Related Experiment Video
Updated: Aug 9, 2026
Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS)
Published on: March 14, 2013
Comparative profiling of amino acids in plasma and serum across children and adults using LC-MS/MS and its
Yanhui Ma1, Yi Liu1, Yuchan Huangfu1
1Department of Laboratory Medicine, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Objective:
Circulating amino acids (AAs) are important biomarkers of nutritional status, metabolic homeostasis, and disease related physiological changes. However, the influence of specimen type and age on AA measurements remains incompletely understood. This study aimed to establish a robust liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for quantifying 29 amino acids (AAs), compare serum and plasma matrices, and investigate age related variations in healthy populations.
Methods:
In a cross-sectional study, a total of 231 healthy adults (≥18 years) and 140 children (<18 years) were recruited from the Shanghai area with a subgroup of 26 adults providing paired serum and plasma samples. Twenty-nine AA quantification was performed using LC-MS/MS with 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate (AQC) derivatization. Method validation followed Clinical and Laboratory Standards Institute (CLSI) guidelines for linearity, lower limit of quantitation (LLOQ), precision, accuracy, carryover, and stability.
Results:
The assay demonstrated excellent linearity (R 2 > 0.99), precision (CV < 15%), and accuracy (bias < 10%) with minimal carryover and acceptable LLOQs for all 29 AAs. Matrix differences and correlations were evaluated using the paired samples, while age related AA profiles were assessed in largely independent serum and plasma cohorts of pediatric and adult. Serum and plasma concentrations correlated well for most AA. However, significant matrix dependent differences were observed for several amino acids, including GABA, Ser, Tau, Sar, and Asp (R 2 < 0.5). Age related analysis revealed that most essential AAs (Leu, Ile, Trp, Phe, His, Tyr) exhibited higher median concentrations in children compared to adults in serum. Conversely, lysine and threonine were significantly higher in adult serum. In plasma, age related differences were less pronounced for essential AAs but consistent for specific non-essential AAs. Bubble plot showed Cit, Arg, and Gln were positively associated with age, while GABA was negatively associated with age.
Conclusion:
The validated LC-MS/MS platform provides a reliable platform for nutritional biomarker research. Matrix selection and age are critical factors in AA interpretation, offering valuable insights for clinical diagnostics and translational metabolomics research.
