Proteomic profiling of nephrotic syndrome in serum using magnetic bead based sample fractionation & MALDI-TOF MS.

Background & objectives: At present, the diagnosis of nephrotic syndrome (NS) requires a renal biopsy which is an invasive procedure. We undertook this pilot study to develop an alternative method and potential new biomarkers for diagnosis, and validated a set of well-integrated tools called ClinProt to investigate serum petidome in NS patients. Methods: The fasting blood samples from 49 patients diagnosed with NS by renal biopsy, including 17 mesangial proliferative glomerulonephritis (MsPGN), 12 minimal change nephrotic syndrome (MCNS), 10 focal segmental glomerulosclerosis (FSGS) and 10 membranous nephropathy (MN), were collected and screened to describe their variability of the serum peptidome. The results in NS group were compared with those in 10 control healthy individuals. Specimens were purified with magnetic beads-based weak cation exchange chromatography and analyzed in a MALDI-TOF MS. Results: The results showed 43, 61, 45 and 19 differential peptide peaks in MsPGN, MCNS, MN and FSGS groups, respectively. A Genetic Algorithm was used to set up the classification models. Cross validation of healthy controls from MsPGN, MCNS, MN and FSGS was 96.18, 100, 98.53 and 94.12 per cent, respectively. The recognition capabilities were 100 per cent. Interpretation & conclusions: Our results showed that proteomic analysis of serum with MALDI-TOF MS is a fast and reproducible approach, which may give an early idea of the pathology of nephrotic syndrome.

A proton nuclear magnetic resonance-based metabonomics study of metabolic profiling in immunoglobulin a nephropathy

OBJECTIVES: Immunoglobulin A nephropathy is the most common cause of chronic renal failure among primary glomerulonephritis patients. The ability to diagnose immunoglobulin A nephropathy remains poor. However, renal biopsy is an inconvenient, invasive, and painful examination, and no reliable biomarkers have been developed for use in routine patient evaluations. The aims of the present study were to identify immunoglobulin A nephropathy patients, to identify useful biomarkers of immunoglobulin A nephropathy and to establish a human immunoglobulin A nephropathy metabolic profile. METHODS: Serum samples were collected from immunoglobulin A nephropathy patients who were not using immunosuppressants. A pilot study was undertaken to determine disease-specific metabolite biomarker profiles in three groups: healthy controls (N = 23), low-risk patients in whom immunoglobulin A nephropathy was confirmed as grades I-II by renal biopsy (N = 23), and high-risk patients with nephropathies of grades IV-V (N = 12). Serum samples were analyzed using proton nuclear magnetic resonance spectroscopy and by applying multivariate pattern recognition analysis for disease classification. RESULTS: Compared with the healthy controls, both the low-risk and high-risk patients had higher levels of phenylalanine, myo-Inositol, lactate, L6 lipids ( = CH-CH2-CH = O), L5 lipids (-CH2-C = O), and L3 lipids (-CH2-CH2-C = O) as well as lower levels of β -glucose, α-glucose, valine, tyrosine, phosphocholine, lysine, isoleucine, glycerolphosphocholine, glycine, glutamine, glutamate, alanine, acetate, 3-hydroxybutyrate, and 1-methylhistidine. CONCLUSIONS: These metabolites investigated in this study may serve as potential biomarkers of immunoglobulin A nephropathy. Point scoring of pattern recognition analysis was able to distinguish immunoglobulin A nephropathy patients from healthy controls. However, there were no obvious differences between the low-risk and high-risk groups in our research. These results offer new, sensitive and specific, noninvasive approaches that may be of great benefit to immunoglobulin A nephropathy patients by enabling earlier diagnosis.