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Proof of concept for quantitative urine NMR metabolomics pipeline for large-scale epidemiology and genetics

Authors :
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
Source :
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
Publication Year :
2019
Publisher :
Oxford University Press, 2019.

Abstract

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.

Details

Language :
English
ISSN :
14643685 and 03005771
Volume :
48
Issue :
3
Database :
OpenAIRE
Journal :
International Journal of Epidemiology
Accession number :
edsair.doi.dedup.....9fcd11577d1403e100e0809fafa20735