Abstract

Background Sample analysis and data interpretation for urine organic acid analyses (OAA) for metabolic diseases have not evolved significantly over the last two decades. We evaluated a number of potential improvements in the technology in order to increase productivity. Increasing numbers of this very important clinical test are being ordered resulting from expanded newborn screening programs and also due to greater clinical awareness of these metabolic disorders. This has resulted in a need for faster turn around times in order to establish a rapid diagnosis and reporting of OAA findings. Methods In this study, we introduced a backflush system which removes residual high boiling point compounds quickly and at a lower oven temperature. We have also introduced deconvolution software (DRS), which provides a mathematical technique that separates overlapping mass spectra based upon peak widths of overlapping compounds and absolute mean retention times. The potential advantages of incorporating DRS into the OAA data processing include a higher match factor (MF) for library searching, elimination of incorrect peak identification, faster data review and minimum human interaction for manual peak integration. Results In this proof of principle investigation, 64 of the most commonly encountered urinary organic acids and acyl glycines that are essential for the diagnosis and clinical follow-up of inborn errors of metabolism were selected and built into a spectral library. DRS with a customized library and quantitation database was able to clearly separate co-eluting compounds including those with very similar mass spectra such as citric acid and isocitric acid. Conclusions We were able to reduce sample analytical time from 60 to 45 min using the backflush system. Deconvolution allowed us to identify common overlapping organic acids and provide more accurate quantitation.

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