Urinary peptidome analyses for the diagnosis of chronic kidney disease in dogs.

Chronic kidney disease (CKD) is clinically important in canine medicine. Current diagnostic tools lack sensitivity for detection of subclinical CKD. The aim of the present study was to evaluate urinary peptidome analysis for diagnosis of CKD in dogs. Capillary electrophoresis coupled to mass spectrometry analysis demonstrated presence of approximately 5400 peptides in dog urine. Comparison of urinary peptide abundance of dogs with and without CKD led to the identification of 133 differentially excreted peptides (adjusted P for each peptide <0.05). Sequence information was obtained for 35 of these peptides. This 35 peptide subset and the total group of 133 peptides were used to construct two predictive models of CKD which were subsequently validated by researchers masked to results in an independent cohort of 20 dogs. Both models diagnosed CKD with an area under the receiver operating characteristic (ROC) curve of 0.88 (95% confidence intervals [CI], 0.72-1.0). Most differentially excreted peptides represented fragments of collagen I, indicating possible association with fibrotic processes in CKD (similar to the equivalent human urinary peptide CKD model, CKD273). This first study of the urinary peptidome in dogs identified peptides that were associated with presence of CKD. Future studies are needed to validate the utility of this model for diagnosis and prediction of progression of canine CKD in a clinical setting.

[Proteome analysis of undiluted vitreous humor in patients with branch retinal vein occlusion]. / Proteomanalyse unverdünnter Glaskörperflüssigkeit bei Patienten mit einem Venenastverschluss.

BACKGROUND: The pathophysiological mechanisms of macular edema secondary to branch retinal vein occlusion (BRVO) remain unclear. OBJECTIVES: To analyze the protein profile of human vitreous of patients with BRVO and to identify specific dysregulated proteins. MATERIALS AND METHODS: Undiluted vitreous humor samples from patients with treatment naïve BRVO and 15 controls with idiopathic floaters were analyzed in this clinical-experimental study using capillary electrophoresis coupled to a mass spectrometer (CE-MS) and tandem mass spectrometry (MS/MS). Quantitative analysis of the dysregulated proteins was performed with enzyme-linked immunosorbent assay (ELISA). Protein-protein interactions were depicted with the STRING database. RESULTS: A total of 84 proteins were found in the human vitreous samples of 15 patients with BRVO and 15 controls. In all, 14 proteins were significant when comparing the signal intensities of BRVO and control samples. Six significant dysregulated proteins with p < 0.001 were further verified with ELISA. Clusterin, complement factor C3, prostaglandin-H2 D­isomerase and vitronectin were significantly upregulated in the BRVO group and opticin was downregulated. The protein interactions analysis showed associations with inflammatory cascades, matrix changes, mechanisms of cell survival und death. CONCLUSIONS: The results of the study reveal that the proteomic composition of vitreous humor differed significantly between the patients with BRVO and the controls. Whether the identified proteins may serve as potential biomarkers for pathophysiology, diagnostics or therapy should be examine in further studies.

A urinary peptide biomarker set predicts worsening of albuminuria in type 2 diabetes mellitus.

AIMS/HYPOTHESIS: Microalbuminuria is considered the first clinical sign of kidney dysfunction and is associated with a poor renal and cardiovascular prognosis in type 2 diabetes. Detection of patients who are prone to develop micro- or macroalbuminuria may represent an effective strategy to start or optimise therapeutic intervention. Here we assessed the value of a urinary proteomic-based risk score (classifier) in predicting the development and progression of microalbuminuria. METHODS: We conducted a prospective case-control study. Cases (n = 44) and controls (n = 44) were selected from the PREVEND (Prevention of Renal and Vascular End-stage Disease) study and from the Steno Diabetes Center (Gentofte, Denmark). Cases were defined by transition from normo- to microalbuminuria or from micro- to macroalbuminuria over a follow-up of 3 years. Controls with no transitions in albuminuria were pair-matched for age, sex and albuminuria status. A model for the progression of albuminuria was built using a proteomic classifier based on 273 urinary peptides. RESULTS: The proteomic classifier was independently associated with transition to micro- or macroalbuminuria (OR 1.35 [95% CI 1.02, 1.79], p = 0.035). The classifier predicted the development and progression of albuminuria on top of albuminuria and estimated GFR (eGFR, area under the receiver operating characteristic [ROC] curve increase of 0.03, p = 0.002; integrated discrimination index [IDI]: 0.105, p = 0.002). Fragments of collagen and α-2-HS-glycoprotein showed significantly different expression between cases and controls. CONCLUSIONS/INTERPRETATION: Although limited by the relatively small sample size, these results suggest that analysis of a urinary biomarker set enables early renal risk assessment in patients with diabetes. Further work is required to confirm the role of urinary proteomics in the prevention of renal failure in diabetes.

A comparison between MALDI-MS and CE-MS data for biomarker assessment in chronic kidney diseases.

Non-invasive detection of diseases, based on urinary proteomics, is becoming an increasingly important area of research, especially in the area of chronic kidney disease (CKD). Different platforms have been used in independent studies, mostly capillary-electrophoresis coupled ESI-MS (CE-MS), liquid chromatography coupled mass spectrometry, and matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). We have compared the performance of CE-MS with MALDI-MS in detecting CKD, based on a cohort of 137 urine samples (62 cases and 75 controls). Data cross-talk between the two platforms was established for the comparison of detected biomarkers. The results demonstrate superior performance of the CE-MS approach in terms of peptide resolution and obtained disease prediction accuracy rates. However, the data also demonstrate the ability of the MALDI-MS approach to separate CKD patients from controls, at slightly reduced accuracy, but expected reduced cost and time. As a consequence, a practical approach can be foreseen where MALDI-MS is employed as an inexpensive, fast, and robust screening tool to detect probable CKD. In a second step, high resolution CE-MS could be used in those patients only that scored negative for CKD in the MALDI-MS analysis, reducing costs and time of such a program.

Clinical proteomics: current techniques and potential applications in the elderly.

In Western societies the process of aging is closely related to the onset of chronic diseases, such as coronary artery disease, diabetic nephropathy or different types of malignancies. Novel biomarkers are urgently needed to assist in managing these diseases. Parallel to technical advancements possibilities for the analysis of the human proteome for biomarkers have recently made considerable progress. In a first part, this article attempts to describe the main proteomic platform technologies, their advantages and disadvantages and will critically review proteomic study design aspects necessary to obtain valuable data, such as choosing suitable clinical specimens, data processing and mining. Physiological age-related alterations in the human proteome have been described and were similar to indolent changes associated with chronic diseases, in particular of the kidneys. Therefore, in a second part this review will introduce several examples for the application of clinical proteomics to aging itself and age-related diseases. Several recent proteome studies with clinically sound designs are available. These performed careful validation in blinded cohorts. It is anticipated that a boost in disease-related proteomic data is expected in the very near future. However, lessons of the past teach the strict adherence to proper technological approaches, appropriate statistics, and large databases to fulfil these high expectations.