Proteomic Identification of Urinary Biomarkers of Diabetic Nephropathy

Rao, Paturi Vishnupriya; Lu, Xinfang; Standley, Melissa; Pattee, Patrick; Neelima, Gundupalle; Girisesh, G.; Dakshinamurthy, KV; Roberts, Charles T.; Nagalla, Srinivasa R.

doi:10.2337/dc06-2056

Cited by 147 publications

(135 citation statements)

References 33 publications

Supporting

Mentioning

123

Contrasting

Unclassified

Order By: Relevance

“…In three independent proteomics scans, ␣ 1 -antitrypsin, a serine protease inhibitor, was present at higher levels in urine and renal tissue of patients with diabetic nephropathy compared with controls (22)(23)(24). Higher levels of ␣ 1B -glycoprotein have also been reported previously in urine of patients with proteinuric diabetic nephropathy compared with normoalbuminuric diabetics (25).…”

Section: Optimizing Proteomics Platform For Urine Biomarker Discoverysupporting

confidence: 52%

Optimizing a Proteomics Platform for Urine Biomarker Discovery

Afkarian

Bhasin

Dillon

et al. 2010

Molecular & Cellular Proteomics

View full text Add to dashboard Cite

Biomarker discovery approaches in urine have been hindered by concerns for reproducibility and inadequate standardization of proteomics protocols. In this study, we describe an optimized quantitative proteomics strategy for urine biomarker discovery, which is applicable to fresh or long frozen samples. We used urine from healthy controls to standardize iTRAQ (isobaric tags for relative and absolute quantitation) for variation induced by protease inhibitors, starting protein and iTRAQ label quantities, protein extraction methods, and depletion of albumin and immunoglobulin G (IgG). We observed the following: With ongoing advances in mass spectrometry (MS) and proteomics technology, proteomics analysis is progressively occupying a central position in biomarker discovery platforms. Biofluids such as urine and blood are the preferred media for proteomics analysis because of their ease of collection and extensive history of use in clinical laboratory practice. Urine, in particular, is an information-rich fluid that can be collected non-invasively and in large quantities. Many urine proteins are produced or shed in the kidney and urogenital tract (1), making urine a promising proximal source of biomarkers for diseases affecting these structures.However, proteomics-based biomarker discovery in urine faces multiple challenges. Urine proteomics is complicated by low urine protein concentration, variations in pH, and high concentrations of salts and urea or other urine components that interfere with sample processing. The urine proteome can also change with individual variables such as hydration, diurnal change, diet, and physical activity as well as variation in sample collection, processing, and storage. In addition, urine proteomics shares the usual challenges of biomarker discovery in other biofluids such as throughput, cost, and the need for a reproducible and quantitative work flow.Isotopic or isobaric labeling methods to reduce variation, increase throughput, and enable quantitative analysis have been developed to address some of these challenges. One such method, isobaric tags for relative and absolute quantitation (iTRAQ) 1 (2), combines relative and absolute peptide quantification with multiplexing ability to enable an increased throughput as well as simultaneous comparison of up to eight samples within one experimental run. Variations induced by urine sample processing have been systematically evaluated for proteomics analyses using two-dimensional gel electrophoresis (3-6), differential gel electrophoresis (7), and liquid chromatography-coupled mass spectrometry (LC-MS) (5,8,9). However, no systematic analyses of urine sample collection and processing have been reported for iTRAQ.Before utilizing iTRAQ-based quantitative proteomics for urine biomarker discovery, we evaluated the impact of variation in several processing steps (addition of protease inhibitors, the starting protein quantities, quantity of the iTRAQ label, protein extraction methods, and depletion of abundant proteins) on iTRAQ protein identifica...

show abstract

Section: Optimizing Proteomics Platform For Urine Biomarker Discoverysupporting

confidence: 52%

Optimizing a Proteomics Platform for Urine Biomarker Discovery

Afkarian

Bhasin

Dillon

et al. 2010

Molecular & Cellular Proteomics

View full text Add to dashboard Cite

show abstract

“…By 2-DE, we found that all children with HIVAN and HIV-HUS showed high urinary levels of these 11 proteins, when compared with samples harvested from HIV-infected children without renal disease, and to the normal values reported in other studies for HIV-negative controls (17)(18)(19)(20)(21)(22)(23)(24). These proteins are: orosomucoid, transferrin, ␣-1-microglobulin, zinc ␣-2-glycoprotein, ␣-1-antitrypsin, complement factor B, haptoglobin, transthyretin, RBP, albumin, and hemopexin ( Figure 1 and Table 1).…”

Section: Proteomicsmentioning

confidence: 58%

Iron-Related Proteins

Soler-García¹,

Johnson²,

Hathout³

et al. 2009

Clinical Journal of the American Society of Nephrology

View full text Add to dashboard Cite

Background: Because of the risk of performing renal biopsies in children with co-morbid conditions, we carried out this study to identify candidate protein biomarkers in the urine of HIV-infected children with renal disease.Design, setting, participants & measurements: Urine samples from HIV-infected children with biopsy proven HIVnephropathy (HIVAN; n ‫؍‬ 4), HIV-associated Hemolytic Uremic Syndrome (HIV-HUS; n ‫؍‬ 2), or no renal disease (n ‫؍‬ 3) were analyzed by two-dimensional electrophoresis (2-DE) and proteomic methods. Positive findings were confirmed in HIVinfected children with (n ‫؍‬ 20) and without (n ‫؍‬ 10) proteinuria using commercially available assays.Results: By 2-DE analysis, a single urine marker was not sufficient to distinguish children with HIVAN from the others. High urine levels of ␤ 2 -microglobulin and retinol-binding protein (RBP) suggested the presence of tubular injury. In addition, we found elevated urine levels of iron and the iron-related proteins, transferrin, hemopexin, haptoglobin, lactoferrin, and neutrophil gelatinase-associated lipocalin (NGAL), in children with HIVAN and HIV-HUS. Furthermore, we detected a significant accumulation of iron in the urine and kidneys of HIV-transgenic (Tg) rats with renal disease.Conclusion: These findings suggest that iron and iron-related proteins might be promising candidate urine biomarkers to identify HIV-infected children at risk of developing HIVAN and HIV-HUS. Moreover, based on the results of previous studies, we speculate that the release or accumulation of iron in the kidney of HIV-infected children may contribute to the rapid progression of their renal disease, and could become a new therapeutic target against HIVAN and HIV-HUS.

show abstract

“…Ceruloplasmin and prostaglandin-H2 D-isomerase were found to be differentially expressed in type 2 diabetic patients with nephropathy; however, the results from separate studies did not agree. In a two-dimensional Difference Gel Electrophoresis (DIGE) study, Paturi et al (22) reported that ceruloplasmin decreased in diabetic patients with normoalbuminuria, and that prostaglandin-H2 D-isomerase decreased in diabetic patients with macroalbuminuria, compared with healthy controls. However, Narita et al (23) and Jiang et al (24) observed increases in these proteins using an immunoradiometric assay and two-dimensional DIGE method, respectively.…”

Section: Resultsmentioning

confidence: 99%

A Tool for Biomarker Discovery in the Urinary Proteome: A Manually Curated Human and Animal Urine Protein Biomarker Database

Shao

et al. 2011

Molecular & Cellular Proteomics

101

View full text Add to dashboard Cite

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. Molecular & Cellular

show abstract

Proteomic Identification of Urinary Biomarkers of Diabetic Nephropathy

Cited by 147 publications

References 33 publications

Optimizing a Proteomics Platform for Urine Biomarker Discovery

Optimizing a Proteomics Platform for Urine Biomarker Discovery

Iron-Related Proteins

A Tool for Biomarker Discovery in the Urinary Proteome: A Manually Curated Human and Animal Urine Protein Biomarker Database

Contact Info

Product

Resources

About