Implementation of Proteomics Biomarkers in Nephrology: From Animal Models to Human Application?

Immunolocalization of Sphingolipid Catabolism Enzymes along the Nephron: Novel Early Urinary Biomarkers of Renal Damage

The objective of this study was to investigate whether the activity of enzymes involved in sphingolipid catabolism could be biomarkers to predict early renal damage in streptozotocin (STZ)-induced diabetic rats and Angiotensin II (Ang II)-induced hypertension rats. Diabetic and hypertensive rats had no changes in plasma creatinine concentration. However, transmission electron microscopy (TEM) analysis showed slight ultrastructural changes in the glomeruli and tubular epithelial cells from diabetic and hypertensive rats. Our results show that the acid sphingomyelinase (aSMase) and neutral sphingomyelinase (nSMase) activity increased in the urine of diabetic rats and decreased in hypertensive rats. Only neutral ceramidase (nCDase) activity increased in the urine of diabetic rats. Furthermore, the immunofluorescence demonstrated positive staining for the nSMase, nCDase, and sphingosine kinase (SphK1) in glomerular mesangial cells, proximal tubule, ascending thin limb of the loop of Henle, thick ascending limb of Henle's loop, and principal cells of the collecting duct in the kidney. In conclusion, our results suggest that aSMase and nCDase activity in urine could be a novel predictor of early slight ultrastructural changes in the nephron, aSMase and nCDase as glomerular injury biomarkers, and nSMase as a tubular injury biomarker in diabetic and hypertensive rats.

Machine Learning-Based Urine Peptidome Analysis to Predict and Understand Mechanisms of Progression to Kidney Failure

Introduction

The identification of patients with chronic kidney disease (CKD) at risk of progressing to kidney failure (KF) is important for clinical decision-making. In this study we assesed whether urinary peptidome (UP) analysis may help classify patients with CKD and improve KF risk prediction.

Methods

The UP was analyzed using capillary electrophoresis coupled to mass spectrometry in a case-cohort sample of 1000 patients with CKD stage G3 to G5 from the French CKD-Renal Epidemiology and Information Network (REIN) cohort. We used unsupervised and supervised machine learning to classify patients into homogenous UP clusters and to predict 3-year KF risk with UP, respectively. The predictive performance of UP was compared with the KF risk equation (KFRE), and evaluated in an external cohort of 326 patients.

Results

More than 1000 peptides classified patients into 3 clusters with different CKD severities and etiologies at baseline. Peptides with the highest discriminative power for clustering were fragments of proteins involved in inflammation and fibrosis, highlighting those derived from α-1-antitrypsin, a major acute phase protein with anti-inflammatory and antiapoptotic properties, as the most significant. We then identified a set of 90 urinary peptides that predicted KF with a c-index of 0.83 (95% confidence interval [CI]: 0.81-0.85) in the case-cohort and 0.89 (0.83-0.94) in the external cohort, which were close to that estimated with the KFRE (0.85 [0.83-0.87]). Combination of UP with KFRE variables did not further improve prediction.

Conclusion

This study shows the potential of UP analysis to uncover new pathophysiological CKD progression pathways and to predict KF risk with a performance equal to that of the KFRE.

Role of protein phosphatase 2A in kidney disease (Review)

Kidney disease affects millions of people worldwide and is a financial burden on the healthcare system. Protein phosphatase 2A (PP2A), which is involved in renal development and the function of ion-transport proteins, aquaporin-2 and podocytes, is likely to serve an important role in renal processes. PP2A is associated with the pathogenesis of a variety of different kidney diseases including podocyte injury, inflammation, tumors and chronic kidney disease. The current review aimed to discuss the structure and function of PP2A subunits in the context of kidney diseases. How dysregulation of PP2A in the kidneys causes podocyte death and the inactivation of PP2A in renal carcinoma tissues is discussed. Inhibition of PP2A activity prevents epithelial-mesenchymal transition and attenuates renal fibrosis, creating a favorable inflammatory microenvironment and promoting the initiation and progression of tumor pathogenesis. The current review also indicates that PP2A serves an important role in protection against renal inflammation. Understanding the detailed mechanisms of PP2A provides information that can be utilized in the design and application of novel therapeutics for the treatment and prevention of renal diseases.

Comparative proteomic analysis of renal proteins from IgA nephropathy model mice and control mice

BACKGROUND

High-IgA ddY (HIGA) mice, an animal model of human IgA nephropathy (IgAN), spontaneously develop nephropathy with glomerular IgA deposition and markedly elevated serum IgA levels from 25 weeks of age.

METHODS

We performed a comparative proteomic analysis of the renal proteins collected from HIGA mice and control C57BL/6 mice at 5 or 38 weeks of age (the H5, H38, C5, and C38 groups) (n = 4 in each group). Proteins were extracted from the left whole kidney of each mouse and analyzed using nano-liquid chromatography-tandem mass spectrometry. The right kidneys were used for histopathological examinations.

RESULTS

Immunohistochemical examinations showed glomerular deposition of IgA and the immunoglobulin joining (J) chain, and increased numbers of interstitial IgA- and J-chain-positive plasma cells in the H38 group. In the proteomic analysis, > 5000 proteins were identified, and 33 proteins with H38/H5 ratios of > 5.0, H38/C38 ratios of > 5.0, and C38/C5 ratios of < 1.5 were selected. Among them, there were various proteins that are known to be involved in human IgAN and/or animal IgAN models. Immunohistochemical examinations validated the proteomic results for some proteins. Furthermore, two proteins that are known to be associated with kidney disease displayed downregulated expression (H38/H5 ratio: 0.01) in the H38 group.

CONCLUSIONS

The results of comparative proteomic analysis of renal proteins were consistent with previous histopathological and serological findings obtained in ddY and HIGA mice. Various proteins that are known to be involved in kidney disease, including IgAN, and potential disease marker proteins exhibited markedly altered levels in HIGA mice.

Proteomic profiling of urine: implications for lupus nephritis

INTRODUCTION

Lupus nephritis (LN) is a common and significant manifestation, affecting 60% of adults and 80% of children with systemic lupus erythematosus, with up to 30% of patients progressing to end stage renal disease. There remains an unmet need for non-invasive markers of disease activity, damage, and response to therapy. In addition, non-invasive biomarkers that predict therapeutic efficacy are needed to enable cost-effective clinical trials of novel agents. Areas covered: This review examines the methodological aspects of urinary proteomics, the role of proteome profiling in identifying promising urinary biomarkers in LN, and the translation of research findings into clinically useful tools in the management of LN. Expert opinion: Targeted and unbiased proteomics have identified several promising urinary biomarkers that predict LN activity, damage (chronicity), and response to therapy. In particular, a combination of biologically plausible urinary biomarkers termed as RAIL (Renal Activity Index for Lupus) has emerged as an excellent predictor of LN activity as well as response to therapy, being able to predict efficacy within 3 months of therapy. If validated in additional large prospective studies, the RAIL biomarkers will transform the care of patients with LN, allowing for a personalized and predictive approach and improved outcomes.

Proteomics for Clinical Assessment of Kidney Disease

Kidney disease is one of the fastest growing causes of death worldwide, disclosing an unmet clinical need for early diagnosis and optimized risk stratification that allows high risk patient selection for clinical trials and for more intensive nephroprotective interventions in the clinic. The current issue of PROTEOMICS-Clinical Applications contains four manuscripts that explore different aspects of clinical proteomics implementation in the context of acute kidney injury, chronic kidney disease and, more specifically, diabetic kidney disease, and kidney transplantation from a diagnostic and risk stratification point of view. Overall, the evidence discussed suggests that chronic kidney disease is an example where clinical proteomics has become a valuable tool ready for clinical implementation, expected to have a major impact in patient management.