Vogl, Franziska C. and Mehrl, Sebastian and Heizinger, Leonhard and Schlecht, Inga and Zacharias, Helena U. and Ellmann, Lisa and Nuernberger, Nadine and Gronwald, Wolfram and Leitzmann, Michael F. and Rossert, Jerome and Eckardt, Kai-Uwe and Dettmer, Katja and Oefner, Peter J. (2016) Evaluation of dilution and normalization strategies to correct for urinary output in HPLC-HRTOFMS metabolomics. ANALYTICAL AND BIOANALYTICAL CHEMISTRY, 408 (29). pp. 8483-8493. ISSN 1618-2642, 1618-2650
Full text not available from this repository. (Request a copy)Abstract
Reliable identification of features distinguishing biological groups of interest in urinary metabolite fingerprints requires the control of total metabolite abundance, which may vary significantly as the kidneys adjust the excretion of water and solutes to meet the homeostatic needs of the body. Failure to account for such variation may lead to misclassification and accumulation of missing data in case of less concentrated urine specimens. Here, different pre- and post-acquisition methods of normalization were compared systematically for their ability to recover features from liquid chromatography-mass spectrometry metabolite fingerprints of urine that allow distinction between patients with chronic kidney disease and healthy controls. Methods of normalization that were employed prior to analysis included dilution of urine specimens to either a fixed creatinine concentration or osmolality value. Post-acquisition normalization methods applied to chromatograms of 1:4 diluted urine specimens comprised normalization to creatinine, osmolality, and sum of all integrals. Dilution of urine specimens to a fixed creatinine concentration resulted not only in the least number of missing values, but it was also the only method allowing the unambiguous classification of urine specimens from healthy and diseased individuals. The robustness of classification could be confirmed for two independent patient cohorts of chronic kidney disease patients and yielded a shared set of 49 discriminant metabolite features.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | CHRONIC KIDNEY-DISEASE; CREATININE; DATABASE; POPULATION; PACKAGE; MS; Metabolic fingerprinting; LC-MS; Urine; Creatinine; Osmolality; Normalization |
| Subjects: | 600 Technology > 610 Medical sciences Medicine |
| Divisions: | Medicine > Institut für Funktionelle Genomik > Lehrstuhl für Funktionelle Genomik (Prof. Oefner) Medicine > Institut für Epidemiologie und Präventivmedizin |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 12 Apr 2019 12:25 |
| Last Modified: | 12 Apr 2019 12:25 |
| URI: | https://pred.uni-regensburg.de/id/eprint/4010 |
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