Determination of inborn errors of metabolism
Applications | 2020 | Thermo Fisher ScientificInstrumentation
The analysis of amino acids and acylcarnitines in dried blood spots is central to newborn screening programs for inborn errors of metabolism. This approach offers rapid, multiplexed detection of metabolic markers, improving early diagnosis and reducing false positives.
This study aimed to implement and validate a flow injection analysis-tandem mass spectrometry (FIA-MS/MS) method for simultaneous quantification of 13 amino acids and 13 acylcarnitines in dried blood spots. The workflow leverages a commercial kit and state-of-the-art instrumentation to meet clinical research requirements.
The described FIA-MS/MS method using a commercial kit and modern instrumentation delivers reliable, accurate quantification of amino acids and acylcarnitines in dried blood spots. It meets clinical research demands and offers a streamlined workflow for newborn screening applications.
LC/MS, LC/MS/MS, LC/QQQ
IndustriesClinical Research
ManufacturerThermo Fisher Scientific
Summary
Importance of the Topic
The analysis of amino acids and acylcarnitines in dried blood spots is central to newborn screening programs for inborn errors of metabolism. This approach offers rapid, multiplexed detection of metabolic markers, improving early diagnosis and reducing false positives.
Objectives and Overview
This study aimed to implement and validate a flow injection analysis-tandem mass spectrometry (FIA-MS/MS) method for simultaneous quantification of 13 amino acids and 13 acylcarnitines in dried blood spots. The workflow leverages a commercial kit and state-of-the-art instrumentation to meet clinical research requirements.
Used Instrumentation
- Thermo Scientific Vanquish Flex Binary UHPLC system (Flow Injection Analysis mode)
- Thermo Scientific TSQ Fortis triple-stage quadrupole mass spectrometer with heated electrospray ionization (HESI)
- Chromsystems MassChrom LC-MS/MS Complete Kit for Amino Acids and Acylcarnitines in DBS
- TraceFinder 4.1 software for data acquisition and processing
Methodology
- Sample Preparation:
3.2 mm DBS punches were extracted with 100 µL of reagent containing isotopically labeled internal standards. Samples were shaken at 600 rpm for 20 min and transferred for analysis. - Flow Injection Analysis:
10 µL of extract injected with a constant flow of 0.09 mL/min, total run time 1.5 min, mobile phases supplied by kit. - Mass Spectrometry:
Operated in positive mode with SRM transitions for each analyte. Key source settings included vaporizer at 150 °C, capillary at 300 °C, and spray voltage of 3500 V.
Key Results and Discussion
- Precision:
Intra-assay CVs below 9% and inter-assay CVs below 12.5% for most analytes; C5DC exhibited slightly higher variability (up to 17.7%). - Accuracy:
Bias for all analytes ranged between -12.8% and 11.8%, meeting kit specifications. - Sensitivity and selectivity were ensured by optimized SRM transitions and isotopic internal calibration.
Benefits and Practical Applications
- Rapid screening workflow compatible with high-throughput newborn screening laboratories.
- Single-injection multiplex analysis reduces sample consumption and preparation time.
- Robust performance supports reliable clinical research in metabolic disorders.
Future Trends and Applications
- Integration with more advanced chromatographic techniques for improved isomer separation.
- Expansion of analyte panels to include additional biomarkers for comprehensive metabolic profiling.
- Automation of sample handling to further increase throughput and reproducibility.
Conclusion
The described FIA-MS/MS method using a commercial kit and modern instrumentation delivers reliable, accurate quantification of amino acids and acylcarnitines in dried blood spots. It meets clinical research demands and offers a streamlined workflow for newborn screening applications.
References
- Lemonde H. Pediatr Child Health. 2014;25:103–107.
- Marca G. J Pharm Biomed Anal. 2014;101:174–182.
- Lund AM. Mol Genet Metab. 2012;107:281–293.
- Sandlers Y. Transl Res. 2017;189:65–75.
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