Urinary proteomics: a tool to discover biomarkers of kidney diseases

There is intense interest in applying proteomics to urine analysis in order to promote a better understanding of kidney disease processes, develop new biomarkers for diagnosis and detect early factors that contribute to end–stage renal diseases. This interest creates numerous opportunities as well as challenges. To fulfill this task, proteomics requires, in its different stages of realization, various technological platforms with high sensitivity, high throughput and large automation ability. In this review, we will give an overview of promising proteomic methods that can be used for analyzing urinary proteome and detecting biomarkers for different kidney diseases. Furthermore, we will focus on the current status and future directions in investigating kidney diseases using urinary proteomics.     

Applications of urinary proteomics in biomarker discovery

Urine is an important source of biomarkers. This article reviews current advances, major challenges, and future prospects in the field of urinary proteomics. Because the practical clinical problem is to distinguish diseases with similar symptoms, merely comparing samples from patients of a particular disease to those of healthy individuals is inadequate for finding biomarkers with sufficient diagnostic power. In addition, the variation of expression levels of urinary proteins among healthy individuals and individuals under different physiological conditions adds to the difficulty in identifying biomarkers. We propose that establishing the natural variation in urinary protein expression among a healthy population can serve as a reference to help identify protein abundance changes that are caused by disease, not by individual variations or physiological changes. We also discuss that comparing protein expression levels between urine and plasma may reveal the physiological function of the kidney and that may facilitate biomarker discovery. Finally, we propose that establishing a data-sharing platform for data collection and integrating results from all urinary biomarker studies will help promote the development of urinary proteomics.     

Using an Isolated Rat Kidney Model to Identify Kidney Origin Proteins in Urine

The use of targeted proteomics to identify urinary biomarkers of kidney disease in urine can avoid the interference of serum proteins. It may provide better sample throughput, higher sensitivity, and specificity. Knowing which urinary proteins to target is essential. By analyzing the urine from perfused isolated rat kidneys, 990 kidney origin proteins with human analogs were identified in urine. Of these proteins, 128 were not found in normal human urine and may become biomarkers with zero background. A total of 297 proteins were not found in normal human plasma. These proteins will not be influenced by other normal organs and will be kidney specific. The levels of 33 proteins increased during perfusion with an oxygen-deficient solution compared to those perfused with oxygen. The 75 proteins in the perfusion-driven urine have a significantly increased abundance ranking compared to their ranking in normal human urine. When compared with existing candidate biomarkers, over ninety percent of the kidney origin proteins in urine identified in this study have not been examined as candidate biomarkers of kidney diseases.     

Biomarker discovery for kidney diseases by mass spectrometry

By the development of soft ionization such as matrix-assisted laser desorption/ionization (MALDI) and electrospray ionization (ESI), mass spectrometry (MS) has become an indispensable technique to analyze proteins. The combination of protein separation and identification such as two-dimensional gel electrophoresis and MS, surface-enhanced laser desorption/ionization-MS, liquid chromatography/MS, and capillary electrophoresis/MS has been successfully applied for proteome analysis of urine and plasma to discover biomarkers of kidney diseases. Some urinary proteins and their proteolytic fragments have been identified as biomarker candidates for kidney diseases. This article reviews recent advances in the application of proteomics using MS to discover biomarkers for kidney diseases.     

Tumor profiling using protein biomarker panels in malignant melanoma: application of tissue microarrays and beyond

In the past decade, analysis of the urinary proteome (urinary proteomics) has intensified in response to the need for novel biomarkers that support early diagnosis of kidney diseases. In particular, this also applies to acute kidney injury, which is a heterogeneous complex syndrome with a still-increasing incidence at the intensive care unit. Unfortunately, this major need remains largely unmet to date. The current report aims to explain why attempts to implement urinary proteomic-discovered acute kidney injury diagnostic candidates in the intensive care unit setting have not yet led to success. Subsequently, some key notes are provided that should enhance the chance of translating selected urinary proteomic candidates to valuable tools for the nephrologist and intensivist in the near future.     

A stable panel comprising 18 urinary proteins in the human healthy population

Just as biomarkers specific for diseases, biomarkers indicative of healthy conditions are valuable for the early diagnosis, monitoring, and prognosis of diseases. Our study focused on discovering via proteomics a stable panel of urinary proteins in the human healthy population. Urine samples were collected three times during 4 months from 100 male and 100 female healthy donors and analyzed through four different fractionation techniques (i.e. in-gel, 2D-LC, OFFGEL, and mRP) coupled with HPLC-Chip-MS/MS. Thus, 1641 urinary proteins were identified with a high confidence, among which 70 exhibiting an intergender/day variation <0.25 were selected and matched with the previously published five largest urinary proteomes to get 56 candidate proteins. Next, a panel comprising 18 intact urinary proteins was constructed by comparing the urinary proteomes via SDS-PAGE and 2DE. Finally, such 18 urinary proteins were validated via enzyme-linked immunosorbent assay in eight healthy individuals. Most of these proteins had been related to multiple rather than to single diseases. Therefore, we surmise that this protein set could be used as a biomarker to assess the human health status. Further determinations of the normal fluctuations of the single urinary proteins in this series using samples from large numbers of healthy individuals are required prior to any application in clinical settings.     

Proteomics approach and techniques in identification of reliable biomarkers for diseases

Biomarkers, also called biological markers, are indicators to identify a biological case or situation as well as detecting any presence of biological activities and processes. Proteins are considered as a type of biomarkers based on their characteristics. Therefore, proteomics approach is one of the most promising approaches in this field. The purpose of this review is to summarize the use of proteomics approach and techniques to identify proteins as biomarkers for different diseases. This review was obtained by searching in a computerized database. So, different researches and studies that used proteomics approach to identify different biomarkers for different diseases were reviewed. Also, techniques of proteomics that are used to identify proteins as biomarkers were collected. Techniques and methods of proteomics approach are used for the identification of proteins' activities and presence as biomarkers for different types of diseases from different types of samples. There are three essential steps of this approach including: extraction and separation of proteins, identification of proteins, and verification of proteins. Finally, clinical trials for new discovered biomarker or undefined biomarker would be on.     

Proteomics and personalized medicine: a focus on kidney disease

ABSTRACT

Introduction: Inter-individual variability in response to drug treatment has induced an increased demand for decisions via personalize medicine. Also, the contribution of proteomics to the era of personalized medicine would seem to be vital in improving therapeutic outcomes.

Areas covered: We review validated biomarkers discovered by proteomics techniques and their use in personalized medicine with the focus on kidney diseases. We discuss this topic with a special emphasis on recent publications and relevant initiatives and depict some limitations that remain for personalized medicine.

Expert opinion: The development of highly accurate biomarkers is essential for optimizing the management of kidney diseases. Various biomarkers of kidney diseases have been identified using proteomic techniques. However, only a few of these biomarkers showed the potential to be used in clinical practice concerning personalized medicine. Therefore, it becomes evident that the combination of multiple biomarkers confers higher accuracy and the ability to depict complex pathophysiological conditions, a prerequisite for personalized treatment. CKD273, a multimarker panel for early CKD detection may serve as a first example for personalized medicine in nephrology. Based on this successful example, proteomics is expected to develop into the key technology to guide personalized intervention.     

Urinary proteomics and molecular determinants of chronic kidney disease: possible link to proteases

Chronic kidney disease (CKD) is the gradual decrease in renal function. Currently available biomarkers are effective only in detecting late stage CKD. Biomarkers of early stage CKD and prognostic biomarkers are required. We review the major findings in urinary proteomics in CKD during the last five years. Significant progress has been made and today urinary proteomics is applied in large randomized trials, and in patient management. Many of the biomarkers indicate altered protease activity. We therefore also review the literature on proteases associated with renal function loss. We anticipate in silico prediction tools of protease activity and additional system biology studies may contribute to biomarker discovery and elucidate the role of proteases in CKD development and progression. These approaches will enable the deciphering of the molecular pathophysiology of CKD, and hence definition of the most appropriate therapeutic targets in the future. Together with stable biomarker panels available today, this will significantly improve patient management.     

A tool for biomarker discovery in the urinary proteome: a manually curated human and animal urine protein biomarker database

Urine is an important source of biomarkers. A single proteomics assay can identify hundreds of differentially expressed proteins between disease and control samples; however, the ability to select biomarker candidates with the most promise for further validation study remains difficult. A bioinformatics tool that allows accurate and convenient comparison of all of the existing related studies can markedly aid the development of this area. In this study, we constructed the Urinary Protein Biomarker (UPB) database to collect existing studies of urinary protein biomarkers from published literature. To ensure the quality of data collection, all literature was manually curated. The website (http://122.70.220.102/biomarker) allows users to browse the database by disease categories and search by protein IDs in bulk. Researchers can easily determine whether a biomarker candidate has already been identified by another group for the same disease or for other diseases, which allows for the confidence and disease specificity of their biomarker candidate to be evaluated. Additionally, the pathophysiological processes of the diseases can be studied using our database with the hypothesis that diseases that share biomarkers may have the same pathophysiological processes. Because of the natural relationship between urinary proteins and the urinary system, this database may be especially suitable for studying the pathogenesis of urological diseases. Currently, the database contains 553 and 275 records compiled from 174 and 31 publications of human and animal studies, respectively. We found that biomarkers identified by different proteomic methods had a poor overlap with each other. The differences between sample preparation and separation methods, mass spectrometers, and data analysis algorithms may be influencing factors. Biomarkers identified from animal models also overlapped poorly with those from human samples, but the overlap rate was not lower than that of human proteomics studies. Therefore, it is not clear how well the animal models mimic human diseases.     

Proteomics of human cerebrospinal fluid: discovery and verification of biomarker candidates in neurodegenerative diseases using quantitative proteomics

There is an urgent need for novel biomarkers that can be used to improve the diagnosis, predict the disease progression, improve our understanding of the pathology or serve as therapeutic targets for neurodegenerative diseases. Cerebrospinal fluid (CSF) is in direct contact with the CNS and reflects the biochemical state of the CNS under different physiological and pathological settings. Because of this, CSF is regarded as an excellent source for identifying biomarkers for neurological diseases and other diseases affecting the CNS. Quantitative proteomics and sophisticated computational software applied to analyze the protein content of CSF has been fronted as an attractive approach to find novel biomarkers for neurological diseases. This review will focus on some of the potential pitfalls in biomarker studies using CSF, summarize the status of the field of CSF proteomics in general, and discuss some of the most promising proteomics biomarker study approaches. A brief status of the biomarker discovery efforts in multiple sclerosis, Alzheimer's disease, and Parkinson's disease is also given.     

Monitoring oxidative stress biomarkers in the lipidome: is there a roadmap for "human inspection"?

Oxidative stress is more and more recognized as the underlying motif for a broad variety of diseases including cancer. Medicine faces the paramount task to develop better diagnostic tools and drug treatment prediction models in the future to significantly enhance the quality of life. Special interest will focus on earlystage disease biomarkers and biomarkers that could predict healing success at the earliest time point after the treatment started. The accelerated formation of so-called reactive oxygen species (ROS) is becoming widely regarded as the underlying process associated with many diseases like myocardial infarction, Alzheimer's, Parkinson's and kidney disease, etc. Once generated within cells and tissues, ROS can react with a variety of cellular metabolites like fatty acids, proteins or DNA. This review investigates the possibilities for various oxidized metabolites as well as proteomics, genomics and bioimaging biomarkers to serve as early-stage disease biomarkers or biomarkers for drug treatment success. We also assess the value of a step-by-step or cascade biomarker approach as a new paradigm in medical diagnostics. Examples are given for possible analytical methodology and tools as well as statistical methods that could be applied. Such an approach may straighten the road toward new medical diagnostics and treatment regimes, which ultimately could lead to a significantly enhanced medical service for patients suffering from chronic and debilitating or deadly diseases including cancer. Examples from recent research are given to show the progress and possibilities for the proposed model.     

The 4th Human Kidney and Urine Proteome Project (HKUPP) Workshop 26 September 2009, Toronto,Canada

The Human Kidney and Urine Proteome Project (HKUPP) was initiated to promote proteomics research in the nephrology field, to better understand kidney functions as well as pathogenic mechanisms of kidney diseases, and to define novel biomarkers and therapeutic targets. The 4th workshop held in September 2009 discussed problems of proteomics analysis for kidney tissues and urine samples and a standard protocol for collection, storage and protein concentration of urine samples was decided upon.     

运动性急性肾损伤与新型肾功能生物标志物

大强度运动中,非创伤性急性肾损伤（acute kindey injury, AKI）经常发生,表现为血尿、蛋白尿、血红蛋白尿等。一般认为,中低程度的运动性急性肾损伤是可逆的,可完全恢复。但动物实验与人类研究均发现,严重的运动性肾损伤会导致“功能性”急性肾损伤发展为“结构性”急性肾损伤,并增加慢性肾病的风险。运动性急性肾损伤对机体的潜在健康威胁已引起国内外相关领域学者的广泛关注。血清肌酐 (serum creatinine, Scr)和尿量作为肾功能的传统经典标志物,不能特异性反映早期肾损伤,而新型肾损伤标志物可进一步明确损伤的位置及严重程度。在运动领域,利用新型生物标志物进行无创性检查,识别早期运动性急性肾损伤非常必要。本文综述了反映肾小球或肾小管损伤、细胞周期停滞和肾损伤修复的新型生物标志物,着重论述了尿中性粒细胞明胶酶相关脂质运载蛋白（NGAL)和肾损伤分子-1（KIM-1)与肾功能的关系,以及长时间耐力运动、急性运动和高强度间歇阻力运动3种运动形式对肾功能的影响,旨在引起重视,精准识别风险,及时进行早干预。     

运动性急性肾损伤与新型肾功能生物标志物

大强度运动中,非创伤性急性肾损伤（acute kindey injury, AKI）经常发生,表现为血尿、蛋白尿、血红蛋白尿等。一般认为,中低程度的运动性急性肾损伤是可逆的,可完全恢复。但动物实验与人类研究均发现,严重的运动性肾损伤会导致“功能性”急性肾损伤发展为“结构性”急性肾损伤,并增加慢性肾病的风险。运动性急性肾损伤对机体的潜在健康威胁已引起国内外相关领域学者的广泛关注。血清肌酐 (serum creatinine, Scr)和尿量作为肾功能的传统经典标志物,不能特异性反映早期肾损伤,而新型肾损伤标志物可进一步明确损伤的位置及严重程度。在运动领域,利用新型生物标志物进行无创性检查,识别早期运动性急性肾损伤非常必要。本文综述了反映肾小球或肾小管损伤、细胞周期停滞和肾损伤修复的新型生物标志物,着重论述了尿中性粒细胞明胶酶相关脂质运载蛋白（NGAL)和肾损伤分子-1（KIM-1)与肾功能的关系,以及长时间耐力运动、急性运动和高强度间歇阻力运动3种运动形式对肾功能的影响,旨在引起重视,精准识别风险,及时进行早干预。     

Clinical proteomics in obstetrics and neonatology

Clinical proteomics has been applied to the identification of biomarkers of obstetric and neonatal disease. We will discuss a number of encouraging studies that have led to potentially valid biomarkers in the context of Down's syndrome, preterm birth, amniotic infections, preeclampsia, intrauterine growth restriction and obstructive uropathies. Obtaining noninvasive biomarkers (e.g., from the maternal circulation, urine or cervicovaginal fluid) may be more feasible for obstetric diseases than for diseases of the fetus, for which invasive methods are required (e.g., amniotic fluid, fetal urine). However, studies providing validated proteomics-identified biomarkers are limited. Efforts should be made to save well-characterized samples of these invasive body fluids so that many valid biomarkers of pregnancy-related diseases will be identified in the coming years using proteomics based analysis upon adoption of ‘clinical proteomics guidelines’.     

Proteomics in atherothrombosis: a future perspective

Atherothrombosis is the primary cause of death in Western countries. The cellular and molecular mechanisms underlying atherosclerosis remain widely unknown. The complex nature of atherosclerotic cardiovascular diseases demands the development of novel technologies that enable discovery of new biomarkers for early disease detection and risk stratification, which may predict clinical outcome. In this review, we outline potential sources and recent proteomic approaches that could be applied in the search of novel biomarkers of cardiovascular risk. In addition, we describe some issues raised in relation to the application of proteomics to blood samples, as well as two novel emerging concepts, such as peptidomics and population proteomics. In the future, the use of high-throughput techniques (proteomic, genomics and metabolomics) will potentially identify novel patterns of biomarkers, which, along with traditional risk factors and imaging techniques, could help to target vulnerable patients and monitor the beneficial effects of pharmacological agents.     

Proteomics in atherothrombosis: a future perspective

Atherothrombosis is the primary cause of death in Western countries. The cellular and molecular mechanisms underlying atherosclerosis remain widely unknown. The complex nature of atherosclerotic cardiovascular diseases demands the development of novel technologies that enable discovery of new biomarkers for early disease detection and risk stratification, which may predict clinical outcome. In this review, we outline potential sources and recent proteomic approaches that could be applied in the search of novel biomarkers of cardiovascular risk. In addition, we describe some issues raised in relation to the application of proteomics to blood samples, as well as two novel emerging concepts, such as peptidomics and population proteomics. In the future, the use of high-throughput techniques (proteomic, genomics and metabolomics) will potentially identify novel patterns of biomarkers, which, along with traditional risk factors and imaging techniques, could help to target vulnerable patients and monitor the beneficial effects of pharmacological agents.     

Urinary proteomic biomarkers in coronary artery disease

Urinary proteomics is emerging as a powerful non-invasive tool for diagnosis and monitoring of variety of human diseases. We tested whether signatures of urinary polypeptides can contribute to the existing biomarkers for coronary artery disease (CAD). We examined a total of 359 urine samples from 88 patients with severe CAD and 282 controls. Spot urine was analyzed using capillary electrophoresis on-line coupled to ESI-TOF-MS enabling characterization of more than 1000 polypeptides per sample. In a first step a "training set" for biomarker definition was created. Multiple biomarker patterns clearly distinguished healthy controls from CAD patients, and we extracted 15 peptides that define a characteristic CAD signature panel. In a second step, the ability of the CAD-specific panel to predict the presence of CAD was evaluated in a blinded study using a "test set." The signature panel showed sensitivity of 98% (95% confidence interval, 88.7-99.6) and 83% specificity (95% confidence interval, 51.6-97.4). Furthermore the peptide pattern significantly changed toward the healthy signature correlating with the level of physical activity after therapeutic intervention. Our results show that urinary proteomics can identify CAD patients with high confidence and might also play a role in monitoring the effects of therapeutic interventions. The workflow is amenable to clinical routine testing suggesting that non-invasive proteomics analysis can become a valuable addition to other biomarkers used in cardiovascular risk assessment.