Searching for new biomarkers of renal diseases through proteomics

Urinary proteomics reveals biological processes related to acute kidney injury in Bothrops atrox envenomings

Acute kidney injury (AKI) is a critical systemic complication caused by Bothrops envenoming, a neglected health problem in the Brazilian Amazon. Understanding the underlying mechanisms leading to AKI is crucial for effectively mitigating the burden of this complication. This study aimed to characterize the urinary protein profile of Bothrops atrox snakebite victims who developed AKI. We analyzed three groups of samples collected on admission: healthy subjects (controls, n = 10), snakebite victims who developed AKI (AKI, n = 10), and those who did not evolve to AKI (No-AKI, n = 10). Using liquid-chromatography tandem mass spectrometry, we identified and quantified (label-free) 1190 proteins. A panel of 65 proteins was identified exclusively in the urine of snakebite victims, with 32 exclusives to the AKI condition. Proteins more abundant or exclusive in AKI's urine were associated with acute phase response, endopeptidase inhibition, complement cascade, and inflammation. Notable proteins include serotransferrin, SERPINA-1, alpha-1B-glycoprotein, and NHL repeat-containing protein 3. Furthermore, evaluating previously reported biomarkers candidates for AKI and renal injury, we found retinol-binding protein, beta-2-microglobulin, cystatin-C, and hepcidin to be significant in cases of AKI induced by Bothrops envenoming. This work sheds light on physiological disturbances caused by Bothrops envenoming, highlighting potential biological processes contributing to AKI. Such insights may aid in better understanding and managing this life-threatening complication.

Proteomics: Its Promise and Pitfalls in Shaping Precision Medicine in Solid Organ Transplantation

Solid organ transplantation is an established treatment of choice for end-stage organ failure. However, all transplant patients are at risk of developing complications, including allograft rejection and death. Histological analysis of graft biopsy is still the gold standard for evaluation of allograft injury, but it is an invasive procedure and prone to sampling errors. The past decade has seen an increased number of efforts to develop minimally invasive procedures for monitoring allograft injury. Despite the recent progress, limitations such as the complexity of proteomics-based technology, the lack of standardization, and the heterogeneity of populations that have been included in different studies have hindered proteomic tools from reaching clinical transplantation. This review focuses on the role of proteomics-based platforms in biomarker discovery and validation in solid organ transplantation. We also emphasize the value of biomarkers that provide potential mechanistic insights into the pathophysiology of allograft injury, dysfunction, or rejection. Additionally, we forecast that the growth of publicly available data sets, combined with computational methods that effectively integrate them, will facilitate a generation of more informed hypotheses for potential subsequent evaluation in preclinical and clinical studies. Finally, we illustrate the value of combining data sets through the integration of 2 independent data sets that pinpointed hub proteins in antibody-mediated rejection.

Targeted urine proteomics in lupus nephritis - a meta-analysis

BACKGROUND

Proteomic approaches are central in biomarker discovery. While mass-spectrometry-based techniques are widely used, novel targeted proteomic platforms have enabled the high-throughput detection of low-abundance proteins in an affinity-based manner. Urine has gained growing attention as an ideal biofluid for monitoring renal disease including lupus nephritis (LN).

METHODS

Pubmed was screened for targeted proteomic studies of LN urine interrogating ≥1000 proteins. Data from the primary studies were combined and a meta-analysis was performed. Shared proteins elevated in active LN across studies were identified, and relevant pathways were elucidated using ingenuity pathway and gene ontology analysis. Urine proteomic data was cross-referenced against renal single-cell RNAseq data from LN kidneys.

RESULTS

Two high-throughput targeted proteomic platforms with capacity to interrogate ≥1000 proteins have been used to investigate LN urine. Twenty-three urine proteins were significantly elevated in both studies, including 10 chemokines, and proteins implicated in angiogenesis, and extracellular matrix turnover. Of these, Cathepsin S, CXCL10, FasL, ferritin, macrophage migration inhibitory factor (MIF), and resistin were also significantly elevated within LN kidneys.

CONCLUSION

Targeted urinary proteomics have uncovered multiple novel biomarkers for LN. Further validation in prospective cohorts and mechanistic studies are warranted to establish their clinical utility.

The association between plasma proteomics and incident cardiovascular disease identifies MMP-12 as a promising cardiovascular risk marker in patients with chronic kidney disease

BACKGROUND AND AIMS

Previous proteomics efforts in patients with chronic kidney disease (CKD) have predominantly evaluated urinary protein levels. Therefore, our aim was to investigate the association between plasma levels of 80 cardiovascular disease-related proteins and the risk of major adverse cardiovascular events (MACE) in patients with CKD.

METHODS

Individuals with CKD stages 3-5 (eGFR below 60 ml min-1 [1.73 m]-2) from three community-based cohorts (PIVUS, ULSAM, SAVA), one diabetes cohort (CARDIPP) and one cohort with peripheral artery disease patients (PADVA) with information on 80 plasma protein biomarkers, assessed with a proximity extension assay, and follow-up data on incident MACE, were used as discovery sample. To validate findings and to asses generalizability to patients with CKD in clinical practice, an outpatient CKD-cohort (Malnutrition, Inflammation and Vascular Calcification (MIVC)) was used as replication sample.

RESULTS

In the discovery sample (total n = 1316), 249 individuals experienced MACE during 7.0 ± 2.9 years (range 0.005-12.9) of follow-up, and in the replication sample, 71 MACE events in 283 individuals over a mean ± SD change of 2.9 ± 1.2 years (range 0.1-4.0) were documented. Applying Bonferroni correction, 18 proteins were significantly associated with risk of MACE in the discovery cohort, adjusting for age and sex in order of significance, GDF-15, FGF-23, REN, FABP4, IL6, TNF-R1, AGRP, MMP-12, AM, KIM-1, TRAILR2, TNFR2, CTSL1, CSF1, PlGF, CA-125, CCL20 and PAR-1 (p < 0.000625 for all). Only matrix metalloproteinase 12 (MMP-12) was significantly associated with an increased risk of MACE in the replication sample (hazard ratio (HR) per SD increase, 1.36, 95% CI (1.07-1.75), p = 0.013).

CONCLUSIONS

Our proteomics analyses identified plasma MMP-12 as a promising cardiovascular risk marker in patients with CKD.

Advances and challenges in pursuing biomarkers for obstructive sleep apnea: Implications for the cardiovascular risk

Obstructive sleep apnea (OSA) is a common clinical condition associated with increased cardiovascular morbidity and mortality. Recent evidence from clinical studies and animal models suggest that OSA can promote cardiovascular disease by inducing autonomic, hemodynamic, inflammatory and metabolic dysregulation. However, most of the evidence addressing hard endpoints in humans is derived from observational studies. Several challenges have been noted in the pursuit of a comprehensive knowledge base about the impact of OSA including: 1) the precise mechanisms by which OSA causes metabolic and cardiovascular consequences are not clear, which limits our current ability to address potential targets in OSA; 2) several patients with OSA, even with severe forms, present with no or mild daytime symptoms. Beyond the obvious challenges for obtaining good adherence for conventional OSA treatments, there is evidence that symptomatic vs. asymptomatic patients with OSA do not necessarily have the same metabolic and cardiovascular outcomes; and 3) the cardiovascular response to OSA treatment may vary even in those patients with good adherence. In this scenario, there is an obvious need to develop biomarkers in the OSA research area. This review focuses on describing the advances that have occurred so far in exploring potential OSA biomarkers with clear emphasis for the cardiovascular risk. Particular attention will be devoted to discuss molecular biomarkers including the potential role of microRNAs, proteomics and metabolomics. We also discuss the major challenges and perspectives in this growing research field.

Searching for prognostic biomarkers for small renal masses in the urinary proteome

Renal cell carcinoma (RCC) is frequently diagnosed incidentally as an early-stage small renal mass (SRM; pT1a, ≤4 cm). Overtreatment of patients with benign or clinically indolent SRMs is increasingly common and has resulted in a recent shift in treatment recommendations. There are currently no available biomarkers that can accurately predict clinical behavior. Therefore, we set out to identify early biomarkers of RCC progression. We employed a quantitative label-free liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) proteomics approach and targeted parallel-reaction monitoring to identify and validate early, noninvasive urinary biomarkers for RCC-SRMs. In total, we evaluated 115 urine samples, including 33 renal oncocytoma (≤4 cm) cases, 30 progressive and 26 nonprogressive clear cell RCC (ccRCC)-SRM cases, in addition to 26 healthy controls. We identified six proteins, which displayed significantly elevated expression in clear cell RCC-SRMs (ccRCC-SRMs) relative to healthy controls. Proteins C12ORF49 and EHD4 showed significantly elevated expression in ccRCC-SRMs compared to renal oncocytoma (≤4 cm). Additionally, proteins EPS8L2, CHMP2A, PDCD6IP, CNDP2 and CEACAM1 displayed significantly elevated expression in progressive relative to nonprogressive ccRCC-SRMs. A two-protein signature (EPS8L2 and CCT6A) showed significant discriminatory ability (areas under the curve: 0.81, 95% CI: 0.70-0.93) in distinguishing progressive from nonprogressive ccRCC-SRMs. Patients (Stage I-IV) with EPS8L2 and CCT6A mRNA alterations showed significantly shorter overall survival (p = 1.407 × 10^-6 ) compared to patients with no alterations. Our in-depth proteomic analysis identified novel biomarkers for early-stage RCC-SRMs. Pretreatment characterization of urinary proteins may provide insight into early RCC progression and could potentially help assign patients to appropriate management strategies.

A comprehensive narrative review of diagnostic biomarkers in human primary membranous nephropathy

Membranous nephropathy (MN) is relatively major cause of nephrotic syndrome in adults which is recognized as an organ-specific autoimmune disease. The etiology of most cases is idiopathic, whereas the secondary MN is caused by systemic autoimmune diseases, infections, medications and malignancies. The idiopathic disease is developed by the formation of sub-epithelial immune complex deposits most likely due to binding the circulating auto-antibodies to intrinsic antigen on podocytes. The major auto antibody is the anti-phospholipase A2 receptor (anti-PLA2R), however, it is not enough sensitive. Several attempts for diagnostic biomarker identification by modern analytical technologies have been devoted recently. This article reviews the biomarker candidates for primary type of MN that are detected by different approaches on human subjects.

Urinary Lipidomics: evidence for multiple sources and sexual dimorphism in healthy individuals

Urinary lipidomics may add new valuable biomarkers to the diagnostic armamentarium for early detection of metabolic and kidney diseases. Sources and composition of urinary lipids in healthy individuals, however, have not been investigated in detail. Shotgun lipidomics was used to quantify lipidomic profiles in native urine samples from 16 individuals (eight men, eight women) collected in five fractions over 24 h. All probands were comprehensively characterized by urinary and clinical indices. The mean total urinary lipid concentration per sample was 0.84 μM in men and 1.03 μM in women. We observed significant intra- and interindividual variations of lipid concentrations over time, but failed to detect a clear circadian pattern. Based on quantity and subclass composition it seems very unlikely that plasma serves as major source for the urinary lipidome. Considering lipid metabolites occurring in at least 20% of all samples 38 lipid species from 7 lipid classes were identified. Four phosphatidylserine and one phosphatidylethanolamine ether species (PE-O 36:5) were detectable in almost all urine samples. Sexual dimorphism has been found mainly for phosphatidylcholines and phosphatidylethanolamines. In men and in women urinary lipid species were highly correlated with urinary creatinine and albumin excretion, reflecting glomerular filtration and tubular transport processes. In women, however, lipid species deriving from urinary cells and cellular constituents of the lower genitourinary tract considerably contributed to the urinary lipidome. In conclusion, our study revealed the potential of urinary lipidomics but also the complexity of methodological challenges which have to be overcome for its implementation as a routine diagnostic tool for renal, urological and metabolic diseases.

Insights into Diabetic Kidney Disease Using Urinary Proteomics and Bioinformatics

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.

Proteomics and peptidomics: moving toward precision medicine in urological malignancies

Urological malignancies are a major cause of morbidity and mortality worldwide. Advances in early detection, diagnosis, prognosis and prediction of treatment response can significantly improve patient care. Proteomic and peptidomic profiling studies are at the center of kidney, prostate and bladder cancer biomarker discovery and have shown great promise for improved clinical assessment. Mass spectrometry (MS) is the most widely employed method for proteomic and peptidomic analyses. A number of MS platforms have been developed to facilitate accurate identification of clinically relevant markers in various complex biological samples including tissue, urine and blood. Furthermore, protein profiling studies have been instrumental in the successful introduction of several diagnostic multimarker tests into the clinic. In this review, we will provide a brief overview of high-throughput technologies for protein and peptide based biomarker discovery. We will also examine the current state of kidney, prostate and bladder cancer biomarker research as well as review the journey toward successful clinical implementation.

Kidney Disease and the Nexus of Chronic Kidney Disease and Acute Kidney Injury: The Role of Novel Biomarkers as Early and Accurate Diagnostics

Chronic kidney disease (CKD) and acute kidney injury (AKI) are interconnected and the presence of one is a risk for the other. CKD is an important predictor of AKI after exposure to nephrotoxic drugs or major surgery, whereas persistent or repetitive injury could result in the progression of CKD. This brings new perspectives to the diagnosis and monitoring of kidney diseases highlighting the need for a panel of kidney-specific biomarkers that reflect functional as well as structural damage and recovery, predict potential risk and provide prognosis. This article discusses the kidney-specific biomarkers, symmetric dimethylarginine (SDMA), clusterin, cystatin B, and inosine.

Urinary Kininogen-1 and Retinol binding protein-4 respond to Acute Kidney Injury: predictors of patient prognosis?

Implementation of therapy for acute kidney injury (AKI) depends on successful prediction of individual patient prognosis. Clinical markers as serum creatinine (sCr) have limitations in sensitivity and early response. The aim of the study was to identify novel molecules in urine which show altered levels in response to AKI and investigate their value as predictors of recovery. Changes in the urinary proteome were here investigated in a cohort of 88 subjects (55 AKI patients and 33 healthy donors) grouped in discovery and validation independent cohorts. Patients’ urine was collected at three time points: within the first 48 h after diagnosis(T1), at 7 days of follow-up(T2) and at discharge of Nephrology(T3). Differential gel electrophoresis was performed and data were confirmed by Western blot (WB), liquid chromatography/mass spectrometry (LC-MS/MS) and enzyme-linked immunosorbent assay (ELISA). Retinol binding protein 4 (RBP4) and kininogen-1 (KNG1) were found significantly altered following AKI. RBP4 increased at T1, and progressively decreased towards normalization. Maintained decrease was observed for KNG1 from T1. Individual patient response along time revealed RBP4 responds to recovery earlier than sCr. In conclusion, KNG1 and RBP4 respond to AKI. By monitoring RBP4, patient’s recovery can be anticipated pointing to a role of RBP4 in prognosis evaluation.

Urinary alpha-1 antitrypsin and CD59 glycoprotein predict albuminuria development in hypertensive patients under chronic renin-angiotensin system suppression

BACKGROUND

Hypertension is a multi-factorial disease of increasing prevalence and a major risk factor for cardiovascular mortality even in the presence of adequate treatment. Progression of cardiovascular disease (CVD) occurs frequently during chronic renin-angiotensin-system (RAS) suppression, and albuminuria is a marker of CV risk. High prevalence of albuminuria in treated hypertensive patients has been demonstrated, but there are no available markers able to predict evolution. The aim of this study was the identification of novel indicators of albuminuria progression measurable in urine of diabetic and non-diabetic patients.

METHODS

1143 hypertensive patients under chronic treatment were followed for a minimum period of 3 years. Among them, 105 diabetic and non-diabetic patients were selected and classified in three groups according to albuminuria development during follow-up: (a) patients with persistent normoalbuminuria; (b) patients developing de novo albuminuria; (c) patients with maintained albuminuria. Differential urine analysis was performed by 2D gel electrophoresis (2D-DIGE) and further confirmed by liquid chromatography-mass spectrometry. Non-parametric statistical tests were applied.

RESULTS

CD59 glycoprotein and alpha-1 antitrypsin (AAT) resulted already altered in patients developing albuminuria de novo, with a similar response in those with maintained albuminuria. A prospective study in a sub-group of normoalbuminuric patients who were clinically followed up for at least 1 year from urine sampling, revealed CD59 and AAT proteins significantly varied in the urine collected from normoalbuminurics who will negatively progress, serving as predictors of future albuminuria development.

CONCLUSIONS

CD59 and AAT proteins are significantly altered in hypertensive patients developing albuminuria. Interestingly, CD59 and AAT are able to predict, in normoalbuminuric individuals, who will develop albuminuria in the future, being potential predictors of vascular damage and CV risk. These findings contribute to early identify patients at risk of developing albuminuria even when this classical predictor is still in the normal range, constituting a novel strategy towards a prompt and more efficient therapeutic intervention with better outcome.

RNA Sequencing Identifies Novel Translational Biomarkers of Kidney Fibrosis

CKD is the gradual, asymptomatic loss of kidney function, but current tests only identify CKD when significant loss has already happened. Several potential biomarkers of CKD have been reported, but none have been approved for preclinical or clinical use. Using RNA sequencing in a mouse model of folic acid-induced nephropathy, we identified ten genes that track kidney fibrosis development, the common pathologic finding in patients with CKD. The gene expression of all ten candidates was confirmed to be significantly higher (approximately ten- to 150-fold) in three well established, mechanistically distinct mouse models of kidney fibrosis than in models of nonfibrotic AKI. Protein expression of these genes was also high in the folic acid model and in patients with biopsy-proven kidney fibrosis. mRNA expression of the ten genes increased with increasing severity of kidney fibrosis, decreased in response to therapeutic intervention, and increased only modestly (approximately two- to five-fold) with liver fibrosis in mice and humans, demonstrating specificity for kidney fibrosis. Using targeted selected reaction monitoring mass spectrometry, we detected three of the ten candidates in human urine: cadherin 11 (CDH11), macrophage mannose receptor C1 (MRC1), and phospholipid transfer protein (PLTP). Furthermore, urinary levels of each of these three proteins distinguished patients with CKD (n=53) from healthy individuals (n=53; P<0.05). In summary, we report the identification of urinary CDH11, MRC1, and PLTP as novel noninvasive biomarkers of CKD.

Chromatography/Mass Spectrometry-Based Biomarkers in the Field of Obstructive Sleep Apnea

Biomarker assessment is based on quantifying several proteins and metabolites. Recent developments in proteomics and metabolomics have enabled detection of these small molecules in biological samples and exploration of the underlying disease mechanisms in obstructive sleep apnea (OSA). This systemic review was performed to identify biomarkers, which were only detected by chromatography and/or mass spectrometry (MS) and to discuss the role of these biomarkers in the field of OSA. We systemically reviewed relevant articles from PubMed and EMBASE referring to proteins and metabolite profiles of biological samples in patients with OSA. The analytical platforms in this review were focused on chromatography and/or MS. In total, 30 studies evaluating biomarkers in patients with OSA using chromatography and/or MS methods were included. Numerous proteins and metabolites, including lipid profiles, adrenergic/dopaminergic biomarkers and derivatives, amino acids, oxidative stress biomarkers, and other micromolecules were identified in patients with OSA. Applying chromatography and/or MS methods to detect biomarkers helps develop an understanding of OSA mechanisms. More proteomic and metabolomic studies are warranted to develop potential diagnostic and clinical monitoring methods for OSA.

An analysis of the impact of pre-analytical factors on the urine proteome: Sample processing time, temperature, and proteolysis

Purpose

We have examined the impact of sample processing time delay, temperature, and the addition of protease inhibitors (PIs) on the urinary proteome and peptidome, an important aspect of biomarker studies.

Experimental design

Ten urine samples from patients with varying pathologies were each divided and PIs added to one‐half, with aliquots of each then processed and frozen immediately, or after a delay of 6 h at 4°C or room temperature (20–22°C), effectively yielding 60 samples in total. Samples were then analyzed by 2D‐PAGE, SELDI‐TOF‐MS, and immunoassay.

Results

Interindividual variability in profiles was the dominant feature in all analyses. Minimal changes were observed by 2D‐PAGE as a result of delay in processing, temperature, or PIs and no changes were seen in IgG, albumin, β₂‐microglobulin, or α₁‐microglobulin measured by immunoassay. Analysis of peptides showed clustering of some samples by presence/absence of PIs but the extent was very patient‐dependent with most samples showing minimal effects.

Conclusions and clinical relevance

The extent of processing‐induced changes and the benefit of PI addition are patient‐ and sample‐dependent. A consistent processing methodology is essential within a study to avoid any confounding of the results.

Toward an integrated pipeline for protein biomarker development

Protein biomarker development is a multidisciplinary task involving basic, translational and clinical research. Integration of multidisciplinary efforts in a single pipeline is challenging, but crucial to facilitate rational discovery of protein biomarkers and alleviate existing disappointments in the field. In this review, we discuss in detail individual phases of biomarker development pipeline, such as biomarker candidate identification, verification and validation. We focus on mass spectrometry as a principal technique for protein identification and quantification, and discuss complementary -omics approaches for selection of biomarker candidates. Proteomic samples, protein-based clinical laboratory tests and limitations of biomarker development are reviewed in detail, and critical assessment of all phases of biomarker development pipeline is provided. This article is part of a Special Issue entitled: Medical Proteomics.

Peptidomics of Urine and Other Biofluids for Cancer Diagnostics

BACKGROUND

Cancer is a leading cause of death worldwide. The low diagnostic sensitivity and specificity of most current cancer biomarkers make early cancer diagnosis a challenging task. The comprehensive study of peptides and small proteins in a living system, known as “peptidomics,” represents an alternative technological approach to the discovery of potential biomarkers for the assessment of a wide variety of pathologies. This review examines the current status of peptidomics for several body fluids, with a focus on urine, for cancer diagnostics applications.

CONTENT

Several studies have used high-throughput technologies to characterize the peptide content of different body fluids. Because of its noninvasive collection and high stability, urine is a valuable source of candidate cancer biomarkers. A wide variety of preanalytical issues concerning patient selection and sample handling need to be considered, because not doing so can affect the quality of the results by introducing bias and artifacts. Optimization of both the analytical strategies and the processing of bioinformatics data is also essential to minimize the false-discovery rate.

SUMMARY

Peptidomics-based studies of urine and other body fluids have yielded a number of biomolecules and peptide panels with potential for diagnosing different types of cancer, especially of the ovary, prostate, and bladder. Large-scale studies are needed to validate these molecules as cancer biomarkers.

The novel diagnostic biomarkers for focal segmental glomerulosclerosis

Background. Focal segmental glomerulosclerosis (FSGS) is a glomerular injury with various pathogenic mechanisms. Urine proteome panel might help in noninvasive diagnosis and better understanding of pathogenesis of FSGS. Method. We have analyzed the urine sample of 11 biopsy-proven FSGS subjects, 8 healthy controls, and 6 patients with biopsy-proven IgA nephropathy (disease controls) by means of liquid chromatography tandem mass spectrometry (nLC-MS/MS). Multivariate analysis of quantified proteins was performed by principal component analysis (PCA) and partial least squares (PLS). Results. Of the total number of 389 proteins, after multivariate analysis and additional filter criterion and comparing FSGS versus IgA nephropathy and healthy subjects, 77 proteins were considered as putative biomarkers of FSGS. CD59, CD44, IBP7, Robo4, and DPEP1 were the most significant differentially expressed proteins. These proteins are involved in pathogenic pathways: complement pathway, sclerosis, cell proliferation, actin cytoskeleton remodeling, and activity of TRPC6.There was complete absence of DPEP1 in urine proteome of FSGS subjects compared with healthy and disease controls. DPEP1 acts via leukotrienes on TRPC6 and results in increased podocyte motility and proteinuria. Conclusion. The results suggest a panel of candidate biomarkers for noninvasive diagnosis of FSGS, while complete absence of DPEP1 might represent a novel marker of FSGS.

Proteomics for breast cancer urine biomarkers

Although the survival of breast cancer (BC) patients has increased over the last two decades due to improved screening programs and postoperative adjuvant systemic therapies, many patients die from metastatic relapse. Current biomarkers used in the clinic are not useful for the early detection of BC, or monitoring its progression, and have limited value in predicting response to treatment. The development of proteomic techniques has sparked new searches for novel protein markers for many diseases including BC. Proteomic techniques allow for a high-throughput analysis of samples with the visualization and quantification of thousands of potential protein and peptide markers. Human urine is one of the most interesting and useful biofluids for routine testing and provides an excellent resource for the discovery of novel biomarkers, with the advantage over tissue biopsy samples due to the ease and less invasive nature of collection. In this review, we summarize the results from studies where urine was used as a source for BC biomarker research and discuss urine sample preparation, its advantage, challenges, and limitation. We focus on the gel-based proteomic approaches as well as the recent development of quantitative techniques in BC urine biomarker detection. Finally, the future use of modern proteomic techniques in BC biomarker identification will be discussed.

A compendium of urinary biomarkers indicative of glomerular podocytopathy

It is well known that glomerular podocyte injury and loss are present in numerous nephropathies and that the pathophysiologic consecution of disease hinges upon the fate of the podocyte. While multiple factors play a hand in glomerulopathy progression, basic logic lends that if one monitors the podocyte's status, that may reflect the status of disease. Recent investigations have focused on what one can elucidate from the noninvasive collection of urine, and have proven that certain, specific biomarkers of podocytes can be readily identified via varying techniques. This paper has brought together all described urinary biomarkers of podocyte injury and is made to provide a concise summary of their utility and testing in laboratory and clinical theatres. While promising in the potential that they hold as tools for clinicians and investigators, the described biomarkers require further comprehensive vetting in the form of larger clinical trials and studies that would give their value true weight. These urinary biomarkers are put forth as novel indicators of glomerular disease presence, disease progression, and therapeutic efficacy that in some cases may be more advantageous than the established parameters/measures currently used in practice.

Nanosized contrast agents to noninvasively detect kidney inflammation by magnetic resonance imaging

Several molecular imaging methods have been developed that use nanosized contrast agents to detect markers of inflammation within tissues. Kidney inflammation contributes to disease progression in a wide range of autoimmune and inflammatory diseases, and a biopsy is currently the only method of definitively diagnosing active kidney inflammation. However, the development of new molecular imaging methods that use contrast agents capable of detecting particular immune cells or protein biomarkers will allow clinicians to evaluate inflammation throughout the kidneys and to assess a patient's response to immunomodulatory drugs. These imaging tools will improve our ability to validate new therapies and to optimize the treatment of individual patients with existing therapies. This review describes the clinical need for new methods of monitoring kidney inflammation and recent advances in the development of nanosized contrast agents for the detection of inflammatory markers of kidney disease.

Applicability of 2D gel electrophoresis and liquid chromatography in proteomic analysis of urine using mass spectrometry MALDI-TOF

Proteomics including the studies of the structure, function and dependences between proteins is more and more extensively applied in human medicine and veterinary medicine. The analysis of protein profiles of tissues and body fluid from healthy and ill individuals allows to identify diagnostic, prognostic and predictive markers in various pathological states in people and animals. This paper presents preparation of urine samples for analysis in the mass spectrometer MALDI-TOF (Ultraflextreme, Bruker, Bremen, Germany) by means of two methods: liquid chromatography based on the system Nano-LC (PROTEINER FC II, Bruker Daltonics, Bremen Germany). and two-direction electrophoresis 2DE (GE Healthcare, United Kingdom). Both methods enable separation of the mixture under consideration into individual fractions of high purity indispensable for obtaining readable mass spectra. The purpose of this paper is to determine applicability of these methods in analysis of protein composition of urine samples.

Proteomics and metabolomics in renal transplantation-quo vadis?

The improvement of long-term transplant organ and patient survival remains a critical challenge following kidney transplantation. Proteomics and biochemical profiling (metabolomics) may allow for the detection of early changes in cell signal transduction regulation and biochemistry with high sensitivity and specificity. Hence, these analytical strategies hold the promise to detect and monitor disease processes and drug effects before histopathological and pathophysiological changes occur. In addition, they will identify enriched populations and enable individualized drug therapy. However, proteomics and metabolomics have not yet lived up to such high expectations. Renal transplant patients are highly complex, making it difficult to establish cause-effect relationships between surrogate markers and disease processes. Appropriate study design, adequate sample handling, storage and processing, quality and reproducibility of bioanalytical multi-analyte assays, data analysis and interpretation, mechanistic verification, and clinical qualification (=establishment of sensitivity and specificity in adequately powered prospective clinical trials) are important factors for the success of molecular marker discovery and development in renal transplantation. However, a newly developed and appropriately qualified molecular marker can only be successful if it is realistic that it can be implemented in a clinical setting. The development of combinatorial markers with supporting software tools is an attractive goal.

From -omics to personalized medicine in nephrology: integration is the key

Large-scale gene, protein and metabolite measurements ('omics') have driven the resolution of biology to an unprecedented high definition. Passing from reductionism to a system-oriented perspective, medical research will take advantage of these high-throughput technologies unveiling their full potential. Integration is the key to decoding the underlying principles that govern the complex functions of living systems. Extensive computational support and statistical modelling is needed to manage and connect the -omic data sets but this, in turn, is speeding up the hypothesis generation in biology enormously and yielding a deep insight into the pathophysiology. This systems biology approach will transform diagnostic and therapeutic strategies with the discovery of novel biomarkers that will enable a predictive and preventive medicine leading to personalized medicine.

A discovery-phase urine proteomics investigation in type 1 diabetes

Diabetes is a chronic metabolic disease which can lead to serious health problems particularly in and to the development of cardiovascular and renal complications. The aim of this study is to possibly identify distinctive molecular features in urine samples which might correlate to the progression and complications of type 1 diabetes. Diabetic patients with normo- and micro-albuminuria have been analyzed and compared to a group of control subjects. Urine proteins of control and type 1 diabetes subjects were investigated in their proteome profiles, using high-resolution two-dimensional gel electrophoresis separation and protein identifications by MALDI-TOF-MS and LC-MS/MS analysis. Proteomics analysis highlighted differential expression of several proteins between control and type 1 diabetes subjects. In particular, five proteins were found to be down-regulated and four proteins up-regulated. Lower protein representations in diabetic subjects were associated with Tamm-Horsfall urinary glycoprotein, apolipoprotein A-I, apolipoprotein E, α2-thiol proteinase inhibitor, and human complement regulatory protein CD59, while higher protein representations were found for α-1-microglobulin, zinc-α2 glycoprotein, α-1B glycoprotein, and retinol-binding protein 4. These differences were maintained comparing control subjects with type 1 diabetes normo-albuminuric and micro-albuminuric subjects. Furthermore, these proteins are correlated to glycosylated hemoglobin and microalbuminuria, confirming their role in diabetic pathology. This study gives new insights on potential molecular mechanisms associated with the complications of type 1 diabetic disease providing evidences of urine proteins potentially exploitable as putative prognostic biomarkers.

Perspectives on systems biology applications in diabetic kidney disease

Diabetic kidney disease (DKD) is a microvascular complication of type 1 and 2 diabetes with a devastating impact on individuals with the disease, their families, and society as a whole. DKD is the single most frequent cause of incident chronic kidney disease cases and accounts for over 40% of the population with end-stage renal disease. Contributing factors for the high prevalence are the increase in obesity and subsequent diabetes combined with an improved long-term survival with diabetes. Environment and genetic variations contribute to DKD susceptibility and progressive loss of kidney function. How the molecular mechanisms of genetic and environmental exposures interact during DKD initiation and progression is the focus of ongoing research efforts. The development of standardized, unbiased high-throughput profiling technologies of human DKD samples opens new avenues in capturing the multiple layers of DKD pathobiology. These techniques routinely interrogate analytes on a genome-wide scale generating comprehensive DKD-associated fingerprints. Linking the molecular fingerprints to deep clinical phenotypes may ultimately elucidate the intricate molecular interplay in a disease stage and subtype-specific manner. This insight will form the basis for accurate prognosis and facilitate targeted therapeutic interventions. In this review, we present ongoing efforts from large-scale data integration translating "-omics" research efforts into improved and individualized health care in DKD.