Proteomic urinary biomarker approach in renal disease: from discovery to implementation

Urinary peptidome analysis in CKD and IgA nephropathy

Background

Chronic kidney disease (CKD) has emerged as a significant challenge to human health and economic stability in aging societies worldwide. Current clinical practice strategies remain insufficient for the early identification of kidney dysfunction, and the differential diagnosis of immunoglobulin A nephropathy (IgAN) predominantly relies on invasive kidney biopsy procedures.

Methods

First, we assessed a case-control cohort to obtain urine samples from healthy controls and biopsy-confirmed CKD patients. Matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) was applied to detect urinary peptide and then these urinary peptide profiles were used to construct diagnostic models to distinguish CKD patients from controls and identify IgAN patients from other nephropathy patients. Furthermore, we assessed the robustness of the diagnostic models and their reproducibility by applying different algorithms.

Results

A rapid and accurate working platform for detecting CKD and its IgAN subtype based on urinary peptide pattern detected by MALDI-TOF MS was established. Naturally occurring urinary peptide profiles were used to construct a diagnostic model to distinguish CKD patients from controls and identify IgAN patients from other nephropathy patients. The performance of several algorithms was assessed and demonstrated that the robustness of the diagnostic models as well as their reproducibility were satisfactory.

Conclusions

The present findings suggest that the CKD-related and IgAN-specific urinary peptides discovered facilitate precise identification of CKD and its IgAN subtype, offering a dependable framework for screening conditions linked to renal dysfunction. This will aid in comprehending the pathogenesis of nephropathy and identifying potential protein targets for the clinical management of nephropathy.

Pursuing Diabetic Nephropathy through Aqueous Humor Proteomics Analysis

In order to determine the possible aqueous humor (AH) proteins involved in diabetic nephropathy (DN) progression, we performed gel electrophoresis-liquid chromatography-tandem mass spectrometry protein profiling of AH samples from 5 patients with proliferative diabetic retinopathy (PDR) combined DN and 5 patients with PDR. Function enrichment analyses were carried out after the identification of differentially expressed proteins (DEPs). Protein-protein interaction networks were then built and the Search Tool for the Retrieval of Interacting Genes database and CytoNCA plugin in Cytoscape were utilized for module analysis. Ingenuity Pathway Analysis (IPA) was used to analyze disease and biological function, Tox function enrichment and upstream regulatory molecules/networks. Fifty-four DEPs were finally confirmed, whose enriched functions and pathways covered cell adhesion, extracellular exosome, complement activation, complement and coagulation cascades, etc. Nine hub genes were identified, including NCAM1, PLG, APOH, C3, PSAP, RBP4, CDH2, NUCB1, and GNS. IPA showed that C3 and PLG are involved in renal and urological system abnormalities. Conclusively, DEPs and hub proteins confirmed in this exploratory AH proteomic analysis may help us gain a deeper understanding of the molecular mechanisms involved in DN progression, providing novel candidate biomarkers for the early detection for diagnosis of DN.

Application of peptide biomarkers in life analysis based on liquid chromatography-mass spectrometry technology

Biomedicine is developing rapidly in the 21st century. Among them, the qualitative and quantitative analysis of peptide biomarkers is of considerable importance for the diagnosis and therapy of diseases and the quality evaluation of drugs and food. The identification and quantitative analysis of peptides have been going on for decades. Traditionally, immunoassays or biological assays are generally used to quantify peptides in biological matrices. However, the selectivity and sensitivity of these methods cannot meet the requirements of the application. The separation and analysis technique of liquid chromatography-mass spectrometry (LC-MS) supplies a reliable alternative. In contrast to immunoassays, LC-MS methods are capable of providing the analytical prowess necessary to satisfy the demands of peptide biomarker research in the life sciences arena. This review article provides a historical account of the in-roads made by LC-MS technology for the detection of peptide biomarkers in the past 10 years, with the focus on the qualification/quantification developments and their applications.

Emergent players in renovascular disease

Renovascular disease (RVD) remains a common etiology of secondary hypertension. Recent clinical trials revealed unsatisfactory therapeutic outcomes of renal revascularization, leading to extensive investigation to unravel key pathophysiological mechanisms underlying irreversible functional loss and structural damage in the chronically ischemic kidney. Research studies identified complex interactions among various players, including inflammation, fibrosis, mitochondrial injury, cellular senescence, and microvascular remodeling. This interplay resulted in a shift of our understanding of RVD from a mere hemodynamic disorder to a pro-inflammatory and pro-fibrotic pathology strongly influenced by systemic diseases like metabolic syndrome (MetS), hypertension, diabetes mellitus, and hyperlipidemia. Novel diagnostic approaches have been tested for early detection and follow-up of RVD progression, using new imaging techniques and biochemical markers of renal injury and dysfunction. Therapies targeting some of the pathological pathways governing the development of RVD have shown promising results in animal models, and a few have moved from bench to clinical research. This review summarizes evolving understanding in chronic ischemic kidney injury.

Urinary and plasma proteomics to discover biomarkers for diagnosing between diabetic nephropathy and minimal change nephrotic syndrome or membranous nephropathy

The choice of treatment for primary nephrotic syndrome depends on the pathologic type of the disorder. Renal biopsy is necessary for a definitive diagnosis, but it is burdensome for the patients, and can be avoided if tests could be performed using urine or plasma. In this study, we analyzed 100 urinary proteins, 141 plasma proteins, and 57 urine/plasma ratios in cases of diabetic nephropathy (DN; n = 11), minimal change nephrotic syndrome (MCNS; n = 14), and membranous nephropathy (MN; n = 23). We found that the combination of urinary retinol-binding protein 4 and SH3 domain-binding glutamic acid-rich-like protein 3 could distinguish between MCNS and DN, with an area under the curve (AUC) of 0.9740. On the other hand, a selectivity index (SI) based on serotransferrin and immunoglobulin G, which is often used in clinical practice, distinguished them with an AUC of 0.9091. Similarly, the combination of urinary afamin and complement C3 urine/plasma ratio could distinguish between MN and DN with an AUC of 0.9842, while SI distinguished them with an AUC of 0.8538. Evidently, the candidates identified in this study were superior to the SI method. Thus, the aim was to test these biomarkers for accurate diagnosis and to greatly reduce the burden on patients.

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Renal biopsy is necessary for a definitive diagnosis of primary nephrotic syndrome.

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Renal biopsy is a heavy burden for patients, and a less burdensome test is desired.

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We discovered at least 6 diagnostic biomarkers using urinary and plasma proteomics.

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Combination allowed to judge the disease more accurately than selectivity index.

Comparison of the amniotic fluid and fetal urine peptidome for biomarker discovery in renal developmental disease

Production of amniotic fluid (AF) is view as predominately driven by excretion of fetal urine (FU). However, the origin of AF peptides, often considered as potential biomarkers of developmental diseases, has never been investigated. Here, we evaluated the FU origin of AF peptides and if the AF peptide content can be used as a surrogate of FU. The abundance of endogenous peptides was analyzed by capillary electrophoresis coupled to mass spectrometry in 216 AF and 64 FU samples. A total of 2668 and 3257 peptides was found in AF and FU respectively. The AF peptidome largely overlapped with the FU peptidome, ranging from 54% in the second pregnancy trimester to 65% in the third trimester. Examination of a subset of 16 paired AF and FU samples revealed that 67 peptides displayed a significant positively correlated abundance in AF and FU, strongly suggesting that their presence in AF was directly associated to FU excretion. As proof-of-concept we showed that measuring the AF abundance of these 67 peptides of FU origin allowed prediction of postnatal renal survival in fetuses with posterior urethral valves. These results demonstrate that the AF peptidome can be considered as a good surrogate of the FU peptidome.

Multiplexed MRM-based protein quantification of putative prognostic biomarkers for chronic kidney disease progression in plasma

Current diagnostic measures for Chronic Kidney Disease (CKD) include detection of reduced estimated glomerular filtration rate (eGFR) and albuminuria, which have suboptimal accuracies in predicting disease progression. The disease complexity and heterogeneity underscore the need for multiplex quantification of different markers. The goal of this study was to determine the association of six previously reported CKD-associated plasma proteins [B2M (Beta-2-microglobulin), SERPINF1 (Pigment epithelium-derived factor), AMBP (Protein AMBP), LYZ (Lysozyme C), HBB (Hemoglobin subunit beta) and IGHA1 (Immunoglobulin heavy constant alpha 1)], as measured in a multiplex format, with kidney function, and outcome. Antibody-free, multiple reaction monitoring mass spectrometry (MRM) assays were developed, characterized for their analytical performance, and used for the analysis of 72 plasma samples from a patient cohort with longitudinal follow-up. The MRM significantly correlated (Rho = 0.5–0.9) with results from respective ELISA. Five proteins [AMBP, B2M, LYZ, HBB and SERPINF1] were significantly associated with eGFR, with the three former also associated with unfavorable outcome. The combination of these markers provided stronger associations with outcome (p < 0.0001) compared to individual markers. Collectively, our study describes a multiplex assay for absolute quantification and verification analysis of previously described putative CKD prognostic markers, laying the groundwork for further use in prospective validation studies.

Urinary proteomics of Henoch-Schönlein purpura nephritis in children using liquid chromatography-tandem mass spectrometry

BACKGROUND

Henoch-Schönlein purpura nephritis (HSPN) is the principal cause of morbidity and mortality in children with Henoch-Schönlein purpura (HSP). However, the criteria for risk assessment currently used is not satisfactory. The urine proteome may provide important clues to indicate the development of HSPN.

METHODS

Here, we detected and compared the urine proteome of patients with HSPN and healthy controls by liquid chromatography-tandem mass spectrometry (LC-MS/MS) in the data-independent acquisition (DIA) mode. The differentially expressed proteins were analysed by gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. For validation, enzyme-linked immunosorbent assay (ELISA) was used to analyse the selected proteins.

RESULTS

A total of 125 proteins (29 upregulated and 96 downregulated) were found to be differentially expressed in children with HSPN compared with the controls. Forty-one proteins were predicted to have direct interactions. The enriched pathways mainly included focal adhesion, cell adhesion molecules, the PI3K-Akt signalling pathway, ECM-receptor interactions and so on. Cell adhesion related to the pathogenesis of HSPN was the main biological process identified in this study. The decrease in two proteins (integrin beta-1 and tenascin) was validated by ELISA.

CONCLUSIONS

Our study provides new insights into the assessment of HSPN progression in children, as well as new potential biomarkers. The data confirm the value of the urinary proteome in capturing the emergence of HSPN.

A single-center study to evaluate the efficacy of a fetal urine peptide signature predicting postnatal renal outcome in fetuses with posterior urethral valves

BACKGROUND

Posterior urethral valves (PUVs) account for 17% of pediatric renal failure. The management of pregnancies involving fetuses with PUV is hampered by the fact that current clinical parameters obtained from fetal ultrasound and/or fetal urine biochemistry are insufficient to predict postnatal renal function. We previously have developed a fetal urine peptide signature (12PUV) that predicted with high precision postnatal renal failure at 2 years of age in fetuses with PUV. Here, we evaluated the accuracy of this signature to predict postnatal renal outcome in fetuses with PUV in an independent single-center study.

METHODS

Thirty-three women carrying fetuses with suspected PUV were included. Twenty-five fetuses received vesicoamniotic shunts during pregnancy. PUV was confirmed postnatally in 23 patients. Of those 23 fetuses, 2 were lost in follow-up. Four and 3 patients died in the pre- and perinatal periods, respectively. Follow-up renal function at 6 months of age was obtained for the remaining 14 patients. The primary outcome was early renal failure, defined by an eGFR < 60 mL/min/1.73 m² before 6 months of age or pre- or perinatal death.

RESULTS

The peptide signature predicted postnatal renal outcome in postnatally confirmed PUV fetuses with an AUC of 0.94 (95%CI 0.74-1.0) and an accuracy of 90% (95%CI 78-100). The signature predicted postnatal renal outcome for the suspected PUV cases with an AUC of 0.89 (95%CI 0.72-0.97) and an accuracy of 84% (95%CI 71-97).

CONCLUSIONS

This single-center study confirms the predictive power of the previously identified 12PUV fetal urinary peptide signature.

Urinary Peptidomic Biomarkers in Kidney Diseases

In order to effectively develop personalized medicine for kidney diseases we urgently need to develop highly accurate biomarkers for use in the clinic, since current biomarkers of kidney damage (changes in serum creatinine and/or urine albumin excretion) apply to a later stage of disease, lack accuracy, and are not connected with molecular pathophysiology. Analysis of urine peptide content (urinary peptidomics) has emerged as one of the most attractive areas in disease biomarker discovery. Urinary peptidome analysis allows the detection of short and long-term physiological or pathological changes occurring within the kidney. Urinary peptidomics has been applied extensively for several years now in renal patients, and may greatly improve kidney disease management by supporting earlier and more accurate detection, prognostic assessment, and prediction of response to treatment. It also promises better understanding of kidney disease pathophysiology, and has been proposed as a “liquid biopsy” to discriminate various types of renal disorders. Furthermore, proteins being the major drug targets, peptidome analysis may allow one to evaluate the effects of therapies at the protein signaling pathway level. We here review the most recent findings on urinary peptidomics in the setting of the most common kidney diseases.

Urinary peptidome analyses for the diagnosis of chronic kidney disease in dogs

Chronic kidney disease (CKD) is clinically important in canine medicine. Current diagnostic tools lack sensitivity for detection of subclinical CKD. The aim of the present study was to evaluate urinary peptidome analysis for diagnosis of CKD in dogs. Capillary electrophoresis coupled to mass spectrometry analysis demonstrated presence of approximately 5400 peptides in dog urine. Comparison of urinary peptide abundance of dogs with and without CKD led to the identification of 133 differentially excreted peptides (adjusted P for each peptide <0.05). Sequence information was obtained for 35 of these peptides. This 35 peptide subset and the total group of 133 peptides were used to construct two predictive models of CKD which were subsequently validated by researchers masked to results in an independent cohort of 20 dogs. Both models diagnosed CKD with an area under the receiver operating characteristic (ROC) curve of 0.88 (95% confidence intervals [CI], 0.72-1.0). Most differentially excreted peptides represented fragments of collagen I, indicating possible association with fibrotic processes in CKD (similar to the equivalent human urinary peptide CKD model, CKD273). This first study of the urinary peptidome in dogs identified peptides that were associated with presence of CKD. Future studies are needed to validate the utility of this model for diagnosis and prediction of progression of canine CKD in a clinical setting.

Integration of transcriptomics, proteomics and metabolomics data to reveal the biological mechanisms of abrin injury in human lung epithelial cells

BACKGROUND

Abrin toxin (AT) is a potent plant toxin that belongs to the type Ⅱ ribosome inactivating protein family and is recognized as an important toxin agent for potential bioweapons. Exposure to AT by way of aerosol is the most lethal route, but the mechanism of injury requires further investigation.

MATERIALS AND METHODS

In the present study, we performed a comprehensive analysis of transcriptomics, proteomics and metabolomics on the potential mechanism of abrin injury in human lung epithelial cells.

RESULTS

In total, 6838 genes, 314 proteins and 178 metabolites showed significant changes in human lung epithelial cells after AT treatment. Using molecular function, pathway, and network analysis, the genes and proteins regulated in AT-treated cells were mainly attributed to amino acid metabolism, lipid metabolism, and genetic information processing. Furthermore, a comprehensive analysis of the transcripts, proteins, and metabolites was performed. The results revealed that the correlated genes, proteins, and metabolism pathways regulated in AT-treated human lung epithelial cells were involved in tryptophan metabolism, biosynthesis of amino acids, and protein digestion and absorption.

CONCLUSION

This study provides large-scale omics data to develop new strategies for the prevention, rapid diagnosis, and treatment of AT poisoning, especially AT from aerosol.

Urinary proteomic biomarkers in oncology: ready for implementation?

Introduction: Biomarkers are expected to improve the management of cancer patients by enabling early detection and prediction of therapeutic response. Proteins reflect a molecular phenotype, have high potential as biomarkers, and also are key targets for intervention. Given the ease of collection and proximity to certain tumors, the urinary proteome is a rich source of biomarkers and several proteins have been already implemented. Areas covered: We examined the literature on urine proteins and proteome analysis in oncology from reports published during the last 5 years to generate an overview on the status of urine protein and peptide biomarkers, with emphasis on their actual clinical value. Expert commentary: A few studies report on biomarkers that are ready to be implemented in patient management, among others in bladder cancer and cholangiocarcinoma. These reports are based on multi-marker approaches. A high number of biomarkers, though, has been described in studies with low statistical power. In fact, several of them have been consistently reported across different studies. The latter should be the focus of attention and be tested in properly designed confirmatory and ultimately, prospective investigations. It is expected that multi-marker classifiers for a specific context-of-use, will be the preferred path toward clinical implementation.

Candidate Treponema pallidum biomarkers uncovered in urine from individuals with syphilis using mass spectrometry

AIM

A diagnostic test that could detect Treponema pallidum antigens in urine would facilitate the prompt diagnosis of syphilis.

MATERIALS & METHODS

Urine from 54 individuals with various clinical stages of syphilis and 6 controls were pooled according to disease stage and interrogated with complementary mass spectrometry techniques to uncover potential syphilis biomarkers.

RESULTS & CONCLUSION

In total, 26 unique peptides were uncovered corresponding to four unique T. pallidum proteins that have low genetic sequence similarity to other prokaryotes and human proteins. This is the first account of direct T. pallidum protein detection in human clinical samples using mass spectrometry. The implications of these findings for future diagnostic test development is discussed. Data are available via ProteomeXchange with identifier PXD009707.

Absolute quantification of cholesteryl esters using liquid chromatography-tandem mass spectrometry uncovers novel diagnostic potential of urinary sediment

BACKGROUND

Urine has been utilized as a source of biomarkers in renal disease. However, urinary lipids have not attracted much attention so far. Here we studied urinary cholesteryl ester (CE) and its relevance in renal disease.

METHODS

Quantitative analysis of CE molecular species in serum, urinary supernatant, and urinary sediment from patients with renal disease (N=64) and non-renal disease (N=23) was carried out using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and deuterated CEs as internal standards.

RESULTS

Validation study showed good precision and accuracy of LC-MS/MS. Many CE species were detected in the urinary sediment and supernatant in the renal disease group, whereas only a few CE species were detected in the other group. In the renal disease group, the sum of the concentrations of all CE species showed a significant correlation between the sediment and the supernatant from urinary samples (r=0.876, p<0.001); however, the composition of CEs was significantly different between them. Further, the composition of CEs of the supernatant was similar to that of the serum.

CONCLUSIONS

Our LC-MS/MS analysis uncovered a distinct CE profile in urinary sediment from patients with renal disease, suggesting a possible contribution of CEs in urothelial cells to the development of renal disease.

Effects of arginine vasopressin on the urine proteome in rats

Biomarkers are the measurable changes associated with a physiological or pathophysiological process. The content of urine frequently changes because it is not controlled by homeostatic mechanisms, and these alterations can be a source of biomarkers. However, urine is affected by many factors. In this study, vasoconstrictor and antidiuretic arginine vasopressin (AVP) were infused into rats using an osmotic pump. The rats’ urinary proteome after one week of infusion was analyzed by label-free LC-MS/MS. A total of 408 proteins were identified; among these proteins, eight and 10 proteins had significantly altered expression in the low and high dose groups, respectively, compared with the control group using the one-way ANOVA analysis followed by post hoc analysis with the least significant difference (LSD) test or Dunnett’s T3 test. Three differential proteins were described in prior studies as related to AVP physiological processes, and nine differential proteins are known disease biomarkers. Sixteen of the 17 differential proteins have human orthologs. These results suggest that we should consider the effects of AVP on urinary proteins in future urinary disease biomarker researches. The study data provide clues regarding underlying mechanisms associated with AVP for future physiological researches on AVP. This study provide a sensitive changes associated with AVP. However, the limitation of this result is that the candidate biomarkers should be further verified and filtered. Large clinical samples must be examined to verify the differential proteins identified in this study before these proteins are used as biomarkers for pathological AVP increased diseases, such as syndrome of inappropriate antidiuretic hormone secretion (SIADH).

Urinary Urea, Uric Acid and Hippuric Acid as Potential Biomarkers in Multiple Sclerosis Patients

Urine is a proven source of metabolite biomarkers and has the potential to be a rapid, noninvasive, inexpensive, and efficient diagnostic tool for various human diseases. Despite these advantages, urine is an under-investigated source of biomarkers for multiple sclerosis (MS). The objective was to investigate the level of some urinary metabolites (urea, uric acid and hippuric acid) in patients with MS and correlate their levels to the severity of the disease, MS subtypes and MS treatment. The urine samples were collected from 73 MS patients-48 with RRMS and 25 with SPMS- and age matched 75 healthy controls. The values of urinary urea, uric acid and hippuric acid in MS patients were significantly decreased, and these metabolites in SPMS pattern showed significantly decrease than RRMS pattern. Also showed significant inverse correlation with expanded disability status scale and number of relapses. Accordingly, they may act as a potential urinary biomarkers for MS, and correlate to disease progression.

Does urinary peptide content differ between COPD patients with and without inherited alpha-1 antitrypsin deficiency?

Differentiating between chronic obstructive pulmonary disease (COPD) patients with normal (PiMM) or deficient (PiZZ) genetic variants of alpha-1 antitrypsin (A1AT) is important not only for understanding the pathobiology of disease progression but also for improving personalized therapies. This pilot study aimed to investigate whether urinary peptides reflect the A1AT-related phenotypes of COPD. Urine samples from 19 clinically stable COPD cases (7 PiMM and 12 PiZZ A1AT) were analyzed by capillary electrophoresis coupled to mass spectrometry. We identified 66 peptides (corresponding to 36 unique proteins) that differed between PiZZ and PiMM COPD. Among these, peptides from the collagen family were the most abundant and divergent. A logistic regression model based on COL1A1 or COL5A3 peptides enabled differentiation between PiMM and PiZZ groups, with a sensitivity of 100% and specificity of 85.71% for COL1A1 and a sensitivity of 91.67% and specificity of 85.71% for COL5A3. Furthermore, patients with PiZZ presented low levels of urinary peptides involved in lipoproteins/lipids and retinoic acid metabolism, such as apolipoprotein A-I and C4, retinol-binding protein 4 and prostaglandin-H2 D-isomerase. However, peptides of MDS1 and EVII complex locus, gelsolin and hemoglobin alpha were found in the urine of COPD cases with PiZZ, but not with PiMM. These capillary electrophoresis coupled to mass spectrometry-based results provide the first evidence that urinary peptide content differs between PiMM and PiZZ patients with COPD.

The nephrologist of tomorrow: towards a kidney-omic future

Omics refers to the collective technologies used to explore the roles and relationships of the various types of molecules that make up the phenotype of an organism. Systems biology is a scientific discipline that endeavours to quantify all of the molecular elements of a biological system. Therefore, it reflects the knowledge acquired by omics in a meaningful manner by providing insights into functional pathways and regulatory networks underlying different diseases. The recent advances in biotechnological platforms and statistical tools to analyse such complex data have enabled scientists to connect the experimentally observed correlations to the underlying biochemical and pathological processes. We discuss in this review the current knowledge of different omics technologies in kidney diseases, specifically in the field of pediatric nephrology, including biomarker discovery, defining as yet unrecognized biologic therapeutic targets and linking omics to relevant standard indices and clinical outcomes. We also provide here a unique perspective on the field, taking advantage of the experience gained by the large-scale European research initiative called "Systems Biology towards Novel Chronic Kidney Disease Diagnosis and Treatment" (SysKid). Based on the integrative framework of Systems biology, SysKid demonstrated how omics are powerful yet complex tools to unravel the consequences of diabetes and hypertension on kidney function.

Urinary proteomics can define distinct diagnostic inflammatory arthritis subgroups

Current diagnostic tests applied to inflammatory arthritis lack the necessary specificity to appropriately categorise patients. There is a need for novel approaches to classify patients with these conditions. Herein we explored whether urinary proteomic biomarkers specific for different forms of arthritis (rheumatoid arthritis (RA), psoriatic arthritis (PsA), osteoarthritis (OA)) or chronic inflammatory conditions (inflammatory bowel disease (IBD)) can be identified. Fifty subjects per group with RA, PsA, OA or IBD and 50 healthy controls were included in the study. Two-thirds of these populations were randomly selected to serve as a training set, while the remaining one-third was reserved for validation. Sequential comparison of one group to the other four enabled identification of multiple urinary peptides significantly associated with discrete pathological conditions. Classifiers for the five groups were developed and subsequently tested blind in the validation test set. Upon unblinding, the classifiers demonstrated excellent performance, with an area under the curve between 0.90 and 0.97 per group. Identification of the peptide markers pointed to dysregulation of collagen synthesis and inflammation, but also novel inflammatory markers. We conclude that urinary peptide signatures can reliably differentiate between chronic arthropathies and inflammatory conditions with discrete pathogenesis.

Urinary biomarkers for renal tract malformations

INTRODUCTION

Renal tract malformations (RTMs) are congenital anomalies of the kidneys and urinary tract, which are the major cause of end-stage renal disease in children. Using immunoassay-based approaches (ELISA, western blot), individual urinary proteins including transforming growth factor β, tumor necrosis factor and monocyte attractant proteins 1 were found to be associated to RTMs. However, only mass spectrometry (MS) based methods leading to the identification of panels of protein-based markers composed of fragments of the extracellular matrix allowed the prediction of progression of RTMs and its complications. Areas covered: In this review, we summarized relevant studies identified in "Pubmed" using the keywords "urinary biomarkers" and "proteomics" and "renal tract malformations" or "hydronephrosis" or "ureteropelvic junction obstruction" or "posterior urethral valves" or "vesicoureteral reflux". These publications represent studies on potential protein-based biomarkers, either individually or combined in panels, of RTMs in human and animal models. Expert commentary: Successful use in the clinic of these protein-based biomarkers will need to involve larger scale studies to reach sufficient power. Improved performance will potentially come from combining immunoassay- and MS-based markers.

The Alternative Pathway of Complement and the Evolving Clinical-Pathophysiological Spectrum of Atypical Hemolytic Uremic Syndrome

Complement-mediated atypical hemolytic uremic syndrome (aHUS) comprises approximately 90% of cases of aHUS, and results from dysregulation of endothelial-anchored complement activation with resultant endothelial damage. The discovery of biomarker ADAMTS13 has enabled a more accurate diagnosis of thrombotic thrombocytopenic purpura (TTP) and an appreciation of overlapping clinical features of TTP and aHUS. Given our present understanding of the pathogenic pathways involved in aHUS, it is unlikely that a specific test will be developed. Rather the use of biomarker data, complement functional analyses, genomic analyses and clinical presentation will be required to diagnose aHUS. This approach would serve to clarify whether a thrombotic microangiopathy present in a complement-amplifying condition arises from the unmasking of a genetically driven aHUS versus a time-limited complement storm-mediated aHUS due to direct endothelial damage in which no genetic predisposition is present. Although both scenarios result in the phenotypic expression of aHUS and involve the alternate pathway of complement activation, long-term management would differ.

Implementation of CE-MS-identified proteome-based biomarker panels in drug development and patient management

The recent advancements in clinical proteomics enabled identification of biomarker panels for a large range of diseases. A number of CE-MS-identified biomarker panels were verified and implemented in clinical studies. Despite multiple challenges, accumulating evidence supports the value and the need for proteome-based biomarker panels. In this perspective, we provide an overview of clinical studies indicating the added value of CE-MS biomarker panels over traditional diagnostics and monitoring methods. We outline apparent advantages of applying novel proteomic biomarker panels for disease diagnosis, prognosis, staging, drug development and patient management. Facing the plethora of benefits associated with the use of CE-MS biomarker panels, we envision their implementation into the medical practice in the near future.

Identification of Symptomatic Fetuses Infected with Cytomegalovirus Using Amniotic Fluid Peptide Biomarkers

Cytomegalovirus (CMV) is the most common cause of congenital infection, and is a major cause of sensorineural hearing loss and neurological disabilities. Evaluating the risk for a CMV infected fetus to develop severe clinical symptoms after birth is crucial to provide appropriate guidance to pregnant women who might have to consider termination of pregnancy or experimental prenatal medical therapies. However, establishing the prognosis before birth remains a challenge. This evaluation is currently based upon fetal imaging and fetal biological parameters, but the positive and negative predictive values of these parameters are not optimal, leaving room for the development of new prognostic factors. Here, we compared the amniotic fluid peptidome between asymptomatic fetuses who were born as asymptomatic neonates and symptomatic fetuses who were either terminated in view of severe cerebral lesions or born as severely symptomatic neonates. This comparison allowed us to identify a 34-peptide classifier in a discovery cohort of 13 symptomatic and 13 asymptomatic neonates. This classifier further yielded 89% sensitivity, 75% specificity and an area under the curve of 0.90 to segregate 9 severely symptomatic from 12 asymptomatic neonates in a validation cohort, showing an overall better performance than that of classical fetal laboratory parameters. Pathway analysis of the 34 peptides underlined the role of viral entry in fetuses with severe brain disease as well as the potential importance of both beta-2-microglobulin and adiponectin to protect the injured fetal brain infected with CMV. The results also suggested the mechanistic implication of the T calcium channel alpha-1G (CACNA1G) protein in the development of seizures in severely CMV infected children. These results open a new field for potential therapeutic options. In conclusion, this study demonstrates that amniotic fluid peptidome analysis can effectively predict the severity of congenital CMV infection. This peptidomic classifier may therefore be used in clinical settings during pregnancy to improve prenatal counseling.

CMV is the most common cause of congenital infection, and can result in significant neonatal morbidity and neurological disabilities. The birth prevalence of congenital CMV is estimated at 0.7% worldwide, and 10 to 20% of these neonates develop severe symptoms. In such cases the outcome is generally poor. Therefore, identification of additional prognostic markers is crucial for prenatal counseling in cases with an infected fetus. This may influence the decision of continuing with the pregnancy or requesting its termination, but also the decision of starting experimental antiviral therapy. The pathophysiology of CMV brain injury is not completely understood, and the identification of new biomarkers of CMV infection might also pave the way towards the development of new therapeutic alternatives. Here, we apply a recently developed and modern non-targeted peptidomics approach to amniotic fluid obtained from symptomatic and asymptomatic CMV-infected fetuses/neonates, followed by network analysis of the peptides of interest in the context of fetal infection and in relation with outcome. Our study identified 34 amniotic fluid peptides that form new prognostic biomarkers that could be used in clinical settings to improve prenatal counseling. In addition, this study provides novel mechanistic insight into the pathobiology of CMV congenital disease.

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.

Causal Genetic Inference Using Haplotypes as Instrumental Variables

In genomic studies with both genotypes and gene or protein expression profile available, causal effects of gene or protein on clinical outcomes can be inferred through using genetic variants as instrumental variables (IVs). The goal of introducing IV is to remove the effects of unobserved factors that may confound the relationship between the biomarkers and the outcome. A valid inference under the IV framework requires pairwise associations and pathway exclusivity. Among these assumptions, the IV expression association needs to be strong for the casual effect estimates to be unbiased. However, a small number of single nucleotide polymorphisms (SNPs) often provide limited explanation of the variability in the gene or protein expression and can only serve as weak IVs. In this study, we propose to replace SNPs with haplotypes as IVs to increase the variant-expression association and thus improve the casual effect inference of the expression. In the classical two-stage procedure, we developed a haplotype regression model combined with a model selection procedure to identify optimal instruments. The performance of the new method was evaluated through simulations and compared with the IV approaches using observed multiple SNPs. Our results showed the gain of power to detect a causal effect of gene or protein on the outcome using haplotypes compared with using only observed SNPs, under either complete or missing genotype scenarios. We applied our proposed method to a study of the effect of interleukin-1 beta (IL-1β) protein expression on the 90-day survival following sepsis and found that overly expressed IL-1β is likely to increase mortality.

Metabolic biomarkers for chronic kidney disease

Chronic kidney disease (CKD) is an increasingly recognized burden for patients and health care systems with high (and growing) global incidence and prevalence, significant mortality, and disproportionately high treatment costs. Yet, the available diagnostic tools are either impractical in clinical routine or have serious shortcomings impeding a well-informed disease management although optimized treatment strategies with proven benefits for the patients have become available. Advances in bioanalytical technologies have facilitated studies that identified genomic, proteomic, and metabolic biomarker candidates, and confirmed some of them in independent cohorts. This review summarizes the CKD-related markers discovered so far, and focuses on compounds and pathways, for which there is quantitative data, substantiating evidence from translational research, and a mechanistic understanding of the processes involved. Also, multiparametric marker panels have been suggested that showed promising diagnostic and prognostic performance in initial analyses although the data basis from prospective trials is very limited. Large-scale studies, however, are underway and will provide the information for validating a set of parameters and discarding others. Finally, the path from clinical research to a routine application is discussed, focusing on potential obstacles such as the use of mass spectrometry, and the feasibility of obtaining regulatory approval for targeted metabolomics assays.

New perspectives on bioactivity of olive oil: evidence from animal models, human interventions and the use of urinary proteomic biomarkers

Olive oil (OO) is the primary source of fat in the Mediterranean diet and has been associated with longevity and a lower incidence of chronic diseases, particularly CHD. Cardioprotective effects of OO consumption have been widely related with improved lipoprotein profile, endothelial function and inflammation, linked to health claims of oleic acid and phenolic content of OO. With CVD being a leading cause of death worldwide, a review of the potential mechanisms underpinning the impact of OO in the prevention of disease is warranted. The current body of evidence relies on mechanistic studies involving animal and cell-based models, epidemiological studies of OO intake and risk factor, small- and large-scale human interventions, and the emerging use of novel biomarker techniques associated with disease risk. Although model systems are important for mechanistic research nutrition, methodologies and experimental designs with strong translational value are still lacking. The present review critically appraises the available evidence to date, with particular focus on emerging novel biomarkers for disease risk assessment. New perspectives on OO research are outlined, especially those with scope to clarify key mechanisms by which OO consumption exerts health benefits. The use of urinary proteomic biomarkers, as highly specific disease biomarkers, is highlighted towards a higher translational approach involving OO in nutritional recommendations.