Application of multi-omic and functional network analysis for paediatric patients diagnosed with idiopathic nephrotic syndrome (CROSBI ID 594301)
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Podaci o odgovornosti
Gethings, A Lee ; Vissers PC Johannes ; John hockcor, John ; McDonald, Stephen ; Kraljević Pavelić, Sandra ; Sedic, Mirela ; Lemac, Maja ; Batinić, Danica ; Langridge, James ; Vasieva, Olga ; Compson, Keith
engleski
Application of multi-omic and functional network analysis for paediatric patients diagnosed with idiopathic nephrotic syndrome
Novel Aspect Use of multi-omic and pathway analysis studies to derive potential biomarkers for patients diagnosed with idiopathic nephrotic syndrome Introduction Idiopathic nephrotic syndrome (INS) is the most prevalent glomerular disease in children. In spite of some progress, its pathogenesis is still unknown and the therapy options are confined to gross immune modulation. A variety of methods for diagnostic and treatment purposes are available for the patients ; however, the lack of understanding regarding the pathogenic mechanisms underlying INS can lead to poor therapeutic response and adverse side-effects. Here, we describe quantitative proteomic and metabolomic approaches to reveal new molecular factors involved in pathogenesis of INS with potential diagnostic and therapeutic significance. Methods Urine samples were collected from 10 children diagnosed with INS receiving no therapy and 10 healthy children. All samples were purified using spin filters followed by affinity depletion of albumin. The purified proteins were recovered and digested with trypsin overnight. Label-free protein expression data were acquired with a oa- TOF using an ion mobility data independent approach, whereby the collision energy was switched between low and elevated energy state during alternate scans and associate precursor and product ions by means of retention and drift time alignment correlated and searched using post processing software. Preliminary Data The collected urine samples were divided into batches for proteomic and metabolomic analysis. For the proteomic studies, samples were purified and depleted of albumin using a combination of spin filters with anti-HSA resin. Proteins were reduced and alkylated prior to digestion with trypsin overnight. Samples were prepared for analysis with 800ng loaded on-column. Samples were anlysed in triplicate. The acquired data was processed and searched against a human database, which was amended to account for N-terminal processed peptides. Normalized label-free quantitation results were generated using TransOmics software. In a similar fashion the diluted neat urine samples were analysed using a small molecule profiling approach. The resulting data was also analyzed using TransOmics, providing a complimentary dataset. Interpretation of the data has shown a significant number of proteins to be over-expressed in the urine from INS patients, which includes a high percentage (approximately 80%) of glycosylated proteins. Metabolites of interest showing statistically significant changes include homocysteine, glutamate and uridine. Pathway analysis tools were used to review the complimentary datasets and hence provide an understanding of the underlying biology of differentially expressed proteins and metabolites. Review and validation of the suggested pathways, strongly suggests correlation with the neuronal system disorders network, specifically acute fatigue.
Urine proteomics; bioinfomatics; idiopathic nephrotic syndrome
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Podaci o prilogu
2013.
objavljeno
Podaci o matičnoj publikaciji
Podaci o skupu
61st ASMS Conference on Mass Spectrometry and Allied Topics
poster
09.07.2013-13.07.2013
Minneapolis (MN), Sjedinjene Američke Države