Uromodulin and α(1)-antitrypsin urinary peptide analysis to differentiate glomerular kidney diseases

Progress in understanding primary glomerular disease: insights from urinary proteomics and in-depth analyses of potential biomarkers based on bioinformatics

Chronic kidney disease (CKD) has become a global public health challenge. While primary glomerular disease (PGD) is one of the leading causes of CKD, the specific pathogenesis of PGD is still unclear. Accurate diagnosis relies largely on invasive renal biopsy, which carries risks of bleeding, pain, infection and kidney vein thrombosis. Problems with the biopsy procedure include lack of glomeruli in the tissue obtained, and the sampling site not being reflective of the overall lesion in the kidney. Repeated renal biopsies to monitor disease progression cannot be performed because of the significant risks of bleeding and kidney vein thrombosis. On the other hand, urine collection, a noninvasive method, can be performed repeatedly, and urinary proteins can reflect pathological changes in the urinary system. Advancements in proteomics technologies, especially mass spectrometry, have facilitated the identification of candidate biomarkers in different pathological types of PGD. Such biomarkers not only provide insights into the pathogenesis of PGD but also are important for diagnosis, monitoring treatment, and prognosis. In this review, we summarize the findings from studies that have used urinary proteomics, among other omics screens, to identify potential biomarkers for different types of PGD. Moreover, we performed an in-depth bioinformatic analysis to gain a deeper understanding of the biological processes and protein-protein interaction networks in which these candidate biomarkers may participate. This review, including a description of an integrated analysis method, is intended to provide insights into the pathogenesis, noninvasive diagnosis, and personalized treatment efforts of PGD and other associated diseases.

Multiplex quantification of C-terminal alpha-1-antitrypsin peptides provides a novel approach for characterizing systemic inflammation

C-terminal peptides (CAAPs) of the highly abundant serine protease alpha-1-antitrypsin (A1AT) have been identified at various lengths in several human materials and have been proposed to serve as putative biomarkers for a variety of diseases. CAAPs are enzymatically formed and these enzymatic activities are often associated with excessive immune responses (e.g. sepsis, allergies). However, most of those CAAPs have been either detected using in vitro incubation experiments or in human materials which are not easily accessible. To gain a comprehensive understanding about the occurrence and function of CAAPs in health and disease, a LC-MS/MS method for the simultaneous detection of nine CAAPs was developed and validated for human plasma (EDTA and lithium-heparin) and serum. Using this newly developed method, we were able to detect and quantify five CAAPs in healthy individuals thereby providing an initial proof for the presence of C36, C37, C40 and C44 in human blood. Concentrations of four CAAPs in a clinical test cohort of patients suffering from sepsis were significantly higher compared to healthy controls. These results reveal that in addition to C42 other fragments of A1AT seem to play a crucial role during systemic infections. The proposed workflow is simple, rapid and robust; thus this method could be used as diagnostic tool in routine clinical chemistry as well as for research applications for elucidating the diagnostic potential of CAAPs in numerous diseases. To this end, we also provide an overview about the current state of knowledge for CAAPs identified in vitro and in vivo.

Urinary Protein and Peptide Markers in Chronic Kidney Disease

Chronic kidney disease (CKD) is a non-specific type of kidney disease that causes a gradual decline in kidney function (from months to years). CKD is a significant risk factor for death, cardiovascular disease, and end-stage renal disease. CKDs of different origins may have the same clinical and laboratory manifestations but different progression rates, which requires early diagnosis to determine. This review focuses on protein/peptide biomarkers of the leading causes of CKD: diabetic nephropathy, IgA nephropathy, lupus nephritis, focal segmental glomerulosclerosis, and membranous nephropathy. Mass spectrometry (MS) approaches provided the most information about urinary peptide and protein contents in different nephropathies. New analytical approaches allow urinary proteomic-peptide profiles to be used as early non-invasive diagnostic tools for specific morphological forms of kidney disease and may become a safe alternative to renal biopsy. MS studies of the key pathogenetic mechanisms of renal disease progression may also contribute to developing new approaches for targeted therapy.

Urine proteomics of primary membranous nephropathy using nanoscale liquid chromatography tandem mass spectrometry analysis

Background

Primary membranous nephropathy (PMN) is an important cause of nephrotic syndrome in adults. Urine proteome may provide important clues of pathophysiological mechanisms in PMN. In the current study, we analyzed and compared the proteome of urine from patients with PMN and normal controls.

Methods

We performed two technical replicates (TMT1 and TMT2) to analyze and compare the urine proteome from patients with PMN and normal controls by tandem mass tag (TMT) technology coupled with nanoscale liquid chromatography tandem mass spectrometry analysis (LC–MS/MS). Gene ontology (GO) enrichment analysis was performed to analyse general characterization of the proteins. The proteins were also matched against the database of Kyoto Encyclopedia of Genes and Genomes (KEGG). For validation, Western blot was used to analyze the selected proteins.

Results

A total of 509 proteins and 411 proteins were identified in TMT1 and TMT2, respectively. 249 proteins were both identified in two technical replicates. GO analysis and KEGG analysis revealed immunization and coagulation were predominantly involved. Among the differential protein, the overexcretion of alpha-1-antitrypsin (A1AT) and afamin (AFM) were validated by Western blot analysis.

Conclusions

Our data showed the important role of immunologic mechanism in the development of PMN, and the value of urinary A1AT and AFM in biomarker discovery of patients with PMN. The discovery of the overexcretion of A1AT and AFM in the urine can help to further elucidate pathogenetic mechanisms involved in PMN.

Electronic supplementary material

The online version of this article (10.1186/s12014-018-9183-3) contains supplementary material, which is available to authorized users.

Urine volatile organic compounds as biomarkers for minimal change type nephrotic syndrome

Urinary volatile organic compounds (VOCs) profiling has recently received considerable attention because it can be obtained noninvasively and conveniently while it can be successfully used in a variety of diseases and can provide unique biomarkers. The aim of current study was to investigate potential biomarkers between minimal change type nephrotic syndrome (MCNS) and normal. Urinary samples were collected from 38 minimal change type nephrotic syndrome patients and 15 healthy controls. Solid phase microextraction (SPME) and chromatography- mass spectrometry (GC-MS) were used to analysis the urinary metabolites. To deal with the final data, the statistical methods principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLSDA) were performed. Six specific VOC biomarkers were present at abnormal levels in the urine of MCNS patients. These VOCs included trans-2,2-dimethyl-4-decene; pyrrole; carbamic acid, monoammonium salt; 1-butyne, 3,3-dimethyl-; diisopropylamine; and 4-heptanone. These biomarkers may be useful as a new diagnostic method and for monitoring the prognosis for MCNS patients.

iTRAQ-Based Proteomics of Chronic Renal Failure Rats after FuShengong Decoction Treatment Reveals Haptoglobin and Alpha-1-Antitrypsin as Potential Biomarkers

Background. Chronic renal failure (CRF) has become a global health problem and bears a huge economic burden. FuShengong Decoction (FSGD) as traditional Chinese medicine has multiple pharmacological effects. Objectives. To understand the underlying molecular mechanism and signaling pathway involved in the FSGD treatment of CRF and screen differentially expressed proteins in rats with CRF treated with FSGD. Methods. Thirty-three male Sprague-Dawley rats were randomly divided into control group, CRF group, and FSGD group. Differentially expressed proteins were screened by iTRAQ coupled with nanoLC-MS/MS, and these identified proteins were later analyzed by GO, KEGG, and STRING. Additionally, haptoglobin (HP) and alpha-1-antitrypsin (AAT) were finally verified by ELISA, Western blot, and real time PCR. Results. A total of 417 proteins were identified. Nineteen differentially expressed proteins were identified in the FSGD group compared with the model group, of which 3 proteins were upregulated and 16 proteins were downregulated. Cluster analysis indicated that inflammatory response was associated with these proteins and complement and coagulation cascade pathways were predominantly involved. The validation methods further confirmed that the levels of HP and AAT were significantly increased. Conclusions. HP and AAT may be the important biomarkers in the pathogenesis of CRF and FSGD therapy.

Comparative differential proteomic analysis of minimal change disease and focal segmental glomerulosclerosis

Background

Minimal change disease (MCD) and primary focal segmental glomerulosclerosis (FSGS) are glomerular diseases characterized by nephrotic syndrome. Their diagnosis requires a renal biopsy, but it is an invasive procedure with potential complications. In a small biopsy sample, where only normal glomeruli are observed, FSGS cannot be differentiated from MCD. The correct diagnosis is crucial to an effective treatment, as MCD is normally responsive to steroid therapy, whereas FSGS is usually resistant.

The purpose of our study was to discover and validate novel early urinary biomarkers capable to differentiate between MCD and FSGS.

Methods

Forty-nine patients biopsy-diagnosed of MCD and primary FSGS were randomly subdivided into a training set (10 MCD, 11 FSGS) and a validation set (14 MCD, 14 FSGS). The urinary proteome of the training set was analyzed by two-dimensional differential gel electrophoresis coupled with mass spectrometry. The proteins identified were quantified by enzyme-linked immunosorbent assay in urine samples from the validation set.

Results

Urinary concentration of alpha-1 antitrypsin, transferrin, histatin-3 and 39S ribosomal protein L17 was decreased and calretinin was increased in FSGS compared to MCD. These proteins were used to build a decision tree capable to predict patient’s pathology.

Conclusions

This preliminary study suggests a group of urinary proteins as possible non-invasive biomarkers with potential value in the differential diagnosis of MCD and FSGS. These biomarkers would reduce the number of misdiagnoses, avoiding unnecessary or inadequate treatments.

Electronic supplementary material

The online version of this article (doi:10.1186/s12882-017-0452-6) contains supplementary material, which is available to authorized users.

α-1-Antitrypsin detected by MALDI imaging in the study of glomerulonephritis: Its relevance in chronic kidney disease progression

Idiopathic glomerulonephritis (GN), such as membranous glomerulonephritis, focal segmental glomerulosclerosis (FSGS), and IgA nephropathy (IgAN), represent the most frequent primary glomerular kidney diseases (GKDs) worldwide. Although the renal biopsy currently remains the gold standard for the routine diagnosis of idiopathic GN, the invasiveness and diagnostic difficulty related with this procedure highlight the strong need for new diagnostic and prognostic biomarkers to be translated into less invasive diagnostic tools. MALDI-MS imaging MALDI-MSI was applied to fresh-frozen bioptic renal tissue from patients with a histological diagnosis of FSGS (n = 6), IgAN, (n = 6) and membranous glomerulonephritis (n = 7), and from controls (n = 4) in order to detect specific molecular signatures of primary glomerulonephritis. MALDI-MSI was able to generate molecular signatures capable to distinguish between normal kidney and pathological GN, with specific signals (m/z 4025, 4048, and 4963) representing potential indicators of chronic kidney disease development. Moreover, specific disease-related signatures (m/z 4025 and 4048 for FSGS, m/z 4963 and 5072 for IgAN) were detected. Of these signals, m/z 4048 was identified as α-1-antitrypsin and was shown to be localized to the podocytes within sclerotic glomeruli by immunohistochemistry. α-1-Antitrypsin could be one of the markers of podocyte stress that is correlated with the development of FSGS due to both an excessive loss and a hypertrophy of podocytes.

Developing proteomic biomarkers for bladder cancer: towards clinical application

Clinical use of proteomic biomarkers has the potential to substantially improve the outcomes of patients with bladder cancer. An unmet clinical need evidently exists for noninvasive biomarkers, which might enable improvements in both the diagnosis and prognosis of patients with bladder cancer, as well as improved monitoring of patients for the presence of recurrence. Urine is considered the optimal noninvasive source of proteomic biomarkers in patients with bladder cancer. Currently, a number of single-protein biomarkers have been detected in urine and tissue using a variety of proteomic techniques, each having specific conceptual considerations and technical implications. Promising preclinical data are available for several of these proteins; however, the combination of single urinary proteins into multimarker panels might better encompass the molecular heterogeneity of bladder cancer within this patient population, and prove more effective in clinical use.

Advances in urinary protein biomarkers for urogenital and non-urogenital pathologies

The discovery of protein biomarkers that reflect the biological state of the body is of vital importance to disease management. Urine is an ideal source of biomarkers that provides a non-invasive approach to diagnosis, prognosis and prediction of diseases. Consequently, the study of the human urinary proteome has increased dramatically over the last 10 years, with many studies being published. This review focuses on urinary protein biomarkers that have shown potential, in initial studies, for diseases affecting the urogenital tract, specifically chronic kidney disease and prostate cancer, as well as other non-urogenital pathologies such as breast cancer, diabetes, atherosclerosis and osteoarthritis. PubMed was searched for peer-reviewed literature on the subject, published in the last 10 years. The keywords used were "urine, biomarker, protein, and/or prostate cancer/breast cancer/chronic kidney disease/diabetes/atherosclerosis/osteoarthritis". Original studies on the subject, as well as a small number of reviews, were analysed including the strengths and weaknesses, and we summarized the performance of biomarkers that demonstrated potential. One of the biggest challenges found is that biomarkers are often shared by several pathologies so are not specific to one disease. Therefore, the trend is shifting towards implementing a panel of biomarkers, which may increase specificity. Although there have been many advances in urinary proteomics, these have not resulted in similar advancements in clinical practice due to high costs and the lack of large data sets. In order to translate these potential biomarkers to clinical practice, vigorous validation is needed, with input from industry or large collaborative studies.

Urinary peptide profiling to differentiate between minimal change disease and focal segmental glomerulosclerosis

BACKGROUND

Minimal change disease (MCD) and primary focal segmental glomerulosclerosis (FSGS) are the main causes of primary idiopathic nephrotic syndrome in children and adults, with diagnosis being essential for the appropriate choice of therapy and requiring renal biopsy. However, the presence of only normal glomeruli on renal biopsy of FSGS patients may lead to the misclassification of these patients as having MCD. The aim of this study was to (i) compare the peptide profile of MCD and FSGS patients with that of a group of healthy subjects, (ii) generate and validate a class prediction model to classify MCD and FSGS patients and (ii) identify candidate biomarkers of these glomerular entities by analysis of the urinary peptidome.

METHODS

The urinary peptide profile was analyzed by magnetic bead-based technology combined with MALDI-TOF mass spectrometry in 44 patients diagnosed of MCD (n = 22) and FSGS (n = 22). The resulting spectra were compiled and analyzed using ClinProTools software.

RESULTS

A class prediction model was developed to differentiate MCD and FSGS patients. The validation of this model correctly classified 81.8% (9/11) of MCD patients and 72.7% (8/11) of FSGS patients. Moreover, the signal with m/z 1913.60, identified as a fragment of uromodulin, and the signal with m/z 2392.54, identified as a fragment of alpha-1-antitrypsin, showed higher and lower peak areas, respectively, in FSGS patients compared with MCD patients.

CONCLUSIONS

The simple, non-invasive technique described in the present study may be a useful tool to help clinicians by confirming diagnoses achieved by renal biopsy, thereby reducing misdiagnoses and avoiding the implementation of inappropriate therapies.

Investigation of CCL18 and A1AT as potential urinary biomarkers for bladder cancer detection

BACKGROUND

In this study, we further investigated the association of two biomarkers, CCL18 and A1AT, with bladder cancer (BCa) and evaluated the influence of potentially confounding factors in an experimental model.

METHODS

In a cohort of 308 subjects (102 with BCa), urinary concentrations of CCL18 and A1AT were assessed by enzyme-linked immunosorbent assay (ELISA). In an experimental model, benign or cancerous cells, in addition to blood, were added to urines from healthy controls and analyzed by ELISA. Lastly, immunohistochemical staining for CCL18 and A1AT in human bladder tumors was performed.

RESULTS

Median urinary protein concentrations of CCL18 (52.84 pg/ml vs. 11.13 pg/ml, p < 0.0001) and A1AT (606.4 ng/ml vs. 120.0 ng/ml, p < 0.0001) were significantly elevated in BCa subjects compared to controls. Furthermore, the addition of whole blood to pooled normal urine resulted in a significant increase in both CCL18 and A1AT. IHC staining of bladder tumors revealed CCL18 immunoreactivity in inflammatory cells only, and there was no significant increase in these immunoreactive cells within benign and cancerous tissue and no association with BCa grade nor stage was noted. A1AT immunoreactivity was observed in the cytoplasm of epithelia cells and intensity of immunostaining increased with tumor grade, but not tumor stage.

CONCLUSIONS

Further development of A1AT as a diagnostic biomarker for BCa is warranted.

The human urine metabolome

Urine has long been a "favored" biofluid among metabolomics researchers. It is sterile, easy-to-obtain in large volumes, largely free from interfering proteins or lipids and chemically complex. However, this chemical complexity has also made urine a particularly difficult substrate to fully understand. As a biological waste material, urine typically contains metabolic breakdown products from a wide range of foods, drinks, drugs, environmental contaminants, endogenous waste metabolites and bacterial by-products. Many of these compounds are poorly characterized and poorly understood. In an effort to improve our understanding of this biofluid we have undertaken a comprehensive, quantitative, metabolome-wide characterization of human urine. This involved both computer-aided literature mining and comprehensive, quantitative experimental assessment/validation. The experimental portion employed NMR spectroscopy, gas chromatography mass spectrometry (GC-MS), direct flow injection mass spectrometry (DFI/LC-MS/MS), inductively coupled plasma mass spectrometry (ICP-MS) and high performance liquid chromatography (HPLC) experiments performed on multiple human urine samples. This multi-platform metabolomic analysis allowed us to identify 445 and quantify 378 unique urine metabolites or metabolite species. The different analytical platforms were able to identify (quantify) a total of: 209 (209) by NMR, 179 (85) by GC-MS, 127 (127) by DFI/LC-MS/MS, 40 (40) by ICP-MS and 10 (10) by HPLC. Our use of multiple metabolomics platforms and technologies allowed us to identify several previously unknown urine metabolites and to substantially enhance the level of metabolome coverage. It also allowed us to critically assess the relative strengths and weaknesses of different platforms or technologies. The literature review led to the identification and annotation of another 2206 urinary compounds and was used to help guide the subsequent experimental studies. An online database containing the complete set of 2651 confirmed human urine metabolite species, their structures (3079 in total), concentrations, related literature references and links to their known disease associations are freely available at http://www.urinemetabolome.ca.

Protein-Protein Interactions: Gene Acronym Redundancies and Current Limitations Precluding Automated Data Integration

Understanding protein interaction networks and their dynamic changes is a major challenge in modern biology. Currently, several experimental and in silico approaches allow the screening of protein interactors in a large-scale manner. Therefore, the bulk of information on protein interactions deposited in databases and peer-reviewed published literature is constantly growing. Multiple databases interfaced from user-friendly web tools recently emerged to facilitate the task of protein interaction data retrieval and data integration. Nevertheless, as we evidence in this report, despite the current efforts towards data integration, the quality of the information on protein interactions retrieved by in silico approaches is frequently incomplete and may even list false interactions. Here we point to some obstacles precluding confident data integration, with special emphasis on protein interactions, which include gene acronym redundancies and protein synonyms. Three human proteins (choline kinase, PPIase and uromodulin) and three different web-based data search engines focused on protein interaction data retrieval (PSICQUIC, DASMI and BIPS) were used to explain the potential occurrence of undesired errors that should be considered by researchers in the field. We demonstrate that, despite the recent initiatives towards data standardization, manual curation of protein interaction networks based on literature searches are still required to remove potential false positives. A three-step workflow consisting of: (i) data retrieval from multiple databases, (ii) peer-reviewed literature searches, and (iii) data curation and integration, is proposed as the best strategy to gather updated information on protein interactions. Finally, this strategy was applied to compile bona fide information on human DREAM protein interactome, which constitutes liable training datasets that can be used to improve computational predictions.

An extensive targeted proteomic analysis of disease-related protein biomarkers in urine from healthy donors

The analysis of protein biomarkers in urine is expected to lead to advances in a variety of clinical settings. Several characteristics of urine including a low-protein matrix, ease of testing and a demonstrated proteomic stability offer distinct advantages over current widely used biofluids, serum and plasma. Improvements in our understanding of the urine proteome and in methods used in its evaluation will facilitate the clinical development of urinary protein biomarkers. Multiplexed bead-based immunoassays were utilized to evaluate 211 proteins in urines from 103 healthy donors. An additional 25 healthy donors provided serial urine samples over the course of two days in order to assess temporal variation in selected biomarkers. Nearly one-third of the evaluated biomarkers were detected in urine at levels greater than 1ng/ml, representing a diverse panel of proteins with respect to structure, function and biological role. The presence of several biomarkers in urine was confirmed by western blot. Several methods of data normalization were employed to assess impact on biomarker variability. A complex pattern of correlations with urine creatinine, albumin and beta-2-microglobulin was observed indicating the presence of highly specific mechanisms of renal filtration. Further investigation of the urinary protein biomarkers identified in this preliminary study along with a consideration of the underlying proteomic trends suggested by these findings should lead to an improved capability to identify candidate biomarkers for clinical development.

Poor histological lesions in IgA nephropathy may be reflected in blood and urine peptide profiling

Background

IgA nephropathy (IgAN) is the most common primary glomerulonephritis worldwide, leading to renal failure in 15% to 40% of cases. IgAN is diagnosed by renal biopsy, an invasive method that is not risk-free. We used blood and urine peptide profiles as a noninvasive method of linking IgAN-associated changes with histological lesions by Oxford classification.

Methods

We prospectively studied 19 patients with biopsy-proven IgAN and 14 healthy subjects from 2006 to 2009, excluding subjects with crescentic glomerulonephritis and collecting clinical and biochemical data at the time of diagnosis and during follow-up (24 months). Histological lesions were evaluated by Oxford classification. Proteomic analysis was performed by combining magnetic bead (MB) technology and mass spectrometry (MALDI-TOF MS) to obtain peptide profiles. Doubling of serum creatinine was considered a variable of poor renal prognosis.

Results

We identified 55 peptides—13 in serum, 26 in plasma, and 16 in urine—that differentiated IgAN patients from healthy subjects. A significant association was noted between serum/plasma and urine peptides and histological findings—ie, tubulointerstitial damage, segmental glomerulosclerosis, and endocapillary injury.

We also identified 3 peptides—corresponding to bradykinin, uromodulin, and alpha-1-antitrypsin—that were associated with severity of lesions, such as tubulointerstitial damage and segmental glomerulosclerosis.

Moreover, blood peptides with m/z 2953, 5337, 9287, and 9289 and urine peptides with m/z 1769, 1898, 1913, 1945, 2491, 2756, 2977, 3004, 3389, and 4752 correlated significantly with poor renal function.

Conclusions

In patients with IgAN, the use of noninvasive approaches, such as blood and urine proteomics, can provide valuable information beyond that of standard diagnostic techniques, allowing us to identify blood and urine peptide profiles that are associated with poor histological lesions in IgAN patients.