Urine peptidomics for clinical biomarker discovery

Recent progress in mass spectrometry-based urinary proteomics

Serum or plasma is frequently utilized in biomedical research; however, its application is impeded by the requirement for invasive sample collection. The non-invasive nature of urine collection makes it an attractive alternative for disease characterization and biomarker discovery. Mass spectrometry-based protein profiling of urine has led to the discovery of several disease-associated biomarkers. Proteomic analysis of urine has not only been applied to disorders of the kidney and urinary bladder but also to conditions affecting distant organs because proteins excreted in the urine originate from multiple organs. This review provides a progress update on urinary proteomics carried out over the past decade. Studies summarized in this review have expanded the catalog of proteins detected in the urine in a variety of clinical conditions. The wide range of applications of urine analysis-from characterizing diseases to discovering predictive, diagnostic and prognostic markers-continues to drive investigations of the urinary proteome.

Clinical applications of plasma proteomics and peptidomics: Towards precision medicine

In the context of precision medicine, disease treatment requires individualized strategies based on the underlying molecular characteristics to overcome therapeutic challenges posed by heterogeneity. For this purpose, it is essential to develop new biomarkers to diagnose, stratify, or possibly prevent diseases. Plasma is an available source of biomarkers that greatly reflects the physiological and pathological conditions of the body. An increasing number of studies are focusing on proteins and peptides, including many involving the Human Proteome Project (HPP) of the Human Proteome Organization (HUPO), and proteomics and peptidomics techniques are emerging as critical tools for developing novel precision medicine preventative measures. Excitingly, the emerging plasma proteomics and peptidomics toolbox exhibits a huge potential for studying pathogenesis of diseases (e.g., COVID-19 and cancer), identifying valuable biomarkers and improving clinical management. However, the enormous complexity and wide dynamic range of plasma proteins makes plasma proteome profiling challenging. Herein, we summarize the recent advances in plasma proteomics and peptidomics with a focus on their emerging roles in COVID-19 and cancer research, aiming to emphasize the significance of plasma proteomics and peptidomics in clinical applications and precision medicine.

CAPN2 acts as an indicator of hepatitis B virus to induce hepatic fibrosis

This study is aimed to investigate whether calpain 2 (CAPN2) serves as an indicator of the hepatitis B virus (HBV) to induce hepatic fibrosis. Differentially-expressed genes (DEGs) in HBV-induced hepatic fibrosis and normal liver tissues were analyzed, and signal pathway which was analyzed by the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis using DEGs. Next, the gene-related network map was constructed using the Search Tool for the Retrieval of Interacting Genes. Moreover, CAPN2 protein expression, level of hepatic fibrosis, CAPN2 messenger RNA level, and protein levels of CAPN2, a-SAM, COL3A1, COL1A1, and MAPK1 were determined using Immunohistochemistry (IHC), hematoxylin and eosin, RT-qPCR, and western blot (WB), respectively. There were 420 DEGs screened in HBV-induced hepatic fibrosis and normal liver tissues, among which, 373 were significantly upregulated and 47 were obviously downregulated. KEGG analysis showed that the upregulated DEGs were mainly concentrated in extracellular matrix-receptor interaction, protein digestion, and absorption signaling pathways. The network diagram analysis showed that the DEGs, such as CAPN2, ITGAV, and CCR2, play the key role in the DEG network map, and CAPN2 related to hepatic fibrosis via MAPK1. The increased CAPN2 expression and obvious hepatic fibrosis was displayed in the HBV-induced hepatic fibrosis tissues. In addition, HBV could induce CAPN2 expression, and the interference of CAPN2 could inhibit the expression of hepatic fibrosis markers, including a-SAM, COL3A1, COL1A1, and MAPK1. CAPN2 is regarded as a biomarker of hepatic fibrosis induced by HBV.

Probing the endogenous peptidomes of cancer for biomarkers: A new endeavor

The life span of cancer patients can be prolonged with appropriate therapies if detected early. Mass screening for early detection of cancer, however, requires sensitive and specific biomarkers obtainable from body fluids such as blood or urine. To date, most biomarker discovery programs focus on the proteome rather than the endogenous peptidome. It has been long-established that tumor cells and stromal cells produce tumor resident proteases (TRPs) to remodel the surrounding tumor microenvironment in support of tumor progression. In fact, proteolytic products of TRPs have been shown to correlate with malignant behavior. Being of low molecular weight, these unique peptides can pass through the endothelial barrier of the vasculature into the bloodstream. As such, the cancer peptidome has increasingly become a focus for biomarker discovery. In this review, we discuss on the various aspects of the peptidome in cancer biomarker research.

Approaches to the discovery of non-invasive urinary biomarkers of prostate cancer

Prostate cancer (PCa) continues to be one of the most common cancers in men worldwide. Prostate specific antigen (PSA) measured in blood has been used for decades as an aid for physicians to detect the presence of prostate cancer. However, the PSA test has limited sensitivity and specificity, leading to unnecessary biopsies, overdiagnosis and overtreatment of patients. For these reasons, there is an urgent need for more accurate PCa biomarkers that can detect PCa with high sensitivity and specificity. Urine is a unique source of potential protein biomarkers that can be measured in a non-invasive way. This review comprehensively summarizes state of the art approaches used in the discovery and validation of urinary biomarkers for PCa. Numerous strategies are currently being used in the discovery of urinary biomarkers for prostate cancer including gel-based separation techniques, mass spectrometry, activity-based proteomic assays and software approaches. Antibody-based approaches remain preferred method for validation of candidate biomarkers with rapidly advancing multiplex immunoassays and MS-based targeted approaches. In the last decade, there has been a dramatic acceleration in the development of new techniques and approaches in the discovery of protein biomarkers for prostate cancer including computational, statistical and data mining methods. Many urinary-based protein biomarkers have been identified and have shown significant promise in initial studies. Examples of these potential biomarkers and the methods utilized in their discovery are also discussed in this review.

Targeted metabolomic analysis of 33 amino acids and biogenic amines in human urine by ion-pairing HPLC-MS/MS: Biomarkers for tacrolimus nephrotoxicity after renal transplantation

Calcineurin inhibitor nephrotoxicity, especially for the widely used tacrolimus, has become a major concern in post-transplant immunosuppression. Multiparametric amino acid metabolomics is useful for biomarker identification of tacrolimus nephrotoxicity, for which specific quantitative methods are highlighted as a premise. This article presents a targeted metabolomic assay to quantify 33 amino acids and biogenic amines in human urine by high-performance liquid chromatography coupled with tandem mass spectrometry. Chromatographic separation was carried out on an Agilent Zorbax SB-C₁₈ column (3.0 × 150 mm, 5 μm) with addition of an ion-pairing agent in the mobile phase, and MS/MS detection was achieved in both the positive and negative multiple reaction monitoring modes. Good correlation coefficients (r² > 0.98) were obtained for most analytes. Intra- and inter-day precision, stability, carryover and incurred sample reanalysis met with the acceptance criteria of the guidance of the US Food and Drug Administration. Analysis on urine from healthy volunteers and renal transplantation patients with tacrolimus nephrotoxicity confirmed symmetric dimethylarginine and serine as biomarkers for kidney injury, with AUC values of 0.95 and 0.81 in receiver operating characteristic analysis, respectively. Additionally, symmetric dimethylarginine exhibited a tight correlation with serum creatinine, and was therefore indicative of renal function. The targeted metabolomic assay was time and cost prohibitive for amino acid analysis in human urine, facilitating the biomarker identification of tacrolimus nephrotoxicity.

Optimization for Peptide Sample Preparation for Urine Peptidomics

Analysis of native or endogenous peptides in biofluids can provide valuable insight into disease mechanisms. Furthermore, the detected peptides may also have utility as potential biomarkers for noninvasive monitoring of human diseases. The noninvasive nature of urine collection and the abundance of peptides in the urine make analysis by high-throughput "peptidomics" methods an attractive approach for investigating the pathogenesis of renal disease. However, urine peptidomics methodologies can be problematic with regard to difficulties associated with sample preparation. The urine matrix can provide significant background interference in making the analytical measurements, in that it hampers both the identification of peptides and the depth of the peptidomics read when utilizing LC-MS-based peptidome analysis. We report on a novel adaptation of the standard solid-phase extraction (SPE) method to a modified SPE (mSPE) approach for improved peptide yield and analysis sensitivity with LC-MS-based peptidomics, in terms of time, cost, clogging of the LC-MS column, peptide yield, peptide quality, and number of peptides identified by each method. The mSPE method provides significantly improved efficiencies for the preparation of samples from urine. The mSPE method is found to be superior to the conventional, standard SPE method for urine peptide sample preparation when applying LC-MS peptidomics analysis, due to optimized sample cleanup that provides improved experimental inference from confidently identified peptides.

Untargeted Screening of Urinary Peptides Using Offline Nano-Liquid Chromatography: MALDI-TOF/TOF Mass Spectrometry

In renal transplantation, the discovery of early urine biomarkers of graft lesions would be useful in helping physicians to improve patient care and minimize the use of invasive techniques such as biopsies. Over the last years, high-resolution mass spectrometry has been used extensively for the search of biomarkers in various biological fluids. Here we describe a procedure based on reverse-phase nano-HPLC, offline plate spotting, and MALDI-TOF and TOF/TOF applied in our laboratory for the search of natural peptides in urine samples from renal transplant patients.

Current state of the art for enhancing urine biomarker discovery

INTRODUCTION

Urine is a highly desirable biospecimen for biomarker analysis because it can be collected recurrently by non-invasive techniques, in relatively large volumes. Urine contains cellular elements, biochemicals, and proteins derived from glomerular filtration of plasma, renal tubule excretion, and urogenital tract secretions that reflect, at a given time point, an individual's metabolic and pathophysiologic state.

AREAS COVERED

High-resolution mass spectrometry, coupled with state of the art fractionation systems are revealing the plethora of diagnostic/prognostic proteomic information existing within urinary exosomes, glycoproteins, and proteins. Affinity capture pre-processing techniques such as combinatorial peptide ligand libraries and biomarker harvesting hydrogel nanoparticles are enabling measurement/identification of previously undetectable urinary proteins. Expert commentary: Future challenges in the urinary proteomics field include a) defining either single or multiple, universally applicable data normalization methods for comparing results within and between individual patients/data sets, and b) defining expected urinary protein levels in healthy individuals.

Early lipid changes in acute kidney injury using SWATH lipidomics coupled with MALDI tissue imaging

Acute kidney injury (AKI) is one of the leading causes of in-hospital morbidity and mortality, particularly in critically ill patients. Although our understanding of AKI at the molecular level remains limited due to its complex pathophysiology, recent advances in both quantitative and spatial mass spectrometric approaches offer new opportunities to assess the significance of renal metabolomic changes in AKI models. In this study, we evaluated lipid changes in early ischemia-reperfusion (IR)-related AKI in mice by using sequential window acquisition of all theoretical spectra (SWATH)-mass spectrometry (MS) lipidomics. We found a significant increase in two abundant ether-linked phospholipids following IR at 6 h postinjury, a plasmanyl choline, phosphatidylcholine (PC) O-38:1 (O-18:0, 20:1), and a plasmalogen, phosphatidylethanolamine (PE) O-42:3 (O-20:1, 22:2). Both of these lipids correlated with the severity of AKI as measured by plasma creatinine. In addition to many more renal lipid changes associated with more severe AKI, PC O-38:1 elevations were maintained at 24 h post-IR, while renal PE O-42:3 levels decreased, as were all ether PEs detected by SWATH-MS at this later time point. To further assess the significance of this early increase in PC O-38:1, we used matrix-assisted laser desorption ionization imaging mass spectrometry (MALDI-IMS) to determine that it occurred in proximal tubules, a region of the kidney that is most prone to IR injury and also rich in the rate-limiting enzymes involved in ether-linked phospholipid biosynthesis. Use of SWATH-MS lipidomics in conjunction with MALDI-IMS for lipid localization will help in elucidating the role of lipids in the pathobiology of AKI.

Urinary Colorimetric Sensor Array and Algorithm to Distinguish Kawasaki Disease from Other Febrile Illnesses

Objectives

Kawasaki disease (KD) is an acute pediatric vasculitis of infants and young children with unknown etiology and no specific laboratory-based test to identify. A specific molecular diagnostic test is urgently needed to support the clinical decision of proper medical intervention, preventing subsequent complications of coronary artery aneurysms. We used a simple and low-cost colorimetric sensor array to address the lack of a specific diagnostic test to differentiate KD from febrile control (FC) patients with similar rash/fever illnesses.

Study Design

Demographic and clinical data were prospectively collected for subjects with KD and FCs under standard protocol. After screening using a genetic algorithm, eleven compounds including metalloporphyrins, pH indicators, redox indicators and solvatochromic dye categories, were selected from our chromatic compound library (n = 190) to construct a colorimetric sensor array for diagnosing KD. Quantitative color difference analysis led to a decision-tree-based KD diagnostic algorithm.

Results

This KD sensing array allowed the identification of 94% of KD subjects (receiver operating characteristic [ROC] area under the curve [AUC] 0.981) in the training set (33 KD, 33 FC) and 94% of KD subjects (ROC AUC: 0.873) in the testing set (16 KD, 17 FC). Color difference maps reconstructed from the digital images of the sensing compounds demonstrated distinctive patterns differentiating KD from FC patients.

Conclusions

The colorimetric sensor array, composed of common used chemical compounds, is an easily accessible, low-cost method to realize the discrimination of subjects with KD from other febrile illness.

Current peptidomics: applications, purification, identification, quantification, and functional analysis

Peptidomics is an emerging field branching from proteomics that targets endogenously produced protein fragments. Endogenous peptides are often functional within the body-and can be both beneficial and detrimental. This review covers the use of peptidomics in understanding digestion, and identifying functional peptides and biomarkers. Various techniques for peptide and glycopeptide extraction, both at analytical and preparative scales, and available options for peptide detection with MS are discussed. Current algorithms for peptide sequence determination, and both analytical and computational techniques for quantification are compared. Techniques for statistical analysis, sequence mapping, enzyme prediction, and peptide function, and structure prediction are explored.

Noninvasive biomarkers of necrotizing enterocolitis

Necrotizing enterocolitis is an acute inflammatory disease, which primarily affects preterm infants, and is a leading cause of morbidity and mortality in the neonatal intensive care unit. Unfortunately, necrotizing enterocolitis can be difficult to distinguish from other diseases and clinical conditions especially during the early course of the disease. This diagnostic uncertainty is particularly relevant to clinical evaluation and medical management and potentially leads to unnecessary and extended periods of cessation of enteral feedings and prolonged courses of parenteral nutrition and antibiotics. Biomarkers are molecular indicators of a disease process, diagnosis, prognosis and can be used to monitor the effects of disease management. Historically, there has been a paucity of reliable and robust biomarkers for necrotizing enterocolitis. However, several studies have recently identified promising biomarkers. Noninvasive samples for biomarker measurement are preferred and may have certain advantages in the preterm infant. In this review article, we focus on recent exciting and promising discoveries in noninvasive biomarkers for necrotizing enterocolitis.

Lipidomics: new insight into kidney disease

Due to the incidence of type-2 diabetes and hypertension, chronic kidney disease (CKD) has emerged as a major public health problem worldwide. CKD results in premature death from accelerated cardiovascular disease and various other complications. Early detection, careful monitoring of renal function, and response to therapeutic intervention are critical for prevention of CKD progression and its complications. Unfortunately, traditional biomarkers of renal function are insufficiently sensitive or specific to detect early stages of disease when therapeutic intervention is most effective. Therefore, more sensitive biomarkers of kidney disease are needed for early diagnosis, monitoring, and effective treatment. CKD results in profound changes in lipid and lipoprotein metabolism that, in turn, contribute to progression of CKD and its cardiovascular complications. Lipids and lipid-derived metabolites play diverse and critically important roles in the structure and function of cells, tissues, and biofluids. Lipidomics is a branch of metabolomics, which encompasses the global study of lipids and their biologic function in health and disease including identification of biomarkers for diagnosis, prognosis, prevention, and therapeutic response for various diseases. This review summarizes recent developments in lipidomics and its application to various kidney diseases including chronic glomerulonephritis, IgA nephropathy, chronic renal failure, renal cell carcinoma, diabetic nephropathy, and acute renal failure in clinical and experimental research. Analytical technologies, data analysis, as well as currently known metabolic biomarkers of kidney diseases are addressed. Future perspectives and potential limitations of lipidomics are discussed.

Mechanistic peptidomics: factors that dictate specificity in the formation of endogenous peptides in human milk

An extensive mass spectrometry analysis of the human milk peptidome has revealed almost 700 endogenous peptides from 30 different proteins. Two in-house computational tools were created and used to visualize and interpret the data through both alignment of the peptide quasi-molecular ion intensities and estimation of the differential enzyme participation. These results reveal that the endogenous proteolytic activity in the mammary gland is remarkably specific and well conserved. Certain proteins-not necessarily the most abundant ones-are digested by the proteases present in milk, yielding endogenous peptides from selected regions. Our results strongly suggest that factors such as the presence of specific proteases, the position and concentration of cleavage sites, and, more important, the intrinsic disorder of segments of the protein drive this proteolytic specificity in the mammary gland. As a consequence of this selective hydrolysis, proteins that typically need to be cleaved at specific positions in order to exert their activity are properly digested, and bioactive peptides encoded in certain protein sequences are released. Proteins that must remain intact in order to maintain their activity in the mammary gland or in the neonatal gastrointestinal tract are unaffected by the hydrolytic environment present in milk. These results provide insight into the intrinsic structural mechanisms that facilitate the selectivity of the endogenous milk protease activity and might be useful to those studying the peptidomes of other biofluids.

Peptidomics of Urine and Other Biofluids for Cancer Diagnostics

BACKGROUND

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

CONTENT

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

SUMMARY

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

A novel urine peptide biomarker-based algorithm for the prognosis of necrotising enterocolitis in human infants

OBJECTIVE

Necrotising enterocolitis (NEC) is a major source of neonatal morbidity and mortality. The management of infants with NEC is currently complicated by our inability to accurately identify those at risk for progression of disease prior to the development of irreversible intestinal necrosis. We hypothesised that integrated analysis of clinical parameters in combination with urine peptide biomarkers would lead to improved prognostic accuracy in the NEC population.

DESIGN

Infants under suspicion of having NEC (n=550) were prospectively enrolled from a consortium consisting of eight university-based paediatric teaching hospitals. Twenty-seven clinical parameters were used to construct a multivariate predictor of NEC progression. Liquid chromatography/mass spectrometry was used to profile the urine peptidomes from a subset of this population (n=65) to discover novel biomarkers of NEC progression. An ensemble model for the prediction of disease progression was then created using clinical and biomarker data.

RESULTS

The use of clinical parameters alone resulted in a receiver-operator characteristic curve with an area under the curve of 0.817 and left 40.1% of all patients in an 'indeterminate' risk group. Three validated urine peptide biomarkers (fibrinogen peptides: FGA1826, FGA1883 and FGA2659) produced a receiver-operator characteristic area under the curve of 0.856. The integration of clinical parameters with urine biomarkers in an ensemble model resulted in the correct prediction of NEC outcomes in all cases tested.

CONCLUSIONS

Ensemble modelling combining clinical parameters with biomarker analysis dramatically improves our ability to identify the population at risk for developing progressive NEC.

Urine protein biomarkers for the diagnosis and prognosis of necrotizing enterocolitis in infants

OBJECTIVES

To test the hypothesis that an exploratory proteomics analysis of urine proteins with subsequent development of validated urine biomarker panels would produce molecular classifiers for both the diagnosis and prognosis of infants with necrotizing enterocolitis (NEC).

STUDY DESIGN

Urine samples were collected from 119 premature infants (85 NEC, 17 sepsis, 17 control) at the time of initial clinical concern for disease. The urine from 59 infants was used for candidate biomarker discovery by liquid chromatography/mass spectrometry. The remaining 60 samples were subject to enzyme-linked immunosorbent assay for quantitative biomarker validation.

RESULTS

A panel of 7 biomarkers (alpha-2-macroglobulin-like protein 1, cluster of differentiation protein 14, cystatin 3, fibrinogen alpha chain, pigment epithelium-derived factor, retinol binding protein 4, and vasolin) was identified by liquid chromatography/mass spectrometry and subsequently validated by enzyme-linked immunosorbent assay. These proteins were consistently found to be either up- or down-regulated depending on the presence, absence, or severity of disease. Biomarker panel validation resulted in a receiver-operator characteristic area under the curve of 98.2% for NEC vs sepsis and an area under the curve of 98.4% for medical NEC vs surgical NEC.

CONCLUSIONS

We identified 7 urine proteins capable of providing highly accurate diagnostic and prognostic information for infants with suspected NEC. This work represents a novel approach to improving the efficiency with which we diagnose early NEC and identify those at risk for developing severe, or surgical, disease.

Optimization for peptide sample preparation for urine peptidomics

Analysis of native or endogenous peptides in biofluids can provide valuable insights into disease mechanisms. Furthermore, the detected peptides may also have utility as potential biomarkers for non-invasive monitoring of human diseases. The non-invasive nature of urine collection and the abundance of peptides in the urine makes analysis by high-throughput ‘peptidomics’ methods , an attractive approach for investigating the pathogenesis of renal disease. However, urine peptidomics methodologies can be problematic with regards to difficulties associated with sample preparation. The urine matrix can provide significant background interference in making the analytical measurements that it hampers both the identification of peptides and the depth of the peptidomics read when utilizing LC-MS based peptidome analysis. We report on a novel adaptation of the standard solid phase extraction (SPE) method to a modified SPE (mSPE) approach for improved peptide yield and analysis sensitivity with LC-MS based peptidomics in terms of time, cost, clogging of the LC-MS column, peptide yield, peptide quality, and number of peptides identified by each method. Expense and time requirements were comparable for both SPE and mSPE, but more interfering contaminants from the urine matrix were evident in the SPE preparations (e.g., clogging of the LC-MS columns, yellowish background coloration of prepared samples due to retained urobilin, lower peptide yields) when compared to the mSPE method. When we compared data from technical replicates of 4 runs, the mSPE method provided significantly improved efficiencies for the preparation of samples from urine (e.g., mSPE peptide identification 82% versus 18% with SPE; p = 8.92E-05). Additionally, peptide identifications, when applying the mSPE method, highlighted the biology of differential activation of urine peptidases during acute renal transplant rejection with distinct laddering of specific peptides, which was obscured for most proteins when utilizing the conventional SPE method. In conclusion, the mSPE method was found to be superior to the conventional, standard SPE method for urine peptide sample preparation when applying LC-MS peptidomics analysis due to the optimized sample clean up that provided improved experimental inference from the confidently identified peptides.

Classical MALDI-MS versus CE-based ESI-MS proteomic profiling in urine for clinical applications

Human urine is an attractive and informative biofluid for medical diagnosis, which has been shown to reflect the (patho)-physiology of not only the urogenital system, but also others such as the cardiovascular system. For this reason, many studies have concentrated on the study of the urine proteome, aiming to find relevant biomarkers that could be applied in a clinical setting. However, this goal can only be achieved after reliable quantitative and qualitative analysis of the urinary proteome. In the last two decades, MS-based platforms have evolved to become indispensable tools for biomarker research. In this review, we will present and compare two of the most clinically relevant analytical platforms that have been used for the study of the urinary proteome, namely CE-based ESI-MS and classical MALDI-MS. These platforms, although not directly comparable, have been extensively used in proteomic profiling and therefore their comparison is fundamentally relevant to this field.

Peptidomic Identification of Serum Peptides Diagnosing Preeclampsia

We sought to identify serological markers capable of diagnosing preeclampsia (PE). We performed serum peptide analysis (liquid chromatography mass spectrometry) of 62 unique samples from 31 PE patients and 31 healthy pregnant controls, with two-thirds used as a training set and the other third as a testing set. Differential serum peptide profiling identified 52 significant serum peptides, and a 19-peptide panel collectively discriminating PE in training sets (n = 21 PE, n = 21 control; specificity = 85.7% and sensitivity = 100%) and testing sets (n = 10 PE, n = 10 control; specificity = 80% and sensitivity = 100%). The panel peptides were derived from 6 different protein precursors: 13 from fibrinogen alpha (FGA), 1 from alpha-1-antitrypsin (A1AT), 1 from apolipoprotein L1 (APO-L1), 1 from inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4), 2 from kininogen-1 (KNG1), and 1 from thymosin beta-4 (TMSB4). We concluded that serum peptides can accurately discriminate active PE. Measurement of a 19-peptide panel could be performed quickly and in a quantitative mass spectrometric platform available in clinical laboratories. This serum peptide panel quantification could provide clinical utility in predicting PE or differential diagnosis of PE from confounding chronic hypertension.

Quantitation of endogenous peptides using mass spectrometry based methods

The mass spectrometry-based 'omics' sub-discipline that focuses on comprehensive, often exploratory, analyses of endogenous peptides involved in cell-to-cell communication is oftentimes referred to as peptidomics. Although the progress in bioanalytical technology development for peptide discovery has been tremendous, perhaps the largest advances have involved robust quantitative mass spectrometric approaches and data mining algorithms. These efforts have accelerated the discovery and validation of biomarkers, functionally important posttranslational modifications, and unexpected molecular interactions, information that aids drug development. In this article we outline the current approaches used in quantitative peptidomics and the technical challenges that stimulate new advances in the field, while also reviewing the newest literature on functional characterizations of endogenous peptides using quantitative mass spectrometry.

Peptidomic analysis of human reflex tear fluid

Tear fluid is a complex mixture of biological compounds, including carbohydrates, lipids, electrolytes, proteins, and peptides. Despite the physiological importance of tear fluid, little is known about the identity of its endogenous peptides. In this study, we analyzed and identified naturally occurring peptide molecules in human reflex tear fluid by means of LC-MALDI-TOF-TOF. Tandem MS analyses revealed 30 peptides, most of which have not been identified before. Twenty-six peptides are derived from the proline-rich protein 4 and 4 peptides are derived from the polymeric immunoglobulin receptor. Based on their structural characteristics, we suggest that the identified tear fluid peptides contribute to the protective environment of the ocular surface.

Untargeted screening of urinary peptides with liquid chromatography coupled to hybrid linear-ion trap tandem mass spectrometry

We formerly developed and applied a liquid chromatography coupled with hybrid triple quadrupole-linear ion trap mass spectrometry technique for the detection and identification of exogenous compounds in clinical and forensic toxicology. In this study, we aimed to adapt this technique to the detection and identification of the constituents of the urinary peptidome. After solid-phase extraction, separation was performed using gradient reversed-phase liquid chromatography. The mass spectrometer was operated in the information-dependent acquisition mode, switching between: a survey scan acquired in the enhanced multi-charged scan mode with dynamic subtraction of background noise; and two dependent scans obtained in the enhanced product ion scan mode. The results obtained show that: (i) the present procedure is able to detect and identify peptides which, together with their inferred parent proteins, are similar to those referenced in the related literature; (ii) the structure of some peptides can generally be resolved from their enhanced product ion spectra; and (iii) confirmation of the sequences proposed through library search by in silico verification of the fragments observed in the enhanced product ion spectra seems to be indispensable to avoid misinterpretations.

Clinical neuroproteomics and biomarkers: from basic research to clinical decision making

Clinical neuroproteomics aims to advance our understanding of disease and injury affecting the central and peripheral nervous systems through the study of protein expression and the discovery of protein biomarkers to facilitate diagnosis and treatment. The general premise of the biomarker field is that in vivo factors present in either tissue or circulating biofluids, reflect pathological changes, and can be identified and analyzed. This approach offers an opportunity to illuminate changes occurring at both the population and patient levels toward the realization of personalized medicine. This review is intended to provide research-driven clinicians with an overview of protein biomarkers of disease and injury for clinical use and to highlight methodology and potential pitfalls. We examine the neuroproteomic biomarker field and discuss the hallmarks and the challenges of clinically relevant biomarker discovery relating to central nervous system pathology. We discuss the issues in the maturation of potential biomarkers from discovery to Food and Drug Administration approval and review several platforms for protein biomarker discovery, including protein microarray and mass spectrometry-based proteomics. We describe the application of microfluidic technologies to the evolution of a robust clinical test. Finally, we highlight several biomarkers currently in use for cancer, ischemia, and injury in the central nervous system. Future efforts using these technologies will result in the maturation of existing and the identification of de novo biomarkers that could guide clinical decision making and advance diagnostic and therapeutic options for the treatment of neurological disease and injury.

Proteomic candidate biomarkers of drug-induced nephrotoxicity in the rat

Improved biomarkers of acute nephrotoxicity are coveted by the drug development industry, regulatory agencies, and clinicians. In an effort to identify such biomarkers, urinary peptide profiles of rats treated with two different nephrotoxins were investigated. 493 marker candidates were defined that showed a significant response to cis-platin comparing a cis-platin treated cohort to controls. Next, urine samples from rats that received three consecutive daily doses of 150 or 300 mg/kg gentamicin were examined. 557 potential biomarkers were initially identified; 108 of these gentamicin-response markers showed a clear temporal response to treatment. 39 of the cisplatin-response markers also displayed a clear response to gentamicin. Of the combined 147 peptides, 101 were similarly regulated by gentamicin or cis-platin and 54 could be identified by tandem mass spectrometry. Most were collagen type I and type III fragments up-regulated in response to gentamicin treatment. Based on these peptides, classification models were generated and validated in a longitudinal study. In agreement with histopathology, the observed changes in classification scores were transient, initiated after the first dose, and generally persistent over a period of 10–20 days before returning to control levels. The data support the hypothesis that gentamicin-induced renal toxicity up-regulates protease activity, resulting in an increase in several specific urinary collagen fragments. Urinary proteomic biomarkers identified here, especially those common to both nephrotoxins, may serve as a valuable tool to investigate potential new drug candidates for the risk of nephrotoxicity.

MS/MS library facilitated MRM quantification of native peptides prepared by denaturing ultrafiltration

Naturally occurring native peptides provide important information about physiological states of an organism and its changes in disease conditions but protocols and methods for assessing their abundance are not well-developed. In this paper, we describe a simple procedure for the quantification of non-tryptic peptides in body fluids. The workflow includes an enrichment step followed by two-dimensional fractionation of native peptides and MS/MS data management facilitating the design and validation of LC- MRM MS assays. The added value of the workflow is demonstrated in the development of a triplex LC-MRM MS assay used for quantification of peptides potentially associated with the progression of liver disease to hepatocellular carcinoma.

A diagnostic algorithm combining clinical and molecular data distinguishes Kawasaki disease from other febrile illnesses

BACKGROUND

Kawasaki disease is an acute vasculitis of infants and young children that is recognized through a constellation of clinical signs that can mimic other benign conditions of childhood. The etiology remains unknown and there is no specific laboratory-based test to identify patients with Kawasaki disease. Treatment to prevent the complication of coronary artery aneurysms is most effective if administered early in the course of the illness. We sought to develop a diagnostic algorithm to help clinicians distinguish Kawasaki disease patients from febrile controls to allow timely initiation of treatment.

METHODS

Urine peptidome profiling and whole blood cell type-specific gene expression analyses were integrated with clinical multivariate analysis to improve differentiation of Kawasaki disease subjects from febrile controls.

RESULTS

Comparative analyses of multidimensional protein identification using 23 pooled Kawasaki disease and 23 pooled febrile control urine peptide samples revealed 139 candidate markers, of which 13 were confirmed (area under the receiver operating characteristic curve (ROC AUC 0.919)) in an independent cohort of 30 Kawasaki disease and 30 febrile control urine peptidomes. Cell type-specific analysis of microarrays (csSAM) on 26 Kawasaki disease and 13 febrile control whole blood samples revealed a 32-lymphocyte-specific-gene panel (ROC AUC 0.969). The integration of the urine/blood based biomarker panels and a multivariate analysis of 7 clinical parameters (ROC AUC 0.803) effectively stratified 441 Kawasaki disease and 342 febrile control subjects to diagnose Kawasaki disease.

CONCLUSIONS

A hybrid approach using a multi-step diagnostic algorithm integrating both clinical and molecular findings was successful in differentiating children with acute Kawasaki disease from febrile controls.

Urine Peptidomic and Targeted Plasma Protein Analyses in the Diagnosis and Monitoring of Systemic Juvenile Idiopathic Arthritis

PURPOSE: Systemic juvenile idiopathic arthritis is a chronic pediatric disease. The initial clinical presentation can mimic other pediatric inflammatory conditions, which often leads to significant delays in diagnosis and appropriate therapy. SJIA biomarker development is an unmet diagnostic/prognostic need to prevent disease complications. EXPERIMENTAL DESIGN: We profiled the urine peptidome to analyze a set of 102 urine samples, from patients with SJIA, Kawasaki disease (KD), febrile illnesses (FI), and healthy controls. A set of 91 plasma samples, from SJIA flare and quiescent patients, were profiled using a customized antibody array against 43 proteins known to be involved in inflammatory and protein catabolic processes. RESULTS: We identified a 17-urine-peptide biomarker panel that could effectively discriminate SJIA patients at active, quiescent, and remission disease states, and patients with active SJIA from confounding conditions including KD and FI. Targeted sequencing of these peptides revealed that they fall into several tight clusters from seven different proteins, suggesting disease-specific proteolytic activities. The antibody array plasma profiling identified an SJIA plasma flare signature consisting of tissue inhibitor of metalloproteinase-1 (TIMP1), interleukin (IL)-18, regulated upon activation, normal T cell expressed and secreted (RANTES), P-Selectin, MMP9, and L-Selectin. CONCLUSIONS AND CLINICAL RELEVANCE: The urine peptidomic and plasma protein analyses have the potential to improve SJIA care and suggest that SJIA urine peptide biomarkers may be an outcome of inflammation-driven effects on catabolic pathways operating at multiple sites. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s12014-010-9058-8) contains supplementary material, which is available to authorized users.