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dc.contributor.authorMirsaeidi M
dc.contributor.authorBanoei MM
dc.contributor.authorWinston BW
dc.contributor.authorSchraufnagel DE
dc.date.accessioned2016-12-15T20:09:30Z
dc.date.available2016-12-15T20:09:30Z
dc.date.issued2015-09
dc.identifier.bibliographicCitationMirsaeidi, M., Banoei, M. M., Winston, B. W. and Schraufnagel, D. E. Metabolomics: Applications and promise in mycobacterial disease. Annals of the American Thoracic Society. 2015. 12(9): 1278-1287. doi: 10.1513/AnnalsATS.201505-279PS.en_US
dc.identifier.issn2329-6933
dc.identifier.urihttp://hdl.handle.net/10027/21404
dc.descriptionThis is a copy of an article published in the Annals of the American Thoracic Society. © 2015 American Thoracic Society Publications. doi: 10.1513/AnnalsATS.201505-279PS.en_US
dc.description.abstractUntil recently, the study of mycobacterial diseases was trapped in culture-based technology that is more than a century old. The use of nucleic acid amplification is changing this, and powerful new technologies are on the horizon. Metabolomics, which is the study of sets of metabolites of both the bacteria and host, is being used to clarify mechanisms of disease, and can identify changes leading to better diagnosis, treatment, and prognostication of mycobacterial diseases. Metabolomic profiles are arrays of biochemical products of genes in their environment. These complex patterns are biomarkers that can allow a more complete understanding of cell function, dysfunction, and perturbation than genomics or proteomics. Metabolomics could herald sweeping advances in personalized medicine and clinical trial design, but the challenges in metabolomics are also great. Measured metabolite concentrations vary with the timing within a condition, the intrinsic biology, the instruments, and the sample preparation. Metabolism profoundly changes with age, sex, variations in gut microbial flora, and lifestyle. Validation of biomarkers is complicated by measurement accuracy, selectivity, linearity, reproducibility, robustness, and limits of detection. The statistical challenges include analysis, interpretation, and description of the vast amount of data generated. Despite these drawbacks, metabolomics provides great opportunity and the potential to understand and manage mycobacterial diseases.en_US
dc.description.sponsorshipSupported by NIH grant 5 T32 HL 82547-7 (M.M.).en_US
dc.publisherAmerican Thoracic Societyen_US
dc.subject-omicsen_US
dc.subjectmetabolomicsen_US
dc.subjectnontuberculousen_US
dc.subjecttuberculosisen_US
dc.titleMetabolomics: Applications and Promise in Mycobacterial Disease.en_US
dc.typeArticleen_US


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