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. 2020 Sep 19;10(9):376.
doi: 10.3390/metabo10090376.

Towards Standardization of Data Normalization Strategies to Improve Urinary Metabolomics Studies by GC×GC-TOFMS

Seo Lin Nam  1 , A Paulina de la Mata  1 , Ryan P Dias  1 , James J Harynuk  1
Affiliations

Towards Standardization of Data Normalization Strategies to Improve Urinary Metabolomics Studies by GC×GC-TOFMS

Seo Lin Nam et al. Metabolites. .

Abstract

Urine is a popular biofluid for metabolomics studies due to its simple, non-invasive collection and its availability in large quantities, permitting frequent sampling, replicate analyses, and sample banking. The biggest disadvantage with using urine is that it exhibits significant variability in concentration and composition within an individual over relatively short periods of time (arising from various external factors and internal processes regulating the body's water and solute content). In treating the data from urinary metabolomics studies, one must account for the natural variability of urine concentrations to avoid erroneous data interpretation. Amongst various proposed approaches to account for broadly varying urine sample concentrations, normalization to creatinine has been widely accepted and is most commonly used. MS total useful signal (MSTUS) is another normalization method that has been recently reported for mass spectrometry (MS)-based metabolomics studies. Herein, we explored total useful peak area (TUPA), a modification of MSTUS that is applicable to GC×GC-TOFMS (and data from other separations platforms), for sample normalization in urinary metabolomics studies. Performance of TUPA was compared to the two most common normalization approaches, creatinine adjustment and Total Peak Area (TPA) normalization. Each normalized dataset was evaluated using Principal Component Analysis (PCA). The results showed that TUPA outperformed alternative normalization methods to overcome urine concentration variability. Results also conclusively demonstrate the risks in normalizing data to creatinine.

Keywords: GC×GC-TOFMS; creatinine; mass spectrometry; metabolomics; normalization; urine.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Comparison of two samples from the same subject. (A) S5M TIC (Total Ion Chromatogram), (B) S5M creatinine peak, (C) S5E TIC, (D) S5E creatinine peak.
Figure 2
Figure 2
PCA score plots with 95% confidence ellipse for (A) without normalization, (B) normalized to creatinine concentration, (C) normalized to TPA, (D) normalization to TUPA.
Figure 3
Figure 3
PCA score plots with 306 variables that were selected for TUPA modelled on the dataset (A) without normalization (B) normalization to creatinine.
See this image and copyright information in PMC

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