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Southeast Asian J Trop Med Public Health ; 1999 ; 30 Suppl 2(): 174-80
Article in English | IMSEAR | ID: sea-35866

ABSTRACT

Gas chromatography mass spectrometry (GC/MS) is widely used in diagnosis of organic acidemias. However, GC/MS has not yet become a routine laboratory test, because of the complexity in interpretation of GC/MS data. We developed a personal computer-based system of automated metabolic profiling and disease detection for the screening of organic acidemias by GC/MS. The data were processed after the GC/MS analysis of urinary organic acids. In this system, 130 kinds of metabolites and 25 disorders of organic acids were enrolled for the search and detection, respectively. Metabolites were identified with methylene unit values (MU). target ions (Q- and C-ions) and their intensity ratios, and semiquantified by peak relative area (%) of the Q-ions to that of an internal standard. Metabolites whose values exceeded the cutoff of the control table were flagged as abnormal. The diseases or pathological condition were automatically evaluated by combination of the abnormal compounds. In this system, index metabolites were categorized into three groups. "AND, "OR" and "NO". The groups, "AND" and "OR" comprised essential and optional compounds, respectively, for the specific diagnosis. The third group, "NO", included compounds which must be absent to reach a diagnosis. We compiled data of MU values and mass spectrum of 130 kinds of index metabolites, and tested the usefulness of this system by analysis of 74 patients with 19 kinds of diseases. In all cases, at least a correct diagnosis could be found among the disease names outputted. We have successfully applied this to a pilot neonatal screening by GC/MS in our regional area, and acylglycine analysis by the stable isotope dilution method with tert-butyldimethylsilyl derivatization. With our system, many people can attend for screening programs using GC/MS.


Subject(s)
Amino Acid Metabolism, Inborn Errors/diagnosis , Amino Acids/urine , Diagnosis, Computer-Assisted , Gas Chromatography-Mass Spectrometry , Humans , Urinalysis/methods
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