Proteomic analysis to discover early urinary biomarkers of type 2 diabetic nephropathy

Objectives. Nephropathy associated with type 2 diabetes mellitus (T2D) is the most frequent cause of end stage renal disease (ESRD) in all Western countries, and a major healthcare problem. In the United States, the incidence of diabetic nephropathy (DN) has increased by 150% in the past 10 years: a similar trend has been reported also in Europe. Despite rapid research progress, predictors able to assess prospectively with high precision the risk for DN in individuals with diabetes are still lacking. Thus, at present the available therapies are usually initiated at more advanced stages of DN, characterized by evident clinical manifestations and progressive decline in glomerular filtration rate (GFR), leading toward both ESRD and cardiovascular events. In this study we made a comparison between the proteomic pattern of a group of normoalbuminuric T2D patients with those of a group of T2D patients with DN (T2DN). Both were compared with a group of healthy subjects, in the search of a diagnostic proteomic pattern that could help to identify patients at increased risk of kidney disease progression. Methods. We used two different proteomic approaches: the Surface-Enhanced Laser Desorption Ionization-Time of Flight technique (SELDI-TOF) and the two-dimensional gel electrophoresis (2-DE) coupled to mass spectrometry (MS). We performed urinary proteomic analysis of 10 T2D patients with microalbuminuria in the normal range, 12 T2DN patients, and 12 healthy subjects as normal controls. For protein profiling with SELDI-TOF, urine samples were analyzed using immobilized metal affinity capture (IMAC30), weak cation exchanger (CM10) and reverse phase (H50) ProteinChip Arrays. Statistical analysis was performed in the obtained spectra (Ciphergen Express 3.0) in order to identify peaks that showed significant differences among groups. Furthermore, urinary proteins were separated and visualized by 2-DE; the differentials spot were selected and identified by MS, using an ESI-Q-TOF mass spectrometer. Results. Comparing the patients proteomic profiles with those of normal controls, we identified 11 progressively and differently expressed proteins. The majority of these proteins resulted significantly increased in both patients groups, and corresponded to: transthyretin precursor, plasma retinol-binding protein, -2-microglobulin, carbonic anhydrase, -2-glycoprotein 1 (or apolipoprotein H), Ig kappa chain C region, Ig kappa chain V-III region SIE and Ig kappa chain V-II region Cum (or Bence-Jones protein). Only 3 proteins were gradually decreased in patients groups, including the prostatic acid phosphatase precursor, the ribonuclease and the kallikrein-3. Conclusions. The proteomic analysis allowed us to identify several increased urinary proteins, not only in T2DN, but also in T2D patients in which the microalbuminuria was in the normal range. These patterns of urinary proteins might represent a potential tool for a better understanding of diabetic renal damage and could help to identify the diabetic patients prone to progress toward DN.