Renal and urinary proteomics: current applications and challenges

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.

DIA-based analysis of the menstrual blood proteome identifies association between CXCL5 and IL1RN and endometriosis

Endometriosis is a gynecological disease related to menstruation that affects nearly 10% of reproductive-age women. However, so far, there are no reliable diagnostic biomarkers for endometriosis, causing a delay in diagnosis of 6.7 ± 6.2 years. Menstrual blood is a non-invasive source of endometrial tissue that can be analyzed for biomarkers of endometriosis. In this study, menstrual blood samples were collected from women with (n = 8) and without (n = 8) endometriosis. Data Independent Acquisition (DIA)-based mass spectrometry and bioinformatic analysis were used to quantify and identify differentially expressed proteins (DEPs) using the thresholds of fold change >1.5 and P value <0.05. A total of 95 DEPs were identified in menstrual blood from women with endometriosis compared to women without endometriosis, of which 64 were up-regulated and 31 were down-regulated. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to functionally annotate DEPs. Protein-protein interaction (PPI) network analysis was then conducted to identify hub genes and the MCODE plugin placed CXCL1, CXCL3, CXCL5, CCL18, and IL1RN in the most significant cluster network. The expression of the above candidate proteins was confirmed by enzyme-linked immunosorbent assay (ELISA), among which CXCL5 and IL1RN protein expression was increased in patients with endometriosis, indicating that CXCL5 and IL1RN in menstrual blood may be useful biomarkers to diagnose endometriosis from non-invasive samples. SIGNIFICANCE: Endometriosis is a common gynecological disease that causes discomfort in many women. Unfortunately, the diagnosis of endometriosis is frequently delayed due to a lack of reliable non-invasive biomarkers. To our knowledge, this is the first time that DIA-MS was used to characterize the proteome and identify the differentially expressed proteins in menstrual blood from women with endometriosis. The results, as confirmed by ELISA, showed that CXCL5 and IL1RN protein expression is significantly increased in patients with endometriosis, indicating that these proteins can be used as biomarkers for endometriosis. This study contributes to the identification of putative endometriosis biomarkers from non-invasive samples and lays the groundwork for future research into the roles of CXCL5 and IL1RN in the pathogenesis of endometriosis.

Contemporary Biomarkers for Renal Transplantation: A Narrative Overview

Renal transplantation (RT) is the preferred treatment for end-stage renal disease. However, clinical challenges persist, i.e., early detection of graft dysfunction, timely identification of rejection episodes, personalization of immunosuppressive therapy, and prediction of long-term graft survival. Biomarkers have emerged as valuable tools to address these challenges and revolutionize RT patient care. Our review synthesizes the existing scientific literature to highlight promising biomarkers, their biological characteristics, and their potential roles in enhancing clinical decision-making and patient outcomes. Emerging non-invasive biomarkers seemingly provide valuable insights into the immunopathology of nephron injury and allograft rejection. Moreover, we analyzed biomarkers with intra-nephron specificities, i.e., glomerular vs. tubular (proximal vs. distal), which can localize an injury in different nephron areas. Additionally, this paper provides a comprehensive analysis of the potential clinical applications of biomarkers in the prediction, detection, differential diagnosis and assessment of post-RT non-surgical allograft complications. Lastly, we focus on the pursuit of immune tolerance biomarkers, which aims to reclassify transplant recipients based on immune risk thresholds, guide personalized immunosuppression strategies, and ultimately identify patients for whom immunosuppression may safely be reduced. Further research, validation, standardization, and prospective studies are necessary to fully harness the clinical utility of RT biomarkers and guide the development of targeted therapies.

Microheterogeneity and Individual Differences of Human Urinary N-Glycome under Normal Physiological Conditions

Urine is considered an outstanding biological fluid for biomarker discovery, reflecting both systemic and urogenital physiology. However, analyzing the N-glycome in urine in detail has been challenging due to the low abundance of glycans attached to glycoproteins compared to free oligosaccharides. Therefore, this study aims to thoroughly analyze urinary N-glycome using LC-MS/MS. The N-glycans were released using hydrazine and labeled with 2-aminopyridine (PA), followed by anion-exchange fractionation before LC-MS/MS analysis. A total of 109 N-glycans were identified and quantified, of which 58 were identified and quantified repeatedly in at least 80% of samples and accounted for approximately 85% of the total urinary glycome signal. Interestingly, a comparison between urine and serum N-glycome revealed that approximately 50% of the urinary glycome could originate from the kidney and urinary tract, where they were exclusively identified in urine, while the remaining 50% were common in both. Additionally, a correlation was found between age/sex and the relative abundances of urinary N-glycome, with more age-related changes observed in women than men. The results of this study provide a reference for human urine N-glycome profiling and structural annotations.

Urinary proteome profiles associated with cognitive decline in community elderly residents—A pilot study

Non-invasive and simple methods enabling easy identification of individuals at high risk of cognitive decline are needed as preventive measures against dementia. This pilot study aimed to explore protein biomarkers that can predict cognitive decline using urine, which can be collected non-invasively. Study subjects were selected from participants in a cohort study of middle-aged and older community-dwelling adults who underwent cognitive testing using the Mini-Mental State Examination and provided spot urine samples at two time points with an interval of approximately 5 years. Seven participants whose cognitive function declined 4 or more points from baseline (Group D) and 7 sex- and age-matched participants whose cognitive function remained within the normal range during the same period (Group M) were selected. Urinary proteomics using mass spectrometry was performed and discriminant models were created using orthogonal partial least squares-discriminant analysis (OPLS-DA). OPLS-DA yielded two models that significantly discriminated between the two groups at baseline and follow-up. Both models had ORM1, ORM2, and SERPINA3 in common. A further OPLS-DA model using baseline ORM1, ORM2, and SERPINA3 data showed similar predictive performance for data at follow-up as it did for baseline data (sensitivity: 0.85, specificity: 0.85), with the receiver operating characteristic curve analysis yielding an area under the curve of 0.878. This prospective study demonstrated the potential for using urine to identify biomarkers of cognitive decline.

DIA mass spectrometry characterizes urinary proteomics in neonatal and adult donkeys

Health monitoring is critical for newborn animals due to their vulnerability to diseases. Urine can be not only a useful and non-invasive tool (free-catch samples) to reflect the physiological status of animals but also to help monitor the progression of diseases. Proteomics involves the study of the whole complement of proteins and peptides, including structure, quantities, functions, variations and interactions. In this study, urinary proteomics of neonatal donkeys were characterized and compared to the profiles of adult donkeys to provide a reference database for healthy neonatal donkeys. The urine samples were collected from male neonatal donkeys on their sixth to tenth days of life (group N) and male adult donkeys aging 4-6 years old (group A). Library-free data-independent acquisition (direct DIA) mass spectrometry-based proteomics were applied to analyze the urinary protein profiles. Total 2179 urinary proteins were identified, and 411 proteins were differentially expressed (P < 0.05) between the two groups. 104 proteins were exclusively expressed in group N including alpha fetoprotein (AFP), peptidase-mitochondrial processing data unit (PMPCB), and upper zone of growth plate and cartilage matrix associated (UCMA), which might be used to monitor the health status of neonatal donkeys. In functional analysis, some differentially expressed proteins were identified related to immune system pathways, which might provide more insight in the immature immunity of neonatal donkeys. To the best of our knowledge, this is the first time to report donkey urinary proteome and our results might provide reference for urinary biomarker discovery used to monitor and evaluate health status of neonatal donkeys.

Urinary Protein Profiling for Potential Biomarkers of Chronic Kidney Disease: A Pilot Study

Proteinuria is a risk factor for chronic kidney disease (CKD) progression and associated complications. However, there is insufficient information on individual protein components in urine and the severity of CKD. We aimed to investigate urinary proteomics and its association with proteinuria and kidney function in early-stage CKD and in healthy individuals. A 24 h urine sample of 42 individuals (21-CKD and 21-healthy individuals) was used for mass spectrometry-based proteomics analysis. An exponentially modified protein abundance index (emPAI) was calculated for each protein. Data were analyzed by Mascot software using the SwissProt database and bioinformatics tools. Overall, 298 unique proteins were identified in the cohort; of them, 250 proteins belong to the control group with median (IQR) emPAI 39.1 (19−53) and 142 proteins belong to the CKD group with median (IQR) emPAI 67.8 (49−117). The level of 24 h proteinuria positively correlated with emPAI (r = 0.390, p = 0.011). The emPAI of some urinary proteomics had close positive (ALBU, ZA2G, IGKC) and negative (OSTP, CD59, UROM, KNG1, RNAS1, CD44, AMBP) correlations (r < 0.419, p < 0.001) with 24 h proteinuria levels. Additionally, a few proteins (VTDB, AACT, A1AG2, VTNC, and CD44) significantly correlated with kidney function. In this proteomics study, several urinary proteins correlated with proteinuria and kidney function. Pathway analysis identified subpathways potentially related to early proteinuric CKD, allowing the design of prospective studies that explore their response to therapy and their relationship to long-term outcomes.

Urinary Biomarkers for Detection of Clinical Endometriosis or Adenomyosis

Endometriosis or adenomyosis can be clinically diagnosed by ultrasound, symptoms, physical examination, and serum CA125. The urinary markers need to be investigated. The aim of our study was to investigate the urinary markers of clinical endometriosis/adenomyosis, and the correlation of serum CA125 was also studied. From the literature, alpha-1 antitrypsin (A1AT), enolase-1, vitamin D binding protein (VDBP), and CA125 in urine and serum were used in our study and measured by enzyme-linked immunosorbent assays (ELISA). Further clinical correlation and detection performance were evaluated. We enrolled 19 normal controls and 33 patients clinically diagnosed with endometriosis/adenomyosis. There were significant differences between studied patients and normal controls, as follows: serum CA125 (130.91 vs. 19.75 U/mL, p = 0.004); urinary CA125-creatinine ratio (5.591 vs. 0.254 ng/mg, p = 0.028); and urinary VDBP-creatinine ratio (28.028 vs. 7.301 ng/mg, p = 0.018). For diagnostic performances, serum CA125 provided the best results, with an area under curve (AUC) of 0.888 (p = 0.001) and accuracy of 86.5%. Other excellent results were also found using urinary VDBP (AUC 0.841, p = 0.001) and A1AT (AUC 0.722, p = 0.011) creatinine ratio. Using three combined biomarkers, serum CA125, urinary VDBP, and A1AT creatinine ratio, provided good detection power (AUC 0.913, p = 0.001, sensitivity 90.9%, specificity 76.5%). Double urine markers used in combination with VDBP and A1AT creatinine ratio also provided good diagnostic performance (AUC 0.809, p = 0.001, sensitivity 81.8%, specificity 76.5%, accuracy 80%). Further development of non-invasive point-of-care tests using these biomarkers could be a fruitful future endeavor.

Differential expression of aerobic oxidative metabolism-related proteins in diabetic urinary exosomes

BACKGROUND

As a metabolic disease, any abnormality in the aerobic oxidation pathway of glucose may lead to the occurrence of diabetes. This study aimed to investigate the changes in proteins related to aerobic oxidative metabolism in urinary exosomes of diabetic patients and normal controls of different ages, and to further verify their correlation with the pathogenesis of diabetes.

METHODS

Samples were collected, and proteomic information of urinary exosomes was collected by LC-MS/MS. ELISA was used to further detect the expression of aerobic and oxidative metabolism-related proteins in urinary exosomes of diabetic patients and normal controls of different ages, and to draw receiver operating characteristic (ROC) curve to evaluate its value in diabetes monitoring.

RESULTS

A total of 17 proteins involved in aerobic oxidative metabolism of glucose were identified in urinary exosome proteins. Compared with normal control, the expressions of PFKM, GAPDH, ACO2 and MDH2 in diabetic patients were decreased, and the expression of IDH3G was increased. The concentrations of PFKM, GAPDH and ACO2 in urinary exosomes were linearly correlated with the expression of MDH2 (P<0.05). These four proteins vary with age, with the maximum concentration in the 45-59 age group. PFKM, GAPDH, ACO2, and MDH2 in urinary exosomes have certain monitoring value. When used in combination, the AUC was 0.840 (95% CI 0.764-0.915).

CONCLUSIONS

In diabetic patients, aerobic oxidative metabolism is reduced, and the expression of aerobic oxidative metabolism-related proteins PFKM, GAPDH, ACO2, and MDH2 in urinary exosomes is reduced, which may become potential biomarkers for monitoring changes in diabetes.

Urinary Proteomics in Kidney Transplantation

Although kidney transplantation is the best treatment option for end stage kidney disease, it is still associated with long-term graft failure. One of the greater challenges for transplant professionals is the ability to identify grafts with a high risk of failure before initial decline of eGFR with irreversible graft changes. Transplantation medicine is facing an emerging need for novel disease end point-specific biomarkers, with practical application in preventive screening, early diagnostic, and improved prognostic and therapeutic utility. The aim of our review was to evaluate the clinical application of urinary proteomics in kidney transplant recipients at risk for any type of future graft failure.

Urinary Proteomics for Noninvasive Prenatal Screening of Trisomy 21: New Biomarker Candidates

Trisomy 21 is a common birth defect in humans. Screening for trisomy 21 is one of the most important tasks in routine prenatal care and robust noninvasive diagnostics are needed in clinical practice. Urinary proteomics offers a new research platform for diagnostics innovation in this context. We report here new biomarker candidates using urinary proteomics profiling. Specifically, we used liquid chromatography-tandem mass spectrometry (LC-MS/MS) to analyze the proteomes of urine samples from 19 pregnant women (aged 28-44 years) carrying fetuses with trisomy 21 and 22 healthy pregnant women (aged 27-42 years) carrying fetuses with normal karyotype. We identified more than 50 differentially expressed proteins between the trisomy 21 group and healthy group, and most of these proteins were associated with the embryonic development. Importantly, tissue inhibitor of metalloproteinases 2 (TIMP2) and lysosomal-associated membrane protein 2 (LAMP2) were further selected as potential urinary protein biomarkers. We found that the combination of TIMP2 and LAMP2 could differentiate fetuses with trisomy 21 from healthy controls with a sensitivity of 74%, a specificity of 82%, and an area under the receiver operating characteristic curves (AUC) value of 0.82 (95% confidence interval, 0.69-0.95). We conclude that TIMP2 and LAMP2 offer promise as biomarker candidates and warrant further clinical research in larger study samples. These findings further our understanding of the pathological processes involved in fetal trisomy 21 and are poised to accelerate the development of new noninvasive potential biomarkers for trisomy 21 prenatal screening.

Kidney stone proteomics: an update and perspectives

INTRODUCTION

Main problems of kidney stone disease are its increasing prevalence and high recurrence rate after calculi removal in almost all areas around the globe. Despite enormous efforts in the past, its pathogenic mechanisms remain unclear and need further elucidations. Proteomics has thus become an essential tool to unravel such sophisticated disease mechanisms at cellular, subcellular, molecular, tissue, and whole organism levels.

AREAS COVERED

This review provides abrief overview of kidney stone disease followed by updates on proteomics for investigating urinary stone modulators, matrix proteins, cellular responses to different types/doses of calcium oxalate (CaOx) crystals, sex hormones and other stimuli, crystal-cell interactions, crystal receptors, secretome, and extracellular vesicles (EVs), all of which lead to better understanding of the disease mechanisms. Finally, the future challenges and translation of these obtained data to the clinic are discussed.

EXPERT OPINION

Knowledge from urinary proteomics for exploring the important stone modulators (either inhibitors or promoters) will be helpful for early detection of asymptomatic cases for prompt prevention of symptoms, complications, and new stone formation. Moreover, these modulators may serve as the new therapeutic targets in the future for successful treatment and prevention of kidney stone disease by medications or other means of intervention.

Urinary proteomic analysis to identify a potential protein biomarker panel for the diagnosis of tuberculosis

Tuberculosis (TB) is caused by Mycobacterium tuberculosis and is one of the primary causes of death worldwide. Rapid and accurate diagnosis of TB is one of the most direct means to reduce the incidence of TB. In this study, urinary proteomic profiling of TB patients and non-TB individual controls (HCs) was performed, and differentially expressed urinary proteins between TB and HCs were compared and exclusively expressed proteins in TB patients were selected to establish a clinically useful disease marker panel. In total, these top 11 targeted proteins with 265 peptides were scheduled for multiple reaction monitoring validation analysis by using urine samples from 52 TB patients and 52 HCs. The result demonstrated that a three-protein combination out of the five-protein panel (namely P22352, Q9P121, P15151, Q13291, and Q8NDA2) exhibited sensitivity rate of 82.7% in the diagnosis of TB. Furthermore, the three-protein combination could differentiate TB from the latent tuberculosis (LTB) effectively, which exhibited specificity rate of 92.3% for the diagnosis of TB from the LTB category. Although more numbers of clinical samples are required for further verification, the results provided preliminary evidence that this "three-protein combination" out of the five-protein panel could probably be a novel TB diagnostic biomarker in clinical application.

Urine proteomics for profiling of mouse toxoplasmosis using liquid chromatography tandem mass spectrometry analysis

BACKGROUND

Toxoplasma gondii is an obligate intracellular parasite that causes toxoplasmosis. Urine is an easily obtained clinical sample that has been widely applied for diagnostic purposes. However, changes in the urinary proteome during T. gondii infection have never been investigated.

METHODS

Twenty four-hour urine samples were obtained from BALB/c mice with acute infection [11 days post infection (DPI)], mice with chronic infection (35 DPI) and healthy controls, and were analyzed using a label-free liquid chromatography tandem mass spectrometry analysis.

RESULTS

We identified a total of 13,414 peptides on 1802 proteins, of which 169 and 47 proteins were significantly differentially expressed at acute and chronic infection phases, respectively. Clustering analysis revealed obvious differences in proteome profiles among all groups. Gene ontology analysis showed that a large number of differentially expressed proteins (DEPs) detected in acute infection were associated with biological binding activity and single-organism processes. KEGG pathway enrichment analysis showed that the majority of these DEPs were involved in disease-related and metabolic pathways.

CONCLUSIONS

Our findings revealed global reprogramming of the urine proteome following T. gondii infection, and data obtained in this study will enhance our understanding of the host responses to T. gondii infection and lead to the identification of new diagnostic biomarkers.

A Comprehensive Urine Proteome Database Generated From Patients With Various Renal Conditions and Prostate Cancer

Urine proteins can serve as viable biomarkers for diagnosing and monitoring various diseases. A comprehensive urine proteome database, generated from a variety of urine samples with different disease conditions, can serve as a reference resource for facilitating discovery of potential urine protein biomarkers. Herein, we present a urine proteome database generated from multiple datasets using 2D LC-MS/MS proteome profiling of urine samples from healthy individuals (HI), renal transplant patients with acute rejection (AR) and stable graft (STA), patients with non-specific proteinuria (NS), and patients with prostate cancer (PC). A total of ~28,000 unique peptides spanning ~2,200 unique proteins were identified with a false discovery rate of <0.5% at the protein level. Over one third of the annotated proteins were plasma membrane proteins and another one third were extracellular proteins according to gene ontology analysis. Ingenuity Pathway Analysis of these proteins revealed 349 potential biomarkers in the literature-curated database. Forty-three percentage of all known cluster of differentiation (CD) proteins were identified in the various human urine samples. Interestingly, following comparisons with five recently published urine proteome profiling studies, which applied similar approaches, there are still ~400 proteins which are unique to this current study. These may represent potential disease-associated proteins. Among them, several proteins such as serpin B3, renin receptor, and periostin have been reported as pathological markers for renal failure and prostate cancer, respectively. Taken together, our data should provide valuable information for future discovery and validation studies of urine protein biomarkers for various diseases.

Understanding glomerular diseases through proteomics

INTRODUCTION

Chronic kidney disease is avery common and complex chronic disease. Uncovering the pathological patterns of CKD on the molecular level of bio-fluids and tissue appears to be both vital and promising for a more favorable outcome. We reviewed recently discovered proteomics biomarkers for CKD to provide new insight into disease pathology.

AREAS COVERED

We review the application of proteome analysis in the context of CKD with various etiologies within the last 5 years. Proteins and peptides associated with CKD as derived from multiple sources (urine, blood and tissue) are reported along with their various biological pathways.

EXPERT OPINION

A systematic and theoretical comprehension of the CKD pathology is essential for its successful management. The underlying complexity of the disease further requires specific conditions for reliable and interpretable results. In this context, clinical proteomics has resulted in first encouraging findings in CKD. A more complete understanding of the biological pathways related to the disease, based on the scope of a holistic proteomic approach, could improve substantially the management of CKD, especially when in conjunction with the current trend of personalized medicine.

Proteomics Profiling of the Urine of Patients with Hyperthyroidism after Anti-Thyroid Treatment

Hyperthyroidism, which is characterized by increased circulating thyroid hormone levels, alters the body’s metabolic and systemic hemodynamic balance and directly influences renal function. In this study, the urinary proteome of patients with hyperthyroidism was characterized using an untargeted proteomic approach with network analysis. Urine samples were collected from nine age-matched patients before and after carbimazole treatment. Differences in the abundance of urinary proteins between hyperthyroid and euthyroid states were determined using a 2D-DIGE coupled to MALDI-TOF mass spectrometry. Alterations in the abundance of urinary proteins, analyzed via Progenesis software, revealed a statistically significant difference in abundance in a total of 40 spots corresponding to 32 proteins, 25 up and 7 down (≥1.5-fold change, ANOVA, p ≤ 0.05). The proteins identified in the study are known to regulate processes associated with cellular metabolism, transport, and acute phase response. The notable upregulated urinary proteins were serotransferrin, transthyretin, serum albumin, ceruloplasmin, alpha-1B-glycoprotein, syntenin-1, and glutaminyl peptide cyclotransferase, whereas the three notable downregulated proteins were plasma kallikrein, protein glutamine gamma-glutamyl transferase, and serpin B3 (SERPINB3). Bioinformatic analysis using ingenuity pathway analysis (IPA) identified the dysregulation of pathways associated with cellular compromise, inflammatory response, cellular assembly, and organization and identified the involvement of the APP and AKT signaling pathways via their interactions with interleukins as the central nodes.

Current State of "Omics" Biomarkers in Pancreatic Cancer

Pancreatic cancer is one of the most fatal malignancies and the seventh leading cause of cancer-related deaths related to late diagnosis, poor survival rates, and high incidence of metastasis. Unfortunately, pancreatic cancer is predicted to become the third leading cause of cancer deaths in the future. Therefore, diagnosis at the early stages of pancreatic cancer for initial diagnosis or postoperative recurrence is a great challenge, as well as predicting prognosis precisely in the context of biomarker discovery. From the personalized medicine perspective, the lack of molecular biomarkers for patient selection confines tailored therapy options, including selecting drugs and their doses or even diet. Currently, there is no standardized pancreatic cancer screening strategy using molecular biomarkers, but CA19-9 is the most well known marker for the detection of pancreatic cancer. In contrast, recent innovations in high-throughput techniques have enabled the discovery of specific biomarkers of cancers using genomics, transcriptomics, proteomics, metabolomics, glycomics, and metagenomics. Panels combining CA19-9 with other novel biomarkers from different "omics" levels might represent an ideal strategy for the early detection of pancreatic cancer. The systems biology approach may shed a light on biomarker identification of pancreatic cancer by integrating multi-omics approaches. In this review, we provide background information on the current state of pancreatic cancer biomarkers from multi-omics stages. Furthermore, we conclude this review on how multi-omics data may reveal new biomarkers to be used for personalized medicine in the future.

Identification of Protein Changes in the Urine of Hypothyroid Patients Treated with Thyroxine Using Proteomics Approach

The thyroid gland and thyroid hormones control a multitude of homeostatic functions including maintenance of fluid and electrolyte balance and normal functioning of the kidneys. Thyroid dysfunction alters the sytemic hemodynamic and metabolic balance, thereby affecting the kidney. In this study, we aimed to identify and characterize the urinary proteome of the patients with hypothyroidism. An untargeted proteomic approach with network analysis was used to identify changes in total urinary proteome in patients with newly diagnosed overt hypothyroidism. Urine samples were collected from nine age-matched patients' before and after l-thyroxine treatment. Differences in the abundance of urinary proteins between hypothyroid and euthyroid states were determined using a two-dimensional difference in gel electrophoresis (2D-DIGE) coupled to matrix-assisted laser desorption and ionization time-of-flight (MALDI TOF) mass spectrometry. Alterations in the abundance of urinary proteins, analyzed by Progenesis software, revealed statistically significant differential abundance in a total of 49 spots corresponding to 42 proteins, 28 up and 14 down (≥1.5-fold change, analysis of variance (ANOVA), p ≤ 0.05). The proteins identified in the study are known to regulate processes related to transport, acute phase response, oxidative stress, generation of reactive oxygen species, cellular proliferation, and endocytosis. Bioinformatic analysis using Ingenuity Pathway Analysis (IPA) identified dysregulation of pathways related to amino acid metabolism, molecular transport, and small-molecule biochemistry and involved the MAPK kinase, vascular endothelial growth factor (VEGF), PI3 kinase/Akt, protein kinase C (PKC), signaling pathways. The identified proteins were involved in the regulation of thyroglobulin (Tg) and thyrotropin (TSH) metabolism. Alterations in their levels indicate the presence of a compensatory mechanism aimed at increasing the regulation of Tg in the hypothyroid state.

Kidney Diseases: The Age of Molecular Markers

Kidney diseases are conditions that increase the morbidity and mortality of those afflicted. Diagnosis of these conditions is based on parameters such as the glomerular filtration rate (GFR), measurement of serum and urinary creatinine levels and equations derived from these measurements (Wasung, Chawla, Madero. Clin Chim Acta 438:350-357, 2015). However, serum creatinine as a marker for measuring renal dysfunction has its limitations since it is altered in several other physiological situations, such as in patients with muscle loss, after intense physical exercise or in people on a high protein diet (Riley, Powers, Welch. Res Q Exerc Sport 52(3):339-347, 1981; Juraschek, Appel, Anderson, Miller. Am J Kidney Dis 61(4):547-554, 2013). Besides the fact that serum creatinine is a marker that indicates glomerular damage, it is necessary the discovery of new biomarkers that reflect not only glomerular damage but also tubular impairment. Recent advances in Molecular Biology have led to the generation or identification of new biomarkers for kidney diseases such as: Acute Kidney Failure (AKI), chronic kidney disease (CKD), nephritis or nephrotic syndrome. There are recent markers that have been used to aid in diagnosis and have been shown to be more sensitive and specific than classical markers, such as neutrophil gelatinase associated lipocalin (NGAL) or kidney injury molecule-1 (KIM-1) (Wasung, Chawla, Madero. Clin Chim Acta 438:350-357, 2015; George, Gounden. Adv Clin Chem 88:91-119, 2019; Han, Bailly, Abichandani, Thadhani, Bonventre. Kidney Int 62(1):237-244, 2002; Fontanilla, Han. Expert Opin Med Diagn 5(2):161-173, 2011). However, early diagnostic biomarkers are still necessary to assist the intervention and monitor of the progression of these conditions.

Peptides in Plasma, Urine, and Dialysate: Toward Unravelling Renal Peptide Handling

PURPOSE

The peptidomes of spent hemodialysate, urine, and plasma are investigated, to shed light on peptide handling in the kidney.

EXPERIMENTAL DESIGN

Fifteen plasma, 15 urine, and 13 spent hemodialysate samples are collected from age- and sex-matched subjects with chronic kidney disease. Peptide identification and quantification are performed with capillary electrophoresis-coupled mass spectrometry.

RESULTS

A total of 6278 urinary peptides, 1743 plasma peptides, and 1727 peptides from spent hemodialysate are detected. Of these, sequences can be assigned to 1580, 419, and 352 peptides, respectively. A strong correlation in peptide abundance between urine and spent hemodialysate (p = 3 × 10-21 , Rho = 0.52), a moderately strong correlation between spent hemodialysate and plasma (p = 4.5 × 10-5 , Rho = 0.30), and no significant correlation between urine and plasma (p = 0.11, Rho = 0.094) are found. Collagen and fibrinogen alpha peptides are highly abundant in all three body fluids. In spent hemodialysate, thymosin ß4 is one of the most abundant peptides, which is shown to be negatively associated with the estimated glomerular filtration rate (Rho = -0.39, p-value = 3.9 × 10-81 ).

CONCLUSION AND CLINICAL RELEVANCE

The correlation of peptide abundance in these three body fluids is lower than expected, supporting the hypothesis that tubular reabsorption has a major impact on urinary peptide content. Further investigation of thymosin ß4 in hemodialysis is thus warranted.

Matrix Remodeling-Associated Protein 5 in Urinary Exosomes as a Potential Novel Marker of Obstructive Nephropathy in Children With Ureteropelvic Junction Obstruction

Recent investigations have described the use of urinary matrix remodeling-associated protein 5 (MXRA5) as a novel biomarker of kidney impairment in the setting of chronic kidney disease. In this study, we aimed to evaluate the possible clinical application of urinary MXRA5 as a useful non-invasive marker in the urine from the affected renal pelvis and bladder of children with ureteropelvic junction obstruction (UPJO). We conducted a prospective cohort study of patients aged <12 months with prenatally diagnosed unilateral UPJO who underwent dismembered pyeloplasty in 2018 or 2019, and a sex- and age-matched control group of healthy children. Blood urea nitrogen and creatinine levels were normal in all the patients. The whole urine and urinary exosomal concentrations of MXRA5 were measured by enzyme-linked immunosorbent assay. The correlations between bladder/renal pelvic MXRA5 levels and differential renal function (DRF) in the affected kidney were also determined. A total of 35 UPJO patients and 12 controls were enrolled in the study. There was no significant difference in whole-urine MXRA5 level between the controls and UPJO patients. However, the exosomal MXRA5 level was significantly lower in the controls than in patients with UPJO (p < 0.05). There were non-significant correlations between bladder and renal pelvis whole-urine MXRA5 levels and DRF (R 2 = 0.1115, p = 0.05 and R 2 = 0.3313, p = 0.0502, respectively). The strongest correlation was between exosomal MXRA5 level in the renal pelvis and DRF (R 2 = 0.8128, p < 0.0001). Urinary exosomal MXRA5 level was significantly higher in children with UPJO than controls. Higher urinary exosomal MXRA5 levels were significantly correlated with lower DRF in the affected kidney in children with UPJO.

Urinary Proteome of Newborn Calves-New Potential in Non-Invasive Neonatal Diagnostic

Urine is a biological diagnostic material suitable not only for the analysis of kidney and urinary tract functions but also the function of other tissues and organs. The urine proteome of adult mammals differs from the urine proteome of neonatal ones. The establishment of urinary protein maps of healthy newborn calves is important for diagnosing and monitoring the progression of various diseases. The experiment was carried out on a Polish-Friesian var. of Black-and-White male calves in the sixth day of postnatal life. The two proteomics approaches used for separation and identification of urinary proteins were: 2-DE with MALDI-TOF-TOF-MS/MS and 1-DE with LC-MS/MS. This resulted in the identification of 692 urinary proteins. The majority of them were classified as extracellular proteins (40.32%), as well as proteins involved in regulation of major cellular processes (31.07%). We have observed the presence of unique proteins associated with embryonic (ameloblastin, alpha-fetoprotein, Delta-like protein, embryo-specific fibronectin 1 transcript variant, Indian hedgehog homolog) and kidney development (angiotensin-converting enzyme, angiotensinogen, aquaporin-1, calbindin, glypican 3, nidogen 1, pro-cathepsin H). Additionally, proteins involved in the renal regulation of water and electrolyte balance (angiotensinogen, angiotensin-converting enzyme, aquaporin-1, ezrin, uromodulin) were detected. Presented in the current study 1-D and 2-D urinary proteomic maps are the basis for the identification and detection of prognostic biomarkers important for defining a calf's health status.

iTRAQ-based comparative proteomics analysis reveals specific urinary biomarkers for various kidney diseases

Background: Proteome studies for multiple renal diseases is bare. Methodology & results: Using isobaric tags for relative and absolute quantitation labeling, many differentially expressed proteins (DEPs) were identified in acute kidney injury (AKI), AKI + chronic kidney disease (CKD), diabetic CKD and nondiabetic CKD with or without IgA nephropathy (IgAN). Comparative analysis indicated that 34, 35, 17, 91 and 14 unique DEPs were found in AKI, AKI + CKD, CKD, diabetic CKD and nondiabetic CKD. Compared with nondiabetic CKD with IgAN, 47 unique DEPs were found in that without IgAN. Serum amyloid A1 (SAA1) and hepatocyte growth factor activator were unregulated in AKI and nondiabetic CKD without IgAN, respectively. Regenerating islet-derived protein 3-α (Reg3A) upregulation is associated with AKI and AKI + CKD patients. Conclusion: This research contributes to urinary biomarker discovery from multiple renal diseases.

Increased urinary exosomal SYT17 levels in chronic active antibody-mediated rejection after kidney transplantation via the IL-6 amplifier

Chronic active antibody-mediated rejection (CAAMR) is a particular problem in kidney transplantation (KTx), and ~25% of grafts are lost by CAAMR. Further, the pathogenesis remains unclear, and there is no effective cure or marker. We previously found that a hyper NFκB-activating mechanism in non-immune cells, called the IL-6 amplifier, is induced by the co-activation of NFκB and STAT3, and that this activation can develop various chronic inflammatory diseases. Here, we show that synaptotagmin-17 (SYT17) is increased in an exosomal fraction of the urine from CAAMR patients, and that this increase is associated with activation of the IL-6 amplifier. Immunohistochemistry showed that SYT17 protein expression was increased in renal tubule cells of the CAAMR group. While SYT17 protein was not detectable in whole-urine samples by western blotting, urinary exosomal SYT17 levels were significantly elevated in the CAAMR group compared to three other histology groups (normal, interstitial fibrosis and tubular atrophy, and calcineurin inhibitors toxicity) after KTx. On the other hand, current clinical laboratory data could not differentiate the CAAMR group from these groups. These data suggest that urinary exosomal SYT17 is a potential diagnostic marker for CAAMR.

DNA Adducts as Biomarkers To Predict, Prevent, and Diagnose Disease-Application of Analytical Chemistry to Clinical Investigations

Characterization of the chemistry, structure, formation, and metabolism of DNA adducts has been one of the most significant contributions to the field of chemical toxicology. This work provides the foundation to develop analytical methods to measure DNA adducts, define their relationship to disease, and establish clinical tests. Monitoring exposure to environmental and endogenous toxicants can predict, diagnose, and track disease as well as guide therapeutic treatment. DNA adducts are one of the most promising biomarkers of toxicant exposure owing to their stability, appearance in numerous biological matrices, and characteristic analytical properties. In addition, DNA adducts can induce mutations to drive disease onset and progression and can serve as surrogate markers of chemical exposure. In this perspective, we highlight significant advances made within the past decade regarding DNA adduct quantitation using mass spectrometry. We hope to expose a broader audience to this field and encourage analytical chemistry laboratories to explore how specific adducts may be related to various pathologies. One of the limiting factors in developing clinical tests to measure DNA adducts is cohort size; ideally, the cohort would allow for model development and then testing of the model to the remaining cohort. The goals of this perspective article are to (1) provide a summary of analyte levels measured using state-of-the-art analytical methods, (2) foster collaboration, and (3) highlight areas in need of further investigation.

Redox Proteomes in Human Physiology and Disease Mechanisms

Redox proteomics is a field of proteomics that is concerned with the characterization of the oxidation state of proteins to gain information about their modulated structure, function, activity, and involvement in different physiological pathways. Oxidative modifications of proteins have been shown to be implicated in normal physiological processes of cells as well as in pathomechanisms leading to the development of cancer, diabetes, neurodegenerative diseases, and some rare hereditary metabolic diseases, like classic galactosemia. Reactive oxygen species generate a variety of reversible and irreversible modifications in amino acid residue side chains and within the protein backbone. These oxidative post-translational modifications (Ox-PTMs) can participate in the activation of signal transduction pathways and mediate the toxicity of harmful oxidants. Thus the application of advanced redox proteomics technologies is important for gaining insights into molecular mechanisms of diseases. Mass-spectrometry-based proteomics is one of the most powerful methods that can be used to give detailed qualitative and quantitative information on protein modifications and allows us to characterize redox proteomes associated with diseases. This Review illustrates the role and biological consequences of Ox-PTMs under basal and oxidative stress conditions by focusing on protein carbonylation and S-glutathionylation, two abundant modifications with an impact on cellular pathways that have been intensively studied during the past decade.

The Urinary Peptidome as a Noninvasive Biomarker Development Strategy for Prenatal Screening of Down's Syndrome

Prenatal screening for Down's syndrome based on maternal age, ultrasound measures, and maternal serum biomarkers is recommended worldwide, but the false-positive rate and poor diagnostic performance of these screening tests remain problematic. Genetic analysis of cell-free DNA in maternal blood has been developed as a new prenatal screening for Down's syndrome, but it has a number of limitations, including turnaround time and cost. Prenatal screening diagnostic innovation calls for new tests that are noninvasive, accurate, and affordable. We report original observations on potential peptide biomarkers in maternal urine for screening of fetal Down's syndrome. The peptidome of urine samples from 23 pregnant women carrying Down's syndrome fetuses and 30 pregnant women carrying fetuses with normal karyotype was fractionated by weak cation exchange magnetic beads and analyzed by MALDI-TOF mass spectrometry. Levels of six peptides (m/z 1022.1, 1032.1, 1099.5, 1155.9, 1306.6, and 2365.6) were significantly altered between the case and control groups after controlling for maternal and gestational age. A classification model was constructed based on these candidate peptides that could differentiate fetuses with Down's syndrome from controls with a sensitivity of 95.7%, a specificity of 70.0%, and an area under receiver operating characteristic curves of 0.909 (95% confidence interval, 0.835-0.984). Peptide peaks at m/z 1099.5 and 1155.9 were identified as the partial sequences of alpha-1-antitrypsin and heat shock protein beta-1, respectively. These new findings support the new idea that maternal urinary peptidome offers prospects for noninvasive biomarker discovery and development for the prenatal screening of fetal Down's syndrome.

Apelin affects the mouse aging urinary peptidome with minimal effects on kidney

Kidney function is altered by age together with a declined filtration capacity of 5–10% per decade after 35 years. Renal aging shares many characteristics with chronic kidney disease. Plasma levels of the bioactive peptide apelin also decline with age and apelin has been shown to be protective in chronic kidney disease. Therefore we evaluated whether apelin could also improve aging-induced renal lesions and function in mice. Since urine is for the major part composed of proteins and peptides originating from the kidney, we first studied apelin-induced changes, in the aging urinary peptidome. Despite the recently published age-associated plasma decrease of apelin, expression of the peptide and its receptor was increased in the kidneys of 24 months old mice. Twenty-eight days treatment with apelin significantly modified the urinary peptidome of 3 and 24 months old mice towards a signature suggesting more advanced age at 3 months, and a younger age at 24 months. The latter was accompanied by a decreased staining of collagen (Sirius red staining) in 24 months old apelin-treated mice, without changing aging-induced glomerular hypertrophy. In addition, apelin was without effect on aging-induced renal autophagy, apoptosis, inflammation and reduced renal function. In conclusion, treatment of aged mice with apelin had a limited effect on kidney lesions although modifying the urinary peptidome towards a younger signature. This supports evidence of apelin inducing more general beneficial effects on other aging organs, muscles in particular, as recently shown for sarcopenia, markers of which end up via the glomerular filtration in urine.

Evaluation of Protein Profiling in a Cohort of Egyptian Population with Renal Cell Carcinoma and Benign Kidney Neoplasms

Abdominal imaging leads to the detection of a large number of renal tumors without the ability to distinguish the type of tumor detected. It is necessary to find a precise way to know the type of tumor to determine the appropriate treatment. The use of urine samples for detecting new biomarkers especially proteins has a great potential. In this work we assessed the proteomic profiling difference in a cohort of Egyptian population with renal neoplasms. Methods: This cohort study was conducted on 85 subjects. They were classified as 40 RCC, 15 benign kidney patients, and 30 healthy controls. Morning urine samples were used for peptidome separation using magnetic beads. Matrix assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS) was applied Using FlexControlTM software. Results: Benign tumors were differentiated from controls by 5 integrated peaks, 12 significant and 2 integrated significant peaks, 17:3,418.8 and 25:4,173.41. While RCC were differentiated from benign by 5 integrated, 28 significant and one integrated significant peak. The RCC group was discriminated from the controls by 5 peaks which were integrated from which 1 was integrated and significant (with mass to charge ratio of 12:3,408.97). The three groups showed protein profiles ranging from 1 to 10 kDa. The external validation was performed for the RCC group versus the control reveled sensitivity of 88.7% and specificity of 73.2% by genetic algorithm. Conclusion: Proteomic approach can be used as a sensitive urinary marker differentiating renal masses in an early diagnostic approach.

Development of biomarkers of genitourinary cancer using mass spectrometry-based clinical proteomics

Prostate, bladder and kidney cancer are the three most common types of genitourinary cancer in the world. Of these, prostate and bladder cancers are within the top 10 most common cancers in men. Notably, kidney cancer causes no obvious symptoms in the early stages. To satisfy clinical-management requirements, researchers have developed numerous biomarkers by applying proteomic approaches using clinical serum, urine and tissue specimens, as well as cell and animal models. Through application of biomarker pipeline protocols, including discovery, verification and validation phases, and mass-spectrometric based proteomic platforms coupled with multiplexed quantification assays, these studies have led to recent rapid progress in this area. With improvements in mass-spectrometric based proteomic techniques, numerous promising biomarker candidates and marker panels for various clinical purposes have been proposed. Verification of novel protein biomarker candidates is very resource demanding (e.g. on the clinical and laboratory sides). With the support of national consortia, it is now possible to investigate the future clinical use of such biomarker strategies and assess their cost-effectiveness in personalized medicine.

Characterization of low molecular weight urinary proteins at varying time intervals in type 2 diabetes mellitus and diabetic nephropathy patients

BACKGROUND

To identify low molecular weight urinary proteins capable of detecting diabetic nephropathy patients which may predict renal alterations at early stages and prevent it from worsening further.

METHOD

Three hundred ninety (390) age-matched subjects were divided into 8 groups depending upon duration of diabetes and the severity of renal damage. Urinary proteome profile of all subjects was determined with the help of microfluidic array. Participants with similar profile were further selected to study proteome map of urinary low molecular weight proteins with the help of 2 dimensional gel electrophoresis.

RESULTS

Out of 390 total patients 268 patients showed a similar one dimensional proteomic pattern. Further, two-dimensional urinary proteomic pattern of these patients with molecular weight < 50 kDa was studied. Eight proteins with molecular weight 11, 15, 17, 23, 34, 38 and 46 kDa were identified with MALDI-QTOF. These low molecular weight proteins showed gradual increase in urinary excretion along with the duration of diabetes and severity of renal damage.

CONCLUSION

The study concludes that proteomic analysis might be a useful tool for detecting some novel markers capable of detecting patients susceptible to diabetic nephropathy in the early phase.

Detection of HIV-1 and Human Proteins in Urinary Extracellular Vesicles from HIV+ Patients

BACKGROUND

Extracellular vesicles (EVs) are membrane bound, secreted by cells, and detected in bodily fluids, including urine, and contain proteins, RNA, and DNA. Our goal was to identify HIV and human proteins (HPs) in urinary EVs from HIV+ patients and compare them to HIV- samples.

METHODS

Urine samples were collected from HIV+ (n = 35) and HIV- (n = 12) individuals. EVs were isolated by ultrafiltration and characterized using transmission electron microscopy, tandem mass spectrometry (LC/MS/MS), and nanoparticle tracking analysis (NTA). Western blots confirmed the presence of HIV proteins. Gene ontology (GO) analysis was performed using FunRich and HIV Human Interaction database (HHID).

RESULTS

EVs from urine were 30-400 nm in size. More EVs were in HIV+ patients, P < 0.05, by NTA. HIV+ samples had 14,475 HPs using LC/MS/MS, while only 111 were in HIV-. HPs in the EVs were of exosomal origin. LC/MS/MS showed all HIV+ samples contained at least one HIV protein. GO analysis showed differences in proteins between HIV+ and HIV- samples and more than 50% of the published HPs in the HHID interacted with EV HIV proteins.

CONCLUSION

Differences in the proteomic profile of EVs from HIV+ versus HIV- samples were found. HIV and HPs in EVs could be used to detect infection and/or diagnose HIV disease syndromes.

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.

Glycopatterns of Urinary Protein as New Potential Diagnosis Indicators for Diabetic Nephropathy

Diabetic nephropathy is a major cause of chronic kidney disease and end-stage kidney disease. However, so little is known about alterations of the glycopatterns in urine with the development of diabetic nephropathy. Presently, we interrogated glycopatterns in urine specimens using a lectin microarray. The results showed that expression levels of Siaα2-6Gal/GalNAc recognized by SNA exhibited significantly increased tendency with the development of diabetic nephropathy; moreover, SNA blotting indicated glycoproteins (90 kDa, 70 kDa, and 40 kDa) in urine may contribute to this alteration. Furthermore, the glycopatterns of (GlcNAc)_2-4 recognized by STL exhibited difference between diabetic and nondiabetic nephropathy. The results of urinary protein microarray fabricated by another 48 urine specimens also indicated (GlcNAc)_2-4 is a potential indictor to differentiate the patients with diabetic nephropathy from nondiabetic nephropathy. Furtherly, STL blotting showed that the 50 kDa glycoproteins were correlated with this alteration. In conclusion, our data provide pivotal information to monitor the development of diabetic nephropathy and distinguish between diabetic nephropathy and nondiabetic renal disease based on precise alterations of glycopatterns in urinary proteins, but further studies are needed in this regard.

Prospective validation of a novel renal activity index of lupus nephritis

Objectives The renal activity index for lupus (RAIL) score was developed in children with lupus nephritis as a weighted sum of six urine biomarkers (UBMs) (neutrophil gelatinase-associated lipocalin, monocyte chemotactic protein 1, ceruloplasmin, adiponectin, hemopexin and kidney injury molecule 1) measured in a random urine sample. We aimed at prospectively validating the RAIL in adults with lupus nephritis. Methods Urine from 79 adults was collected at the time of kidney biopsy to assay the RAIL UBMs. Using receiver operating characteristic curve analysis, we evaluated the accuracy of the RAIL to discriminate high lupus nephritis activity status (National Institutes of Health activity index (NIH-AI) score >10), from low/moderate lupus nephritis activity status (NIH-AI score ≤10). Results In this mixed racial cohort, high lupus nephritis activity was present in 15 patients (19%), and 71% had proliferative lupus nephritis. Use of the identical RAIL algorithm developed in children resulted in only fair prediction of lupus nephritis activity status of adults (area under the receiver operating characteristic curve (AUC) 0.62). Alternative weightings of the six RAIL UBMs as suggested by logistic regression yielded excellent accuracy to predict lupus nephritis activity status (AUC 0.88). Accuracy of the model did not improve with adjustment of the UBMs for urine creatinine or albumin, and was little influenced by concurrent kidney damage. Conclusions The RAIL UBMs provide excellent prediction of lupus nephritis activity in adults. Age adaption of the RAIL is warranted to optimize its discriminative validity to predict high lupus nephritis activity status non-invasively.

Urine Proteomics in the Era of Mass Spectrometry

With the technological advances of mass spectrometry (MS)-based platforms, clinical proteomics is one of the most rapidly growing areas in biomedical research. Urine proteomics has become a popular subdiscipline of clinical proteomics because it is an ideal source for the discovery of noninvasive disease biomarkers. The urine proteome offers a comprehensive view of the local and systemic physiology since the proteome is primarily composed of proteins/peptides from the kidneys and plasma. The emergence of MS-based proteomic platforms as prominent bioanalytical tools in clinical applications has enhanced the identification of protein-based urinary biomarkers. This review highlights the characteristics of urine that make it an attractive biofluid for biomarker discovery and the impact of MS-based technologies on the clinical assessment of urinary protein biomarkers.

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.

Excessive amount of lactose in the diet of two-week-old calves induces urinary protein changes

Abstract. The present paper was undertaken to analyse and identify urinary proteins that were significantly altered in urine of calves in response to short-term administration of milk replacer with lactose addition. We used 2-D electrophoresis combined with matrix-assisted laser desorption/ionisation and time-of-flight (MALDI-TOF) mass spectrometry. Of all spots analysed, four showed significantly decreased abundance: alpha-1-antiproteinase (A1AT), serotransferrin (TF), sex hormone-binding globulin (SHBG) and cytochrome P450 2E1 (CYP2E1). One displayed an increased abundance: adenosine triphosphate (ATP)-citrate synthase. The changes in abundance of SHBG and CYP2E1 proteins were caused by the direct effect of an oversupply of sugar, while A1AT, TF and ATP-citrate synthase showed altered abundance probably due to indirect effects. The results of this study confirmed that calves' urine is a very precious biological material to evaluate the renal function, and it may be valuable in veterinary and zootechnical diagnostics.

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

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

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.

Acute kidney injury prediction in cardiac surgery patients by a urinary peptide pattern: a case-control validation study

Background

Acute kidney injury (AKI) is a prominent problem in hospitalized patients and associated with increased morbidity and mortality. Clinical medicine is currently hampered by the lack of accurate and early biomarkers for diagnosis of AKI and the evaluation of the severity of the disease.

In 2010, we established a multivariate peptide marker pattern consisting of 20 naturally occurring urinary peptides to screen patients for early signs of renal failure. The current study now aims to evaluate if, in a different study population and potentially various AKI causes, AKI can be detected early and accurately by proteome analysis.

Methods

Urine samples from 60 patients who developed AKI after cardiac surgery were analyzed by capillary electrophoresis-mass spectrometry (CE-MS). The obtained peptide profiles were screened by the AKI peptide marker panel for early signs of AKI. Accuracy of the proteomic model in this patient collective was compared to that based on urinary neutrophil gelatinase-associated lipocalin (NGAL) and kidney injury molecule-1 (KIM-1) ELISA levels. Sixty patients who did not develop AKI served as negative controls.

Results

From the 120 patients, 110 were successfully analyzed by CE-MS (59 with AKI, 51 controls). Application of the AKI panel demonstrated an AUC in receiver operating characteristics (ROC) analysis of 0.81 (95 % confidence interval: 0.72–0.88). Compared to the proteomic model, ROC analysis revealed poorer classification accuracy of NGAL and KIM-1 with the respective AUC values being outside the statistical significant range (0.63 for NGAL and 0.57 for KIM-1).

Conclusions

This study gives further proof for the general applicability of our proteomic multimarker model for early and accurate prediction of AKI irrespective of its underlying disease cause.

Electronic supplementary material

The online version of this article (doi:10.1186/s13054-016-1344-z) contains supplementary material, which is available to authorized users.

Body fluid peptide and protein signatures in diabetic kidney diseases

Body fluid protein-based biomarkers carry the hope of improving patient management in diabetes by enabling more accurate and earlier detection of diabetic kidney disease (DKD), but also of defining the most suitable therapeutic targets. We present the data on some of the best studied individual protein markers in body fluids and conclude that their potential in clinical application for assessing DKD is moderate. Proteome-based approaches aiming at the identification of panels of body fluid biomarkers might be a valid alternative. We discuss the past (first) clinical proteomics studies in DKD, stressing their drawbacks but also the lessons that could be learned from them, as well as the more recent studies that have a potential for actual clinical implementation. We also highlight relevant issues and current problems associated with clinical proteomics from discovery towards application, and give suggestions for solutions that may help guiding proteomic studies, thereby removing some of the current hurdles for implementation of potentially beneficial results.

Antioxidant enzymes as redox-based biomarkers: a brief review

The field of redox proteomics focuses to a large extent on analyzing cysteine oxidation in proteins under different experimental conditions and states of diseases. The identification and localization of oxidized cysteines within the cellular milieu is critical for understanding the redox regulation of proteins under physiological and pathophysiological conditions, and it will in turn provide important information that are potentially useful for the development of novel strategies in the treatment and prevention of diseases associated with oxidative stress. Antioxidant enzymes that catalyze oxidation/reduction processes are able to serve as redox biomarkers in various human diseases, and they are key regulators controlling the redox state of functional proteins. Redox regulators with antioxidant properties related to active mediators, cellular organelles, and the surrounding environments are all connected within a network and are involved in diseases related to redox imbalance including cancer, ischemia/reperfusion injury, neurodegenerative diseases, as well as normal aging. In this review, we will briefly look at the selected aspects of oxidative thiol modification in antioxidant enzymes and thiol oxidation in proteins affected by redox control of antioxidant enzymes and their relation to disease. [BMB Reports 2015; 48(4): 200-208]

[Analysis of differentially expressed proteome in urine from non-small cell lung cancer patients]

背景与目的

筛查非小细胞肺癌（non-small cell lung cancer, NSCLC）患者尿液中差异表达蛋白，确定可用于NSCLC早期诊断、监测预后和治疗评估的生物标记物。

方法

分别收集40例已病理证实初诊NSCLC患者、8例肺部良性疾病患者和22例健康志愿者的尿液样本。利用0.9%一维十二烷基硫酸钠-聚丙烯酰胺凝胶电泳（sodium dode-cyl sulfate polyacrylamide gel electrophoresis, 1D SDS-PAGE）技术和MS-Thermo-Orbitrap-Velos质谱分析仪对NSCLC组和非肿瘤组尿液中蛋白质进行分离、提取及识别，鉴定出NSCLC患者尿液中的差异表达蛋白。应用SPSS 20.0软件中受试者工作特征曲线（receiver operating characteristic curve, ROC）分别对其敏感性、特异性进行分析，并进行实验验证，从而确定出与NSCLC相关的生物标记物。

结果

NSCLC患者组和非肿瘤组尿液差异性表达蛋白质集中表现在90 kDa、60 kDa和20 kDa-30 kDa凝胶条带中。在NSCLC患者尿液蛋白分析中发现了4种与NSCLC相关的差异表达蛋白，包括上调蛋白LRG1、CA1和下调蛋白VPS4B、YWHAZ。这4种差异表达蛋白作为独立的NSCLC生物标记物其敏感性较低：LRG1蛋白敏感性83.0%（25/30）、特异性90.0%（18/20）；CA1蛋白敏感性60.0%（18/30）、特异性90.0%（18/20)；VPS4B蛋白敏感性73.3%（22/30）、特异性90.0%（18/20）；YWHAZ蛋白敏感性60.0%（18/30）、特异性95.0%（19/20）。而采用蛋白质组合模式对NSCLC进行筛查、诊断，则其敏感性和特异性分别可高达96.7%（29/30）和85%（17/20）。

结论

LRG1、CA1蛋白在NSCLC患者尿液中高表达，而VPS4B、YWHAZ蛋白呈低表达，差异表达蛋白均提示有可能成为用于NSCLC早期筛查、监测预后和治疗评估的生物标记物。LRG1、CA1、VPS4B和YWHAZ尿液蛋白作为单一生物标记物应用于NSCLC筛查和诊断的敏感性较低，而采用蛋白质组合模式明显优于独立模式对NSCLC的筛查和诊断，故蛋白质组合模式在临床诊疗中将更具有良好应用价值和前景。