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A matrix-induced ion suppression method to normalize concentration in urinary metabolomics studies using flow
Guan-yuan Chen1, Hsiao-wei Liao1, Yufeng Jane Tseng2
1School of Pharmacy, College of Medicine, National Taiwan University, Taipei, Taiwan; The Metabolomics Core Laboratory, Center of Genomic Medicine, National Taiwan University, Taipei, Taiwan.
Abstract:
Normalizing the total urine concentration is important for minimizing bias in urinary metabolomics analysis comparisons. In this study, we report a matrix-induced ion suppression (MIIS)-based method to normalize concentration using flow injection analysis coupled with electrospray ionization mass spectrometry (FIA-ESI-MS). An ion suppression indicator (ISI) was spiked into urine samples, and the intensity of the extracted ion chromatogram (EIC) for ISI in a urine matrix was subtracted by the EIC for a blank solution and used to calculate the extent to which the signal was reduced by the urine matrix. A series dilution of pooled urine samples was used to correlate the urine concentration and level of ion suppression for ISI. A regression equation was used to estimate the relative concentration of unknown urine samples. The MIIS method was validated for linearity, precision and accuracy. We obtained a good correlation using a quadratic regression model for 1- to 32-fold urine dilutions (R(2)=0.998). The reproducibility (n=4) and intermediate precision (n=3) were below 5% RSD, and the accuracy ranged from 97.15% to 102.10%. The established method was used to estimate the relative concentrations of 16 urine samples, and the results were compared with commonly used normalization methods. Pearson's correlation test was used to demonstrate that the MIIS method correlated highly with the creatinine and osmolarity methods; the correlation coefficients were 0.93 and 0.99, respectively. We successfully applied this method to a urinary metabolomics study on breast cancer. This study demonstrated the MIIS method is simple, accurate and can contribute to data integrity in urinary metabolomics studies.
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