B-180 A Component Equation Approach to Resolving Calibration Curve Nonlinearity When Using Stable Isotope-Labeled Internal Standards for Quantifying Amino Acids With Mass Spectrometry

Abstract

Abstract Background Stable isotope-labeled internal standards (SIL-IS) have been widely used with mass spectrometry to accurately quantify analytes. However, over an extended dynamic range, calibration curves calculated with the relative ratio of analytes to their corresponding SIL-IS are typically nonlinear. This makes accurate estimation of sample concentration difficult, especially at lower concentrations. Highly multiplexed clinical mass spectrometry assays routinely face this challenge. The component equation assumes interaction between an analyte and its SIL-IS causes the nonlinearity. Modeling this resulted in a linear calibration curve and high accuracy across the dynamic range. We compared the component equation with other calibration methods to quantify amino acids. Methods A total of 47 compounds were serially diluted and added with extraction solution containing a SIL-IS mixture to prepare 7 levels of calibrators. Calibrators were chromatographically separated using a Sciex ExionLC system with an Imtakt Intrada Amino Acid column and injected into a Sciex Citrine triple-quadrupole mass spectrometer. Seven different fitting methods were compared for calibration of each amino acid: non-weighted linear, quadratic and cubic models, linear models with 1/X and 1/X2 weighting, Padé[1,1] approximation, and component equation. Results Results for an example amino acid, tyrosine, are shown in the table below. Most models yield high accuracy at high concentrations, however, all models recorded significantly higher bias for the lowest calibrator than the component equation (≥55.7% vs 11.8%). The component equation outperformed all other models for mean bias (≥16.6% vs 5.9%). Similar results were obtained for the complete set of analytes. Conclusions When compared to other popular calibration methods to quantify a panel of amino acids, the component equation generated a linear curve and the greatest accuracy across all concentrations. The application of this simple equation could overcome the limitations of existing weighting and non-linear fitting approaches when using SIL-IS for quantifying analytes with mass spectrometry.