Combination of injection volume calibration by creatinine and MS signals' normalization to overcome urine variability in LC-MS-based metabolomics studies.

It is essential to choose one preprocessing method for liquid chromatography-mass spectrometry (LC-MS)-based metabolomics studies of urine samples in order to overcome their variability. However, the commonly used normalization methods do not substantially reduce the high variabilities arising from differences in urine concentration, especially for signal saturation (abundant metabolites exceed the dynamic range of the instrumentation) or missing values. Herein, a simple preacquisition strategy based on differential injection volumes calibrated by creatinine (to reduce the concentration differences between the samples), combined with normalization to "total useful MS signals" or "all MS signals", is proposed to overcome urine variabilities. This strategy was first systematically compared with other popular normalization methods by application to serially diluted urine samples. Then, the method has been verified using rat urine samples of pre- and postinoculation of Walker 256 carcinoma cells. The results showed that the calibration of injection volumes based on creatinine values could effectively eliminate intragroup differences caused by variations in the concentrations of urinary metabolites, thus giving better parallelism and clustering effects. In addition, peak area normalization could further eliminate intraclass differences. Therefore, the strategy of combining peak area normalization with calibration of injection volumes of urine samples based on their creatinine values is effective for solving problems associated with urinary metabolomics.