Journal
METABOLOMICS
Volume 18, Issue 8, Pages -Publisher
SPRINGER
DOI: 10.1007/s11306-022-01916-5
Keywords
Acylcarnitines; Serum; SPE-LC-MS; MS; Data-independent acquisition; Data-dependent acquisition; Multiple reaction monitoring
Categories
Funding
- CRUE-CSIC agreement
- Springer Nature
- Spanish Ministerio of Science and Innovation [PID2019-111373RBI00]
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This study presents a strategy for identification and quantitative determination of acylcarnitines, metabolites involved in fatty acid beta-oxidation and organic acid metabolism, for evaluating metabolic disorders. The method combines data-independent acquisition and data-dependent acquisition techniques, achieving high accuracy and precision. The study also reveals significant differences in the acylcarnitines profiles between obese and non-obese individuals.
Acylcarnitines (ACs) are metabolites involved in fatty acid beta-oxidation and organic acid metabolism. Metabolic disorders associated to these two processes can be evaluated by determining the complete profile of ACs. In this research, we present an overall strategy for identification, confirmation, and quantitative determination of acylcarnitines in human serum. By this strategy we identified the presence of 47 ACs from C2 to C24 with detection of the unsaturation degree by application of a data-independent acquisition (DIA) liquid chromatography-tandem mass spectrometry (LC-MS/MS) method. Complementary, quantitative determination of ACs is based on a high-throughput and fully automated method consisting of solid-phase extraction on-line coupled to LC-MS/MS in data-dependent acquisition (DDA) to improve analytical features avoiding the errors associated to sample processing. Quantitation limits were at pg mL(-1) level, the intra-day and between-day variability were below 15-20%, respectively; and the accuracy, expressed as bias, was always within +/- 25%. The proposed method was tested with 40 human volunteers to determine the relative concentration of ACs in serum and identify predominant forms. Significant differences were detected by comparing the ACs profile of obese versus non-obese individuals.
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