The purpose of our work was to investigate on the potentials of full scan high resolution mass spectrometry (HRMS) with an Orbitrap instrument for the metabolic profiling of human serum and the detection of biomarkers indicative of disease. We thus compared the untargeted metabolic profiles obtained by liquid chromatography (LC)-HRMS in serum in a case-control study employing a small set (20 cases and 20 controls) of samples obtained from a intrauterine growth restriction (IUGR) investigation. A large number of features (ionic species with specific retention times) were shown to differ between the two classes of samples. From their accurate mass measurements, elemental compositions of the difference molecules could be calculated, and chemical identification of those metabolites is now in process, by comparison with available data bases. Further validation study are required employing a larger number of samples. Conclusions: The results obtained by an untargeted metabolomic approach in serum samples from an IUGR case control study put in evidence that high resolution mass spectrometry and bioinformatic data analysis can be efficiently employed to discover differences between a “normal” and a “pathological” status.

Searching for biomarkers of disease through anuntargeted metabonomic approach

FAVRETTO, DONATA;COSMI, ERICH;VOGLIARDI, SUSANNA;C. Terranova;RAGAZZI, EUGENIO;FERRARA, SANTO
2009

Abstract

The purpose of our work was to investigate on the potentials of full scan high resolution mass spectrometry (HRMS) with an Orbitrap instrument for the metabolic profiling of human serum and the detection of biomarkers indicative of disease. We thus compared the untargeted metabolic profiles obtained by liquid chromatography (LC)-HRMS in serum in a case-control study employing a small set (20 cases and 20 controls) of samples obtained from a intrauterine growth restriction (IUGR) investigation. A large number of features (ionic species with specific retention times) were shown to differ between the two classes of samples. From their accurate mass measurements, elemental compositions of the difference molecules could be calculated, and chemical identification of those metabolites is now in process, by comparison with available data bases. Further validation study are required employing a larger number of samples. Conclusions: The results obtained by an untargeted metabolomic approach in serum samples from an IUGR case control study put in evidence that high resolution mass spectrometry and bioinformatic data analysis can be efficiently employed to discover differences between a “normal” and a “pathological” status.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11577/2483539
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