Recommendations about structuring proteomic biomarker studies should increase the probability that such markers will be clinically useful.

Human mesenchymal stem cells (hMSCs) constitute a population of multipotent adherent cells able to give rise to multiple mesenchymal lineages such as osteoblasts, adipocytes, or chondrocytes. So far, the most common source of MSCs has been the bone marrow (BM); however BM-MSC harvesting and processing exhibits major drawbacks and limitations. Thus, identification and characterization of alternative sources of MSCs are of great importance. In the present study, we isolated and expanded fetal MSCs from second-trimester amniotic fluid (AF). We documented that these cells are of embryonic origin, can differentiate under appropriate conditions into cell types derived from all three germ layers, and express the pluripotency marker Oct-4, the human Nanog protein, and the stage-specific embryonic antigen-4 (SSEA-4). Furthermore, we systematically tested the immunophenotype of cultured MSCs by flow cytometry analysis using a wide variety of markers. Direct comparison of this phenotype to the one derived from cultured BM-MSCs demonstrated that cultured MSCs from both sources exhibit similar expression patterns. Using the two-dimensional gel electrophoresis and matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS) approach, we have generated for the first time the protein map of cultured AF-MSCs by identifying 261 proteins, and we compared it directly to that of cultured BM-MSCs. The functional pattern of the identified proteins from both sources was similar. However, cultured AF-MSCs displayed a number of unique proteins related to proliferation and primitive phenotype, which may confer to the distinct features of the two types. Considering the easy access to this new cell source and the yield of expanded MSCs for stem cell research, AF may provide an excellent source of MSCs both for basic research and for potential therapeutic applications.

Progressive CKD is generally detected at a late stage by a sustained decline in eGFR and/or the presence of significant albuminuria. With the aim of early and improved risk stratification of patients with CKD, we studied urinary peptides in a large cross-sectional multicenter cohort of 1990 individuals, including 522 with follow-up data, using proteome analysis. We validated that a previously established multipeptide urinary biomarker classifier performed significantly better in detecting and predicting progression of CKD than the current clinical standard, urinary albumin. The classifier was also more sensitive for identifying patients with rapidly progressing CKD. Compared with the combination of baseline eGFR and albuminuria (area under the curve [AUC]=0.758), the addition of the multipeptide biomarker classifier significantly improved CKD risk prediction (AUC=0.831) as assessed by the net reclassification index (0.303±−0.065; P<0.001) and integrated discrimination improvement (0.058±0.014; P<0.001). Correlation of individual urinary peptides with CKD stage and progression showed that the peptides that associated with CKD, irrespective of CKD stage or CKD progression, were either fragments of the major circulating proteins, suggesting failure of the glomerular filtration barrier sieving properties, or different collagen fragments, suggesting accumulation of intrarenal extracellular matrix. Furthermore, protein fragments associated with progression of CKD originated mostly from proteins related to inflammation and tissue repair. Results of this study suggest that urinary proteome analysis might significantly improve the current state of the art of CKD detection and outcome prediction and that identification of the urinary peptides allows insight into various ongoing pathophysiologic processes in CKD.