Urine protein patterns can serve as diagnostic tools in patients with IgA nephropathy

Proteomics and Its Current Application in Biomedical Area: Concise Review

Biomedical researchers tirelessly seek cutting-edge technologies to advance disease diagnosis, drug discovery, and therapeutic interventions, all aimed at enhancing human and animal well-being. Within this realm, proteomics stands out as a pivotal technology, focusing on extensive studies of protein composition, structure, function, and interactions. Proteomics, with its subdivisions of expression, structural, and functional proteomics, plays a crucial role in unraveling the complexities of biological systems. Various sophisticated techniques are employed in proteomics, including polyacrylamide gel electrophoresis, mass spectrometry analysis, NMR spectroscopy, protein microarray, X-ray crystallography, and Edman sequencing. These methods collectively contribute to the comprehensive understanding of proteins and their roles in health and disease. In the biomedical field, proteomics finds widespread application in cancer research and diagnosis, stem cell studies, and the diagnosis and research of both infectious and noninfectious diseases. In addition, it plays a pivotal role in drug discovery and the emerging frontier of personalized medicine. The versatility of proteomics allows researchers to delve into the intricacies of molecular mechanisms, paving the way for innovative therapeutic approaches. As infectious and noninfectious diseases continue to emerge and the field of biomedical research expands, the significance of proteomics becomes increasingly evident. Keeping abreast of the latest developments in proteomics applications becomes paramount for the development of therapeutics, translational research, and study of diverse diseases. This review aims to provide a comprehensive overview of proteomics, offering a concise outline of its current applications in the biomedical domain. By doing so, it seeks to contribute to the understanding and advancement of proteomics, emphasizing its pivotal role in shaping the future of biomedical research and therapeutic interventions.

Dynamics of urine proteomics biomarker and disease progression in patients with IgA nephropathy

BACKGROUND

Immunoglobulin A nephropathy (IgAN) frequently leads to kidney failure. The urinary proteomics-based classifier IgAN237 may predict disease progression at the time of kidney biopsy. We studied whether IgAN237 also predicts progression later in the course of IgAN.

METHODS

Urine from patients with biopsy-proven IgAN was analyzed using capillary electrophoresis-mass spectrometry at baseline (IgAN237-1, n = 103) and at follow-up (IgAN237-2, n = 89). Patients were categorized as "non-progressors" (IgAN237 ≤0.38) and "progressors" (IgAN237 >0.38). Estimated glomerular filtration rate (eGFR) and urinary albumin-creatinine ratio slopes were calculated.

RESULTS

Median age at biopsy was 44 years, interval between biopsy and IgAN237-1 was 65 months and interval between IgAN237-1 and IgAN237-2 was 258 days (interquartile range 71-531). IgAN237-1 and IgAN237-2 values did not differ significantly and were correlated (rho = 0.44, P < .001). Twenty-eight percent and 26% of patients were progressors based on IgAN237-1 and IgAN237-2, respectively. IgAN237 inversely correlated with chronic eGFR slopes (rho = -0.278, P = .02 for score-1; rho = -0.409, P = .002 for score-2) and with ±180 days eGFR slopes (rho = -0.31, P = .009 and rho = -0.439, P = .001, respectively). The ±180 days eGFR slopes were worse for progressors than for non-progressors (median -5.98 versus -1.22 mL/min/1.73 m2 per year for IgAN237-1, P < .001; -3.02 vs 1.08 mL/min/1.73 m2 per year for IgAN237-2, P = .0047). In multiple regression analysis baseline progressor/non-progressor according to IgAN237 was an independent predictor of eGFR180days-slope (P = .001).

CONCLUSION

The urinary IgAN237 classifier represents a risk stratification tool in IgAN also later in the course of the dynamic disease. It may guide patient management in an individualized manner.

Rapid and Accurate Measurement of the Na+/K+ Balance in Urine for Remote Patient Monitoring Using a Symmetric Electrode Architecture

The daily monitoring of the electrolyte balance in human bodies is challenging due to the lack of a low-cost, user-friendly device that can be used remotely by patients. In this study, a potentiometric sensor for the measurement of the ratio of Na⁺ and K⁺ ions has been fabricated using a solid-state carbon-based internal layer. PVC-type membranes are deposited using an autodispenser with a fabrication rate of approximately one sensor every 10 s, allowing mass production with limited investments. The symmetric architecture of the sensor unit, built without a reference electrode, permits a very fast stabilization of the signal, under 20 s, even without preconditioning. Measurements using buffer solutions in the range Na⁺/K⁺ = 1 to Na⁺/K⁺ = 10 indicate that less than 2 min, including the single-point calibration, is necessary to provide an estimation of the Na⁺/K⁺ balance with the same accuracy as that of a conventional sensing unit (±10%). Five sensors have been tested repeatedly over 30 days, and they maintained a constant level of performance regarding membrane sensitivity and response time. A remote measurement for the ratio between Na⁺ and K⁺ ions in urine samples showed results in agreement with a commercially available sensor. This sensor design could create new perspectives in remote healthcare for the quick detection of several diseases related to electrolyte balance.

Progress in understanding primary glomerular disease: insights from urinary proteomics and in-depth analyses of potential biomarkers based on bioinformatics

Chronic kidney disease (CKD) has become a global public health challenge. While primary glomerular disease (PGD) is one of the leading causes of CKD, the specific pathogenesis of PGD is still unclear. Accurate diagnosis relies largely on invasive renal biopsy, which carries risks of bleeding, pain, infection and kidney vein thrombosis. Problems with the biopsy procedure include lack of glomeruli in the tissue obtained, and the sampling site not being reflective of the overall lesion in the kidney. Repeated renal biopsies to monitor disease progression cannot be performed because of the significant risks of bleeding and kidney vein thrombosis. On the other hand, urine collection, a noninvasive method, can be performed repeatedly, and urinary proteins can reflect pathological changes in the urinary system. Advancements in proteomics technologies, especially mass spectrometry, have facilitated the identification of candidate biomarkers in different pathological types of PGD. Such biomarkers not only provide insights into the pathogenesis of PGD but also are important for diagnosis, monitoring treatment, and prognosis. In this review, we summarize the findings from studies that have used urinary proteomics, among other omics screens, to identify potential biomarkers for different types of PGD. Moreover, we performed an in-depth bioinformatic analysis to gain a deeper understanding of the biological processes and protein-protein interaction networks in which these candidate biomarkers may participate. This review, including a description of an integrated analysis method, is intended to provide insights into the pathogenesis, noninvasive diagnosis, and personalized treatment efforts of PGD and other associated diseases.

Non-Invasive Nasal Discharge Fluid and Other Body Fluid Biomarkers in Alzheimer’s Disease

The key to current Alzheimer’s disease (AD) therapy is the early diagnosis for prompt intervention, since available treatments only slow the disease progression. Therefore, this lack of promising therapies has called for diagnostic screening tests to identify those likely to develop full-blown AD. Recent AD diagnosis guidelines incorporated core biomarker analyses into criteria, including amyloid-β (Aβ), total-tau (T-tau), and phosphorylated tau (P-tau). Though effective, the accessibility of screening tests involving conventional cerebrospinal fluid (CSF)- and blood-based analyses is often hindered by the invasiveness and high cost. In an attempt to overcome these shortcomings, biomarker profiling research using non-invasive body fluid has shown the potential to capture the pathological changes in the patients’ bodies. These novel non-invasive body fluid biomarkers for AD have emerged as diagnostic and pathological targets. Here, we review the potential peripheral biomarkers, including non-invasive peripheral body fluids of nasal discharge, tear, saliva, and urine for AD.

Urine proteomics for prediction of disease progression in patients with IgA nephropathy

BACKGROUND

Risk of kidney function decline in immunoglobulin A (IgA) nephropathy (IgAN) is significant and may not be predicted by available clinical and histological tools. To serve this unmet need, we aimed at developing a urinary biomarker-based algorithm that predicts rapid disease progression in IgAN, thus enabling a personalized risk stratification.

METHODS

In this multicentre study, urine samples were collected in 209 patients with biopsy-proven IgAN. Progression was defined by tertiles of the annual change of estimated glomerular filtration rate (eGFR) during follow-up. Urine samples were analysed using capillary electrophoresis coupled mass spectrometry. The area under the receiver operating characteristic curve (AUC) was used to evaluate the risk prediction models.

RESULTS

Of the 209 patients, 64% were male. Mean age was 42 years, mean eGFR was 63 mL/min/1.73 m2 and median proteinuria was 1.2 g/day. We identified 237 urine peptides showing significant difference in abundance according to the tertile of eGFR change. These included fragments of apolipoprotein C-III, alpha-1 antitrypsin, different collagens, fibrinogen alpha and beta, titin, haemoglobin subunits, sodium/potassium-transporting ATPase subunit gamma, uromodulin, mucin-2, fractalkine, polymeric Ig receptor and insulin. An algorithm based on these protein fragments (IgAN237) showed a significant added value for the prediction of IgAN progression [AUC 0.89; 95% confidence interval (CI) 0.83-0.95], as compared with the clinical parameters (age, gender, proteinuria, eGFR and mean arterial pressure) alone (0.72; 95% CI 0.64-0.81).

CONCLUSIONS

A urinary peptide classifier predicts progressive loss of kidney function in patients with IgAN significantly better than clinical parameters alone.

OMICS in Chronic Kidney Disease: Focus on Prognosis and Prediction

Chronic kidney disease (CKD) patients are characterized by a high residual risk for cardiovascular (CV) events and CKD progression. This has prompted the implementation of new prognostic and predictive biomarkers with the aim of mitigating this risk. The ‘omics’ techniques, namely genomics, proteomics, metabolomics, and transcriptomics, are excellent candidates to provide a better understanding of pathophysiologic mechanisms of disease in CKD, to improve risk stratification of patients with respect to future cardiovascular events, and to identify CKD patients who are likely to respond to a treatment. Following such a strategy, a reliable risk of future events for a particular patient may be calculated and consequently the patient would also benefit from the best available treatment based on their risk profile. Moreover, a further step forward can be represented by the aggregation of multiple omics information by combining different techniques and/or different biological samples. This has already been shown to yield additional information by revealing with more accuracy the exact individual pathway of disease.

Evaluation of red blood cell parameters provided by the UF-5000 urine auto-analyzer in patients with glomerulonephritis

OBJECTIVES

The microscopic examination of hematuria, a cardinal symptom of glomerulonephritis (GN), is time-consuming and labor-intensive. As an alternative, the fully automated urine particle analyzer UF-5000 can interpret the morphological information of the glomerular red blood cells (RBCs) using parameters such as UF-5000 small RBCs (UF-%sRBCs) and Lysed-RBCs.

METHODS

Hematuria samples from 203 patients were analyzed using the UF-5000 and blood and urine chemistries to determine the cut-off values of RBC parameters for GN and non-glomerulonephritis (NGN) classification and confirm their sensitivity to the IgA nephropathy and non-IgA nephropathy groups.

RESULTS

The UF-%sRBCs and Lysed-RBCs values differed significantly between the GN and NGN groups. The cut-off value of UF-%sRBCs was >56.8% (area under the curve, 0.649; sensitivity, 94.1%; specificity, 38.1%; positive predictive value, 68.3%; and negative predictive value, 82.1%), while that for Lysed-RBC was >4.6/μL (area under the curve, 0.708; sensitivity, 82.4%; specificity, 56.0%; positive predictive value, 72.6%; and negative predictive value, 69.1%). Moreover, there was no significant difference in the sensitivity between the IgA nephropathy and non-IgA nephropathy groups (87.1 and 89.8% for UF-%sRBCs and 83.9 and 78.4% for Lysed-RBCs, respectively). In the NGN group, the cut-off values showed low sensitivity (56.0% for UF-%sRBCs and 44.0% for Lysed-RBCs).

CONCLUSIONS

The RBC parameters of the UF-5000, specifically UF-%sRBCs and Lysed-RBCs, showed good cut-off values for the diagnosis of GN.

Urinary Peptides as Potential Non-Invasive Biomarkers for Lupus Nephritis: Results of the Peptidu-LUP Study

Background: Lupus nephritis (LN) is a severe manifestation of Systemic Lupus Erythematosus (SLE). The therapeutic strategy relies on kidney biopsy (KB) results. We tested whether urinary peptidome analysis could non-invasively differentiate active from non-active LN. Design: Urinary samples were collected from 93 patients (55 with active LN and 38 with non-active LN), forming a discovery (n = 42) and an independent validation (n = 51) cohort. Clinical characteristics were collected at inclusion and prospectively for 24 months. The urinary peptidome was analyzed by capillary-electrophoresis coupled to mass-spectrometry, comparing active LN to non-active LN, and assessing chronic lesions and response to therapy. The value of previously validated prognostic (CKD273) and differential diagnostic (LN172) signatures was evaluated. Results: Urinary peptides could not discriminate between active and non-active LN or predict early response to therapy. Tubulo-interstitial fibrosis was correlated to the CKD273. The LN172 score identified 92.5% of samples as LN. Few patients developed new-onset CKD. Conclusions: We validated the CKD273 and LN172 classifiers but did not identify a robust signature that could predict active LN and replace KB. The value of urinary peptidome to predict long-term CKD, or renal flares in SLE, remains to be evaluated.

Monitoring Immune Responses in IgA Nephropathy: Biomarkers to Guide Management

IgA nephropathy (IgAN) is the commonest biopsy-reported primary glomerulonephritis worldwide. It has an incidence which peaks among young adults, and 30 to 40% of patients' progress to end stage kidney disease within twenty years of diagnosis. Ten-year kidney survival rates have been reported to be as low as 35% in some parts of the world. The successful management of IgAN is limited by an incomplete understanding of the pathophysiology of IgAN and a poor understanding of how pathophysiology may vary both from patient to patient and between patient groups, particularly across races. This is compounded by a lack of rigorously designed and delivered clinical trials in IgAN. This is slowly changing, with a number of Phase 2 and 3 clinical trials of novel therapies targeting a number of different putative pathogenic pathways in IgAN due to report in the next 5 years. From our current, albeit limited, understanding of the pathophysiology of IgAN it is unlikely a single therapy will be effective in all patients with IgAN. The successful management of IgAN in the future is, therefore, likely to be reliant on targeted therapies, carefully selected based on an individualized understanding of a patient's risk of progression and underlying pathophysiology. The potential role of biomarkers to facilitate personalization of prognostication and treatment of IgAN is immense. Here we review the progress made over the past decade in identifying and validating new biomarkers, with a particular focus on those that reflect immunological responses in IgAN.

Differential expression of peptides serves as an indicator of IgA nephropathy in pediatric patients

Peptide profiles change significantly with aging and peptide biomarkers discovered in adult patients may not be suitable for the evaluation of pediatric patients. The present study was designed to explore alterations in the serum peptidome profile of pediatric patients with IgA nephropathy (IgAN). A total of 17 children diagnosed with IgAN were recruited as the experimental group, 11 sex-matched healthy children were recruited as a healthy control group and 18 sex-matched children with other glomerular diseases were recruited as a disease control group. Serum peptides of each subject were enriched and analyzed by liquid chromatography with tandem mass spectrometry and the subsequently identified IgAN-specific peptides were evaluated using Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analysis. Subsequently, the function of the IgAN-specific peptides was predicted via sequence comparison with other known functional bioactive peptides. A total of 123 peptides with a fold change >2 (P<0.05) and 48 peptides with a fold change >5 (P<0.05) were identified to be differentially expressed between the pediatric IgAN group and the two other groups. Consequently, two putative peptides that may have bioactive effects in the pathogenesis of IgAN in pediatric patients were identified. The serum peptidome profile of pediatric patients with IgAN was significantly different from the disease control group and the healthy control group. These differentially expressed peptides may serve as biomarkers for the minimally invasive diagnosis of pediatric patients with IgAN. Additionally, the potential bioactive peptides specifically expressed in pediatric IgAN patients that were identified in this study may lay a foundation for exploring new therapies for IgAN, such as the creation of novel peptide drugs.

Proteomics-Based Machine Learning Approach as an Alternative to Conventional Biomarkers for Differential Diagnosis of Chronic Kidney Diseases

Diabetic nephropathy, hypertension, and glomerulonephritis are the most common causes of chronic kidney diseases (CKD). Since CKD of various origins may not become apparent until kidney function is significantly impaired, a differential diagnosis and an appropriate treatment are needed at the very early stages. Conventional biomarkers may not have sufficient separation capabilities, while a full-proteomic approach may be used for these purposes. In the current study, several machine learning algorithms were examined for the differential diagnosis of CKD of three origins. The tested dataset was based on whole proteomic data obtained after the mass spectrometric analysis of plasma and urine samples of 34 CKD patients and the use of label-free quantification approach. The k-nearest-neighbors algorithm showed the possibility of separation of a healthy group from renal patients in general by proteomics data of plasma with high confidence (97.8%). This algorithm has also be proven to be the best of the three tested for distinguishing the groups of patients with diabetic nephropathy and glomerulonephritis according to proteomics data of plasma (96.3% of correct decisions). The group of hypertensive nephropathy could not be reliably separated according to plasma data, whereas analysis of entire proteomics data of urine did not allow differentiating the three diseases. Nevertheless, the group of hypertensive nephropathy was reliably separated from all other renal patients using the k-nearest-neighbors classifier “one against all” with 100% of accuracy by urine proteome data. The tested algorithms show good abilities to differentiate the various groups across proteomic data sets, which may help to avoid invasive intervention for the verification of the glomerulonephritis subtypes, as well as to differentiate hypertensive and diabetic nephropathy in the early stages based not on individual biomarkers, but on the whole proteomic composition of urine and blood.

Chronic kidney disease: a review of proteomic and metabolomic approaches to membranous glomerulonephritis, focal segmental glomerulosclerosis, and IgA nephropathy biomarkers

Chronic Kidney Disease (CKD) is a global health problem annually affecting millions of people around the world. It is a comprehensive syndrome, and various factors may contribute to its occurrence. In this study, it was attempted to provide an accurate definition of chronic kidney disease; followed by focusing and discussing on molecular pathogenesis, novel diagnosis approaches based on biomarkers, recent effective antigens and new therapeutic procedures related to high-risk chronic kidney disease such as membranous glomerulonephritis, focal segmental glomerulosclerosis, and IgA nephropathy, which may lead to end-stage renal diseases. Additionally, a considerable number of metabolites and proteins that have previously been discovered and recommended as potential biomarkers of various CKD_s using ‘-omics-’ technologies, proteomics, and metabolomics were reviewed.

Noninvasive Urinary Monitoring of Progression in IgA Nephropathy

Standard methods for detecting and monitoring of IgA nephropathy (IgAN) have conventionally required kidney biopsies or suffer from poor sensitivity and specificity. The Kidney Injury Test (KIT) Assay of urinary biomarkers has previously been shown to distinguish between various kidney pathologies, including chronic kidney disease, nephrolithiasis, and transplant rejection. This validation study uses the KIT Assay to investigate the clinical utility of the non-invasive detection of IgAN and predicting the progression of renal damage over time. The study design benefits from longitudinally collected urine samples from an investigator-initiated, multicenter, prospective study, evaluating the efficacy of corticosteroids versus Rituximab for preventing progressive IgAN. A total of 131 urine samples were processed for this study; 64 urine samples were collected from 34 IgAN patients, and urine samples from 64 demographically matched healthy controls were also collected; multiple urinary biomarkers consisting of cell-free DNA, methylated cell-free DNA, DMAIMO, MAMIMO, total protein, clusterin, creatinine, and CXCL10 were measured by the microwell-based KIT Assay. An IgA risk score (KIT-IgA) was significantly higher in IgAN patients as compared to healthy control (87.76 vs. 14.03, p < 0.0001) and performed better than proteinuria in discriminating between the two groups. The KIT Assay biomarkers, measured on a spot random urine sample at study entry could distinguish patients likely to have progressive renal dysfunction a year later. These data support the pursuit of larger prospective studies to evaluate the predictive performance of the KIT-IgA score in both screening for non-invasive diagnosis of IgAN, and for predicting risk of progressive renal disease from IgA and utilizing the KIT score for potentially evaluating the efficacy of IgAN-targeted therapies.

Proteomics and Leishmaniasis: Potential Clinical Applications

Leishmaniases are diseases caused by protozoan parasites of the genus Leishmania. They are endemic in 98 countries, affect around 12 million people worldwide and may present several distinct clinical forms. Unfortunately, there are only a few drugs available for treatment of leishmaniasis, which are toxic and not always effective. Different parasite species and different clinical forms require optimization of the treatment or more specific therapies, which are not available. The emergence of resistance is also a matter of concern. Besides, diagnosis can sometimes be complicated due to atypical manifestations and associations with other pathologies. In this review, proteomic data are presented and discussed in terms of their application in important issues in leishmaniasis such as parasite resistance to chemotherapy, diagnosis of active disease in patients and dogs, markers for different clinical forms, identification of virulence factors, and their potential use in vaccination. It is shown that proteomics has contributed to the discovery of potential biomarkers for prognosis, diagnosis, therapeutics, monitoring of disease progression, treatment follow-up and identification of vaccine candidates for specific diseases. However, the authors believe its capabilities have not yet been fully explored for routine clinical analysis for several reasons, which will be presented in this review.

A critical review of adverse effects to the kidney: mechanisms, data sources, and in silico tools to assist prediction

INTRODUCTION

The kidney is a major target for toxicity elicited by pharmaceuticals and environmental pollutants. Standard testing which often does not investigate underlying mechanisms has proven not to be an adequate hazard assessment approach. As such, there is an opportunity for the application of computational approaches that utilize multiscale data based on the Adverse Outcome Pathway (AOP) paradigm, coupled with an understanding of the chemistry underpinning the molecular initiating event (MIE) to provide a deep understanding of how structural fragments of molecules relate to specific mechanisms of nephrotoxicity. Aims covered: The aim of this investigation was to review the current scientific landscape related to computational methods, including mechanistic data, AOPs, publicly available knowledge bases and current in silico models, for the assessment of pharmaceuticals and other chemicals with regard to their potential to elicit nephrotoxicity. A list of over 250 nephrotoxicants enriched with, where possible, mechanistic and AOP-derived understanding was compiled. Expert opinion: Whilst little mechanistic evidence has been translated into AOPs, this review identified a number of data sources of in vitro, in vivo, and human data that may assist in the development of in silico models which in turn may shed light on the interrelationships between nephrotoxicity mechanisms.

Possible Mechanisms by Which Enzymatic Degradation of Human Serum Albumin Can Lead to Bioactive Peptides and Biomarkers

Partial enzymatic degradation of human serum albumin in vivo can lead to the generation of peptides with novel functions or to peptides that might serve as biomarkers for disease. In pathological conditions, biomarkers are possibly produced from the protein in the lysosomes and set free by cell death, or cell death could release acid endoproteases which produce biomarkers by degrading extracellular albumin. Alternatively, lysosomes or secretory granules can be stimulated to release enzymes which produce bioactive peptides from albumin. In physiological conditions, it is proposed that bioactive peptides can be made by enzymatic attack on the protein bound to the endosomal neonatal Fc receptor. The peptides formed could leave the cell, together with native albumin, by exocytosis. Thus, the receptor could have a new function in addition to saving albumin from degradation in the lysosomes. Large amounts of albumin are degraded every day, and this fact can compensate for the short in vivo half-lives of the bioactive peptides. One or more of the procedures outlined above could also apply to other plasma proteins or to structural proteins.

Noninvasive diagnosis of chronic kidney diseases using urinary proteome analysis

Background

In spite of its invasive nature and risks, kidney biopsy is currently required for precise diagnosis of many chronic kidney diseases (CKDs). Here, we explored the hypothesis that analysis of the urinary proteome can discriminate different types of CKD irrespective of the underlying mechanism of disease.

Methods

We used data from the proteome analyses of 1180 urine samples from patients with different types of CKD, generated by capillary electrophoresis coupled to mass spectrometry. A set of 706 samples served as the discovery cohort, and 474 samples were used for independent validation. For each CKD type, peptide biomarkers were defined using statistical analysis adjusted for multiple testing. Potential biomarkers of statistical significance were combined in support vector machine (SVM)-based classifiers.

Results

For seven different types of CKD, several potential urinary biomarker peptides (ranging from 116 to 619 peptides) were defined and combined into SVM-based classifiers specific for each CKD. These classifiers were validated in an independent cohort and showed good to excellent accuracy for discrimination of one CKD type from the others (area under the receiver operating characteristic curve ranged from 0.77 to 0.95). Sequence analysis of the biomarkers provided further information that may clarify the underlying pathophysiology.

Conclusions

Our data indicate that urinary proteome analysis has the potential to identify various types of CKD defined by pathological assessment of renal biopsies and current clinical practice in general. Moreover, these approaches may provide information to model molecular changes per CKD.

Reprint of: Proteomics in cardiovascular diseases: Unveiling sex and gender differences in the era of precision medicine

Cardiovascular diseases (CVDs) represent the most important cause of mortality in women and in men. Contrary to the long-standing notion that the effects of the major risk factors on CVD outcomes are the same in both sexes, recent evidence recognizes new, potentially independent, sex/gender-related risk factors for CVDs, and sex/gender-differences in the clinical presentation of CVDs have been demonstrated. Furthermore, some therapeutic options may not be equally effective and safe in men and women. In this context, proteomics offers an extremely useful and versatile analytical platform for biomedical researches that expand from the screening of early diagnostic and prognostic biomarkers to the investigation of the molecular mechanisms underlying CDVs. In this review, we summarized the current applications of proteomics in the cardiovascular field, with emphasis on sex and gender-related differences in CVDs.

SIGNIFICANCE

Increasing evidence supports the profound effect of sex and gender on cardiovascular physio-pathology and the response to drugs. A clear understanding of the mechanisms underlying sexual dimorphisms in CVDs would not only improve our knowledge of the etiology of these diseases, but could also inform health policy makers and guideline committees in tailoring specific interventions for the prevention, treatment and management of CVDs in both men and women.

Urinary proteomics using capillary electrophoresis coupled to mass spectrometry for diagnosis and prognosis in kidney diseases

PURPOSE OF REVIEW

Urine is the most useful of body fluids for biomarker research. Therefore, we have focused on urinary proteomics, using capillary electrophoresis coupled to mass spectrometry, to investigate kidney diseases in recent years.

RECENT FINDINGS

Several urinary proteomics studies for the detection of various kidney diseases have indicated the potential of this approach aimed at diagnostic and prognostic assessment. Urinary protein biomarkers such as collagen fragments, serum albumin, α-1-antitrypsin, and uromodulin can help to explain the processes involved during disease progression.

SUMMARY

Urinary proteomics has been used in several studies in order to identify and validate biomarkers associated with different kidney diseases. These biomarkers, with improved sensitivity and specificity when compared with the current gold standards, provide a significant alternative for diagnosis and prognosis, as well as improving clinical decision-making.

Candidate Urine Peptide Biomarkers for IgA Nephropathy: Where Are We Now?

Early detection, prognosis, and management of IgA nephropathy (IgAN) remain a challenge. Histological examination of renal tissue still comprises the only way to confirm an IgAN diagnosis. It is of great importance to establish noninvasive diagnostic, prognostic, and predictive biomarkers that would improve the clinical care and outcome of patients suffering from IgAN. This review summarises the findings from previous mass spectrometry- (MS-) based studies dedicated to the discovery of urinary peptide profiles specific to IgAN. There is a substantial number of urinary peptides that have been discovered to date, which show promise as biomarkers of IgAN; however, all of them require further, rigorous validation in well-planned studies, involving a large number of subjects who represent diverse and numerous populations.

Proteomics for Biomarker Identification and Clinical Application in Kidney Disease

Treatment effectiveness for kidney disease is limited by lack of accuracy, sensitivity, specificity of diagnostic, prognostic, and therapeutic biomarkers. The gold standard test renal biopsy along with serum creatinine and proteinuria is often necessary to establish a diagnosis, particularly in glomerular disease. Proteomics has become a powerful tool for novel biomarker discovery in kidney disease. Novel proteomics offer earlier and more accurate diagnosis of renal pathology than possible with traditional biomarkers such as serum creatinine and urine protein. In addition, proteomic biomarkers could also be useful to choose the most suitable therapeutic targets. This review focuses on the current status of proteomic biomarkers from animal models (5/6 nephrectomy, unilateral ureteral obstruction, and diabetic nephropathy) and human studies (chronic kidney disease, glomerular diseases, transplantation, dialysis, acute and drug-induced kidney injury) to assess relevant findings and clinical usefulness. Current issues and problems related to the discovery, validation, and clinical application of proteomic biomarkers are discussed. We also describe several proteomic strategies highlighting technologic advancements, specimen selection, data processing and analysis. This review might provide help in future proteomic studies to improve the diagnosis and management of kidney disease.

Proteomics in cardiovascular diseases: Unveiling sex and gender differences in the era of precision medicine

Cardiovascular diseases (CVDs) represent the most important cause of mortality in women and in men. Contrary to the long-standing notion that the effects of the major risk factors on CVD outcomes are the same in both sexes, recent evidence recognizes new, potentially independent, sex/gender-related risk factors for CVDs, and sex/gender-differences in the clinical presentation of CVDs have been demonstrated. Furthermore, some therapeutic options may not be equally effective and safe in men and women. In this context, proteomics offers an extremely useful and versatile analytical platform for biomedical researches that expand from the screening of early diagnostic and prognostic biomarkers to the investigation of the molecular mechanisms underlying CDVs. In this review, we summarized the current applications of proteomics in the cardiovascular field, with emphasis on sex and gender-related differences in CVDs.

SIGNIFICANCE

Increasing evidence supports the profound effect of sex and gender on cardiovascular physio-pathology and the response to drugs. A clear understanding of the mechanisms underlying sexual dimorphisms in CVDs would not only improve our knowledge of the etiology of these diseases, but could also inform health policy makers and guideline committees in tailoring specific interventions for the prevention, treatment and management of CVDs in both men and women.

Comparative proteomic analysis of urine and laser microdissected glomeruli in IgA nephropathy

The purpose of the present study was to identify the differential proteins that synchronously change in urine and glomeruli and could be used to monitor glomerular lesions of IgA nephropathy (IgAN). The proteomes of urine and glomeruli from four IgAN patients who were graded III/IV according to the grading system of Lee et al. were compared to the urine proteomes of four healthy volunteers and the glomeruli proteomes of adjacent normal tissue from four patients with renal tumors, respectively. Western blot, enzyme-linked immunosorbent assay and immunofluorescence assay were applied to verify the results of the proteomic analysis. In the proteomic analysis of urine from IgAN patients and healthy volunteers, 714 proteins were identified, with 246 proteins identified as differential proteins. In the proteomic analysis of glomeruli from renal biopsy tissue of IgAN patients and from adjacent normal tissue of patients with renal tumors, 161 proteins were identified altogether, and 20 proteins of these were recognized as differential proteins. After comparatively analyzing the differential proteins identified in the urine and glomeruli, five synchronously changed differential proteins were found: complement C9, Ig kappa chain C region and three cytoskeleton proteins. In summary, our findings indicate that certain immunological indices in urine appear to be associated with glomerular lesions of IgAN.

Pro: urine proteomics as a liquid kidney biopsy: no more kidney punctures!

In this article, the benefits of urinary proteomics in comparison with kidney biopsy are discussed. The majority of urinary proteins are generated by the kidney, hence the urinary proteome holds substantial information on the kidney, and assessment of the urinary proteome could be considered a 'liquid biopsy'. The main question is how well the information contained in the urinary proteome can be assessed today, if it is ready to be routinely used, and what are the advantages and possible disadvantages in comparison with current standards. Since chronic kidney disease (CKD) is by far the largest area in nephrology based on the number of patients affected, the focus of this article is on CKD. Substantial progress was made in the last decade in urinary proteomics, and today we have comparable urinary proteome datasets of tens of thousands of subjects available. Clinical proteomics studies in CKD including close to, or even exceeding, 1000 subjects have recently been published, demonstrating a benefit over the current state-of-the-art in diagnosis and especially prognosis. The first large multicentric randomized controlled intervention trial aiming at preventing CKD by employing urinary proteomics-guided intervention has been initiated recently. These data provide ample evidence for the utility and value of urinary proteomics in nephrology. A further consideration is that the purpose of the biopsy, be it 'liquid' or 'solid', is to guide intervention. However, essentially all drug targets are proteins, not microscopic structures. Therefore, obtaining information on the proteome to guide intervention appears to be the most appropriate approach. Presenting more detailed evidence, I argue that urinary proteome analysis can, in most cases, be employed to guide therapeutic intervention, can be repeated multiple times as it is without any direct risk or discomfort and can be considered as a liquid biopsy.

The Origin and Activities of IgA1-Containing Immune Complexes in IgA Nephropathy

IgA nephropathy (IgAN) is the most common primary glomerulonephritis, frequently leading to end-stage renal disease, as there is no disease-specific therapy. IgAN is diagnosed from pathological assessment of a renal biopsy specimen based on predominant or codominant IgA-containing immunodeposits, usually with complement C3 co-deposits and with variable presence of IgG and/or IgM. The IgA in these renal deposits is galactose-deficient IgA1, with less than a full complement of galactose residues on the O-glycans in the hinge region of the heavy chains. Research from the past decade led to the definition of IgAN as an autoimmune disease with a multi-hit pathogenetic process with contributing genetic and environmental components. In this process, circulating galactose-deficient IgA1 (autoantigen) is bound by antiglycan IgG or IgA (autoantibodies) to form immune complexes. Some of these circulating complexes deposit in glomeruli, and thereby activate mesangial cells and induce renal injury through cellular proliferation and overproduction of extracellular matrix components and cytokines/chemokines. Glycosylation pathways associated with production of the autoantigen and the unique characteristics of the corresponding autoantibodies in patients with IgAN have been uncovered. Complement likely plays a significant role in the formation and the nephritogenic activities of these complexes. Complement activation is mediated through the alternative and lectin pathways and probably occurs systemically on IgA1-containing circulating immune complexes as well as locally in glomeruli. Incidence of IgAN varies greatly by geographical location; the disease is rare in central Africa but accounts for up to 40% of native-kidney biopsies in eastern Asia. Some of this variation may be explained by genetically determined influences on the pathogenesis of the disease. Genome-wide association studies to date have identified several loci associated with IgAN. Some of these loci are associated with the increased prevalence of IgAN, whereas others, such as deletion of complement factor H-related genes 1 and 3, are protective against the disease. Understanding the molecular mechanisms and genetic and biochemical factors involved in formation and activities of pathogenic IgA1-containing immune complexes will enable the development of future disease-specific therapies as well as identification of non-invasive disease-specific biomarkers.

Update on immunoglobulin a nephropathy. Part II: Clinical, diagnostic and therapeutical aspects

Immunoglobulin A nephropathy (IgAN) is characterized by different clinical manifestations and by long-term different outcomes. Major problem for the physicians is to understanding which patients are at risk of a disease evolution and to prescribe the right therapy to the right patients. Indeed, in addition to patients with a stable disease with no trend to evolution or even with a spontaneous recovery, patients with an active disease and patients with a rapidly evolving glomerulonephritis are described. Several histopathological, biological and clinical markers have been described and are currently used to a better understanding of patients at risk, to suggest the right therapy and to monitor the therapy effect and the IgAN evolution over time. The clinical markers are the most reliable and allow to divide the IgAN patients into three categories: The low risk patients, the intermediate risk patients and the high risk patients. Accordingly, the therapeutic measures range from no therapy with the only need of repeated controls, to supportive therapy eventually associated with low dose immunosuppression, to immunosuppressive treatment in the attempt to avoid the evolution to end stage renal disease. However the current evidence about the different therapies is still matter of discussion. New drugs are in the pipeline and are described. They are object of randomized controlled trials, but studies with a number of patients adequately powered and with a long follow up are needed to evaluate efficacy and safety of these new drugs.

Urinary Biomarkers of Brain Diseases

Biomarkers are the measurable changes associated with a physiological or pathophysiological process. Unlike blood, urine is not subject to homeostatic mechanisms. Therefore, greater fluctuations could occur in urine than in blood, better reflecting the changes in human body. The roadmap of urine biomarker era was proposed. Although urine analysis has been attempted for clinical diagnosis, and urine has been monitored during the progression of many diseases, particularly urinary system diseases, whether urine can reflect brain disease status remains uncertain. As some biomarkers of brain diseases can be detected in the body fluids such as cerebrospinal fluid and blood, there is a possibility that urine also contain biomarkers of brain diseases. This review summarizes the clues of brain diseases reflected in the urine proteome and metabolome.

Introduction to Proteomics Technologies

Compared to genomics or transcriptomics, proteomics is often regarded as an "emerging technology," i.e., as not having reached the same level of maturity. While the successful implementation of proteomics workflows and technology still requires significant levels of expertise and specialization, great strides have been made to make the technology more powerful, streamlined and accessible. In 2014, two landmark studies published the first draft versions of the human proteome.We aim to provide an introduction specifically into the background of mass spectrometry (MS)-based proteomics. Within the field, mass spectrometry has emerged as a core technology. Coupled to increasingly powerful separations and data processing and bioinformatics solution, it allows the quantitative analysis of whole proteomes within a matter of days, a timescale that has made global comparative proteome studies feasible at last. We present and discuss the basic concepts behind proteomics mass spectrometry and the accompanying topic of protein and peptide separations, with a focus on the properties of datasets emerging from such studies.

Immunoglobulin A nephropathy: current progress and future directions

Immunoglobulin A (IgA) nephropathy is the most prevalent form of primary glomerulonephritis that often leads to end-stage kidney failure, thereby representing a major health challenge worldwide. Tremendous effort has been dedicated to the diagnosis, monitoring, and treatment of the disease, and the past several years have witnessed exciting advances that have enriched our understanding of the biology, etiology, and pathology of IgA nephropathy. The disease is characterized by predominant deposition of IgA immune complexes that progressively causes activation of mesangial cells, glomerular inflammation, and ultimately renal injury. Multiple recent independent high-throughput studies in cohorts have identified key susceptibility alleles, such as the major histocompatibility complex loci that are significantly associated with the risk of disease occurrence. Notably, a fraction of these risk loci encode proteins that participate in immune defense against mucosal pathogens, particularly intestinal nematodes, indicating a linkage between IgA-mediated antihelminth immunity and the pathogenesis of IgA nephropathy. The emerging "omics" technology also allows for systemic analysis of urinary and serum samples as a noninvasive procedure for diagnosis and prognosis, as demonstrated by several studies implicating the proteomic signature and microRNA profile as promising diagnostic and prognostic parameters. In the clinic, the current treatment protocol relies on suppression of the renin-angiotensin system to control blood pressure and proteinuria. This review scrutinizes and summarizes recent relevant findings that aim to translate researchers' benchside knowledge of disease initiation and development into patients' bedside diagnosis and therapy.

Urine proteomic analysis in cystinuric children with renal stones

INTRODUCTION

The gene mutations responsible for cystinuria do not fully explain kidney stone activity, suggesting that specific proteins may serve as promoters of cystine precipitation, aggregation or epithelial adherence. In this study we assessed (1) the differences in the urinary proteins between children with cystinuria and kidney stones (CYS) and healthy controls (HC), with particular attention to the fibrosis-related proteins, and (2) the presence of diagnostic biomarkers for CYS.

MATERIAL AND METHODS

We conducted a pilot study comparing individual urinary proteomes of 2 newly diagnosed children with CYS and 2 age- and gender-matched HC, using liquid chromatography-mass spectrometry. Relative protein abundance was estimated using spectral counting. Proteins of interest in both CYS and HC were selected using the following criteria: i) ≥5 spectral counts; ii) ≥2-fold difference in spectral counts; and iii) ≤0.05 p-value for the Fisher's Exact Test.

DISCUSSION

This study demonstrates a different urinary polypeptide profile in two children with CYS compared to two HC. Of the 623 proteins identified by proteomic analysis, 180 exhibited at least a 2-fold increased relative abundance in CYS compared to HC. Of these, 39 were involved in response to stress, 26 in response to wounding, 21 in inflammatory response, 18 in immune response, and 4 in cellular response to oxidative stress. 133 proteins were found only in children with CYS, 33 of which met the selection criteria. Of these 33 unique proteins, six are known to be associated with fibrosis pathways (Table). The major limitation of this study is the small number of samples that were analyzed. Validation using highly specific methods such as ELISA is needed.

CONCLUSION

We provide proteomic evidence of oxidative injury, inflammation, wound healing and fibrosis in two children with CYS. We speculate that oxidative stress and inflammation may cause remodeling via actin and vimentin pathways, leading to fibrosis. Additionally, we identified ITIH and MMP-9 as potential diagnostic biomarkers and novel therapeutic targets in CYS. These proteins merit further investigation.

Matching Kidneys and Urines: Establishing Noninvasive Surrogates of Intrarenal Events in Primary Glomerulonephritis

Kidney biopsy is the gold standard procedure for providing diagnostic and prognostic information for patients with glomerular-based diseases, however, the utility of this procedure for assessing longitudinal disease activity is limited. The intense search for noninvasive biomarkers of kidney disease activity and injury is driven in large part by the inherent risks of the kidney biopsy procedure and limited information derived from the morphologic description of biopsy findings. Furthermore, gaps in our understanding of the core intrarenal molecular processes underlying the development and progression of glomerular-based diseases has limited the development of effective targeted therapy. In this review, we discuss the potential utility of molecular analysis of the urine to provide a dynamic window into intrarenal molecular and morphologic responses. We focus on molecular analysis of the urine to identify noninvasive surrogate markers of kidney responses, with the goal of using these biomarkers as more sensitive indicators of progression and tissue-level responses to therapeutic interventions in patients with primary glomerulonephritis.

Proteomics and autoimmune kidney disease

Proteomics has long been considered an ideal platform, and urine an ideal source for biomarker discovery in human autoimmune kidney diseases. A number of studies have examined the urine proteome to identify biomarkers of disease activity, kidney pathology, and response to therapy. Increasingly, proteomic studies of kidney disease have expanded to include blood, circulating cells and kidney tissue. Recently the clinical potential of renal proteomics has been realized through a handful of investigations whose results appear to be applicable to patient care. In this review, approaches to the proteomic evaluation of autoimmune kidney diseases will be considered in the context of developing clinically useful disease biomarkers.

Sandwich enzyme-linked immunosorbent assay for the quantification of human serum albumin fragment 408-423 in bodily fluids

Urinary levels of human serum albumin (hSA) fragment 408-423 have been proposed to represent an early marker for graft-versus-host disease (GvHD) and chronic kidney diseases. Here, we developed an enzyme-linked immunosorbent assay (ELISA) for the quantification of hSA(408-423). The sandwich ELISA has a detection limit of 0.5ng/ml and is highly specific for hSA(408-423) because it does not cross-react with other albumin fragments or the full-length precursor. This ELISA allows rapid and convenient quantification of hSA(408-423) in bodily fluids, further clarifying the prognostic and diagnostic value of this peptide in GvHD, kidney disease, and other disorders.

Advances in urinary protein biomarkers for urogenital and non-urogenital pathologies

The discovery of protein biomarkers that reflect the biological state of the body is of vital importance to disease management. Urine is an ideal source of biomarkers that provides a non-invasive approach to diagnosis, prognosis and prediction of diseases. Consequently, the study of the human urinary proteome has increased dramatically over the last 10 years, with many studies being published. This review focuses on urinary protein biomarkers that have shown potential, in initial studies, for diseases affecting the urogenital tract, specifically chronic kidney disease and prostate cancer, as well as other non-urogenital pathologies such as breast cancer, diabetes, atherosclerosis and osteoarthritis. PubMed was searched for peer-reviewed literature on the subject, published in the last 10 years. The keywords used were "urine, biomarker, protein, and/or prostate cancer/breast cancer/chronic kidney disease/diabetes/atherosclerosis/osteoarthritis". Original studies on the subject, as well as a small number of reviews, were analysed including the strengths and weaknesses, and we summarized the performance of biomarkers that demonstrated potential. One of the biggest challenges found is that biomarkers are often shared by several pathologies so are not specific to one disease. Therefore, the trend is shifting towards implementing a panel of biomarkers, which may increase specificity. Although there have been many advances in urinary proteomics, these have not resulted in similar advancements in clinical practice due to high costs and the lack of large data sets. In order to translate these potential biomarkers to clinical practice, vigorous validation is needed, with input from industry or large collaborative studies.

Urinary protein selectivity in nephrotic syndrome and pregnancy: resurrection of a biomarker when renal biopsy is contraindicated

Significant proteinuria in pregnancy can indicate the presence of serious conditions requiring investigation and treatment. The nephrotic syndrome in pregnancy presents a multitude of difficulties and is a relative contraindication of renal biopsy, particularly in the third trimester. We present a case of nephrotic syndrome of unknown cause presenting at 33 weeks of pregnancy. With renal biopsy contraindicated, we used the urine protein selectivity test, a largely discarded test predicting steroid-responsive nephrotic syndrome, to help inform the decision to give steroids. This led to a successful clinical outcome including the avoidance of neonatal ICU care for baby.

Mass spectrometry-based proteomics in Chest Medicine, Gerontology, and Nephrology: subgroups omics for personalized medicine

Mass spectrometry (MS) is currently the most promising tool for studying proteomics to investigate largescale proteins in a specific proteome. Emerging MS-based proteomics is widely applied to decipher complex proteome for discovering potential biomarkers. Given its growing usage in clinical medicine for biomarker discovery to predict, diagnose and confer prognosis, MS-based proteomics can benefit study of personalized medicine. In this review we introduce some fundamental MS theory and MS-based quantitative proteomic approaches as well as several representative clinical MS-based proteomics issues in Chest Medicine, Gerontology, and Nephrology.

Fibrinogen alpha chain precursor and apolipoprotein A-I in urine as biomarkers for noninvasive diagnosis of calcium oxalate nephrolithiasis: a proteomics study

Calcium oxalate nephrolithiasis is the most common urological disease, but noninvasive and convenient methods of diagnosis are rarely available. Objective. The present study aimed to identify potential urine biomarkers for noninvasive diagnosis of CaOx nephrolithiasis. Methodology. Urine samples from 72 patients with CaOx nephrolithiasis and 30 healthy controls were collected and proteomics analysis was performed using matrix-assisted laser desorption/ionization-time of flight-mass spectrometer (MALDI-TOF-MS). Results. Thirteen proteins/peptides displayed statistically significant differences. The peptides of m/z 1207.23 and 2773.86 were selected by the genetic algorithm (GA) to build a possible diagnostic model. The area under the curve of m/z 1207.23 and 2773.86 was 0.936 and 0.987, respectively. The diagnostic model in distinguishing patients and healthy subjects showed 100% sensitivity and specificity. The peak at m/z 2773.86 was identified as fibrinogen alpha chain (FGA) with the sequence G.EGDFLAEGGGVR.G, and the peak at m/z 2773.86 was identified as apolipoprotein A-I (apoA-I) with the sequence L.PVLESFKVSFLSALEEYTKKLNTQ. Conclusion. The study results strongly suggested that urinary FGA and apoA-I are highly sensitive and specific biomarkers for noninvasive diagnosis of CaOx nephrolithiasis.

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.

Unveiling the rat urinary proteome with three complementary proteomics approaches

Urine is a suitable biological fluid to look for markers of physiological and pathological processes, including renal and nonrenal diseases. In addition, it is an optimal body sample for diagnosis, because it is easily obtained without invasive procedures and can be sampled in large quantities at almost any time. Rats are frequently used as a model to study human diseases, and rat urine has been analyzed to search for disease biomarkers. The normal human urinary proteome has been studied extensively, but the normal rat urinary proteome has not been studied in such depth. In light of this, we were prompted to analyze the normal rat urinary proteome using three complementary proteomics platforms: SDS-PAGE separation, followed by LC-ESI-MS/MS; 2DE, followed by MALDI-TOF-TOF and 2D-liquid chromatography-chromatofocusing, followed by LC-ESI-Q-TOF. A total of 366 unique proteins were identified, of which only 5.2% of unique proteins were identified jointly by the three proteomics platforms used. This suggests that simultaneous proteomics techniques provide complementary and nonredundant information. Our analysis affords the most extensive rat urinary protein database currently available and this may be useful in the study of renal physiology and in the search for biomarkers related to renal and nonrenal diseases.

Urinary peptide profiling to differentiate between minimal change disease and focal segmental glomerulosclerosis

BACKGROUND

Minimal change disease (MCD) and primary focal segmental glomerulosclerosis (FSGS) are the main causes of primary idiopathic nephrotic syndrome in children and adults, with diagnosis being essential for the appropriate choice of therapy and requiring renal biopsy. However, the presence of only normal glomeruli on renal biopsy of FSGS patients may lead to the misclassification of these patients as having MCD. The aim of this study was to (i) compare the peptide profile of MCD and FSGS patients with that of a group of healthy subjects, (ii) generate and validate a class prediction model to classify MCD and FSGS patients and (ii) identify candidate biomarkers of these glomerular entities by analysis of the urinary peptidome.

METHODS

The urinary peptide profile was analyzed by magnetic bead-based technology combined with MALDI-TOF mass spectrometry in 44 patients diagnosed of MCD (n = 22) and FSGS (n = 22). The resulting spectra were compiled and analyzed using ClinProTools software.

RESULTS

A class prediction model was developed to differentiate MCD and FSGS patients. The validation of this model correctly classified 81.8% (9/11) of MCD patients and 72.7% (8/11) of FSGS patients. Moreover, the signal with m/z 1913.60, identified as a fragment of uromodulin, and the signal with m/z 2392.54, identified as a fragment of alpha-1-antitrypsin, showed higher and lower peak areas, respectively, in FSGS patients compared with MCD patients.

CONCLUSIONS

The simple, non-invasive technique described in the present study may be a useful tool to help clinicians by confirming diagnoses achieved by renal biopsy, thereby reducing misdiagnoses and avoiding the implementation of inappropriate therapies.