Urine proteome analysis may allow noninvasive differential diagnosis of diabetic nephropathy

Self-Sustaining Triboelectric Nanosensors for Real-Time Urine Analysis in Smart Toilets

Healthcare has undergone a revolutionary shift with the advent of smart technologies, and smart toilets (STs) are among the innovative inventions offering non-invasive continuous health monitoring. The present technical challenges toward this development include limited sensitivity of integrated sensors, poor stability, slow response and the requirement external energy supply alongside manual sample collection. In this article, triboelectric nanosensor array (TENSA) is introduced featuring electrodes crafted from laser-induced 3D graphene with functional polymers like polystyrene, polyimide, and polycaprolactone for real-time urine analysis while generating 50 volts output via urine droplet-based triboelectrification. Though modulating interfacial double-layer capacitance, these sensors exhibit exceptional sensitivity and selectivity in detecting a broad spectrum of urinary biomarkers, including ions, glucose, and urea with a classification precision of 95% and concentration identification accuracy of up to 0.97 (R2), supported by artificial neural networks. Upon exposure to urine samples containing elevated levels of Na+, K+, and NH4 +, a notable decrease (ranging from 32% to 68%) is observed in output voltages. Conversely, urea induces an increase up to 13%. Experimental validation confirms the stability, robustness, reliability, and reproducibility of TENSA, representing a significant advancement in healthcare technology, offering the potential for improved disease management and prevention strategies.

Multi-omics analysis reveals the potential pathogenesis and therapeutic targets of diabetic kidney disease

Clinicians have long been interested in understanding the molecular basis of diabetic kidney disease (DKD)and its potential treatment targets. Its pathophysiology involves protein phosphorylation, one of the most recognizable post-transcriptional modifications, that can take part in many cellular functions and control different metabolic processes. In order to recognize the molecular and protein changes of DKD kidney, this study applied Tandem liquid chromatography-mass spectrometry (LC-MS/MS) and Next-Generation Sequencing, along with Tandem Mass Tags (TMT) labeling techniques to evaluate the mRNA, protein and modified phosphorylation sites between DKD mice and model ones. Based on Gene Ontology (GO) and KEGG pathway analyses of transcriptome and proteome, The molecular changes of DKD include accumulation of extracellular matrix, abnormally activated inflammatory microenvironment, oxidative stress and lipid metabolism disorders, leading to glomerulosclerosis and tubulointerstitial fibrosis. Oxidative stress has been emphasized as an important factor in DKD and progression to ESKD, which is directly related to podocyte injury, albuminuria and renal tubulointerstitial fibrosis. A histological study of phosphorylation further revealed that kinases were crucial. Three groups of studies have found that RAS signaling pathway, RAP1 signaling pathway, AMPK signaling pathway, PPAR signaling pathway and HIF-1 signaling pathway were crucial for the pathogenesis of DKD. Through this approach, it was discovered that targeting specific molecules, proteins, kinases and critical pathways could be a promising approach for treating DKD.

Diagnostic value of α1-MG and URBP in early diabetic renal impairment

Aims/Introduction: Diabetic kidney disease (DKD) is defined as diabetes with impaired renal function, elevated urinary albumin excretion, or both. DKD is one of the most common microvascular complications of diabetes and plays an important role in the cause of end-stage renal disease (ESRD). About 5% of people with type 2 diabetes (T2DM) already have kidney damage at the time they are diagnosed, but other triggers of renal insufficiency, such as obesity, hyperlipidemia, glomerular atherosclerosis are often present, making it difficult to define "diabetic kidney disease" or "diabetic nephropathy" precisely in epidemiology or clinical practice. Therefore, the aim of this study is to identify diabetic patients with CKD at an early stage, and evaluate the value of tubular injury markers including α1-microglobulin (α1-MG), β2-microglobulin (β2-MG), N-acetyl-beta-D-glucosaminidase (NAG) and Urinary retinol binding protein (URBP) in the development of diabetes to DKD. Materials and methods: We recruited a total of 182 hospitalized patients with T2DM in the First Affiliated Hospital of Zhengzhou University from February 2018 to April 2023. We collected basic clinical characteristics and laboratory biochemical parameters of the patients. Based on their levels of urinary albumin creatinine ratio (UACR) and glomerular filtration rate (GFR), patients were divided into DM group (UACR≤30 mg/g and eGFR≥90 mL/min/1.73 m2, n = 63) and DKD group (UACR>30 mg/g or eGFR<90 mL/min/1.73 m2, n = 119) excluding other causes of chronic kidney disease. We further developed diagnostic models to improve the ability to predict the risk of developing DKD by screening potential risk factors using univariate and multivariate logistic regression analysis. Calibration plots and curve analysis were used to validate the model and clinical usefulness. Next, we screened patients with relatively normal estimated glomerular filtration rate (eGFR) (≥90 mL/min/1.73 m2) to investigate whether tubular injury markers could accurately predict the risk of DKD in patients with normal renal function. We defined the rate of GFR decline as a prognostic indicator of renal function in patients and collected the information of the re-hospitalized DKD patients to determine whether the relevant indicators had an impact on the renal prognosis. Results: The patients with DKD had higher levels of tubular injury markers than patients with DM. URBP, α1-MG, eGFR were statistically different in both univariate and multivariate logistic regression analyses and displayed great predictive power after modeling with an area under curve of 0.987. The calibration curve showed medium agreement. Decision curve showed it would add more net benefits for clinical decision. After adjusting eGFR and serum creatinine (Scr), URBP was demonstrated to be associated with early renal function impairment. Conclusion: Tubular injury markers play an important role in early diabetic renal function impairment.

Insulin and the kidneys: a contemporary view on the molecular basis

Insulin is a hormone that is composed of 51 amino acids and structurally organized as a hexamer comprising three heterodimers. Insulin is the central hormone involved in the control of glucose and lipid metabolism, aiding in processes such as body homeostasis and cell growth. Insulin is synthesized as a large preprohormone and has a leader sequence or signal peptide that appears to be responsible for transport to the endoplasmic reticulum membranes. The interaction of insulin with the kidneys is a dynamic and multicenter process, as it acts in multiple sites throughout the nephron. Insulin acts on a range of tissues, from the glomerulus to the renal tubule, by modulating different functions such as glomerular filtration, gluconeogenesis, natriuresis, glucose uptake, regulation of ion transport, and the prevention of apoptosis. On the other hand, there is sufficient evidence showing the insulin receptor's involvement in renal functions and its responsibility for the regulation of glucose homeostasis, which enables us to understand its contribution to the insulin resistance phenomenon and its association with the progression of diabetic kidney disease.

Early renal structural changes and potential biomarkers in diabetic nephropathy

Diabetic nephropathy is one of the most serious microvascular complications of diabetes mellitus, with increasing prevalence and mortality. Currently, renal function is assessed clinically using albumin excretion rate and glomerular filtration rate. But before the appearance of micro-albumin, the glomerular structure has been severely damaged. Glomerular filtration rate based on serum creatinine is a certain underestimate of renal status. Early diagnosis of diabetic nephropathy has an important role in improving kidney function and delaying disease progression with drugs. There is an urgent need for biomarkers that can characterize the structural changes associated with the kidney. In this review, we focus on the early glomerular and tubular structural alterations, with a detailed description of the glomerular injury markers SMAD1 and Podocalyxin, and the tubular injury markers NGAL, Netrin-1, and L-FABP in the context of diabetic nephropathy. We have summarized the currently studied protein markers and performed bioprocess analysis. Also, a brief review of proteomic and scRNA-seq method in the search of diabetic nephropathy.

Prevalence and Prognostic Relevance of Isolated Tubular Dysfunction in Patients With Acute Heart Failure

BACKGROUND

Renal dysfunction includes glomerular dysfunction (GD) and tubular dysfunction (TD); however, there is limited information regarding the prevalence, coexistence, and prognostic relevance of TD and GD among patients with acute heart failure (AHF).

METHODS AND RESULTS

This study reviewed 489 patients with AHF who had undergone testing at the time of their admission to identify GD (estimated glomerular filtration rate <60 mL/min/1.73 m2) and TD (urinary β-2-microglobulin ≥300 µg/gCr). Patients were grouped according to the presence/absence of GD and TD as having neither condition (n=116), isolated TD (n=101), isolated GD (n=83), or coexisting GD plus TD (n=189). During a median follow up of 466 days (interquartile range: 170-871 days), 107 deaths were observed. Kaplan-Meier curve analysis revealed that, relative to the absence of a GD and TD group, higher mortality rates were observed in the groups with isolated TD, isolated GD, and coexisting GD plus TD (log-rank P<0.001). Similarly, the adjusted Cox regression analyses revealed that significantly higher risks of mortality were associated with isolated TD, isolated GD, and coexisting GD plus TD. Moreover, isolated GD and isolated TD were both independently associated with increased risks of all-cause mortality.

CONCLUSIONS

As a significant proportion of patients with AHF had isolated TD and an increased risk of mortality, patients with AHF should be screened for TD even if they do not have GD.

Effects of Smoking on Diabetic Nephropathy

Diabetes is a systemic metabolic disease with serious complications that cause significant stress on the healthcare system. Diabetic kidney disease is the primary cause of end stage renal disease globally and its progression is accelerated by various factors. Another major healthcare hazard is tobacco consumption and smoking has deleterious effects on renal physiology. Prominent factors are defined as sympathetic activity, atherosclerosis, oxidative stress and dyslipidemia. This review aims to enlighten the mechanism underlying the cumulative negative effect of simultaneous exposure to hyperglycemia and nicotine.

BoxCar increases the depth and reproducibility of diabetic urinary proteome analysis

PURPOSE

Mass spectrometry-based proteomics performs well in high throughput detection of urinary proteins. Nonetheless, protein identification depth and reproducibility remain the challenges in diabetic urinary proteome with high complexity and broad dynamic range, especially for low-abundant proteins. As a new data acquisition strategy, the BoxCar method was reported to benefit for low-abundant protein identification. Whether it is propitious to diabetic samples with high dynamic range proteomes has not been discussed yet. We aimed to apply BoxCar method to diabetic urine sample analysis, and to compare it with standard data dependent acquisition (DDA) method on protein identification in detail.

EXPERIMENTAL DESIGN

We performed seven technical replicates analysis on two urine samples from healthy individuals and diabetic patients to evaluate protein detection of BoxCar and standard DDA methods on single sample. Further comparison of two methods was made on multiple diabetic urine samples.

RESULTS

BoxCar could increase over 20% of identified proteins and performed better quantitative reproducibility than standard DDA method either in single or multiple diabetic urinary samples. BoxCar also improved the detection of low-abundant proteins. Functional enrichment analysis of normal albuminuria or microalbuminuria samples indicated that BoxCar acquired more diabetes-related biological information.

CONCLUSIONS AND CLINICAL RELEVANCE

The study demonstrates that BoxCar could enhance the depth and reproducibility in diabetic urinary proteome analysis, which provides reference for mass spectrometry approach selection in clinical urinary proteomic research.

Global Epidemiology, Health Outcomes, and Treatment Options for Patients With Type 2 Diabetes and Kidney Failure

The burden of type 2 diabetes and related complications has steadily increased over the last few decades and is one of the foremost global public health threats in the 21st century. Diabetes is one of the leading causes of chronic kidney disease and kidney failure and is an important contributor to the cardiovascular morbidity and mortality in this population. In addition, up to one in three patients who have received kidney transplants develop post-transplant diabetes, but the management of this common complication continues to pose a significant challenge for clinicians. In this review, we will describe the global prevalence and temporal trend of kidney failure attributed to diabetes mellitus in both developing and developed countries. We will examine the survival differences between treated kidney failure patients with and without type 2 diabetes, focusing on the survival differences in those on maintenance dialysis or have received kidney transplants. With the increased availability of novel hypoglycemic agents, we will address the potential impacts of these novel agents in patients with diabetes and kidney failure and in those who have developed post-transplant diabetes.

Advances in Current Diabetes Proteomics: From the Perspectives of Label- free Quantification and Biomarker Selection

BACKGROUND

Due to its prevalence and negative impacts on both the economy and society, the diabetes mellitus (DM) has emerged as a worldwide concern. In light of this, the label-free quantification (LFQ) proteomics and diabetic marker selection methods have been applied to elucidate the underlying mechanisms associated with insulin resistance, explore novel protein biomarkers, and discover innovative therapeutic protein targets.

OBJECTIVE

The purpose of this manuscript is to review and analyze the recent computational advances and development of label-free quantification and diabetic marker selection in diabetes proteomics.

METHODS

Web of Science database, PubMed database and Google Scholar were utilized for searching label-free quantification, computational advances, feature selection and diabetes proteomics.

RESULTS

In this study, we systematically review the computational advances of label-free quantification and diabetic marker selection methods which were applied to get the understanding of DM pathological mechanisms. Firstly, different popular quantification measurements and proteomic quantification software tools which have been applied to the diabetes studies are comprehensively discussed. Secondly, a number of popular manipulation methods including transformation, pretreatment (centering, scaling, and normalization), missing value imputation methods and a variety of popular feature selection techniques applied to diabetes proteomic data are overviewed with objective evaluation on their advantages and disadvantages. Finally, the guidelines for the efficient use of the computationbased LFQ technology and feature selection methods in diabetes proteomics are proposed.

CONCLUSION

In summary, this review provides guidelines for researchers who will engage in proteomics biomarker discovery and by properly applying these proteomic computational advances, more reliable therapeutic targets will be found in the field of diabetes mellitus.

Reckoning the Dearth of Bioinformatics in the Arena of Diabetic Nephropathy (DN)—Need to Improvise

Diabetic nephropathy (DN) is a recent rising concern amongst diabetics and diabetologist. Characterized by abnormal renal function and ending in total loss of kidney function, this is becoming a lurking danger for the ever increasing population of diabetics. This review touches upon the intensity of this complication and briefly reviews the role of bioinformatics in the area of diabetes. The advances made in the area of DN using proteomic approaches are presented. Compared to the enumerable inputs observed through the use of bioinformatics resources in the area of proteomics and even diabetes, the existing scenario of skeletal application of bioinformatics advances to DN is highlighted and the reasons behind this discussed. As this review highlights, almost none of the well-established tools that have brought breakthroughs in proteomic research have been applied into DN. Laborious, voluminous, cost expensive and time-consuming methodologies and advances in diagnostics and biomarker discovery promised through beckoning bioinformatics mechanistic approaches to improvise DN research and achieve breakthroughs. This review is expected to sensitize the researchers to fill in this gap, exploiting the available inputs from bioinformatics resources.

Roles of kininogen-1, basement membrane specific heparan sulfate proteoglycan core protein, and roundabout homolog 4 as potential urinary protein biomarkers in diabetic nephropathy

Diabetic nephropathy, a major complication of diabetes mellitus (DM), is increasing worldwide and the large majority of patients have type 2 DM. Microalbuminuria has been used as a diagnostic marker of diabetic nephropathy. But owing to its insufficient sensitivity and specificity, other biomarkers are being sought. In addition, the pathophysiology of diabetic nephropathy is not fully understood and declines in renal function occur even without microalbuminuria. In this study, we investigated urinary proteins from three study groups (controls, and type 2 diabetic subjects with or without microalbuminuria). Non-targeted label-free Nano-LC QTOF analysis was conducted to discover underlying mechanisms and protein networks, and targeted label-free Nano-LC QTOF with SWATH was performed to qualify discovered protein candidates. Twenty-eight proteins were identified as candidates and functionally analyzed via String DB, gene ontology and pathway analysis. Four predictive mechanisms were analyzed: i) response to stimulus, ii) platelet activation, signaling and aggregation, iii) ECM-receptor interaction, and iv) angiogenesis. These mechanisms can provoke kidney dysfunction in type 2 diabetic patients via endothelial cell damage and glomerulus structural alteration. Based on these analyses, three proteins (kininogen-1, basement membrane-specific heparan sulfate proteoglycan core protein, and roundabout homolog 4) were proposed for further study as potential biomarkers. Our findings provide insights that may improve methods for both prevention and diagnosis of diabetic nephropathy.

Urinary miRNA-27b-3p and miRNA-1228-3p correlate with the progression of Kidney Fibrosis in Diabetic Nephropathy

Diabetic Nephropathy (DN) is a chronic complication of diabetes and the primary cause of end stage renal disease. Differential diagnosis for DN requires invasive histological investigation, thus there is need for non-invasive biomarkers to discriminate among different histological lesions in diabetic patients. With the aim to identify a pattern of differentially expressed miRNAs in kidney biopsies of DN patients, we assayed miRNA expression in kidney biopsies from DN patients, diabetic patients with membranous nephropathy and patients with normal histology. Nine miRNAs were differentially expressed among the three groups, and 2 miRNAs (miR-27b-3p and miR-1228-3p) showed interaction with an ubiquitin-conjugating E2 enzyme variant (UBE2v1). UBE2v1 mediates the formation of lysine 63-linked ubiquitin chains, a mechanism we previously showed as involved in DN kidney fibrosis. Both miRNAs were validated as down-regulated in biopsies and urines of DN patients, possibly affected by DNA methylation. Interestingly, the urinary levels of both miRNAs could also discriminate among different degrees of renal fibrosis. Finally, we showed that the combined urinary expression of both miRNAs was also able to discriminate DN patients from other glomerulonephritides in diabetic patients. In conclusion we identified two miRNAs potentially useful as candidate biomarkers of tubular-interstitial fibrosis in diabetic patients with DN.

Clinical Proteomics in Kidney Disease: From Discovery to Clinical Application

Proteome analysis has been applied in multiple studies in the context of chronic kidney disease, aiming at improving our knowledge on the molecular pathophysiology of the disease. The approach is generally based on the hypothesis that proteins are key in maintaining kidney function, and disease is a clinical consequence of a significant change of the protein level. Knowledge on critical proteins and their alteration in disease should in turn enable identification of ideal biomarkers that could guide patient management. In addition, all drugs currently employed target proteins. Hence, proteome analysis also promises to enable identifying the best suited therapeutic target, and, in combination with biomarkers, could be used as the rationale basis for personalized intervention. To assess the current status of proteome analysis in the context of CKD, we present the results of a systematic review, of up-to-date scientific research, and give an outlook on the developments that can be expected in near future. Based on the current literature, proteome analysis has already seen implementation in the management of CKD patients, and it is expected that this approach, also supported by the positive results generated to date, will see advanced high-throughput application.

Histological Evidence of Diabetic Kidney Disease Precede Clinical Diagnosis

BACKGROUND

In the absence of a histological diagnosis, persistent albuminuria is globally accepted as the main diagnostic criteria for diabetic kidney disease (DKD).

METHODS

In the present retrospective study, we evaluated data from an Italian cohort of 42 deceased diabetic donors (mainly with type 2 diabetes). Using the kidney biopsies obtained at the time of donation to evaluate single or double allocation based on Karpinski score, we determined the prevalence of histological lesions attributable to diabetes.

RESULTS

All 42 donors presented with proteinuria in the normal range and an estimated glomerular filtration rate (eGFR) (chronic kidney disease [CKD]-EPI) >60 mL/min/1.73 m2. A kidney biopsy was available for 36 patients; of these, one was not interpretable and 32 showed histopathological lesions consistent with DKD and encompassing all histological classes. Thus, we found a relatively high proportion of histologically proven DKD that had been clinically undiagnosed, as none of the patient had significant proteinuria and eGFR <60 mL/min/1.73 m2.

CONCLUSIONS

The data we present here support the need to implement routine kidney biopsies in normoalbuminuric diabetic subjects in the early stages of CKD. Such strategy may help to improve risk stratification in diabetic patients and guide therapeutic decisions during the early stages of the disease.

Proteomic and metabolomic approaches in the search for biomarkers in chronic kidney disease

Chronic kidney disease (CKD) is an aging-related disorder that represents a major global public health burden. Current biochemical biomarkers, such as serum creatinine and urinary albumin, have important limitations when used to identify the earliest indication of CKD or in tracking the progression to more advanced CKD. These issues underline the importance of finding and testing new molecular biomarkers that are capable of successfully meeting this clinical need. The measurement of changes in nature and/or levels of proteins and metabolites in biological samples from patients provide insights into pathophysiological processes. Proteomic and metabolomic techniques provide opportunities to record dynamic chemical signatures in patients over time. This review article presents an overview of the recent developments in the fields of metabolomics and proteomics in relation to CKD. Among the many different proteomic biomarkers proposed, there is particular interest in the CKD273 classifier, a urinary proteome biomarker reported to predict CKD progression and with implementation potential. Other individual non-invasive peptidomic biomarkers that are potentially relevant for CKD detection include type 1 collagen, uromodulin and mucin-1. Despite the limited sample sizes and variability of the metabolomics studies, some metabolites such as trimethylamine N-oxide, kynurenine and citrulline stand out as potential biomarkers in CKD.

Evaluation of urinary biomarkers for prediction of diabetic kidney disease: a propensity score matching analysis

BACKGROUND

The aim of this study was to evaluate the diagnostic value of six urinary biomarkers for prediction of diabetic kidney disease (DKD).

METHODS

The cross-sectional study recruited 1053 hospitalized patients with type 2 diabetes mellitus (T2DM), who were categorized into the diabetes mellitus (DM) with normoalbuminuria (NA) group (n = 753) and DKD group (n = 300) according to 24-h urinary albumin excretion rate (24-h UAE). Data on the levels of six studied urinary biomarkers [transferrin (TF), immunoglobulin G (IgG), retinol-binding protein (RBP), β-galactosidase (GAL), N-acetyl-beta-glucosaminidase (NAG), and β2-microglobulin (β2MG)] were obtained. The propensity score matching (PSM) method was applied to eliminate the influences of confounding variables.

RESULTS

Patients with DKD had higher levels of all six urinary biomarkers. All indicators demonstrated significantly increased risk of DKD, except for GAL and β2MG. Single RBP yielded the greatest area under the curve (AUC) value of 0.920 compared with the other five markers, followed by TF (0.867) and IgG (0.867). However, GAL, NAG, and β2MG were shown to have a weak prognostic ability. The diagnostic values of the different combinations were not superior to the single RBP.

CONCLUSIONS

RBP, TF, and IgG could be used as reliable or good predictors of DKD. The combined use of these biomarkers did not improve DKD detection.

Renal Histology in Diabetic Patients

Background:

The diagnosis of diabetic nephropathy is based on the course of clinical manifestations and renal biopsy. Renal biopsy is usually performed in patients with atypical presentations.

Objectives:

This study was performed to analyze various renal histopathological lesions in diabetic patients and to establish a clinicopathological correlation.

Materials and Methods:

In this retrospective study, the authors analyzed renal histology of 40 patients with type 2 diabetes mellitus who presented with atypical features of diabetic renal involvement and underwent renal biopsy at the Military Hospital Mohammed V, Rabat, Morocco, between January 2008 and December 2016.

Results:

About 60% of the patients had isolated diabetic nephropathy, 35% had isolated nondiabetic renal diseases and 5% had both. Patients with nondiabetic renal diseases had significantly higher hematuria (P = 0.02), shorter duration of diabetes (P = 0.009), higher mean estimated glomerular filtration rate (P = 0.04) and lower prevalence of diabetic retinopathy (P < 0.001). The most common histological lesion in patients with nondiabetic renal diseases was IgA nephropathy (25%). In patients with diabetic nephropathy, the most common histological class was Class III (42.3%). Furthermore, higher histological classes were associated with lower estimated glomerular filtration rate (P < 0.001) as well as higher prevalence of diabetic retinopathy (P = 0.009) and nephrotic proteinuria (P = 0.04).

Conclusions:

This study found that in Rabat, Morocco, the most common histopathological lesion in patients with diabetes was diabetic nephropathy. Hematuria, shorter duration of diabetes, higher mean estimated glomerular filtration rate and lower prevalence of diabetic retinopathy were reported among those with nondiabetic renal diseases. These findings are in accord with that of studies from other countries. However, large sample size and long-term follow-up clinical studies are needed to demonstrate the renal pathological implications and renal outcomes in type 2 diabetes mellitus patients with renal involvement.

Differential proteome analysis of diabetes mellitus type 2 and its pathophysiological complications

The prevalence of Diabetes Mellitus Type 2 (DM 2) is increasing every passing year due to some global changes in lifestyles of people. The exact underlying mechanisms of the progression of this disease are not yet known. However recent advances in the combined omics more particularly in proteomics and genomics have opened a gateway towards the understanding of predetermined genetic factors, progression, complications and treatment of this disease. Here we shall review the recent advances in proteomics that have led to an early and better diagnostic approaches in controlling DM 2 more importantly the comparison of structural and functional protein biomarkers that are modified in the diseased state. By applying these advanced and promising proteomic strategies with bioinformatics applications and bio-statistical tools the prevalence of DM 2 and its associated disorders i-e nephropathy and retinopathy are expected to be controlled.

Urine proteome analysis by C18 plate-matrix-assisted laser desorption/ionization time-of-flight mass spectrometry allows noninvasive differential diagnosis and prediction of diabetic nephropathy

Diabetic nephropathy (DN) is one of the most common complications in diabetic patients. New noninvasive markers are still needed for the early detection of DN before identifiable alternations in kidney function or urine albumin excretion occurs. A C18 plate and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) were used to compare the urinary protein profiles of 238 subjects from the following 4 groups: patients with type 2 diabetic (T2D) with microalbuminuria, patients with DM without micro- or macroalbuminuria, patients with micro- or macroalbuminuria due to nondiabetic disease, and healthy controls. β2-microglobulin (B2M) and Clara-cell protein (CC16) were found to be highly released in the urine of patients with proteinuria due to nondiabetic or diabetic diseases. In differentiating nephropathy from healthy subject, the B2M and CC16 markers have a combined sensitivity and specificity of 77.3% and 91.8%, respectively. In distinguishing T2D with microalbuminuria from T2D patients, the combined markers have sensitivity and specificity of 66% and 73%, respectively. The predictive ability of B2M and CC16 for early renal functional decline (ERFD) was validated in 125 T2D patients with a follow-up times. The odds ratio (OR) of combined B2M and CC16 markers for developing ERFD was 7.59 (95% CI: 1.97-29.24). The detection of B2M and CC16 with the C18 plate-MALDI-TOF MS approach could be an attractive and practical assay for rapid diagnosis of nephropathy in nondiabetic/diabetic patients and as a predictor of ERFD among T2D patients who had not manifested significant kidney disease at baseline.

Urinary RKIP/p-RKIP is a potential diagnostic and prognostic marker of clear cell renal cell carcinoma

Clear cell Renal Cell Carcinoma (ccRCC) causes over 13,000 deaths each year, and about 20,000 new cases/year in Europe. In most cases, the causes are unknown and, most importantly, there are no reliable biomarkers for the diagnosis and prognosis of this disease. The search for sensitive biomarkers for early diagnosis and prognosis of clear cell Renal Cell Carcinoma (ccRCC) is currently a fast growing field. We carried out proteomics analysis of 93 urinary samples of healthy subjects (HS) and patients affected by ccRCC, prostate cancer (PCa) and chronic kidney disease (CKD), that was able to successfully distinguish each group.

The most significant candidate biomarker was identified by mass spectrometry as Raf Kinase Inhibitor Protein (RKIP), a key regulator of cell signaling, already described in several cancer types as a metastasis suppressor. By combining ELISA, immunoblotting and tissue microarray, we demonstrated that, in ccRCC, urinary excretion of RKIP and its phosphorylated form (p-RKIP) reflected the tissue expression of these putative biomarkers. Baseline urinary RKIP, evaluated in an independent cohort of 56 ccRCC patients and 28 HS, successfully distinguished both groups and, most importantly, a cut-off value of 10 ng/mg/g Pr/uCr enabled a highly accurate prediction of Cancer-specific survival and Progression-free survival. Furthermore, p-RKIP was totally undetectable in both tissue and urine samples of ccRCC, showing a great potential for diagnostics purposes.

Our data indicate that urinary RKIP encompasses both the unphosphorylated and the phosphorylated form and that their combined evaluation can help in the diagnosis and prognosis of ccRCC.

Role of Kidney Biopsies for Biomarker Discovery in Diabetic Kidney Disease

Although estimated glomerular filtration rate and albuminuria are well-established biomarkers of diabetic kidney disease (DKD), additional biomarkers are needed, especially for the early stages of the disease when both albuminuria and estimated glomerular filtration rate may still be in the normal range and are less helpful for identifying those at risk of progression. Traditional biomarker studies for early DKD are challenging because of a lack of good early clinical end points, and most rely on changes in existing imprecise biomarkers to assess the value of new biomarkers. There are well-characterized changes in kidney structure, however, that are highly correlated with kidney function, always precede the clinical findings of DKD and, at preclinical stages, predict DKD progression. These structural parameters may thus serve as clinically useful end points for identifying new biomarkers of early DKD. In addition, investigators are analyzing tissue transcriptomic data to identify pathways involved in early DKD which may have associated candidate biomarkers measurable in blood or urine, and differentially expressed microRNAs and epigenetic modifications in kidney tissue are beginning to yield important observations which may be useful in identifying new clinically useful biomarkers. This review examines the emerging literature on the use of kidney tissue in biomarker discovery in DKD.

Ubiquitin Urine Levels in Burn Patients

The objective of this study was to determine whether urine ubiquitin levels are elevated after burns and to assess whether urine ubiquitin could be useful as a noninvasive biomarker for burn patients. Forty burn patients (%TBSA: 20 ± 22; modified Baux scores: 73 ± 26) were included (control: 11 volunteers). Urine was collected in 2-hour intervals for 72 hours, followed by 12-hour intervals until discharge from the intensive care unit. Ubiquitin concentrations were analyzed by enzyme linked immunosorbent assay and Western blot. Total protein was determined with a Bradford assay. Patient characteristics and clinical parameters were documented. Urine ubiquitin concentrations, renal ubiquitin excretion, and excretion rates were correlated with patient characteristics and outcomes. Initial urine ubiquitin concentrations were 362 ± 575 ng/ml in patients and 14 ± 18 ng/ml in volunteers (P < .01). Renal ubiquitin excretion on day 1 was 292.6 ± 510.8 μg/24 hr and 21 ± 27 μg/24 hr in volunteers (P < .01). Initial ubiquitin concentrations correlated with modified Baux scores (r = .46; P = .02). Ubiquitin levels peaked at day 6 postburn, whereas total protein concentrations and serum creatinine levels remained within the normal range. Total renal ubiquitin excretion and excretion rates were higher in patients with %TBSA ≥20 than with %TBSA <20, in patients who developed sepsis/multiple organ failure than in patients without these complications and in nonsurvivors vs survivors. These data suggest that ubiquitin urine levels are significantly increased after burns. Renal ubiquitin excretion and/or excretion rates are associated with %TBSA, sepsis/multiple organ failure, and mortality. Although these findings may explain previous correlations between systemic ubiquitin levels and outcomes after burns, the large variability of ubiquitin urine levels suggests that urine ubiquitin will not be useful as a noninvasive disease biomarker.

Hidden targets of ubiquitin proteasome system: To prevent diabetic nephropathy

Diabetic nephropathy (DN) is the major cause of end stage renal failure. Although, several therapeutic targets have emerged to prevent the progression of DN, the number of people with DN still continues to rise worldwide, suggesting an urgent need of novel targets to prevent DN completely. Currently, the role of ubiquitin proteasome system (UPS) has been highlighted in the pathogenesis and progression of various diseases like obesity, insulin resistance, atherosclerosis, cancers, neurodegerative disorders and including secondary complications of diabetes. UPS mainly involves in protein homeostatis through ubiquitination (post translational modification) and proteasomal degradation of various proteins. Ubiquitination, not only involves in proteasomal degradation, but also directs the substrate proteins to participate in multitude of cell signalling pathways. However, very little is known about ubiquitination and UPS in the progression of DN. This review mainly focuses on UPS and its components including E2 conjugating enzymes, E3 ligases and deubiquitinases (DUBs) in the development of DN and thus may help us to find novel therapeutic targets with in UPS to prevent DN completely in future.

Urinary Excretion of Kidney Aquaporins as Possible Diagnostic Biomarker of Diabetic Nephropathy

Diabetic nephropathy (DN) is a microangiopathic complication of diabetes mellitus (DM) affecting one-third of diabetic patients. The large variability in the clinical presentation of renal involvement in patients with DM makes kidney biopsy a prerequisite for a correct diagnosis. However, renal biopsy is an invasive procedure associated with risk of major complications. Numerous studies aimed to identify a noninvasive biomarker of DN but, so far, none of these is considered to be sufficiently specific and sensitive. Water channel aquaporins (AQPs), expressed at the plasma membrane of epithelial tubular cells, are often dysregulated during DN. In this work, we analyzed the urine excretion of AQP5 and AQP2 (uAQP5 and uAQP2), via exosomes, in 35 diabetic patients: 12 normoalbuminuric with normal renal function (DM), 11 with proteinuric nondiabetic nephropathy (NDN), and 12 with histological diagnosis and classification of DN. ELISA and WB analysis independently showed that uAQP5 was significantly increased in DN patients. Interestingly, linear regression analysis showed a positive correlation between uAQP5 and the histological class of DN. The same analysis, focusing on uAQP2, showed comparable results. Taken together, these data suggest a possible use of AQP5 and AQP2 as novel noninvasive biomarkers to help in classifying the clinical stage of DN.

Urinary Proteomics for Diagnosis and Monitoring of Diabetic Nephropathy

The last decade has seen a surge in publications describing novel biomarkers for early detection of diabetic nephropathy (DN), but as yet none have outperformed albuminuria in well-designed prospective studies. This is partially attributable to our incomplete understanding of the many complex interrelated mechanisms underlying DN development, a heterogeneous process unlikely to be captured by a single biomarker. Proteomics offers the advantage of simultaneously analysing the entire protein content of a biological sample, and the technique has gained attention as a potential tool for a more accurate diagnosis of disease at an earlier stage as well as a means by which to unravel the pathogenesis of complex diseases such as DN using an untargeted approach. This review will discuss the potential of proteomics as both a clinical and research tool, evaluating exploratory work in animal models as well as diagnostic potential in human subjects.

Lysine 63 ubiquitination is involved in the progression of tubular damage in diabetic nephropathy

The purpose of our study was to evaluate how hyperglycemia (HG) influences Lys63 protein ubiquitination and its involvement in tubular damage and fibrosis in diabetic nephropathy (DN). Gene and protein expression of UBE2v1, a ubiquitin-conjugating E2-enzyme variant that mediates Lys63-linked ubiquitination, and Lys63-ubiquitinated proteins increased in HK2 tubular cells under HG. Matrix-assisted laser desorption/ionization-time of flight/tandem mass spectrometry identified 30 Lys63-ubiquitinated proteins, mainly involved in cellular organization, such as β-actin, whose Lys63 ubiquitination increased under HG, leading to cytoskeleton disorganization. This effect was reversed by the inhibitor of the Ubc13/UBE2v1 complex NSC697923. Western blot analysis confirmed that UBE2v1 silencing in HK2 under HG, restored Lys63-β-actin ubiquitination levels to the basal condition. Immunohistochemistry on patients with type 2 diabetic (T2D) revealed an increase in UBE2v1- and Lys63-ubiquitinated proteins, particularly in kidneys of patients with DN compared with control kidneys and other nondiabetic renal diseases, such as membranous nephropathy. Increased Lys63 ubiquitination both in vivo in patients with DN and in vitro, correlated with α-SMA expression, whereas UBE2v1 silencing reduced HG-induced α-SMA protein levels, returning them to basal expression. In conclusion, UBE2v1- and Lys63-ubiquitinated proteins increase in vitro under HG, as well as in vivo in T2D, is augmented in patients with DN, and may affect cytoskeleton organization and influence epithelial-to-mesenchymal transition. This process may drive the progression of tubular damage and interstitial fibrosis in patients with DN.-Pontrelli, P., Conserva, F., Papale, M., Oranger, A., Barozzino, M., Vocino, G., Rochetti, M. T., Gigante, M., Castellano, G., Rossini, M., Simone, S., Laviola, L., Giorgino, F., Grandaliano, G., Di Paolo, S., Gesualdo, L. Lysine 63 ubiquitination is involved in the progression of tubular damage in diabetic nephropathy.

Low molecular weight fucoidan modulates P-selectin and alleviates diabetic nephropathy

Diabetic nephropathy (DN) is a serious microvascular complication that can lead to chronic and end-stage renal failure. It is understood that inflammation is associated with the onset and process of DN. Low molecular weight fucoidan (LMWF) isolated from Saccharina japonica has anti-inflammatory properties. Therefore, this study aimed to explore the mechanism of LMWF in DN model induced by streptozotocin. The biochemical indices levels showed LMWF reduced the DN diagnostic indices to protect renal function. The HE stained sections exhibited LMWF protected normal morphological structures and reduced inflammatory cell infiltration in the kidneys of DN rats. Furthermore, the levels of P-selectin and selectin-dependent inflammatory cytokines resulting from LMWF were obviously decreased at both the transcriptional and protein levels. Thus, our results found that LMWF protected the renal function in DN rats and alleviated inflammation through the modulation of P-selectin and inflammatory cytokines. LMWF may have therapeutic potential against DN.

Proteomics for prediction of disease progression and response to therapy in diabetic kidney disease

The past decade has resulted in multiple new findings of potential proteomic biomarkers of diabetic kidney disease (DKD). Many of these biomarkers reflect an important role in the (patho)physiology and biological processes of DKD. Situations in which proteomics could be applied in clinical practice include the identification of individuals at risk of progressive kidney disease and those who would respond well to treatment, in order to tailor therapy for those at highest risk. However, while many proteomic biomarkers have been discovered, and even found to be predictive, most lack rigorous external validation in sufficiently powered studies with renal endpoints. Moreover, studies assessing short-term changes in the proteome for therapy-monitoring purposes are lacking. Collaborations between academia and industry and enhanced interactions with regulatory agencies are needed to design new, sufficiently powered studies to implement proteomics in clinical practice.

Urinary Markers of Tubular Injury in Early Diabetic Nephropathy

Diabetic nephropathy (DN) is a common and serious complication of diabetes associated with adverse outcomes of renal failure, cardiovascular disease, and premature mortality. Early and accurate identification of DN is therefore of critical importance to improve patient outcomes. Albuminuria, a marker of glomerular involvement in early renal damage, cannot always detect early DN. Thus, more sensitive and specific markers in addition to albuminuria are needed to predict the early onset and progression of DN. Tubular injury, as shown by the detection of tubular injury markers in the urine, is a critical component of the early course of DN. These urinary tubular markers may increase in diabetic patients, even before diagnosis of microalbuminuria representing early markers of normoalbuminuric DN. In this review we summarized some new and important urinary markers of tubular injury, such as neutrophil gelatinase associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1), liver-type fatty acid binding protein (L-FABP), N-acetyl-beta-glucosaminidase (NAG), alpha-1 microglobulin (A1M), beta 2-microglobulin (B2-M), and retinol binding protein (RBP) associated with early DN.

A Systems Biology Overview on Human Diabetic Nephropathy: From Genetic Susceptibility to Post-Transcriptional and Post-Translational Modifications

Diabetic nephropathy (DN), a microvascular complication occurring in approximately 20-40% of patients with type 2 diabetes mellitus (T2DM), is characterized by the progressive impairment of glomerular filtration and the development of Kimmelstiel-Wilson lesions leading to end-stage renal failure (ESRD). The causes and molecular mechanisms mediating the onset of T2DM chronic complications are yet sketchy and it is not clear why disease progression occurs only in some patients. We performed a systematic analysis of the most relevant studies investigating genetic susceptibility and specific transcriptomic, epigenetic, proteomic, and metabolomic patterns in order to summarize the most significant traits associated with the disease onset and progression. The picture that emerges is complex and fascinating as it includes the regulation/dysregulation of numerous biological processes, converging toward the activation of inflammatory processes, oxidative stress, remodeling of cellular function and morphology, and disturbance of metabolic pathways. The growing interest in the characterization of protein post-translational modifications and the importance of handling large datasets using a systems biology approach are also discussed.

Differential urinary glycoproteome analysis of type 2 diabetic nephropathy using 2D-LC-MS/MS and iTRAQ quantification

Background

Diabetic nephropathy (DN) is the leading cause of chronic kidney failure and end-stage kidney disease. More accurate and non-invasive test for the diagnosis and monitoring the progression of DN is urgently needed for the better care of such patients.

Methods

In this study we utilized urinary glycoproteome to discover the differential proteins during the course of type 2 DN. The urinary glycoproteins from normal controls, normalbuminuira, microalbuminura, and macroalbuminuria patients were enriched by concanavalin A (ConA) and analyzed by 2DLC/MS/MS and isobaric tags for relative and absolute quantitation quantification.

Results

A total of 478 proteins were identified and 408 were annotated as N-linked glycoproteins. A total of 72, 107 and 123 differential proteins were identified in normalbuminuria, microalbuminuria and macroalbuminuria, respectively. By bioinformatics analysis, in normalbuminruia state, cell proliferation and cell movement were activated, which might reflect the compensatory phase during the disease development. In micro- and macro-albuminuria, cell death and apoptosis was activated, which might reflect the de-compensatory phase. Pathway analysis showed acute phase proteins, the member of high density lipoprotein and low density lipoprotein proteins were changed, indicating the role of the inflammatory response and lipid metabolism abnormality in the pathogenesis of DN. Six selected differential proteins were validated by Western Blot. Alpha-1-antitrypsin (SERPINA1) and Ceruloplasmin are the two markers with excellent area under curve values (0.929 and 1.000 respectively) to distinguish the microalbuminuria and normalbuminuria. For the first time, we found pro-epidermal growth factor and prolactin-inducible protein were decreased in macroalbuminuria stage, which might reflect the inhibition of cell viability and the activation of cell death in kidney.

Conclusions

Above data indicated that urinary glycoproteome could be useful to distinguish the differences in protein profiles in different stages in DN, which will help better individualized care of patients in DN.

Electronic supplementary material

The online version of this article (doi:10.1186/s12967-015-0712-9) contains supplementary material, which is available to authorized users.

Urinary biomarkers for early diabetic nephropathy: beyond albuminuria

Diabetic nephropathy (DN) is the most common cause of end-stage kidney disease in the USA and accounts for a significant increase in morbidity and mortality in patients with diabetes. Early detection is critical in improving clinical management. Although microalbuminuria is regarded as the gold standard for diagnosing the onset of DN, its predictive powers are limited. Consequently, great efforts have been made in recent years to identify better strategies for the detection of early stages of DN and progressive kidney function decline in diabetic patients. Here, we review the various urinary biomarkers that have emerged from these studies which hold promise as more sensitive diagnostic tools for the earlier detection of diabetic kidney disease and the prediction of progression to end-stage kidney disease. A number of key biomarkers present in the urine have been identified that reflect kidney injury at specific sites along the nephron, including glomerular/podocyte damage and tubular damage, oxidative stress, inflammation and activation of the intrarenal renin-angiotensin system. We also describe newer approaches, including urinary microRNAs, which are short noncoding mRNAs that regulate gene expression, and urine proteomics, that can be used to identify potential novel biomarkers in the development and progression of diabetic kidney disease.

Proteomic approaches by SELDI and MALDI-TOF/MS for CTL analysis

Extracellular stimuli activate, on target cells, a number of signal transduction processes regulating gene expression and the function and/or synthesis of the proteins. In order to highlight the slight changes of the quantity and quality of the proteome it is essential to optimize preparative strategies able to improve the signals of the less expressed proteins and to standardize the use of high-throughput techniques useful to detect them. We describe a complete workflow useful to enrich, from PBMC protein extracts and extrapolated to their subpopulations, the low-molecular-weight proteins and peptides and to detect them by SELDI-TOF protein profiling. The described protocol can also be applied to MALDI-TOF/MS instruments in order to obtain fast, reproducible, and high-quality protein profiles.

Acute kidney injury in a diabetic haemophiliac: one step at a time

We present a young man with type 1 diabetes mellitus and haemophilia A; who presented with oliguric acute kidney injury (AKI). He is also known to have chronic hepatitis C virus infection. On presentation, he had an active urinary sediment warranting a renal biopsy for definitive diagnosis and management. Although he was at high risk for bleeding we elected for renal biopsy with appropriate factor VIII supplementation and monitoring. Ultrasound-guided percutaneous renal biopsy was successful with no immediate or long-term complications. Biopsy revealed advanced diabetic glomerulosclerosis with mild chronic interstitial inflammation.

Proteomics and diabetic nephropathy: what have we learned from a decade of clinical proteomics studies?

Diabetic nephropathy (DN) has become the most frequent cause of chronic kidney disease worldwide due to the constant increase of the incidence of type 2 diabetes mellitus in developed and developing countries. The understanding of the pathophysiological mechanisms of human diseases through a large-scale characterization of the protein content of a biological sample is the key feature of the proteomics approach to the study of human disease. We discuss the main results of over 10 years of tissue and urine proteomics studies applied to DN in order to understand how far we have come and how far we still have to go before obtaining a full comprehension of the molecular mechanisms involved in the pathogenesis of DN and identifying reliable biomarkers for accurate management of patients.

Diabetic nephropathy: diagnosis and treatment

Nephropathy remains a major cause of morbidity and a key determinant of mortality in patients with type 1 or type 2 diabetes mellitus. Research is ongoing to identify biomarkers that in addition to albuminuria and glomerular filtration rate assist in the prediction and monitoring of renal disease in diabetes mellitus. Current strategies to treat this condition focus on intensification of glycaemic control and excellent control of blood pressure using regimens based on blockade of the renin-angiotensin system. Other approaches to control blood pressure and afford renoprotection are under active clinical investigation, including renal denervation and endothelin receptor antagonism. With increasing understanding of the underlying pathophysiological processes implicated in diabetic nephropathy, new specific renoprotective treatment strategies are anticipated to become available over the next few years.

A clinical stratification tool for chronic kidney disease progression rate based on classification tree analysis

BACKGROUND

Registry-based studies have identified risk factors for chronic kidney disease (CKD) and for progression to end-stage renal disease. However, usually, these studies do not incorporate sequential measurements of kidney function and provide little information on the prognosis of individual patients. The aim of this study is to identify which combinations of demographic and clinical characteristics are useful to discriminate patients with a differential annual decline in glomerular filtration rate (GFR).

METHODS

This observational retrospective study includes patients enlisted in the registry of the Prevention of Progressive Renal Insufficiency Project of Emilia-Romagna region (Italy) from July 2004 to June 2010, with at least four serum creatinine measurements. Classification tree analysis (CTA) was used to identify subgroups of patients with a different annual GFR decline using demographic and laboratory data collected at study entry.

RESULTS

The CTA procedure generated seven mutually exclusive groups. Among patients with proteinuria, those with a baseline estimated GFR (eGFR) of >33 mL/min/1.73 m(2) exhibited the fastest illness progression in the study population (-3.655 mL/min/1.73 m(2)), followed by patients with a baseline eGFR of <33 mL/min/1.73 m(2) and a baseline serum phosphorus of >4.3 mg/dL (-2.833 mL/min/1.73 m(2)). Among patients without proteinuria, those aged <67 years exhibited a significantly faster progression, which was even faster for the subgroup with diabetes. Among patients aged >67 years, females had on average a stable eGFR over time, with a large variability.

CONCLUSIONS

It is possible to rely on a few variables typically accessible in routine clinical practice to stratify patients with a different CKD progression rate. Stratification can be used to guide decisions about the follow-up schedule, treatments to slow progression of kidney disease, prevent its complications and to begin planning for dialysis and transplantation.

Recent technological developments in proteomics shed new light on translational research on diabetic microangiopathy

Diabetic microangiopathy has become a heavy social burden worldwide, but at present it is still difficult to predict and diagnose this ailment at an early stage. Various proteomics approaches have been applied to the pathophysiological study of diabetic microangiopathy. Conventional proteomics methods, including gel-based methods, exhibit limited sensitivity and robustness and have typically been used in high- or middle-abundance biomarker discovery. Clinical samples from patients with diabetic microangiopathy, such as biopsy samples, are minute in size. Therefore sample preparation, quantitative labelling and mass spectrometry technologies need to be optimized for low-abundance protein detection, multiple-sample processing and precision quantitation. In this review, we briefly introduce the recent technological developments in proteomics methods and summarize current proteomics-based, translational research on diabetic microangiopathy. Recent technological developments in proteomics tools may shed new light on the pathogenesis of diabetic microangiopathy and biomarkers and therapeutic targets related to this condition.

Association of urinary laminin G-like 3 and free K light chains with disease activity and histological injury in IgA nephropathy

BACKGROUND AND OBJECTIVES

IgA nephropathy has variable clinical presentation and progression. Its definitive diagnosis and prognosis require renal biopsy. The identification of new biomarkers allowing noninvasive diagnosis and monitoring of disease activity would be advantageous. This study analyzed the urine proteome of IgA nephropathy patients at an early stage of disease.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

Urine from 49 IgA nephropathy patients, 42 CKD patients, and 40 healthy individuals was analyzed by surface-enhanced laser desorption/ionization time of flight/mass spectrometry. Differentially excreted proteins were identified by matrix-enhanced laser desorption/ionization time of flight/mass spectrometry, confirmed by immunologic methods, and validated in an independent set of patients (14 IgA nephropathy and 24 CKD). All patients were recruited at the Division of Nephrology of the University of Foggia from January of 2005 to March of 2007.

RESULTS

Two proteins, with 21,598 and 23,458 m/z, were significantly decreased in IgA nephropathy and identified as Perlecan laminin G-like 3 peptide and Ig κ light chains, respectively. Western blot analysis confirmed the lower urinary excretion of laminin G-like 3 in IgA nephropathy patients compared with CKD patients and healthy individuals. Immunonephelometry analysis confirmed the lower urinary excretion of free κ light chains in IgA nephropathy patients compared with CKD patients and healthy individuals. Immunohistochemistry analysis justified the urinary excretion profile of such proteins in IgA nephropathy. Finally, urinary free κ light chains and laminin G-like 3 concentration inversely correlated with severity of clinical and histologic features of our IgA nephropathy cohort.

CONCLUSIONS

Laminin G-like 3 and free κ light chains can contribute to the noninvasive assessment of IgA nephropathy disease activity.

Poor histological lesions in IgA nephropathy may be reflected in blood and urine peptide profiling

Background

IgA nephropathy (IgAN) is the most common primary glomerulonephritis worldwide, leading to renal failure in 15% to 40% of cases. IgAN is diagnosed by renal biopsy, an invasive method that is not risk-free. We used blood and urine peptide profiles as a noninvasive method of linking IgAN-associated changes with histological lesions by Oxford classification.

Methods

We prospectively studied 19 patients with biopsy-proven IgAN and 14 healthy subjects from 2006 to 2009, excluding subjects with crescentic glomerulonephritis and collecting clinical and biochemical data at the time of diagnosis and during follow-up (24 months). Histological lesions were evaluated by Oxford classification. Proteomic analysis was performed by combining magnetic bead (MB) technology and mass spectrometry (MALDI-TOF MS) to obtain peptide profiles. Doubling of serum creatinine was considered a variable of poor renal prognosis.

Results

We identified 55 peptides—13 in serum, 26 in plasma, and 16 in urine—that differentiated IgAN patients from healthy subjects. A significant association was noted between serum/plasma and urine peptides and histological findings—ie, tubulointerstitial damage, segmental glomerulosclerosis, and endocapillary injury.

We also identified 3 peptides—corresponding to bradykinin, uromodulin, and alpha-1-antitrypsin—that were associated with severity of lesions, such as tubulointerstitial damage and segmental glomerulosclerosis.

Moreover, blood peptides with m/z 2953, 5337, 9287, and 9289 and urine peptides with m/z 1769, 1898, 1913, 1945, 2491, 2756, 2977, 3004, 3389, and 4752 correlated significantly with poor renal function.

Conclusions

In patients with IgAN, the use of noninvasive approaches, such as blood and urine proteomics, can provide valuable information beyond that of standard diagnostic techniques, allowing us to identify blood and urine peptide profiles that are associated with poor histological lesions in IgAN patients.

Proteome-base biomarkers in diabetes mellitus: progress on biofluids' protein profiling using mass spectrometry

The worldwide number of individuals suffering from diabetes mellitus (DM) has been projected to rise from 171 million in 2000 to 366 million in 2030. Identification of specific biomarkers for prediction and monitoring of DM is needed not only for the adequate screening diagnosis but also to assist the design of interventions to prevent or delay progression of this pathology and its attendant complications. Proteomic methods based on MS hold special promise for the identification of novel biomarkers that might form the foundation for new clinical tests, but to date, their contribution has been somehow unfruitful. Indeed, from more than 300 proteins found differently modulated in body fluids from diabetic patients, approximately 50 were validated with other approaches like ELISA or Western blotting and the clinical trials are being initiated to employ biofluids' proteomics (specifically urinary proteomics) in clinical decision. This review provides an overview of MS-based applications in the identification of potential biomarkers for DM, emphasizing the methodological challenges involved.

Diabetic nephropathy: traditional to proteomic markers

Diabetic nephropathy (DN) is one of the major microvascular complications of diabetes and it is defined as a rise in the urinary albumin excretion (UAE) rate and abnormal renal function. Currently, changes in albuminuria are considered a hallmark of onset or progression of DN. However, some patients with diabetes have advanced renal pathological changes and progressive kidney function decline even if urinary albumin levels are in the normal range, indicating that albuminuria is not the perfect marker for the early detection of DN. The present article provides an overview of the literature reporting some relevant biomarkers that have been found to be associated with DN and that potentially may be used to predict the onset and/or monitor the progression of nephropathy. In particular, biomarkers of renal damage, inflammation, and oxidative stress may be useful tools for detection at an early stage or prediction of DN. Proteomic-based biomarker discovery represents a novel strategy to improve diagnosis, prognosis and treatment of DN; however, proteomics-based approaches are not yet available in most of the clinical chemistry laboratories. The use of a panel with a combination of biomarkers instead of urinary albumin alone seems to be an interesting approach for early detection of DN, including markers of glomerular damage (e.g., albumin), tubular damage (e.g., NAG and KIM-1), inflammation (e.g., TNF-α) and oxidative stress (e.g., 8-OHdG) because these mechanisms contribute to the development and outcomes of this disease.