Background: CKD is characterized by a sustained proinflammatory response of the immune system, promoting hypertension and cardiovascular disease. The underlying mechanisms are incompletely understood but may be linked to gut dysbiosis. Dysbiosis has been described in adults with CKD; however, comorbidities limit CKD-specific conclusions. Methods: We analyzed the fecal microbiome, metabolites, and immune phenotypes in 48 children (with normal kidney function, CKD stage G3–G4, G5 treated by hemodialysis [HD], or kidney transplantation) with a mean±SD age of 10.6±3.8 years. Results: Serum TNF-α and sCD14 were stage-dependently elevated, indicating inflammation, gut barrier dysfunction, and endotoxemia. We observed compositional and functional alterations of the microbiome, including diminished production of short-chain fatty acids. Plasma metabolite analysis revealed a stage-dependent increase of tryptophan metabolites of bacterial origin. Serum from patients on HD activated the aryl hydrocarbon receptor and stimulated TNF-α production in monocytes, corresponding to a proinflammatory shift from classic to nonclassic and intermediate monocytes. Unsupervised analysis of T cells revealed a loss of mucosa-associated invariant T (MAIT) cells and regulatory T cell subtypes in patients on HD. Conclusions: Gut barrier dysfunction and microbial metabolite imbalance apparently mediate the proinflammatory immune phenotype, thereby driving the susceptibility to cardiovascular disease. The data highlight the importance of the microbiota-immune axis in CKD, irrespective of confounding comorbidities.

Untargeted metabolomics is an important tool in studying health and disease and is employed in fields such as biomarker discovery and drug development, as well as precision medicine. Although significant technical advances were made in the field of mass-spectrometry driven metabolomics, instrumental drifts, such as fluctuations in retention time and signal intensity, remain a challenge, particularly in large untargeted metabolomics studies. Therefore, it is crucial to consider these variations during data processing to ensure high-quality data. Here, we will provide recommendations for an optimal data processing workflow using intrastudy quality control (QC) samples that identifies errors resulting from instrumental drifts, such as shifts in retention time and metabolite intensities. Furthermore, we provide an in-depth comparison of the performance of three popular batch-effect correction methods of different complexity. By using different evaluation metrics based on QC samples and a machine learning approach based on biological samples, the performance of the batch-effect correction methods were evaluated. Here, the method TIGER demonstrated the overall best performance by reducing the relative standard deviation of the QCs and dispersion-ratio the most, as well as demonstrating the highest area under the receiver operating characteristic with three different probabilistic classifiers (Logistic regression, Random Forest, and Support Vector Machine). In summary, our recommendations will help to generate high-quality data that are suitable for further downstream processing, leading to more accurate and meaningful insights into the underlying biological processes.

The uremic toxins indoxyl sulfate (IS) and p-cresyl sulfate (pCS) accumulate in patients with chronic kidney disease (CKD) as a consequence of altered gut microbiota metabolism and a decline in renal excretion. Despite of solid experimental evidence for nephrotoxic effects, the impact of uremic toxins on the progression of CKD has not been investigated in representative patient cohorts. In this analysis, IS and pCS serum concentrations were measured in 604 pediatric participants (mean eGFR of 27 ± 11 ml/min/1.73m2) at enrolment into the prospective Cardiovascular Comorbidity in Children with CKD study. Associations with progression of CKD were analyzed by Kaplan-Meier analyses and Cox proportional hazard models. During a median follow up time of 2.2 years (IQR 4.3–0.8 years), the composite renal survival endpoint, defined as 50% loss of eGFR, or eGFR <10ml/min/1.73m2 or start of renal replacement therapy, was reached by 360 patients (60%). Median survival time was shorter in patients with IS and pCS levels in the highest versus lowest quartile for both IS (1.5 years, 95%CI [1.1,2.0] versus 6.0 years, 95%CI [5.0,8.4]) and pCS (1.8 years, 95%CI [1.5,2.8] versus 4.4 years, 95%CI [3.4,6.0]). Multivariable Cox regression disclosed a significant association of IS, but not pCS, with renal survival, which was independent of other risk factors including baseline eGFR, proteinuria and blood pressure. In this exploratory analysis we provide the first data showing a significant association of IS, but not pCS serum concentrations with the progression of CKD in children, independent of other known risk factors. In the absence of comorbidities, which interfere with serum levels of uremic toxins, such as diabetes, obesity and metabolic syndrome, these results highlight the important role of uremic toxins and accentuate the unmet need of effective elimination strategies to lower the uremic toxin burden and abate progression of CKD.

Kidney transplantation (KT) is the best treatment for end-stage kidney disease, with graft survival critically affected by the recipient's immune response. The role of the gut microbiome in modulating this immune response remains underexplored. Our study investigates how microbiome alterations might associate with allograft rejection by analyzing the gut microbiome using 16S rRNA gene amplicon sequencing of a multicenter prospective study involving 562 samples from 245 individuals of which 217 received KT. Overall, gut microbiome composition showed gradual recovery post-KT, mirroring CKD-to-health transition as indicated by an increase of Shannon diversity. Prior to graft rejection, we observed a decrease in microbial diversity and SCFA-producing taxa. Functional analysis highlighted a decreased potential for SCFA production in patients preceding the rejection event, validated by quantitative PCR for the production potential of propionate and butyrate. Post-rejection analysis revealed normalization of these microbiome features. Comparison to published microbiome signatures from CKD patients demonstrated a partial overlap of the microbiome alterations preceding graft rejection with the alterations typically found in CKD. Our findings suggest that alterations in gut microbiome composition and function may precede and influence KT rejection, suggesting potential implications as biomarkers or for early therapeutic microbiome-targeting interventions.

Introduction: Hemolytic-uremic syndrome (HUS) is a common cause for intrarenal acute kidney injury in childhood. More than 90% of HUS cases are associated with an infection by Shigatoxin-producing Escherichia coli (STEC) whereas the reminder comprises a heterogeneous group (here classified as Non-STEC-HUS). Renal impairment can persist in patients with HUS. This study presents data from four decades investigating the short- and long-term outcome of HUS in childhood. Materials and Methods: In a retrospective single-center-study clinical and laboratory data of the acute phase and of 1- to 10-year follow-up visits of children with HUS were analyzed. Results: 92 HUS-patients were identified from 1996 to 2014 (STEC-HUS-group: n = 76; Non-STEC-HUS-group: n = 16) and 220 HUS-patients between 1976 and 1995. STEC-HUS was increasingly caused by Non-O157 strains and mortality rate declined over the past decades (1.3 vs. 9.5%). Renal sequelae persisted more often in the group 1976–1995 (39.3%) than in the group 1996–2014 (28.3%), but more than 50% of all patients were lost to follow-up. Conclusion: Although renal outcome has improved over the investigated last decades, patients with HUS still face a high risk of permanent renal damage. These findings underline the importance of a consequent long-term follow-up in HUS-patients.