3P-32 PDF
Normalization of metabolome data for a large-scale study using mass spectrometry
Metabolomics is a promising avenue for biomarker discovery. Although the quality of metabolome, both global metabolomics (G-Met) and targeted metabolomics (T-Met) using mass spectrometry (MS), largely depends on the instrumentation, potential bottlenecks still exist at data normalization, especially for a large-scale study. Therefore, we established a normalization method of G-Met data to compensate for intra- and inter-batch differences. Then we applied our method for 1,008 plasma samples, which were obtained from our cohort study. Samples were deproteinized in a 96-well plate using an automated liquid-handling system, and conducted to UHPLC-QTOF/MS, LC-FTMS or GC-MS/MS. The variations of plate were significantly reduced using our normalization method. The normalization method should prove useful for the discovery and development of biomarkers for diseases in a large-scale study.