MSACL 2019 EU Abstract

Evaluation of an Artificial Serum as a Surrogate Matrix for Calibration Samples for a Preeclampsia Risk Prediction Test

Anna Catharina Suhr, Leslie Walter Brown, Isabel Vega-Carrascal, Paloma Muñiz-Ortea, Robin Tuytten
Metabolomic Diagnostics, Cork, Ireland

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Anna Catharina Suhr (Presenter) Metabolomic Diagnostics

Presenter Bio: Dr Anna Suhr graduated from the University of Hamburg, Germany, with a degree in Pharmaceutical Sciences. In 2017, she completed her thesis in clinical mass spectrometry at the Institute of Laboratory Medicine at the Ludwig Maximilian University of Munich. As a Research Scientist at Metabolomic Diagnostics (Cork, Ireland), Dr Suhr is responsible for conducting product development of biomarker-based risk stratification tests by means of LC-MS/MS. This research is supported by a Marie Sklodowska-Curie Individual Fellowship (Society and Enterprise Panel).

Relevant Financial Disclosures (within past 24 months) Grant/Research Support Marie Sklodowska-Curie grant agreement No 789083 Salary Metabolomic Diagnostics Conflict mitigation NOT REQUIRED.

Introduction
A specific challenge of developing LC-MS assays for the quantification of endogenous compounds such as biomarkers, is the choice of a suitable matrix for the preparation of calibrators and QC samples. Ideally, these samples should consist of the authentic biological matrix containing an accurately known concentration of the analyte. For endogenous substances, care should be taken using the authentic biological matrix since it typically contains a baseline concentration of the analyte complicating the preparation of calibrators. Furthermore, the use of the authentic matrix may lead to lot-to-lot variation affecting the manufacturability of calibrators and QC samples. In isotope-dilution mass spectrometry, the use of a surrogate matrix which mimics the authentic biological matrix as much as possible but is analyte-free has been proposed as a means to overcome this challenge (1, 2).

Here we evaluate the suitability of a protein-free substitute for plasma or serum, SeraSub™ (CST Technologies, New York, USA), as a surrogate matrix for the preparation of calibrators for PrePsia™ (Metabolomic Diagnostics, Cork, Ireland). PrePsia™ is a screening test to predict the risk for preterm preeclampsia in early pregnancy involving the analysis of specific metabolite biomarkers employing LC-MS/MS.

Methods
Plasma samples and calibrators were prepared using Stable Isotope Labeled Internal Standards (SIL-ISTD) and protein precipitation. Target endogenous small molecules were analysed by multiplexing ESI-LC-MS/MS assay. The validity of SeraSub™ as a surrogate matrix was evaluated by assessing: (i) levels of endogenous analyte, (ii) linearity in intended calibration interval, (iii) repeatability (% CV), and (iv) matrix effect. Results were compared with BSA 5% in PBS, an established surrogate matrix.

Results
SeraSub™ showed no traces of analytes of interest, whereas for BSA this was highly dependent on the procurement source. Both SeraSub™ and BSA showed comparable linearity in the intended calibration interval (SeraSub™ r2>0.96; BSA r2>0.98; using 7 calibrator levels), and acceptable repeatability for all target metabolites (CV<15% for 6 replicates per calibrator per matrix). Spiking both surrogate matrices and plasma with the SIL-ISTDs chosen for the respective metabolites revealed differential matrix effects.

Conclusion
Our results show that SeraSub™ is a promising alternative surrogate matrix to BSA 5% in PBS for LC-MS assays. However, for commercial assay development, the choice between SeraSub™ and other possible surrogate matrices will also consider further aspects such as price, availability, lot-to-lot variability and long-term stability.

1. van de Merbel NC. TrAC 2008;27(10):924-33.
2. Hess C, Sydow K, Kueting T, et al. Forensic Sci. Int. 2018;283:150-55.

Acknowledgements
This project has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 789083.