Literature DB >> 30574040

Urinary Proteomics in Biomarker Discovery of Kidney-Related Disorders: Diabetic Nephropathy and Drug-Induced Nephrotoxicity in Chronic Headache.

Elisa Bellei1, Emanuela Monari1, Stefania Bergamini1, Luigi Alberto Pini1,2, Tomasi Aldo1, Tomris Ozben3.   

Abstract

OBJECTIVE: Urinary proteomics is primarily applied to the study of renal and urogenital tract disorders. Here are reported two distinct successful examples of this approach for the discovery of early urinary biomarkers of kidney-related dysfunctions: diabetic nephropathy (DN), a well-known complication of diabetes frequently leading to dialysis, and drug-induced nephrotoxicity, a possible condition caused by medication-overuse headache (MOH). Early detection of kidney disorders based on selective biomarkers could permit to diagnose patients at the initial stage of the disease, where the therapy may be suspended or prevent disease advancement.
METHODS: Urine samples were first concentrated and desalted. Subsequently, they were subjected to two-dimensional gel electrophoresis (2-DE) coupled to mass spectrometry (MS) for protein identification. Furthermore, some proteins were verified by Western blot and ELISA test.
RESULTS: In diabetes-related study, 11 differentially expressed proteins were detected (8 up-regulated and 3 down-regulated) in type 2 diabetic (T2D) and T2DN patients compared to the healthy control subjects. In the MOH study, a total of 21 over-excreted proteins were revealed in urine of non-steroidal anti-inflammatory drugs (NSAIDs) and mixtures abusers vs controls. Particularly, 4 proteins were positively validated by immunob-lotting and EUSA.
CONCLUSION: Urinary proteomics allows non-invasive assessment of renal diseases at an early stage by the identification of characteristic protein pattern.

Entities:  

Keywords:  biomarkers; diabetic nephropathy; drug-induced nephrotoxicity; urinary proteomics

Year:  2018        PMID: 30574040      PMCID: PMC6295592     

Source DB:  PubMed          Journal:  EJIFCC        ISSN: 1650-3414


INTRODUCTION

Proteomics is the study of protein expression in a definite tissue, cell type or biological body fluid. The comparison of protein patterns between healthy subjects and patients with a given pathological condition can be useful to identify specific diagnostics or prognostics biomarkers of diseases. Particularly, urinary proteomics has rapidly developed and has been extensively applied in the field of early diagnostics and differentiation of renal damage (1). Urine is a valuable source of proteins and peptides; it has the advantage of being obtained non-invasively, easily and frequently, and in a large quantity. It has been defined as a fluid biopsy of the kidney and urogenital tract, thus providing considerable information about these organs. Consequently, many changes in kidney and urogenital tract function may be detected in the urinary proteome (2). Urine proteomics studies were conducted in the search for early biomarkers of renal changes in: type 2 diabetic nephropathy (T2DN), a complication linked to diabetes, which leads to end-stage renal disease (3); drug-induced nephrotoxicity in medication-overuse headache (MOH), a chronic disorder associated with overuse of analgesic drugs or compounds for acute headache (4-6).

MATERIALS AND METHODS

Subjects

1) Diabetic nephropathy

Diabetic patients were enrolled from the “Division of Nephrology, Dialysis and Renal Transplantation” of the University-Hospital of Modena and Reggio Emilia, Italy: 10 normoal-buminuric patients with type 2 diabetes (T2D), 12 T2DN patients with microalbuminuria (range 130-280 mg/mL) and/or proteinuria (>10 mg/dL), and a control group of 12 healthy volunteer subjects with a history of regular renal function. The duration of diabetes was similar in the two patients groups. Moreover, all groups were matched for age and gender (3).

2) Drug-induced nephrotoxicity

A total of 87 MOH patients were recruited from the “Headache and Drug Abuse Center”, University-Hospital of Modena and Reggio Emilia, Italy. They were divided into three groups, according to the type of the primary abused drug, as follows: 31 patients who consumed exclusively triptans, 27 non-steroidal anti-inflammatory drugs (NSAIDs) and 29 taking mixtures. Healthy volunteers (n=30) were enrolled as controls. Each group was matched for age and gender; moreover, patients showed similar MOH duration, days with headache/month and about daily drug intake. Kidney diseases and urogenital tract dysfunctions, together with other important illness, were considered as exclusion criteria (5). Both studies were in compliance with the ethical principles for medical research involving human subjects, in accordance with the Declaration of Helsinki. Written informed consent were received from both, patients and healthy subjects.

Urine proteomics analysis

Morning midstream urine samples were collected and immediately centrifuged at 800 g for 10 min at +4C°, to remove cell debris and contaminants. Commonly, human urine has a very diluted protein concentration and, at the same time, a high-salt content, which hampers the proteomicanalysis. Sample preparation is therefore a pivotal step in urinary proteomics, especially during two-dimensional polyacrylamide gel electrophoresis (2-DE) (2). In order to concentrate proteins, eliminating the interfering salts, urine samples were treated with filter devices, 3 kDa MW-cut off (Merck Millipore). Subsequently, total protein content was estimated by the spectrophotometric Bradford method, and 100 mg of protein was premixed with a specific lysis buffer. The first-dimension separation (isoelec-trofocalization) was performed using IPG strips 17 cm long, wide pH range 3-10 (Bio-Rad), while in the second-dimension separation, 8-16% polyacrylamide gradient gels were used, that finally were staining with a silver-nitrate staining protocol. Afterwards, gels images were acquired with a calibrated densitometer (GS800 model, Bio-Rad) and analyzed by a specific image analysis software (PDQuest, Bio-Rad), to reveal differentially expressed protein spots among the patients and control groups (3, 5). The spots of interest were cut from the gels and subjected to trypsin digestion. Peptides were finally extracted and analyzed by the mass spectrometry using a quadrupole-time of flight-liquid chromatography mass spectrometer (Q-ToF-LC/MS, Agilent-Technologies). In the second study (drug-induced nephrotoxicity), the results obtained by proteomic analysis were further confirmed and validated by Western blot and ELISA test (6).

RESULTS AND DISCUSSION

1) Diabetic nephropathy

Comparing the urinary proteomic profiles obtained by 2-DE analysis, 11 differential proteins were identified that progressively changed between controls and T2D and T2DN patients. Precisely, 8 proteins were significantly up-regulated: transthyretin precursor, Ig k chain C region, Ig k chain V-II region Cum, Ig k-chain V-III region SIE, carbonic anhydrase 1, retinol binding protein, beta-2-microglobulin precursor and beta-2-glycoprotein 1. Except for the last one, all the other proteins were in the low MW range (<30 kDa). Three proteins were found down-regulated: prostatic acid phosphatase precursor, ribonuclease 2 and kallikrein-3 (Table 1).
Table 1

Differentially expressed proteins detected in T2D and T2DN patients by MS

Protein nameAcc. number[(a)]MW (kDa)Function
Up-regulated proteins
Transthyretin precursorP0276616.0Hormone-binding
Ig Kappa chain C-regionP0183411.8Immune response
Ig Kappa chain V-ll region CumP0161412.8Antigen-binding
Ig Kappa chain V-ll region SIEP0162011.9Immune response
Carbonic anhydrase 1P0091528.8Miscellaneous
Plasma retinol-binding proteinP0275323.3Transport
Beta-2-microglobulin precursorP6176913.8Immune response
Beta-2-glycoprotein 1P0274939.6Binding protein
Down-regulated proteins
Prostatic acid phosphatase precursorP1530944.9Dephosphorylation
Ribonuclease 2P1015318.9Miscellaneous
Kallikrein-3P0728829.3Hydrolysis

(a) Primary accession number from the SwissProt database.

Proteomic analysis allowed to detect alterations of urinary proteins in both T2DN and T2D normoalbuminuric patients. Thus, this protein pattern might be of potential interest to identify diabetic patients prone to develop nephropathy, contributing to a better understanding of diabetic-related renal damage. The strength of proteomics in this research area has been confirmed also by recently published review articles (7, 8).

2) Drug-induced nephrotoxicity

In this study both qualitative and quantitative differences in urine of MOH patients were studied and revealed. Interestingly, by 2-DE combined with MS analysis, 21 over-excreted proteins and a significantly higher number of total protein spots were identified in the urine of NSAIDs, mixtures and triptans abusers compared to the controls (Table 2).
Table 2

Differentially expressed proteins identified by Q-ToF-LC/MS

Protein nameAcc. number[(a)]MW (kDa)Over-expression vs controls[(b)]
MixturesNSAIDsTriptans
Low-MW proteins
Prostaglandin-H2-D-isomeraseP4122218.7XXX
Ig kappa chain C regionP0183411.8XXNS
Perlecan (fragment)P98160479.2XXX
TransthyretinP0276615.9NSXNS
Proactivator polypeptideP076029.11XXX
Nuclear transport factor 2P6197014.6XXX
Fatty acid-binding proteinQ0146915.5NSXX
Beta-2-microglobulinP6176911.7NSXX
Protein S100-A11P3194911.8NSXX
Non-secretory ribonucleaseP1015318.9XXNS
Cystatin-CP0103413.3XXNS
Protein S100-A8P0510910.8XXX
Medium - MW proteins
Alpha-1-antitrypsinP0100946.9XXNS
Actin, cytoplasmic!P6070942.1XXX
Alpha-1-microglobulinP0276039.9XXNS
Apolipoprotein HP0274938.3NSXNS
Serpin B3P2950844.6XXX
Annexin AlP0408338.6XXX
High - MW proteins
Serum albuminP0276866.5XXNS
UromodulinP0791169.7XXX
Inter-α-trypsin inhibitor heavy chain H4Q1462470.6XXNS

(a) Primary accession number from the SwissProt database

(b) Expression difference calculated by the PDQuest software: x: significant, NS: not-significant

Some differentially expressed proteins detected by proteomic analysis were found to be strongly related to renal injury (9), as assessed by an extensive literature review. Particularly, 4 proteins were validated by Western blot: prostaglandin-H2 D-synthase (PTGDS), uromodulin (UROM), alpha-1-microglobulin (AMBP) and cystatin-C (CYSC), as shown in Figure 1.
Figure 1

Western blot analysis

Immunoblotting allowed to confirm previous data of over-expression of these proteins in urine of MOH patients (especially NSAIDs and mixtures abusers) vs normal controls (6). Finally, PTGDS was further quantified by the ELISA test (Figure 2), which proved its significant increase in all MOH groups: mixtures (681 ± 218 ng/mL), NSAIDs (572 ± 135 ng/mL,) and triptans (450 ± 116 ng/mL), compared to the controls (303 ± 130 ng/mL). These data points, expressed as mean ± standard deviation, were in strict accordance with MS and Western blot results (6).
Figure 2

ELISA test of PTGDS protein

The results of this study allowed to define the urinary protein profile of MOH, in relation to the type of drug abused. The use of powerful proteomic methodologies could permit to identify promising candidate biomarkers of kidney dysfunctions, and consequently those chronic headache patients at risk to develop drug-induced nephrotoxicity.

CONCLUSIONS

In conclusion, urinary proteomics proved to be a suitable tool in nephro-toxicological research. Actually, its application may be useful in the search of early biomarkers, providing important diagnostics and prognostics indications. Additionally, the study of the urinary proteome can offer significant data for a better understanding of renal pathophysiology.
  9 in total

1.  Urinary clusterin, cystatin C, beta2-microglobulin and total protein as markers to detect drug-induced kidney injury.

Authors:  Frank Dieterle; Elias Perentes; André Cordier; Daniel R Roth; Pablo Verdes; Olivier Grenet; Serafino Pantano; Pierre Moulin; Daniel Wahl; Andreas Mahl; Peter End; Frank Staedtler; François Legay; Kevin Carl; David Laurie; Salah-Dine Chibout; Jacky Vonderscher; Gérard Maurer
Journal:  Nat Biotechnol       Date:  2010-05       Impact factor: 54.908

Review 2.  Urinary proteomics--a tool for biomarker discovery.

Authors:  Miljana Pejcic; Slavica Stojnev; Vladisav Stefanovic
Journal:  Ren Fail       Date:  2010-01       Impact factor: 2.606

3.  Applying proteomics to diagnosis of diabetic kidney disease.

Authors:  Rafael Noal Moresco; José Antonio Mainardi De Carvalho
Journal:  Expert Rev Proteomics       Date:  2017-09-15       Impact factor: 3.940

4.  Proteomic analysis of early urinary biomarkers of renal changes in type 2 diabetic patients.

Authors:  Elisa Bellei; Elena Rossi; Leonardo Lucchi; Simona Uggeri; Alberto Albertazzi; Aldo Tomasi; Anna Iannone
Journal:  Proteomics Clin Appl       Date:  2008-03-07       Impact factor: 3.494

5.  Proteomic analysis of urine in medication-overuse headache patients: possible relation with renal damages.

Authors:  Elisa Bellei; Aurora Cuoghi; Emanuela Monari; Stefania Bergamini; Luca Isaia Fantoni; Maurizio Zappaterra; Simona Guerzoni; Annalisa Bazzocchi; Aldo Tomasi; Luigi Alberto Pini
Journal:  J Headache Pain       Date:  2011-10-14       Impact factor: 7.277

Review 6.  Human Urine Proteomics: Analytical Techniques and Clinical Applications in Renal Diseases.

Authors:  Shiva Kalantari; Ameneh Jafari; Raheleh Moradpoor; Elmira Ghasemi; Ensieh Khalkhal
Journal:  Int J Proteomics       Date:  2015-11-29

7.  Validation of potential candidate biomarkers of drug-induced nephrotoxicity and allodynia in medication-overuse headache.

Authors:  Elisa Bellei; Emanuela Monari; Stefania Bergamini; Aurora Cuoghi; Aldo Tomasi; Simona Guerzoni; Michela Ciccarese; Luigi Alberto Pini
Journal:  J Headache Pain       Date:  2015-08-15       Impact factor: 7.277

8.  Discovery by a proteomic approach of possible early biomarkers of drug-induced nephrotoxicity in medication-overuse headache.

Authors:  Elisa Bellei; Emanuela Monari; Aurora Cuoghi; Stefania Bergamini; Simona Guerzoni; Michela Ciccarese; Tomris Ozben; Aldo Tomasi; Luigi Alberto Pini
Journal:  J Headache Pain       Date:  2013-01-30       Impact factor: 7.277

Review 9.  Proteomics for prediction of disease progression and response to therapy in diabetic kidney disease.

Authors:  Michelle J Pena; Harald Mischak; Hiddo J L Heerspink
Journal:  Diabetologia       Date:  2016-06-25       Impact factor: 10.122

  9 in total
  1 in total

Review 1.  Perspectives in systems nephrology.

Authors:  Maja T Lindenmeyer; Fadhl Alakwaa; Michael Rose; Matthias Kretzler
Journal:  Cell Tissue Res       Date:  2021-05-24       Impact factor: 4.051

  1 in total

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