Urinary Epidermal Growth Factor/Creatinine Ratio and Graft Failure in Renal Transplant Recipients:A Prospective Cohort Study

Graft failure (GF) remains a significant limitation to improve long-term outcomes in renal transplant recipients (RTR). Urinary epidermal growth factor (uEGF) is involved in kidney tissue integrity, with a reduction of its urinary excretion being associated with fibrotic processes and a wide range of renal pathologies. We aimed to investigate whether, in RTR, uEGF is prospectively associated with GF. In this prospective cohort study, RTR with a functioning allograft >= 1-year were recruited and followed-up for three years. uEGF was measured in 24-hours urine samples and normalized by urinary creatinine (Cr). Its association with risk of GF was assessed by Cox-regression analyses and its predictive ability by C-statistic. In 706 patients, uEGF/Cr at enrollment was 6.43 [IQR 4.07-10.77] ng/mg. During follow-up, 41(6%) RTR developed GF. uEGF/Cr was inversely associated with the risk of GF (HR 0.68 [95% CI 0.59-0.78]; P <0.001), which remained significant after adjustment for immunosuppressive therapy, estimated Glomerular Filtration Rate, and proteinuria. C-statistic of uEGF/Cr for GF was 0.81 (P <0.001). We concluded that uEGF/Cr is independently and inversely associated with the risk of GF and depicts strong prediction ability for this outcome. Further studies seem warranted to elucidate whether uEGF might be a promising marker for use in clinical practice

Metabolic pathways and immunometabolism in rare kidney diseases

Objectives To characterise renal tissue metabolic pathway gene expression in different forms of glomerulonephritis. Methods Patients with nephrotic syndrome (NS), antineutrophil cytoplasmic antibody-associated vasculitis (AAV), systemic lupus erythematosus (SLE) and healthy living donors (LD) were studied. Clinically indicated renal biopsies were obtained at time of diagnosis and microdissected into glomerular and tubulointerstitial compartments. Microarray-derived differential gene expression of 88 genes representing critical enzymes of metabolic pathways and 25 genes related to immune cell markers was compared between disease groups. Correlation analyses measured relationships between metabolic pathways, kidney function and cytokine production. Results Reduced steady state levels of mRNA species were enriched in pathways of oxidative phosphorylation and increased in the pentose phosphate pathway (PPP) with maximal perturbation in AAV and SLE followed by NS, and least in LD. Transcript regulation was isozymes specific with robust regulation in hexokinases, enolases and glucose transporters. Intercorrelation networks were observed between enzymes of the PPP (eg, transketolase) and macrophage markers (eg, CD68) (r=0.49, p<0.01). Increased PPP transcript levels were associated with reduced glomerular filtration rate in the glomerular (r=-0.49, p<0.01) and tubulointerstitial (r=-0.41, p<0.01) compartments. PPP expression and tumour necrosis factor activation were tightly co-expressed (r=0.70, p<0.01). Conclusion This study demonstrated concordant alterations of the renal transcriptome consistent with metabolic reprogramming across different forms of glomerulonephritis. Activation of the PPP was tightly linked with intrarenal macrophage marker expression, reduced kidney function and increased production of cytokines. Modulation of glucose metabolism may offer novel immune-modulatory therapeutic approaches in rare kidney diseases

Validation of plasma biomarker candidates for the prediction of eGFR decline in patients with type 2 diabetes

Objective: The decline of estimated glomerular filtration rate (eGFR) in patients with type 2 diabetes is variable and early interventions would likely be cost effective. We elucidated the contribution of 17 plasma biomarkers to the prediction of eGFR loss on top of clinical risk factors. Research Design and Methods: We studied participants in PROVALID, a prospective multinational cohort study of patients with type 2 diabetes and a follow up of more than 24 months (n = 2560; baseline median eGFR 84 mL/min/1.73m2, UACR 8.1 mg/g). The 17 biomarkers were measured at baseline in 481 samples using Luminex technology and ELISA. The prediction of eGFR decline was evaluated by linear mixed modeling. Results: In univariable analyses nine of the 17 markers showed significant differences in median concentration between the two groups. A linear mixed model for eGFR obtained by variable selection exhibited an adjusted R2 of 62%. A panel of twelve biomarkers was selected by the procedure and accounted for 34% of the total explained variability, of which 32% were due to five markers. Each biomarker’s individual contribution to the prediction of eGFR decline on top of clinical predictors was generally low. When included into the model, baseline eGFR exhibited the largest explained variability of eGFR decline (R2 of 79%) and the contribution of each biomarker dropped below 1%. Conclusions: In this longitudinal study of patients with type 2 diabetes and maintained eGFR at baseline, 12 of the 17 candidate biomarkers were associated with eGFR decline, but their predictive power was low

The immune cell landscape in kidneys of patients with lupus nephritis.

Lupus nephritis is a potentially fatal autoimmune disease for which the current treatment is ineffective and often toxic. To develop mechanistic hypotheses of disease, we analyzed kidney samples from patients with lupus nephritis and from healthy control subjects using single-cell RNA sequencing. Our analysis revealed 21 subsets of leukocytes active in disease, including multiple populations of myeloid cells, T cells, natural killer cells and B cells that demonstrated both pro-inflammatory responses and inflammation-resolving responses. We found evidence of local activation of B cells correlated with an age-associated B-cell signature and evidence of progressive stages of monocyte differentiation within the kidney. A clear interferon response was observed in most cells. Two chemokine receptors, CXCR4 and CX3CR1, were broadly expressed, implying a potentially central role in cell trafficking. Gene expression of immune cells in urine and kidney was highly correlated, which would suggest that urine might serve as a surrogate for kidney biopsies

Strategy and rationale for urine collection protocols employed in the NEPTUNE study

Abstract Background Glomerular diseases are potentially fatal, requiring aggressive interventions and close monitoring. Urine is a readily-accessible body fluid enriched in molecular signatures from the kidney and therefore particularly suited for routine clinical analysis as well as development of non-invasive biomarkers for glomerular diseases. Methods The Nephrotic Syndrome Study Network (NEPTUNE; ClinicalTrials.gov Identifier NCT01209000) is a North American multicenter collaborative consortium established to develop a translational research infrastructure for nephrotic syndrome. This includes standardized urine collections across all participating centers for the purpose of discovering non-invasive biomarkers for patients with nephrotic syndrome due to minimal change disease, focal segmental glomerulosclerosis, and membranous nephropathy. Here we describe the organization and methods of urine procurement and banking procedures in NEPTUNE. Results We discuss the rationale for urine collection and storage conditions, and demonstrate the performance of three experimental analytes (neutrophil gelatinase-associated lipocalin [NGAL], retinol binding globulin, and alpha-1 microglobulin) under these conditions with and without urine preservatives (thymol, toluene, and boric acid). We also demonstrate the quality of RNA and protein collected from the urine cellular pellet and exosomes. Conclusions The urine collection protocol in NEPTUNE allows robust detection of a wide range of proteins and RNAs from urine supernatant and pellets collected longitudinally from each patient over 5 years. Combined with the detailed clinical and histopathologic data, this provides a unique resource for exploration and validation of new or accepted markers of glomerular diseases. Trial registration ClinicalTrials.gov Identifier NCT01209000http://deepblue.lib.umich.edu/bitstream/2027.42/116023/1/12882_2015_Article_185.pd

Rationale and Design of the Nephrotic Syndrome Study Network (NEPTUNE) Match in Glomerular Diseases: Designing the Right Trial for the Right Patient, Today

Glomerular diseases are classified using a descriptive taxonomy that is not reflective of the heterogeneous underlying molecular drivers. This limits not only diagnostic and therapeutic patient management, but also impacts clinical trials evaluating targeted interventions. The Nephrotic Syndrome Study Network (NEPTUNE) is poised to address these challenges. The study has enrolled \u3e850 pediatric and adult patients with proteinuric glomerular diseases who have contributed to deep clinical, histologic, genetic, and molecular profiles linked to long-term outcomes. The NEPTUNE Knowledge Network, comprising combined, multiscalar data sets, captures each participant\u27s molecular disease processes at the time of kidney biopsy. In this editorial, we describe the design and implementation of NEPTUNE Match, which bridges a basic science discovery pipeline with targeted clinical trials. Noninvasive biomarkers have been developed for real-time pathway analyses. A Molecular Nephrology Board reviews the pathway maps together with clinical, laboratory, and histopathologic data assembled for each patient to compile a Match report that estimates the fit between the specific molecular disease pathway(s) identified in an individual patient and proposed clinical trials. The NEPTUNE Match report is communicated using established protocols to the patient and the attending nephrologist for use in their selection of available clinical trials. NEPTUNE Match represents the first application of precision medicine in nephrology with the aim of developing targeted therapies and providing the right medication for each patient with primary glomerular disease

Transcript-Specific Expression Profiles Derived from Sequence-Based Analysis of Standard Microarrays

Background: Alternative mRNA processing mechanisms lead to multiple transcripts (i.e. splice isoforms) of a given gene which may have distinct biological functions. Microarrays like Affymetrix GeneChips measure mRNA expression of genes using sets of nucleotide probes. Until recently probe sets were not designed for transcript specificity. Nevertheless, the reanalysis of established microarray data using newly defined transcript-specific probe sets may provide information about expression levels of specific transcripts. Methodology/Principal Findings: In the present study alignment of probe sequences of the Affymetrix microarray HGU133A with Ensembl transcript sequences was performed to define transcript-specific probe sets. Out of a total of 247,965 perfect match probes, 95,008 were designated ‘‘transcript-specific’’, i.e. showing complete sequence alignment, no crosshybridization, and transcript-, not only gene-specificity. These probes were grouped into 7,941 transcript-specific probe sets and 15,619 gene-specific probe sets, respectively. The former were used to differentiate 445 alternative transcripts of 215 genes. For selected transcripts, predicted by this analysis to be differentially expressed in the human kidney, confirmatory real-time RT-PCR experiments were performed. First, the expression of two specific transcripts of the genes PPM1A (PP2CA_HUMAN and P35813) and PLG (PLMN_HUMAN and Q5TEH5) in human kidneys was determined by the transcriptspecific array analysis and confirmed by real-time RT-PCR. Secondly, disease-specific differential expression of single transcripts of PLG and ABCA1 (ABCA1_HUMAN and Q5VYS0_HUMAN) was computed from the available array data sets and confirmed by transcript-specific real-time RT-PCR. Conclusions: Transcript-specific analysis of microarray experiments can be employed to study gene-regulation on the transcript level using conventional microarray data. In this study, predictions based on sufficient probe set size and foldchange are confirmed by independent mean

Urinary Epidermal Growth Factor as a Marker of Disease Progression in Children With Nephrotic Syndrome.

Introduction: Childhood-onset nephrotic syndrome has a variable clinical course. Improved predictive markers of long-term outcomes in children with nephrotic syndrome are needed. This study tests the association between baseline urinary epidermal growth factor (uEGF) excretion and longitudinal kidney function in children with nephrotic syndrome. Methods: The study evaluated 191 participants younger than 18 years enrolled in the Nephrotic Syndrome Study Network, including 118 with their first clinically indicated kidney biopsy (68 minimal change disease; 50 focal segmental glomerulosclerosis) and 73 with incident nephrotic syndrome without a biopsy. uEGF was measured at baseline for all participants and normalized by the urine creatinine (Cr) concentration. Renal epidermal growth factor (EGF) mRNA was measured in the tubular compartment microdissected from kidney biopsy cores from a subset of patients. Linear mixed models were used to test if baseline uEGF/Cr and EGF mRNA expression were associated with change in estimated glomerular filtration rate (eGFR) over time. Results: Higher uEGF/Cr at baseline was associated with slower eGFR decline during follow-up (median follow-up = 30 months). Halving of uEGF/Cr was associated with a decrease in eGFR slope of 2.0 ml/min per 1.73 m Conclusion: uEGF/Cr may be a useful noninvasive biomarker that can assist in predicting the long-term course of kidney function in children with incident nephrotic syndrome

Assessment of differentially methylated loci in individuals with end-stage kidney disease attributed to diabetic kidney disease : an exploratory study

Publisher Copyright: © 2021, The Author(s).Background: A subset of individuals with type 1 diabetes mellitus (T1DM) are predisposed to developing diabetic kidney disease (DKD), the most common cause globally of end-stage kidney disease (ESKD). Emerging evidence suggests epigenetic changes in DNA methylation may have a causal role in both T1DM and DKD. The aim of this exploratory investigation was to assess differences in blood-derived DNA methylation patterns between individuals with T1DM-ESKD and individuals with long-duration T1DM but no evidence of kidney disease upon repeated testing to identify potential blood-based biomarkers. Blood-derived DNA from individuals (107 cases, 253 controls and 14 experimental controls) were bisulphite treated before DNA methylation patterns from both groups were generated and analysed using Illumina’s Infinium MethylationEPIC BeadChip arrays (n = 862,927 sites). Differentially methylated CpG sites (dmCpGs) were identified (false discovery rate adjusted p ≤ × 10–8 and fold change ± 2) by comparing methylation levels between ESKD cases and T1DM controls at single site resolution. Gene annotation and functionality was investigated to enrich and rank methylated regions associated with ESKD in T1DM. Results: Top-ranked genes within which several dmCpGs were located and supported by functional data with methylation look-ups in other cohorts include: AFF3, ARID5B, CUX1, ELMO1, FKBP5, HDAC4, ITGAL, LY9, PIM1, RUNX3, SEPTIN9 and UPF3A. Top-ranked enrichment pathways included pathways in cancer, TGF-β signalling and Th17 cell differentiation. Conclusions: Epigenetic alterations provide a dynamic link between an individual’s genetic background and their environmental exposures. This robust evaluation of DNA methylation in carefully phenotyped individuals has identified biomarkers associated with ESKD, revealing several genes and implicated key pathways associated with ESKD in individuals with T1DM.Peer reviewe