Urinary peptidomics and bioinformatics for the detection of diabetic kidney disease.
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ABSTRACT:
SUBMITTER: Brondani LA
PROVIDER: S-EPMC6985249 | biostudies-literature | 2020 Jan
REPOSITORIES: biostudies-literature
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Urinary peptidomics and bioinformatics for the detection of diabetic kidney disease.
Brondani Letícia de Almeida LA Soares Ariana Aguiar AA Recamonde-Mendoza Mariana M Dall'Agnol Angélica A Camargo Joíza Lins JL Monteiro Karina Mariante KM Silveiro Sandra Pinho SP
Scientific reports 20200127 1
The aim of this study was to establish a peptidomic profile based on LC-MS/MS and random forest (RF) algorithm to distinguish the urinary peptidomic scenario of type 2 diabetes mellitus (T2DM) patients with different stages of diabetic kidney disease (DKD). Urine from 60 T2DM patients was collected: 22 normal (stage A1), 18 moderately increased (stage A2) and 20 severely increased (stage A3) albuminuria. A total of 1080 naturally occurring peptides were detected, which resulted in the identifica ...[more]
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Project description:A number of proteomic and peptidomic analyses of urine from diabetic subjects have been published in the quest for a biomarker that predicts progression of nephropathy. Less attention has been paid to the relationships between urinary proteins and the underlying biological processes revealed by the analyses. In this review, we focus on the biological processes identified by studying urinary proteins and protein-protein interactions at each stage of diabetic nephropathy to provide an overview of the events underlying progression of kidney disease reflected in the urine. In uncomplicated diabetes, proteomic/peptidomic analyses indicate that early activation of fibrotic pathways in the kidney occurs before the onset of microalbuminuria. In incipient nephropathy, when albumin excretion rates are abnormal, proteomic/peptidomic analyses suggest that changes in glomerular permselectivity and tubular reabsorption account, at least in part, for the proteins and peptides that appear in the urine. Finally, overt nephropathy is characterized by proteins involved in wound healing, ongoing fibrosis, and inflammation. These findings suggest that there is a spectrum of biological processes in the diabetic kidney and that assessing protein networks may be more informative than individual markers with respect to the stage of disease and the risk of progression.
| S-EPMC5373465 | biostudies-literature
Project description:Mechanisms underlying the onset and progression of nephropathy in diabetic patients are not fully elucidated. Deregulation of proteolytic systems is a known path leading to disease manifestation, therefore we hypothesized that proteases aberrantly expressed in diabetic nephropathy (DN) may be involved in the generation of DN-associated peptides in urine. We compared urinary peptide profiles of DN patients (macroalbuminuric, n = 121) to diabetic patients with no evidence of DN (normoalbuminuric, n = 118). 302 sequenced, differentially expressed peptides (adjusted p-value < 0.05) were analysed with the Proteasix tool predicting proteases potentially involved in their generation. Activity change was estimated based on the change in abundance of the investigated peptides. Predictions were correlated with transcriptomics (Nephroseq) and relevant protein expression data from the literature. This analysis yielded seventeen proteases, including multiple forms of MMPs, cathepsin D and K, kallikrein 4 and proprotein convertases. The activity of MMP-2 and MMP-9, predicted to be decreased in DN, was investigated using zymography in a DN mouse model confirming the predictions. Collectively, this proof-of-concept study links urine peptidomics to molecular changes at the tissue level, building hypotheses for further investigation in DN and providing a workflow with potential applications to other diseases.
| S-EPMC5680307 | biostudies-literature
Project description:BackgroundDiabetic kidney disease (DKD) is the leading cause of end-stage kidney disease (ESKD) in the world. Emerging evidence has shown that urinary mRNAs may serve as early diagnostic and prognostic biomarkers of DKD. In this article, we aimed to first establish a novel bioinformatics-based methodology for analyzing the "urinary kidney-specific mRNAs" and verify their potential clinical utility in DKD.MethodsTo select candidate mRNAs, a total of 127 Affymetrix microarray datasets of diabetic kidney tissues and other tissues from humans were compiled and analyzed using an integrative bioinformatics approach. Then, the urinary expression of candidate mRNAs in stage 1 study (n?=?82) was verified, and the one with best performance moved on to stage 2 study (n?=?80) for validation. To avoid potential detection bias, a one-step Taqman PCR assay was developed for quantification of the interested mRNA in stage 2 study. Lastly, the in situ expression of the selected mRNA was further confirmed using fluorescent in situ hybridization (FISH) assay and bioinformatics analysis.ResultsOur bioinformatics analysis identified sixteen mRNAs as candidates, of which urinary BBOX1 (uBBOX1) levels were significantly upregulated in the urine of patients with DKD. The expression of uBBOX1 was also increased in normoalbuminuric diabetes subjects, while remained unchanged in patients with urinary tract infection or bladder cancer. Besides, uBBOX1 levels correlated with glycemic control, albuminuria and urinary tubular injury marker levels. Similar results were obtained in stage 2 study. FISH assay further demonstrated that BBOX1 mRNA was predominantly located in renal tubular epithelial cells, while its expression in podocytes and urothelium was weak. Further bioinformatics analysis also suggested that tubular BBOX1 mRNA expression was quite stable in various types of kidney diseases.ConclusionsOur study provided a novel methodology to identify and analyze urinary kidney-specific mRNAs. uBBOX1 might serve as a promising biomarker of DKD. The performance of the selected urinary mRNAs in monitoring disease progression needs further validation.
| S-EPMC6394064 | biostudies-literature
Project description:In patients with diabetic kidney disease (DKD), plasma renin activity is usually decreased, but there is limited information on urinary renin and its origin. Urinary renin was evaluated in samples from patients with longstanding type I diabetes mellitus and mice with streptozotocin-induced diabetes mellitus. Renin-reporter mouse model (Ren1d-Cre;mT/mG) was made diabetic with streptozotocin to examine whether the distribution of cells of the renin lineage was altered in a chronic diabetic environment. Active renin was increased in urine samples from patients with DKD (n=36), compared with those without DKD (n=38; 3.2 versus 1.3 pg/mg creatinine; P<0.001). In mice with streptozotocin-induced diabetes mellitus, urine renin was also increased compared with nondiabetic controls. By immunohistochemistry, in mice with streptozotocin-induced diabetes mellitus, juxtaglomerular apparatus and proximal tubular renin staining were reduced, whereas collecting tubule staining, by contrast, was increased. To examine the role of filtration and tubular reabsorption on urinary renin, mice were either infused with either mouse or human recombinant renin and lysine (a blocker of proximal tubular protein reabsorption). Infusion of either form of renin together with lysine markedly increased urinary renin such that it was no longer different between nondiabetic and diabetic mice. Megalin mRNA was reduced in the kidney cortex of streptozotocin-treated mice (0.70±0.09 versus 1.01±0.04 in controls, P=0.01) consistent with impaired tubular reabsorption. In Ren1d-Cre;mT/mG with streptozotocin-induced diabetes mellitus, the distribution of renin lineage cells within the kidney was similar to nondiabetic renin-reporter mice. No evidence for migration of cells of renin linage to the collecting duct in diabetic mice could be found. Renin mRNA in microdissected collecting ducts from streptozotocin-treated mice, moreover, was not significantly different than in controls, whereas in kidney cortex, largely reflecting juxtaglomerular apparatus renin, it was significantly reduced. In conclusion, in urine from patients with type 1 diabetes mellitus and DKD and from mice with streptozotocin-induced diabetes mellitus, renin is elevated. This cannot be attributed to production from cells of the renin lineage migrating to the collecting duct in a chronic hyperglycemic environment. Rather, the elevated levels of urinary renin found in DKD are best attributed to altered glomerular filteration and impaired proximal tubular reabsorption.
| S-EPMC6561816 | biostudies-literature
Project description:Diabetic nephropathy (DN) is the most common cause of chronic kidney disease. Although several parameters are used to evaluate renal damage, in many instances, there is no pathological change until damage is already advanced. Mass spectrometry-based proteomics is a novel tool to identify newer diagnostic markers. To identify urinary proteins associated with renal complications in diabetes, we collected urine samples from 10 type 2 diabetes patients each with normoalbuminuria, micro- and macro-albuminuria and compared their urinary proteome with that of 10 healthy individuals. Urinary proteins were concentrated, depleted of albumin and five other abundant plasma proteins and in-gel trypsin digested after prefractionation on sodium dodecyl sulfate polyacrylamide gel electrophoresis. The peptides were analyzed using a nanoflow reverse phase liquid chromatography system coupled to linear trap quadrupole-Orbitrap mass spectrometer. We identified large number of proteins in each group, of which many were exclusively present in individual patient groups. A total of 53 proteins were common in all patients but were absent in the controls. The majority of the proteins were functionally binding, biologically involved in metabolic processes, and showed enrichment of alternative complement and blood coagulation pathways. In addition to identifying reported proteins such as α2-HS-glycoprotein and Vitamin D binding protein, we detected novel proteins such as CD59, extracellular matrix protein 1 (ECM1), factor H, and myoglobin in the urine of macroalbuminuria patients. ECM1 and factor H are known to influence mesangial cell proliferation, and CD59 causes microvascular damage by influencing membrane attack complex deposition, suggestive their biological relevance to DN. Thus, we have developed a proteome database where various proteins exclusively present in the patients may be further investigated for their role as stage-specific markers and possible therapeutic targets.
| S-EPMC5131383 | biostudies-literature
Project description:BackgroundAlbuminuria is an early sign but not a strong predictor of diabetic kidney disease (DKD). Owing to their high stability, urinary exosomal miRNAs can be useful predictors of the progression of early-stage DKD to renal failure; fluid biopsies are ideal for detecting abnormalities in these miRNAs. The aim of this study was to identify novel differentially expressed miRNAs as urine biomarkers for type 2 DKD by comparing between patients of type 2 diabetes (T2D) with and without macroalbuminuria.MethodsTen patients with T2D, including five who had no renal disease and five with macroalbuminuria (DKD G1-2A3), were selected for this study. Exosome- (UExo-) derived miRNA profiles were used to identify candidate biomarkers, a subset of which was verified using quantitative reverse transcription PCR.ResultsA total of 496 UExo-derived miRNA species were found to be differentially expressed (>2-fold) in patients with DKD, compared to those with T2D. A validation analysis revealed that three miRNAs (miR-362-3p, miR-877-3p, and miR-150-5p) were upregulated and one (miR-15a-5p) was downregulated. These miRNAs might regulate DKD through p53, mTOR, and AMPK pathways.ConclusionsIn conclusion, UExo-derived miRNAs were altered in type 2 DKD. MiR-362-3p, miR-877-3p, miR-150-5p, and miR-15a-5p might be novel biomarkers for incipient DKD.
| S-EPMC5605810 | biostudies-literature
Project description:BackgroundDiabetic kidney disease (DKD) is a common and potentially fatal consequence of diabetes. Chronic renal failure or end-stage renal disease may result over time. Numerous studies have demonstrated the function of the microbiota in health and disease. The use of advanced urine culture techniques revealed the presence of resident microbiota in the urinary tract, undermining the idea of urine sterility. Studies have demonstrated that the urine microbiota is related with urological illnesses; nevertheless, the fundamental mechanisms by which the urinary microbiota influences the incidence and progression of DKD remain unclear. The purpose of this research was to describe key characteristics of the patients with DKD urinary microbiota in order to facilitate the development of diagnostic and therapeutic for DKD.MethodsWe evaluated the structure and composition of the microbiota extracted from urine samples taken from DKD patients (n = 19) and matched healthy controls (n = 15) using 16S rRNA gene sequencing. Meanwhile, serum metabolite profiles were compared using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Associations between clinical characteristics, urine microbiota, and serum metabolites were also examined. Finally, the interaction between urine microbiota and serum metabolites was clarified based on differential metabolite abundance analysis.ResultsThe findings indicated that the DKD had a distinct urinary microbiota from the healthy controls (HC). Taxonomic investigations indicated that the DKD microbiome had less alpha diversity than a control group. Proteobacteria and Acidobacteria phyla increased in the DKD, while Firmicutes and Bacteroidetes decreased significantly (P < 0.05). Acidobacteria was the most prevalent microbiota in the DKD, as determined by the Linear discriminant analysis Effect Size (LEfSe) plot. Changes in the urinary microbiota of DKD also had an effect on the makeup of metabolites. Short-chain fatty acids (SCFAs) and protein-bound uremic toxins (PBUTs) were shown to be specific. Then we discovered that arginine and proline metabolism was the primary mechanism involved in the regulation of diabetic kidney disease.ConclusionsThis study placed the urinary microbiota and serum metabolite of DKD patients into a functional framework and identified the most abundant microbiota in DKD (Proteobacteria and Acidobacteria). Arginine metabolites may have a major effect on DKD patients, which correlated with the progression of DKD.
| S-EPMC10382294 | biostudies-literature
Project description:BackgroundSeveral urinary biomarkers have good diagnostic value for diabetic kidney disease (DKD); however, the predictive value is limited with the use of single biomarkers. We investigated the clinical value of Luminex liquid suspension chip detection of several urinary biomarkers simultaneously.MethodsThe study included 737 patients: 585 with diabetes mellitus (DM) and 152 with DKD. Propensity score matching (PSM) of demographic and medical characteristics identified a subset of 78 patients (DM = 39, DKD = 39). Two Luminex liquid suspension chips were used to detect 11 urinary biomarkers according to their molecular weight and concentration. The biomarkers, including cystatin C (CysC), nephrin, epidermal growth factor (EGF), kidney injury molecule-1 (KIM-1), retinol-binding protein4 (RBP4), α1-microglobulin (α1-MG), β2-microglobulin (β2-MG), vitamin D binding protein (VDBP), tissue inhibitor of metalloproteinases-1 (TIMP-1), tumor necrosis factor receptor-1 (TNFR-1), and tumor necrosis factor receptor-2 (TNFR-2) were compared in the DM and DKD groups. The diagnostic values of single biomarkers and various biomarker combinations for early diagnosis of DKD were assessed using receiver operating characteristic (ROC) curve analysis.ResultsUrinary levels of VDBP, RBP4, and KIM-1 were markedly higher in the DKD group than in the DM group (p < 0.05), whereas the TIMP-1, TNFR-1, TNFR-2, α1-MG, β2-MG, CysC, nephrin, and EGF levels were not significantly different between the groups. RBP4, KIM-1, TNFR-2, and VDBP reached p < 0.01 in univariate analysis and were entered into the final analysis. VDBP had the highest AUC (0.780, p < 0.01), followed by RBP4 (0.711, p < 0.01), KIM-1 (0.640, p = 0.044), and TNFR-2 (0.615, p = 0.081). However, a combination of these four urinary biomarkers had the highest AUC (0.812), with a sensitivity of 0.742 and a specificity of 0.760.ConclusionsThe urinary levels of VDBP, RBP4, KIM-1, and TNFR-2 can be detected simultaneously using Luminex liquid suspension chip technology. The combination of these biomarkers, which reflect different mechanisms of kidney damage, had the highest diagnostic value for DKD. However, this finding should be explored further to understand the synergistic effects of these biomarkers.
| S-EPMC11369644 | biostudies-literature
Project description:BackgroundAs one of the most prevalent diagnostic indicators of diabetic kidney disease (DKD), albumin-to-creatinine ratio (ACR) shows considerably limited predictive power in clinical application. We analyzed microarray expression profiling of urine to seek for differentially expressed miRNAs for potential biomarkers of DKD.MethodsUrine samples from type 2 diabetes mellitus (T2DM) patients with (30 mg/g < ACR < 300 mg/g, DKD group) or without DKD (ACR < 30 mg/g, DM group) were collected for miRNA microarray analysis. The differentially expressed miRNAs were screened by bioinformatics analysis and validated by quantitative real-time PCR. Target genes of differentially expressed miRNAs were predicted in miRDB, Targetscan, and microRNA.org databases. We also conducted the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathways analysis to explore for potential mechanisms in DKD.ResultsNine miRNAs were down-regulated and seventeen miRNAs were up-regulated in DKD group, compared to DM group. The levels of miR-3137 and miR-4270 in DKD group were 0.670 ± 0.505 and 2.116 ± 1.762 times than those in DM group, respectively, showing great significance. A total of 1076 target genes were simultaneously predicted by miRDB, Targetscan, and microRNA.org databases. According to the GO analysis results, disorders of endomembrane system may be one of the major pathological changes in DKD. In addition, Rap 1 signaling pathway is also altered obviously in DKD, discovered by the KEGG analysis.ConclusionMiR-3137 and miR-4270 show the potential for urinary biomarkers of DKD. The pathological changes of DKD may be related to disorders of endomembrane system and alternation of Rap1 signaling pathway.
| S-EPMC7755759 | biostudies-literature
Project description:Urinary exosomal miRNAs can reflect the physiological and possibly pathophysiological state of cells lining the kidney and participate in the regulation of transcription and translation of proteins, which are playing an important role in the pathogenesis of diabetic kidney disease. In the present study, urine was collected from DM and DKD patients with a duration more than 10 years and urinary exosomal miRNA profiling was conducted in urinary exosomes obtained from three patients with type 2 diabetes (DM) and three patients with type 2 diabetic kidney disease (DKD) using Exiqon's microRNA arrays. In total, the expression of 14 miRNAs (miR-4491, miR-2117, miR-4507, miR-5088-5P, miR-1587, miR-219a-3p, miR-5091, miR-498, miR-4687-3p, miR-516b-5p, miR-4534, miR-1275, miR-5007-3p, and miR-4516) was up-regulated (>2-fold) in DKD patients compared to healthy controls and DM patients. We used qRT-PCR based analysis of these 14 miRNAs in urinary exosomes from 14 DKD to 14 DM patients in confirmation cohort, among which seven miRNAs were consistent with the microarray results. The expressions of miR-4534 and miR-516b-5p correlated with trace proteinuria levels in the confirmation cohort. In conclusion, it has been confirmed that the expression of urinary exosomal miRNA in patients with type 2 diabetes DKD has changed. Mir-4534 might affect the FoxO signaling pathway by targeting BNIP3, and is expected to become a new biomarker for the progression of type 2 DKD disease, which will provide further research on the pathogenesis of DKD.
| S-EPMC7484971 | biostudies-literature