Investigation of vesicoureteral reflux by target and untargeted metabolomic approaches in urine using CE-MS, CESI-MS, RPLC-MS and HILIC-MS as analytical platforms

Author(s)

Karina Trevisan Rodrigues

• Document type: Doctoral Thesis
• Press: São Paulo.
• Institution: Universidade de São Paulo (USP). Conjunto das Químicas (IQ e FCF) (CQ/DBDCQ)
• Defense date: 2017-09-14

Examining board members

Marina Franco Maggi Tavares; Nilson Antonio de Assunção; Jorge Cesar Masini; Pedro Vitoriano de Oliveira; Alessandra Sussulini

• Advisor: Marina Franco Maggi Tavares

Abstract

Vesicoureteral reflux (VUR) is one of the most commonly urologic conditions diagnosed among children. A high degree of this condition can cause kidney scarring, kidney failure and high blood pressure. Voiding cystourethrography is the standard method for diagnosis; however, this procedure involves sedation, bladder catheterization and exposes the child to a significant amount of radiation. Metabolomics has provided new insights about the disease and aims to discover specific metabolites associated with it. Thus, there is a considerable potential for the implementation of metabolic profile in clinical analyses. Thus, we attempted to establish a noninvasive alternative to identify children with VUR through metabolomics approach. For target metabolomics, a CE-MS method was developed and validated for the separation and quantitative analysis of 27 amino acids in urine. Experimental parameters related to the CE-MS interface (based on co-axial sheath liquid, SHL), background electrolyte (BGE) and mass spectrometer (MS) settings were optimized providing a good separation of 27 amino acids, including the isomers L-leucine, L-isoleucine and L-alloisoleucine, in less than 30 min. The SHL was composed of 0.50% (v/v) formic acid in 60% (v/v) methanol-water delivered at a flow rate of 5 µL min-1. The BGE consisted of 0.80 mol L-1 formic acid and 15% (v/v) methanol. A pH stacking procedure was implemented to enhance sensitivity (a 12.5% (v/v) NH4OH solution was injected at 0.5 psi/9 s prior to samples). The proposed method was thoroughly validated according to FDA and ICH protocols exhibiting acceptable parameters. A successful quantification of amino acids in urine samples from the VUR cohort was achieved. The statistical evaluation of the results showed that some of the amino acids may carry information for the discrimination of the urine samples between the test and control groups. For untargeted metabolomics analysis, methods by RPLC-MS and HILIC-MS were optimized. Five columns with different properties were investigated for RPLC and four columns for HILIC; additionally, the influence of additives and pH of the mobile phase were investigated. The optimum conditions were determined assessing the peak shape, signal-to-noise ratio, retention time, number of molecular features detected and their distribution during the elution gradient. The best condition obtained for RPLC uses CSH C18 column and mobile phase composed by 0.1% (v/v) formic acid in water (A) and 0.1% (v/v) formic acid in acetonitrile (B). For HILIC, the best performance was obtained with the zwitterionic ZIC-HILIC column and mobile phase composed by 10 mmol L-1 ammonium acetate pH 6.8 (B) and 95% (v/v) acetonitrile and 5% (v/v) 200 mmol L-1 ammonium acetate pH 6.8 (A). Urine samples from the control and test groups were submitted to global metabolomics analysis by RPLC-MS using the optimized method and by CESI-MS. The results indicated that several metabolic pathways may have been altered by VUR. Changes of carnitine and acylcarnitine levels, amino acids and derivatives, purines and others was observed. Furthermore, the presence of acylcarnitines in the urine may indicate mitochondrial damage and the decrease of tryptophan and increase of the kynurenic acid indicate a change in the metabolism of tryptophan. (AU)

• FAPESP's process: 12/09822-0 - Evaluation of urinary global fingerprint of vesicoureteral reflux for CE-MS
• Grantee: Karina Trevisan Rodrigues
• Support Opportunities: Scholarships in Brazil - Doctorate