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Updated: Sep 15, 2025

Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry UPLC-MS
Published on: March 14, 2013
Enhancing primary newborn screening efficiency for congenital adrenal hyperplasia with LC-MS/MS/MS
Alexander Gaudl1, Laura Lehmicke1, Ronald Biemann1
1Institute of Laboratory Medicine, Clinical Chemistry, and Molecular Diagnostics, Leipzig University Medical Center, Leipzig, Germany.
Background:
Newborn screening (NBS) for congenital adrenal hyperplasia (CAH) by immunoassay (IA) suffers from analytical limitations like cross reactivity and matrix effects. Alternative tandem-mass spectrometric approaches are not suitable for high-throughput screening due to long analysis times. In this study, a rapid 1.5 min LC-MS/MS/MS (MS3) assay was applied for the first time, maturity-dependent cutoffs were determined, and the diagnostic efficiency was compared to IA for primary CAH NBS.
Methods:
1730 selected residual dried blood samples from routine NBS (gestation week 24-41) were subjected to online-SPE-LC-MS3 quantitation of 17-Hydroxyprogesterone (17-OHP). This approach utilizes two-stage fragmentation (MS3, 17-OHP m/z 329/285/123) carried out by triple quadrupole-ion trap hybrid MS. Cutoff values were calculated depending on gestational age (GA) and birthweight (BW). Diagnostic efficiency was compared to an established IA for primary CAH screening.
Results:
Intermediate precision was 10-13 % with an accuracy of 99-101 % (n = 50). Cutoff values based on GA as well as BW decreased with increasing maturity and weight of the newborns, ranging from 136 nmol/L whole blood for extreme preterm babies to 15 nmol/L whole blood for term babies. Combining LC-MS3 with GA- and BW-dependent cutoffs reduced the number of false-positive results from 731 to 15, while identifying all confirmed cases of CAH.
Conclusion:
By application of LC-MS3 and the combinatory cutoff approach, the positive predictive value for CAH-screening improved from 1% to 32%, presenting a major benefit in diagnostic efficiency over the commonly applied IA strategy. This underlines the potential of MS3 technology in clinical use.

