolytic intermediates, and 3-hydroxybutyrate as a ketone body representative. The observed changes are to be seen as a superposition of changes in the comprehensive inter-organ metabolic exchange, when the restricted function of one organ may induce compensatory effects or cause secondary alterations. Particular differences in plasma metabolite levels in patients with acute cellular and antibody-mediated allograft rejection were considered rather to be related to the loss of kidney function than to the molecular mechanism of graft rejection since they largely follow the alterations observed by restricted allograft function. In the end, we showed using a simple mathematical model, multilinear regression, that the basal plasmatic metabolites correlated with allograft function expressed by the level of glomerular filtration rate (with creatinine: p-value = 4.0 × 10⁻²⁶ and r = 0.94, without creatinine: p-value = 3.2 × 10⁻²² and r = 0.91) make the noninvasive estimation of the allograft function feasible.

COVID-19 infection remains a threat to the health systems of many countries. Potential success in the fight against the COVID-19 pandemic is the vaccination of high-risk groups, including patients with end-stage kidney disease (ESKD) and after solid organ transplantation (SOT). Immunosuppression in kidney transplant recipients can also reduce the immunogenicity of SARS-CoV-2 vaccines (varied by vaccine platform), available data suggest that they are efficacious in approximately 50–70%, compared to non-transplant situations. In this paper, we present a newly developed acute humoral and cellular rejection with acute allograft failure and need of hemodialysis 14 days after administration of the adenovirus vectored SARS-CoV-2 vaccine (AstraZeneca; CHADOx1, AZD1222). This occurred in a patient who previously had an asymptomatic COVID-19 infection. Case reports of acute allograft rejection after vaccination against SARS-CoV-2 can help stratify risk groups of patients who develop hyperimmune reactions. However, it is also possible that those with a previous mild primary COVID-19 infection may also develop acute allograft rejections upon COVID-19 re-infection.

Background and Objectives: Post-transplant diabetes mellitus (PTDM) is a significant risk factor for the survival of graft recipients and occurs in 10–30% of patients after kidney transplant (KT). PTDM is associated with premature cardiovascular morbidity and mortality. Weight gain, obesity, and dyslipidemia are strong predictors of PTDM, and by modifying them with an active lifestyle it is possible to reduce the incidence of PTDM and affect the long-term survival of patients and grafts. The aim of our study was to determine the effect of regular physical activity on the development of PTDM and its risk factors in patients after KT. Materials and Methods: Participants in the study had to achieve at least 150 min of moderate-intensity physical exertion per week. The study group (n = 22) performed aerobic or combined (aerobic + strength) types of sports activities. Monitoring was provided by the sports tracker (Xiaomi Mi Band 4 compatible with the Mi Fit mobile application). The control group consisted of 22 stable patients after KT. Each patient underwent an oral glucose tolerance test (oGTT) at the end of the follow-up. The patients in both groups have the same immunosuppressive protocol. The total duration of the study was 6 months. Results: The patients in the study group had significantly more normal oGTT results at 6 months compared to the control group (p < 0.0001). In the control group, there were significantly more patients diagnosed with PTDM (p = 0.0212) and with pre-diabetic conditions (impaired plasma glucose and impaired glucose tolerance) at 6 months (p = 0.0078). Conclusions: Regular physical activity after KT provides significant prevention against the development of pre-diabetic conditions and PTDM.

BACKGROUND AND AIMS: Non-invasive diagnosis of graft rejection after kidney transplantation is still an unresolved issue. Changes in serum metabolite concentrations reflect the various processes involved in the graft, and thus graft rejection. Metabolomics approach might help with non-invasive diagnosis of graft rejection based on identification of T-cell activation. METHOD: In a group of 55 patients after primary kidney transplantation (average follow-up 68.4 months, median 59 months) we identified patients with cellular rejection (ACR), antibody mediated rejection (AMR) and control group (CG)—patients without history of graft rejection. We used NMR metabolomic approach to determine the relative levels of metabolites in blood plasma. RESULTS: From 23 evaluated metabolites: lactate was significantly increased in CG and in ACR against AMR (P < 0.05), whilst plasma glutamine decreased in CG against ACR (P < 0.05) and AMR (P < 0.05) groups. Further, tyrosine was significantly increased in CG against AMR (P < 0.05). All three branched chain α-keto acids (BCKAs) behaved similarly. However, little over significance cut off were CG >AMR. When discriminating CG and AMR, Random Forest discriminatory algorithm performed with AUC = 0.849 when included also evaluated plasma creatinine and with AUC = 0.83 when creatinine was excluded (other metabolites with the highest discriminatory power were glutamine, lactate, tyrosine and BCKAs). CONCLUSION: Metabolomic approach to blood plasma in patients after kidney transplantation seems to be very promising when looking for non-invasive techniques assessing graft viability/survival. The observed metabolomic changes were able to very well discriminate between patients with AMR and control group. However, discrimination of ACR against CG and AMR was rather poor.

Background: Protein–energy wasting (PEW) is a major predictor of morbidity and mortality in patients with chronic kidney disease (CKD), even before the initiation of dialysis. Its multifactorial pathogenesis includes reduced dietary intake, chronic inflammation, metabolic acidosis, hormonal disturbances, and dysbiosis of the gut microbiota. Early recognition and targeted management are crucial for preventing muscle loss, functional decline, and adverse outcomes. Methods: This narrative review summarises and integrates current evidence from the literature on nutritional and metabolic interventions to prevent and treat protein–energy wasting in patients with nondialysis chronic kidney disease. Relevant clinical trials, meta-analyses, and experimental studies published up to date were evaluated, focusing on dietary strategies, metabolic modulation, physical exercise, and gut microbiome-targeted therapies. Results: Adequate energy and protein intake remain the cornerstone of PEW management, based on available clinical and observational evidence. Individualised diets emphasising high-quality and plant-based proteins, oral nutritional supplements, and ketoanalogues can attenuate muscle wasting. Correction of metabolic acidosis and inflammation enhances protein anabolism and nitrogen balance. Physical exercise acts synergistically with dietary interventions to preserve muscle mass and function. Novel approaches—such as modulating the gut–kidney axis with pre-, pro-, and postbiotics or supplementing with short-chain fatty acids—show promise in improving metabolic and inflammatory profiles. Conclusions: The management of PEW in nondialysis CKD requires a personalised approach that integrates nutrition, physical activity, metabolic correction and microbiome modulation. Early, coordinated intervention may help to slow the progression of CKD and improve patient survival and quality of life.

Background and Objectives: It has been confirmed that adiponectin/leptin (A/L) ratio correlates better with cardiometabolic risk factors than hormone levels alone. The aim of our study was to determine the risk of developing post-transplant diabetes mellitus (PTDM) and other metabolic conditions depending on A/L ratio after kidney transplantation (KT). Material and Methods: In a prospective analysis, the studied samples were divided into three groups: control group, prediabetes and PTDM group. Pre-transplantation, at 3, 6 and 12 months after KT, we recorded basic characteristics of donor and recipient. We also monitored levels of adipocytokines and calculated A/L ratio. Results: During observed period, we recorded significant increase in A/L ratio in control group (p = 0.0013), on the contrary, a significant decrease in PTDM group (p = 0.0003). Using Cox regression Hazard model, we identified age at time of KT (HR 2.8226, p = 0.0225), triglycerides at 1 year (HR 3.5735, p = 0.0174) and A/L ratio < 0.5 as independent risk factors for prediabetes and PTDM 1-year post-transplant (HR 3.1724, p = 0.0114). Conclusions: This is the first study to evaluate the relationship between A/L and risk of PTDM and associated metabolic states after KT. We found out that A/L ratio <0.5 is independent risk factor for prediabetes and PTDM 1 year post-transplant.