Proof of concept for quantitative urine NMR metabolomics pipeline for large-scale epidemiology and genetics
| Autor: | Johannes Kettunen, Jaspal S. Kooner, Pauli Ohukainen, Minna Männikkö, Olga Anufrieva, Qin Wang, Michael Hill, Marjo-Riitta Järvelin, Mika Ala-Korpela, Jussi Ekholm, John C Chambers, George Davey Smith, Tuulia Tynkkynen, Jouko Vepsäläinen, Susan M. Ring, Michael V. Holmes, Matthew Goodwin, Sirkka Keinänen-Kiukaanniemi |
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| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
0301 basic medicine
medicine.medical_specialty Magnetic Resonance Spectroscopy genome-wide analyses Epidemiology multicentre Metabolite Population Urine 030204 cardiovascular system & hematology Biology Proof of Concept Study 1117 Public Health and Health Services 03 medical and health sciences chemistry.chemical_compound Metabolomics 0302 clinical medicine medicine Humans Spectral analysis education Nmr based metabolomics 030304 developmental biology Genetics open access 0303 health sciences education.field_of_study Shape fitting 0104 Statistics General Medicine urine Metabolomics data Miscellaneous Epidemiologic Studies 030104 developmental biology chemistry Fully automated serum Genome-Wide Association Study |
| Zdroj: | International Journal of Epidemiology Tynkkynen, T, Wang, Q, Ekholm, J, Anufrieva, O, Ohukainen, P, Vepsäläinen, J, Männikkö, M, Keinänen-Kiukaanniemi, S, Holmes, M V, Goodwin, M, Ring, S, Chambers, J C, Kooner, J, Järvelin, M-R, Kettunen, J, Hill, M, Davey Smith, G & Ala-Korpela, M 2019, ' Proof of concept for quantitative urine NMR metabolomics pipeline for large-scale epidemiology and genetics ', International Journal of Epidemiology, vol. 48, no. 3, pp. 978-993 . https://doi.org/10.1093/ije/dyy287, https://doi.org/10.1093/ije/dyy287 |
| ISSN: | 1464-3685 0300-5771 |
| DOI: | 10.1093/ije/dyy287 |
| Popis: | Background Quantitative molecular data from urine are rare in epidemiology and genetics. NMR spectroscopy could provide these data in high throughput, and it has already been applied in epidemiological settings to analyse urine samples. However, quantitative protocols for large-scale applications are not available. Methods We describe in detail how to prepare urine samples and perform NMR experiments to obtain quantitative metabolic information. Semi-automated quantitative line shape fitting analyses were set up for 43 metabolites and applied to data from various analytical test samples and from 1004 individuals from a population-based epidemiological cohort. Novel analyses on how urine metabolites associate with quantitative serum NMR metabolomics data (61 metabolic measures; n = 995) were performed. In addition, confirmatory genome-wide analyses of urine metabolites were conducted (n = 578). The fully automated quantitative regression-based spectral analysis is demonstrated for creatinine and glucose (n = 4548). Results Intra-assay metabolite variations were mostly Conclusion Quantitative urine metabolomics data suggest broad novelty for systems epidemiology. A roadmap for an open access methodology is provided. |
| Databáze: | OpenAIRE |
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