Discovery Of Urinary Biomarkers Research Articles

Metabolic phenotyping for discovery of urinary biomarkers of diet, xenobiotics and blood pressure in the INTERMAP Study: an overview.

The etiopathogenesis of cardiovascular diseases (CVDs) is multifactorial. Adverse blood pressure (BP) is a major independent risk factor for epidemic CVD affecting ~40% of the adult population worldwide and resulting in significant morbidity and mortality. Metabolic phenotyping of biological fluids has proven its application in characterizing low-molecular-weight metabolites providing novel insights into gene-environmental-gut microbiome interaction in relation to a disease state. In this review, we synthesize key results from the INTERnational study of MAcro/micronutrients and blood Pressure (INTERMAP) Study, a cross-sectional epidemiologic study of 4680 men and women aged 40-59 years from Japan, the People's Republic of China, the United Kingdom and the United States. We describe the advancements we have made regarding the following: (1) analytical techniques for high-throughput metabolic phenotyping; (2) statistical analyses for biomarker identification; (3) discovery of unique food-specific biomarkers; and (4) application of metabolome-wide association studies to gain a better understanding into the molecular mechanisms of cross-cultural and regional BP differences.

Comparison of different statistical approaches for urinary peptide biomarker detection in the context of coronary artery disease.

BackgroundWhen combined with a clinical outcome variable, the size, complexity and nature of mass-spectrometry proteomics data impose great statistical challenges in the discovery of potential disease-associated biomarkers. The purpose of this study was thus to evaluate the effectiveness of different statistical methods applied for urinary proteomic biomarker discovery and different methods of classifier modelling in respect of the diagnosis of coronary artery disease in 197 study subjects and the prognostication of acute coronary syndromes in 368 study subjects.ResultsComputing the discovery sub-cohorts comprising {scriptscriptstyle raisebox{1ex}{2}!left/ !raisebox{-1ex}{3}right.} of the study subjects based on the Wilcoxon rank sum test, t-score, cat-score, binary discriminant analysis and random forests provided largely different numbers (ranging from 2 to 398) of potential peptide biomarkers. Moreover, these biomarker patterns showed very little overlap limited to fragments of type I and III collagens as the common denominator. However, these differences in biomarker patterns did mostly not translate into significant differently performing diagnostic or prognostic classifiers modelled by support vector machine, diagonal discriminant analysis, linear discriminant analysis, binary discriminant analysis and random forest. This was even true when different biomarker patterns were combined into master-patterns.ConclusionIn conclusion, our study revealed a very considerable dependence of peptide biomarker discovery on statistical computing of urinary peptide profiles while the observed diagnostic and/or prognostic reliability of classifiers was widely independent of the modelling approach. This may however be due to the limited statistical power in classifier testing. Nonetheless, our study showed that urinary proteome analysis has the potential to provide valuable biomarkers for coronary artery disease mirroring especially alterations in the extracellular matrix. It further showed that for a comprehensive discovery of biomarkers and thus of pathological information, the results of different statistical methods may best be combined into a master pattern that then can be used for classifier modelling.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-016-1390-1) contains supplementary material, which is available to authorized users.

Potential urinary aging markers of 20-month-old rats.

Urine is a very good source for biomarker discovery because it accumulates changes in the body. However, a major challenge in urinary biomarker discovery is the fact that the urinary proteome is influenced by various elements. To circumvent these problems, simpler systems, such as animal models, can be used to establish associations between physiological or pathological conditions and alterations in the urinary proteome. In this study, the urinary proteomes of young (two months old) and old rats (20 months old; nine in each group) were analyzed using LC-MS/MS and quantified using the Progenesis LC-MS software. A total of 371 proteins were identified, 194 of which were shared between the young and old rats. Based on criteria of a fold change ≥2, P < 0.05 and identification in each rat of the high-abundance group, 33 proteins were found to be changed (15 increased and 18 decreased in old rats). By adding a more stringent standard (protein spectral counts from every rat in the higher group greater than those in the lower group), eight proteins showed consistent changes in all rats of the groups; two of these proteins are also altered in the urinary proteome of aging humans. However, no shared proteins between our results and the previous aging plasma proteome were identified. Twenty of the 33 (60%) altered proteins have been reported to be disease biomarkers, suggesting that aging may share similar urinary changes with some diseases. The 33 proteins corresponded to 28 human orthologs which, according to the Human Protein Atlas, are strongly expressed in the kidney, intestine, cerebellum and lung. Therefore, the urinary proteome may reflect aging conditions in these organs.

The Potential Urinary Aging Markers from 20‐month‐old Rats

Different organs may have different aging processes. Is it possible to find markers of aging from different organs?Biomarker is measurable changes associated with physiological and/or pathophysiological conditions. Urine can be better source for biomarker discovery because it accumulates the changes of body while body removes them from blood by homeostatic mechanisms.The urinary proteome is influenced by various factors, which is a major challenge in urinary biomarker discovery. To circumvent these problems, simpler systems, such as animal models, should be used to establish direct associations between physiological or pathological conditions and changes in the urinary proteome.In this study, the urinary proteome of young (2‐month‐old) and old rats (20‐month‐old; 9 in each group) were analyzed using LC‐MS/MS (liquid chromatography‐mass spectrometry) and quantified using the Progenesis LC‐MS software. A total of 371 proteins were identified, 194 of which were shared between young and old rats. Based on the criteria of a fold change ≥ 2, P &lt; 0.05 and being identified in each rat in the high abundance group, 33 proteins were changed (15 up‐regulated and 18 down‐regulated in old rats). By adding a more stringent standard (protein spectral counts from every rat in the higher group greater than those in the lower group), 8 proteins were changed consistently in all rats of between the groups, 2 of which are also altered in the urinary proteome of aging humans. There are no shared proteins between our results and the previous aging plasma proteome. Twenty of the 33 (60 %) changed proteins have been reported to be disease biomarkers, which implies that aging may share similar urinary changes with some diseases. The 33 proteins corresponded to 28 human orthologs, which are strongly expressed in the kidney, intestine, cerebellum and lung, according to the human protein ATLAS. Therefore, the urinary proteome may reflect aging conditions in these organs. More age groups should be included in the study if more mass spectrometry time could be available for this study.Support or Funding InformationThis work was supported by the National Basic Research Program of China (2012CB517606, 2013CB530805, 2014CBA02005 and 2013FY114100).

Effect of Low-Dose Aspirin on Candidate Biomarkers in the Urine Proteome

A biomarker is a measurable change associated with a physiological or pathophysiological process. Unlike blood, which is homeostatic, urine is more likely to reflect changes in the body; urine is also a promising source of biomarker discovery because changes in physiology are accumulated in this fluid. However, urinary biomarker discovery remains a major challenge because the urinary proteome is influenced by various factors. Low-dose aspirin is widely used for preventing myocardial infarction, ischemic stroke and vascular death among patients at both high and low risk for these events as well as some cancers. Because animal models allow for controlling genetic and environmental factors, in this study, the effects of aspirin on the urinary proteome were analysed in rats. Urinary samples were collected before and at 7 days after administration of low-dose aspirin (50mg/ kg.d). A total of 191 proteins were identified by Nano LC-MS/MS and then quantified using Scaffold software. Twelve of these proteins were significantly altered, suggesting that aspirin affects the urinary proteome. Nine of the 12 proteins have been previously reported as candidate disease biomarkers, suggesting that these effects must be considered in future urinary biomarker research. Additionally, the changes in protein induced by low-dose aspirin were distinct from those caused by heparin and argatroban treatments; this indicates that the urinary proteome can distinguish blood coagulation status induced by different coagulation mechanisms, which may help in the design of more specific treatment plans for patients. Two significantly up-regulated proteins, pro-EGF and CD10, were selected for further validation by western blotting, and the results were consistent with those of mass spectrometry. Therefore, we propose that these two proteins may be used for monitoring platelet aggregation.

Comprehensive data analysis of human ureter proteome.

Comprehensive human ureter proteome dataset was generated from OFFGel fractionated ureter samples. Our result showed that among 2217 non-redundant ureter proteins, 751 protein candidates (33.8%) were detected in urine as urinary protein/polypeptide or exosomal protein. On the other hand, comparing ureter protein hits (48) that are not shown in corresponding databases to urinary bladder and prostate human protein atlas databases pinpointed 21 proteins that might be unique to ureter tissue. In conclusion, this finding offers future perspectives for possible identification of ureter disease-associated biomarkers such as ureter carcinoma. In addition, Cytoscape GO annotation was examined on the final ureter dataset to better understand proteins molecular function, biological processes, and cellular component. The ureter proteomic dataset published in this article will provide a valuable resource for researchers working in the field of urology and urine biomarker discovery.

Discovery of urinary metabolomic biomarkers for early detection of acute kidney injury.

The discovery of new biomarkers for early detection of drug-induced acute kidney injury (AKI) is clinically important. In this study, sensitive metabolomic biomarkers identified in the urine of rats were used to detect cisplatin-induced AKI. Cisplatin (10 mg kg(-1), i.p.) was administered to Sprague-Dawley rats, which were subsequently euthanized after 1, 3 or 5 days. In cisplatin-treated rats, mild histopathological alterations were noted at day 1, and these changes were severe at days 3 and 5. Blood urea nitrogen (BUN) and serum creatinine (SCr) levels were significantly increased at days 3 and 5. The levels of new urinary protein-based biomarkers, including kidney injury molecule-1 (KIM-1), glutathione S-transferase-α (GST-α), tissue inhibitor of metalloproteinase-1 (TIMP-1), vascular endothelial growth factor (VEGF), calbindin, clusterin, neutrophil, neutrophil gelatinase-associated lipocalin (NGAL), and osteopontin, were significantly elevated at days 3 and 5. Among urinary metabolites, trigonelline and 3-indoxylsulfate (3-IS) levels were significantly decreased in urine collected from cisplatin-treated rats prior to histological kidney damage. However, carbon tetrachloride (CCl4), a hepatotoxicant, did not affect these urinary biomarkers. Trigonelline is closely associated with GSH depletion and results in insufficient antioxidant capacity against cisplatin-induced AKI. The predominant cisplatin-induced AKI marker appeared to be reduced in urinary 3-IS levels. Because 3-IS is predominantly excreted via active secretion in proximal tubules, a decrease is indicative of tubular damage. Further, urinary excretion of 3-IS levels was markedly reduced in patients with AKI compared to normal subjects. The area under the curve receiver operating characteristics (AUC-ROC) for 3-IS was higher than for SCr, BUN, lactate dehydrogenase (LDH), total protein, and glucose. Therefore, low urinary or high serum 3-IS levels may be more useful for early detection of AKI than conventional biomarkers.

A proteomic glimpse into human ureter proteome.

Urine has evolved as one of the most important biofluids in clinical proteomics due to its noninvasive sampling and its stability. Yet, it is used in clinical diagnostics of several disorders by detecting changes in its components including urinary protein/polypeptide profile. Despite the fact that majority of proteins detected in urine are primarily originated from the urogenital (UG) tract, determining its precise source within the UG tract remains elusive. In this article, we performed a comprehensive analysis of ureter proteome to assemble the first unbiased ureter dataset. Next, we compared these data to urine, urinary exosome, and kidney mass spectrometric datasets. Our result concluded that among 2217 nonredundant ureter proteins, 751 protein candidates (33.8%) were detected in urine as urinary protein/polypeptide or exosomal protein. On the other hand, comparing ureter protein hits (48) that are not shown in corresponding databases to urinary bladder and prostate human protein atlas databases pinpointed 21 proteins that might be unique to ureter tissue. In conclusion, this finding offers future perspectives for possible identification of ureter disease‐associated biomarkers such as ureter carcinoma. In addition, the ureter proteomic dataset published in this article will provide a valuable resource for researchers working in the field of urology and urine biomarker discovery. All MS data have been deposited in the ProteomeXchange with identifier PXD002620 (http://proteomecentral.proteomexchange.org/dataset/PXD002620).

Advancing Urinary Protein Biomarker Discovery by Data-Independent Acquisition on a Quadrupole-Orbitrap Mass Spectrometer.

The promises of data-independent acquisition (DIA) strategies are a comprehensive and reproducible digital qualitative and quantitative record of the proteins present in a sample. We developed a fast and robust DIA method for comprehensive mapping of the urinary proteome that enables large scale urine proteomics studies. Compared to a data-dependent acquisition (DDA) experiments, our DIA assay doubled the number of identified peptides and proteins per sample at half the coefficients of variation observed for DDA data (DIA = ∼8%; DDA = ∼16%). We also tested different spectral libraries and their effects on overall protein and peptide identifications and their reproducibilities, which provided clear evidence that sample type-specific spectral libraries are preferred for reliable data analysis. To show applicability for biomarker discovery experiments, we analyzed a sample set of 87 urine samples from children seen in the emergency department with abdominal pain. The whole set was analyzed with high proteome coverage (∼1300 proteins/sample) in less than 4 days. The data set revealed excellent biomarker candidates for ovarian cyst and urinary tract infection. The improved throughput and quantitative performance of our optimized DIA workflow allow for the efficient simultaneous discovery and verification of biomarker candidates without the requirement for an early bias toward selected proteins.

Differences in Blood and Urine Biomarker Discovery

Submit Manuscript | http://medcraveonline.com and sensitive markers should be in urine instead of blood during the early stage of disease. This explains why it is so hard to find an early biomarker in blood for so many years. When biomarkers appear in blood, the disease is already in the stage when homeostasis mechanisms are impaired, changes caused by the disease can not be effectively removed from blood. Even though I am not saying it is easy to find biomarker in urine since we have not made significant progress in discover many clinically usable biomarkers, I have to propose and encourage more researchers, more companies, more funding agencies to give more support on urine biomarker discovery, after all urine is where the early markers reside.

Discovery of urinary biomarkers of whole grain rye intake in free-living subjects using nontargeted LC-MS metabolite profiling.

Whole grain (WG) intake is associated with decreased risk of developing colorectal cancer, type 2 diabetes, and cardiovascular disease and its comorbidities. However, the role of specific grains is unclear. Moreover, intake of specific WG is challenging to measure accurately with traditional dietary assessment methods. Our aim was to use nontargeted metabolite profiling to discover specific urinary biomarkers for WG rye to objectively reflect intake under free-living conditions. WG rye intake was estimated by weighed food records, and 24 h urine collections were analyzed by LC-MS. Multivariate modeling was undertaken by repeated double cross-validated partial least squares regression against reported WG rye intake, which correlated well with multivariate prediction estimates (r = 0.67-0.80, p < 0.001), but not with intakes of WG wheat or oats. Hydroxyhydroxyphenyl acetamide sulfate, 3,5-dihydroxyphenylpropionic acid sulfate, caffeic acid sulfate, and hydroxyphenyl acetamide sulfate were among the 20 features that had the greatest potential as intake biomarkers of WG. In addition, three compounds exhibited MS/MS fragmentation of carnitine structures. With this nontargeted approach, we confirmed the specificity of alkylresorcinol metabolites as biomarkers for WG rye intake, but also discovered other compounds that should be evaluated as putative biomarkers in future studies.

Comparative Tissue Proteomics of Microdissected Specimens Reveals Novel Candidate Biomarkers of Bladder Cancer

More than 380,000 new cases of bladder cancer are diagnosed worldwide, accounting for ∼150,200 deaths each year. To discover potential biomarkers of bladder cancer, we employed a strategy combining laser microdissection, isobaric tags for relative and absolute quantitation labeling, and liquid chromatography-tandem MS (LC-MS/MS) analysis to profile proteomic changes in fresh-frozen bladder tumor specimens. Cellular proteins from four pairs of surgically resected primary bladder cancer tumor and adjacent nontumorous tissue were extracted for use in two batches of isobaric tags for relative and absolute quantitation experiments, which identified a total of 3220 proteins. A DAVID (database for annotation, visualization and integrated discovery) analysis of dysregulated proteins revealed that the three top-ranking biological processes were extracellular matrix organization, extracellular structure organization, and oxidation-reduction. Biological processes including response to organic substances, response to metal ions, and response to inorganic substances were highlighted by up-expressed proteins in bladder cancer. Seven differentially expressed proteins were selected as potential bladder cancer biomarkers for further verification. Immunohistochemical analyses showed significantly elevated levels of three proteins-SLC3A2, STMN1, and TAGLN2-in tumor cells compared with noncancerous bladder epithelial cells, and suggested that TAGLN2 could be a useful tumor tissue marker for diagnosis (AUC = 0.999) and evaluating lymph node metastasis in bladder cancer patients. ELISA results revealed significantly increased urinary levels of both STMN1 and TAGLN2 in bladder cancer subgroups compared with control groups. In comparisons with age-matched hernia urine specimens, urinary TAGLN2 in bladder cancer samples showed the largest fold change (7.13-fold), with an area-under-the-curve value of 0.70 (p < 0.001, n = 205). Overall, TAGLN2 showed the most significant overexpression in individual bladder cancer tissues and urine specimens, and thus represents a potential biomarker for noninvasive screening for bladder cancer. Our findings highlight the value of bladder tissue proteome in providing valuable information for future validation studies of potential biomarkers in urothelial carcinoma.

Discovery of novel candidate urinary protein biomarkers for prostate cancer in a multiethnic cohort of South African patients via label-free mass spectrometry.

Improvement in diagnostic accuracy of prostate cancer (PCa) progression using MS-based methods to analyze biomarkers in our African, Caucasian, and Mixed Ancestry patients can advance early detection and treatment monitoring. MS-based proteomic analysis of pooled (N = 36) and individual samples (N = 45) of PCa, benign prostatic hyperplasia, normal healthy controls, and patients with other uropathies was used to identify differences in proteomics profile. Samples were analyzed for potential biomarkers and proteome coverage in African, Caucasian, and Mixed Ancestry PCa patients. A total of 1102 and 5595 protein groups and nonredundant peptides, respectively, were identified in the pooling experiments (FDR = 0.01). Twenty potential biomarkers in PCa were identified and fold differences ± 2SD were observed in 17 proteins using intensity-based absolute quantification. Analysis of 45 individual samples yielded 1545 and 9991 protein groups and nonredundant peptides, respectively. Seventy-three (73) proteins groups, including existing putative PCa biomarkers, were found to be potential biomarkers of PCa by label-free quantification and demonstrated ethnic trends within our PCa cohort. Urinary proteomics is a promising route to PCa biomarker discovery and may serve as source of ethnic-related biomarkers of PCa.

Urinary Candidate Biomarker Discovery in a Rat Unilateral Ureteral Obstruction Model

Urine has the potential to become a better source of biomarkers. Urinary proteins are affected by many factors; therefore, differentiating between the variables associated with any particular pathophysiological condition in clinical samples is challenging. To circumvent these problems, simpler systems such as animal models should be used to establish a direct relationship between disease progression and urine changes. Obstructive nephropathy is one of the most significant causes of chronic kidney disease, and its predominant end‐stage change is irreversible interstitial fibrosis. To better detect a set of obstructive nephropathy candidate urinary biomarkers, a unilateral ureteral obstruction (UUO) model was used to observe tubular injury and the eventual development of renal fibrosis, as well as to identify differential urinary proteins in this process. In this study, urine samples were collected from the residuary ureter linked to the kidney 1 and 3 weeks after UUO to mimic urine from patients with obstructive nephropathy. Compared with the sham operation group, 7 and 19 significantly changed proteins were identified by LC‐MS/MS in the UUO 1 and 3 week groups, respectively. These proteins identified in rat models of UUO may serve as candidate biomarkers of renal tubular injury and interstitial fibrosis in obstructive nephropathy.

Urinary candidate biomarker discovery in a rat unilateral ureteral obstruction model.

Urine has the potential to become a better source of biomarkers. Urinary proteins are affected by many factors; therefore, differentiating between the variables associated with any particular pathophysiological condition in clinical samples is challenging. To circumvent these problems, simpler systems, such as animal models, should be used to establish a direct relationship between disease progression and urine changes. In this study, a unilateral ureteral obstruction (UUO) model was used to observe tubular injury and the eventual development of renal fibrosis, as well as to identify differential urinary proteins in this process. Urine samples were collected from the residuary ureter linked to the kidney at 1 and 3 weeks after UUO. Five hundred proteins were identified and quantified by LC-MS/MS, out of which 7 and 19 significantly changed in the UUO 1- and 3-week groups, respectively, compared with the sham-operation group. Validation by western blot showed increased levels of Alpha-actinin-1 and Moesin in the UUO 1-week group, indicating that they may serve as candidate biomarkers of renal tubular injury, and significantly increased levels of Vimentin, Annexin A1 and Clusterin in the UUO 3-week group, indicating that they may serve as candidate biomarkers of interstitial fibrosis.

Urine biomarker discovery using label free proteomics reveals novel markers for the monitoring of treatment for mucopolysaccharide disorders

Urine biomarker discovery using label free proteomics reveals novel markers for the monitoring of treatment for mucopolysaccharide disorders

Focused metabolomics using liquid chromatography/electrospray ionization tandem mass spectrometry for analysis of urinary conjugated cholesterol metabolites from patients with Niemann-Pick disease type C and 3β-hydroxysteroid dehydrogenase deficiency.

Various conjugated cholesterol metabolites are excreted in urine of the patients with metabolic abnormalities and hepatobiliary diseases. We aimed to examine the usefulness of precursor ion scan and neutral loss scan for the characterization of conjugated cholesterol metabolites in urine. A mixture of authentic standards of conjugated cholesterol metabolites was used for investigating the performance of the present method. The urine of patients with Niemann-Pick diseases type C and 3β-hydroxysteroid dehydrogenase deficiency were analysed by precursor ion scan of m/z 97, 74, and 124. A precursor ion scan of m/z 97 was effective for identifying conjugates with ester sulphates on hydroxyl groups whereas ester sulphates on phenolic alcohols were signalled by a neutral loss scan of 80 Da. Monosaccharide-conjugated cholesterol metabolites were signalled by a precursor ion scan of m/z 113. Although precursor ion scan of m/z 74 and 124 was effective for finding glycine- and taurine-conjugated metabolites, high intensity of product ions (m/z 74 and 124) disturbed measurement of other multiply conjugated metabolites. The urine samples contained many conjugated cholesterol metabolites, and there were several disease-specific intense peaks. We found several unknown intense peaks with three known peaks in urine of the Niemann-Pick type C patient. In the patient with 3β-hydroxysteroid dehydrogenase deficiency, intense peaks that were tentatively identified as 5-cholenoic acid sulphates and their glycine and taurine conjugates were present. The method should lead to the discovery of new urinary biomarkers for these disturbances of cholesterol catabolism and transport.

Early markers of Fabry disease revealed by proteomics.

Fabry disease (FD) is an X-linked lysosomal storage disorder caused by a deficiency of the lysosomal hydrolase α-galactosidase A (α-GalA) that leads to the intra-lysosomal accumulation of globotriaosylceramide (Gb3) in various organ systems. As a consequence, a multisystems disorder develops, culminating in stroke, progressive renal and cardiac dysfunction. Enzyme replacement therapy (ERT) offers a specific treatment for patients affected by FD, though the monitoring of treatment is hindered by a lack of surrogate markers of response. Remarkably, due to the high heterogeneity of the Fabry phenotype, both diagnostic testing and treatment decisions are more challenging in females than in males; thus, reliable biomarkers for Fabry disease are needed, particularly for female patients. Here, we use a proteomic approach for the identification of disease-associated markers that can be used for the early diagnosis of FD as well as for monitoring the effectiveness of ERT. Our data show that the urinary proteome of Fabry naïve patients is different from that of normal subjects. In addition, biological pathways mainly affected by FD are related to immune response, inflammation, and energetic metabolism. In particular, the up-regulation of uromodulin, prostaglandin H2 d-isomerase and prosaposin in the urine of FD patients was demonstrated; these proteins might be involved in kidney damage at the tubular level, inflammation and immune response. Furthermore, comparing the expression of these proteins in Fabry patients before and after ERT treatment, a decrease of their concentration was observed, thus demonstrating the correlation between the identified markers and the effectiveness of the pharmacological treatment.

Role for urinary biomarkers in diagnosis of acute rejection in the transplanted kidney.

Despite the introduction of potent immunosuppressive medications within recent decades, acute rejection still accounts for up to 12% of all graft losses, and is generally associated with an increased risk of late graft failure. Current detection of acute rejection relies on frequent monitoring of the serum creatinine followed by a diagnostic renal biopsy. This strategy is flawed since an alteration in the serum creatinine is a late clinical event and significant irreversible histologic damage has often already occurred. Furthermore, biopsies are invasive procedures that carry their own inherent risk. The discovery of non-invasive urinary biomarkers to help diagnose acute rejection has been the subject of a significant amount of investigation. We review the literature on urinary biomarkers here, focusing on specific markers perforin and granzyme B mRNAs, FOXP3 mRNA, CXCL9/CXCL10 and miRNAs. These and other biomarkers are not yet widely used in clinical settings, but our review of the literature suggests that biomarkers may correlate with biopsy findings and provide an important early indicator of rejection, allowing more rapid treatment and better graft survival.

Urinary protein biomarker database: a useful tool for biomarker discovery.

An open-access biomarker database offers a convenient tool for researchers to acquire existing knowledge about proteins and diseases by simply querying its Web site. Biologists can use the biomarker database to assess the confidence and disease specificity of their own research results by cross-study comparison, and bioinformaticians can use it to discover new relationships between diseases and proteins by reanalyzing data via new strategies. This chapter introduces the urinary protein biomarker database, a manually curated database that aim to collect all studies of urinary protein biomarkers from published literature. In the current stage, this database includes very few disease-specific biomarker candidates that have been reported by multiple studies, reflecting current status in the field of urinary biomarker discovery. We believe that this situation will be improved with the development of technologies and accumulation of data, and a more complete and precise biomarker database will play more important role in future studies.