MSACL 2025 Abstract

Development/Validation of a Quantitative Ultra-Performance Liquid Chromatography Quadrupole Time-of-Flight (UPLC-QTof) Method for Urine Organic Acid Analysis

Yi Xiao (1, 2), Michael Wakefield (3), Mari Ishak Gabra (1), Edward Leung (1, 2)
(1) Department of Pathology and Laboratory Medicine, Children’s Hospital Los Angeles, Los Angeles, CA (2) Department of Pathology, Keck School of Medicine, University of Southern California, Los Angeles, CA (3) Waters Corporation, Milford, MA

Yi Xiao, Ph.D. (Presenter) Children’s Hospital Los Angeles

Presenter Bio: Yi Xiao, Ph.D., DABCC, CLS is currently an assistant professor of Clinical Pathology at Keck School of Medicine of USC, and assistant director of the core laboratory and the special chemistry/biochemical genetics laboratory at Children’s Hospital Los Angeles. He received his PhD in Biochemistry from Vanderbilt University, and completed clinical chemistry fellowship from a ComACC-accredited fellowship program from Children’s Hospital Los Angeles.

Relevant Financial Disclosures (within past 24 months, reported on Jul 17, 2025) Other Potential Conflicts Waters Corporation / Speaker Conflict mitigation NOT REQUIRED.

INTRODUCTION:
Urine organic acid (UOA) analysis is essential for diagnosing inborn errors of metabolism (IEMs). Traditionally, UOA analysis is performed with gas chromatography-mass spectrometry (GC-MS) and requires time-consuming sample preparation procedures including liquid-liquid extraction and derivatization. There is an opportunity to perform UOA analysis with liquid chromatography-mass spectrometry (LC-MS) due to the rapid development in the past few years. We describe the development and validation of a quantitative ultra-performance liquid chromatography quadrupole time-of-flight (UPLC-QTof) method for UOA analysis with a “dilute-and-shoot” approach.

METHODS:
Urine specimens were diluted to normalize creatinine concentrations to 1 mmol/L. 20 µL of each urine specimen (diluted), calibrator, or quality control (QC) material was mixed with 400 µL of mobile phase A (0.05% formic acid in water) and a mixture of isotope-labeled internal standards. After centrifugation, 10 µL of the supernatant was analyzed using a Xevo G3 QTof mass spectrometer (Waters) with a ACQUITYTM Premier HSS T3 1.8 µm VanGuardTM FIT 2.1 x 150 mm column (Waters). Data collection was performed with negative electrospray ionization (ESI) mode using the MSE method to produce fragment ions when applicable. Repeatability, reproducibility, and carryover were assessed using the QC materials. The analytical measuring range (AMR) was assessed using synthetic urine spiked with increasing concentrations of each organic acid. Accuracy was assessed by method comparison with the UOA test performed by the traditional GC-MS method and by spike-recovery study using a pooled urine specimen. Matrix effect was evaluated with matrix dilution study. Strategies to obtain linear rather than quadratic calibration curves were also explored.

RESULTS:
An optimized UPLC method was used to enable high-resolution separation of selected UOAs (N = 29) and isomers. Total analytical time was 20 min per injection. Both linear and quadratic regressions were used to build the calibration curves. AMR and correlation coefficients of a few representative UOAs were: orotic acid (3.4 to 214.2 mmol/mol creatinine, R^2 = 0.99, linear regression); 2-methylcitric acid (4 to 189 mmol/mol creatinine, R^2 = 0.99, linear regression); 3-methylcrotonylglycine (0.3 to 18.0 mmol/mol creatinine, R^2 = 0.99, linear regression). Repeatability and reproducibility were mostly <=10% CV and no carryover was observed. Spike-recovery study demonstrated recoveries between 80% and 120%, and method comparison study demonstrated no discrepancies.

CONCLUSION:
We have developed and validated a novel UPLC-QTof method for UOA analysis to support the diagnosis of IEMs with acceptable analytical and clinical performances. Compared with the traditional GC-MS method, the UPLC-QTof method requires a very small specimen volume and does not require laborious and time-consuming sample preparation steps. Continued optimization of the method will be pursued to measure more UOAs to support the diagnosis of a broader range of IEMs.