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Automated annotation and quantification of metabolites in 1H NMR data of biological origin

2012; Springer Science+Business Media; Volume: 403; Issue: 2 Linguagem: Inglês

10.1007/s00216-012-5789-x

1618-2650

Erik Alm, Tove Slagbrand, K. Magnus Åberg, Erik Wahlström, Ingela Gustafsson, Johan Lindberg,

Traditional Chinese Medicine Studies

In 1H NMR metabolomic datasets, there are often over a thousand peaks per spectrum, many of which change position drastically between samples. Automatic alignment, annotation, and quantification of all the metabolites of interest in such datasets have not been feasible. In this work we propose a fully automated annotation and quantification procedure which requires annotation of metabolites only in a single spectrum. The reference database built from that single spectrum can be used for any number of 1H NMR datasets with a similar matrix. The procedure is based on the generalized fuzzy Hough transform (GFHT) for alignment and on Principal-components analysis (PCA) for peak selection and quantification. We show that we can establish quantities of 21 metabolites in several 1H NMR datasets and that the procedure is extendable to include any number of metabolites that can be identified in a single spectrum. The procedure speeds up the quantification of previously known metabolites and also returns a table containing the intensities and locations of all the peaks that were found and aligned but not assigned to a known metabolite. This enables both biopattern analysis of known metabolites and data mining for new potential biomarkers among the unknowns.