The utilization of profiles to classify samples has been used in analytical chemistry since decades ago. In proteomics, mass spectrometry, MS, profiling of complex proteomes comprises three main steps, (i) an appropriate sample treatment developed for each particular type of sample is needed, (ii) an adequate mass spectrometer is necessary and (iii) bioinformatics tools are needed to handle large sets of data provided by MALDI-MS-based profiling. As both, bioinformatics and MALDI-MS have reached maturity, currently the bottleneck in proteome profiling remains sample treatment [1]. The aim of this study was to differentiate patients with glomerulonephritis and diabetic nephropathy using (i) peritoneal dialysate effluent, (ii) matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and (iii) bioinformatics tools.