Mass Spectrometry: A Guide For The Clinician (original) (raw)
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The widespread availability, suitability, and high sensitivity of chromatography-mass spectrometry for chemical profiling analysis of multi-component biosamples are demonstrated by the comprehensive analysis of metabolites in all kind of biofluids or tissue and cell extracts. This review provides an overview of current chromatographic-mass spectrometric metabonomic methods and applications. The focus is on the description of global metabolic profiling techniques as well as on additional important aspects of metabonomics research such as sample pretreatment and information mining methods including strategies for the identification of potential biomarkers.
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Metabolomics has the capability of providing predisposition, diagnostic, prognostic, and therapeutic biomarker profiles of individual patients, since a large number of metabolites can be measured in an unbiased manner from biological samples. In this setting, 1H-Nuclear Magnetic Resonance (NMR) spectroscopy of biofluids such as plasma, urine, and fecal water offers the opportunity to identify patterns of biomarker changes that reflects the physiological or pathological status of an individual patient.In this chapter, we show as a metabolomics study can be used to diagnose a disease, classifying patients as healthy or as pathological taking into account individual variability.
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The development and use of HPLC-MS for the study of metabonomics is reviewed. To date the technique has been applied to the analysis of urine samples obtained from studies in rodents in investigations of physiological variation (e.g., factors such as strain, gender, diurnal variation, etc.) and toxicity. Examples are provided of the use of conventional HPLC, capillary methods and the recently introduced highresolution systems based on a combination of high pressure and small particle size ("UPLC"). Comparison is also made of the use of 1 H NMR spectroscopy and HPLC-MS for the analysis of biofluid samples and the advantages and limitations of the two approaches are assessed. Likely future developments are considered.
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Strategies such as genomics, proteomics and metabonomics are being applied with increasing frequency in the pharmaceutical industry. For each of these approaches, toxicological response can be measured by terms of deviation from control or baseline status. However, in order to accurately define drug-induced response, it is necessary to characterize the normal degree of physiological variation in the absence of stimuli. Here, 1 H NMR spectroscopic-based analyses of the metabolic composition of urine in experimental animals under various normal physiological conditions are reviewed. In particular, the effects of inter-animal and diurnal variation, gender, age, diet, species, strain, hormonal status and stress on the biochemical composition of urine are explored. Pattern recognition methods facilitate the comparison of urine NMR spectra over a given time-course, enabling the establishment of changes in profile and highlighting the dynamic metabolic status of an organism. Thus metabonomic approaches based on information-rich spectroscopic data sets can be used to evaluate normal physiological variation and for investigation of drug safety issues.
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Overview An optimized Waters exact mass LC/MS System with a dedicated MassLynx 4.0 Software Application Manager has been developed to facilitate the rapid metabonomic analysis of biological fluids. This system is of particular utility in the pharmaceutical industry for the analysis of clinical trial or safety assessment samples, typically urine or plasma. The system and Applications Manager provide a complete solution to facilitate the collection and statistical analysis of bioanalytical data. By employing exact mass and MS/MS analysis the facile identification of putative endogenous biomarkers is accomplished. This application note shows the use of the Waters Metabonomics MS System with the MarkerLynx Application Manager for the analysis of samples resulting from a 90-day rat safety tolerability study.