BACKGROUND: Gas chromatograph mass-spectrometric (GC/MS) method of analysis for urinary organic acids is used for the diagnosis of a variety of metabolic disorders. The method is time-consuming and does not allow for improvements in sample throughput. Although the sample preparation and the data processing have been improved, the long GC/MS analysis time still remains to be problematic. METHODS: The fast-GC/MS method, which utilizes a short microbore capillary GC column and fast temperature programming, was applied to the analysis for urinary organic acids. Urine samples obtained from 15 patients with 9 different disorders and 16 healthy controls were analyzed using conventional GC/MS and fast-GC/MS. RESULTS: Analysis cycle time was shortened from 1 h to 15 min. The automated data system uses retention indices determined by conventional-GC/MS for the identification of 134 organic acids. These retention indices can also be used in data obtained by fast-GC/MS. New fast-GC/MS method with the automated data system gave the same diagnostic results as conventional-GC/MS except for 1 healthy control. CONCLUSIONS: The combined system of fast-GC/MS and the automated data system will be powerful tools in clinical laboratories due to increased sample throughput and reduced analysis costs.
BACKGROUND: Gas chromatograph mass-spectrometric (GC/MS) method of analysis for urinary organic acids is used for the diagnosis of a variety of metabolic disorders. The method is time-consuming and does not allow for improvements in sample throughput. Although the sample preparation and the data processing have been improved, the long GC/MS analysis time still remains to be problematic. METHODS: The fast-GC/MS method, which utilizes a short microbore capillary GC column and fast temperature programming, was applied to the analysis for urinary organic acids. Urine samples obtained from 15 patients with 9 different disorders and 16 healthy controls were analyzed using conventional GC/MS and fast-GC/MS. RESULTS: Analysis cycle time was shortened from 1 h to 15 min. The automated data system uses retention indices determined by conventional-GC/MS for the identification of 134 organic acids. These retention indices can also be used in data obtained by fast-GC/MS. New fast-GC/MS method with the automated data system gave the same diagnostic results as conventional-GC/MS except for 1 healthy control. CONCLUSIONS: The combined system of fast-GC/MS and the automated data system will be powerful tools in clinical laboratories due to increased sample throughput and reduced analysis costs.