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Automated pathway a...
Automated pathway and reaction prediction facilitates in silico identification of unknown metabolites in human cohort studies
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- Quell, Jan D. (författare)
- Technical University of Munich,Helmholtz Zentrum München
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- Römisch-Margl, Werner (författare)
- Helmholtz Zentrum München
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- Colombo, Marco (författare)
- University of Edinburgh
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- Krumsiek, Jan (författare)
- Helmholtz Zentrum München
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- Evans, Anne M. (författare)
- Metabolon Inc.
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- Mohney, Robert (författare)
- Metabolon Inc.
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- Salomaa, Veikko (författare)
- Finnish National Institute for Health and Welfare
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- De Faire, Ulf (författare)
- Karolinska Institutet,Karolinska Institute
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- Groop, Leif C. (författare)
- Lund University,Lunds universitet,Translationell Muskel Forskning,Forskargrupper vid Lunds universitet,Translational Muscle Research,Lund University Research Groups
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- Agakov, Felix (författare)
- Pharmatics Limited
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- Looker, Helen C. (författare)
- University of Dundee
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- McKeigue, Paul M. (författare)
- University of Edinburgh
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- Colhoun, Helen M. (författare)
- University of Dundee
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- Kastenmüller, Gabi (författare)
- Helmholtz Zentrum München
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(creator_code:org_t)
- Elsevier BV, 2017
- 2017
- Engelska.
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Ingår i: Journal of Chromatography B: Analytical Technologies in the Biomedical and Life Sciences. - : Elsevier BV. - 1570-0232 .- 1873-376X. ; 1071, s. 58-67
- Relaterad länk:
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http://dx.doi.org/10...
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https://doi.org/10.1...
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http://kipublication...
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Abstract
Ämnesord
Stäng
- Identification of metabolites in non-targeted metabolomics continues to be a bottleneck in metabolomics studies in large human cohorts. Unidentified metabolites frequently emerge in the results of association studies linking metabolite levels to, for example, clinical phenotypes. For further analyses these unknown metabolites must be identified. Current approaches utilize chemical information, such as spectral details and fragmentation characteristics to determine components of unknown metabolites. Here, we propose a systems biology model exploiting the internal correlation structure of metabolite levels in combination with existing biochemical and genetic information to characterize properties of unknown molecules.Levels of 758 metabolites (439 known, 319 unknown) in human blood samples of 2279 subjects were measured using a non-targeted metabolomics platform (LC-MS and GC-MS). We reconstructed the structure of biochemical pathways that are imprinted in these metabolomics data by building an empirical network model based on 1040 significant partial correlations between metabolites. We further added associations of these metabolites to 134 genes from genome-wide association studies as well as reactions and functional relations to genes from the public database Recon 2 to the network model. From the local neighborhood in the network, we were able to predict the pathway annotation of 180 unknown metabolites. Furthermore, we classified 100 pairs of known and unknown and 45 pairs of unknown metabolites to 21 types of reactions based on their mass differences. As a proof of concept, we then looked further into the special case of predicted dehydrogenation reactions leading us to the selection of 39 candidate molecules for 5 unknown metabolites. Finally, we could verify 2 of those candidates by applying LC-MS analyses of commercially available candidate substances. The formerly unknown metabolites X-13891 and X-13069 were shown to be 2-dodecendioic acid and 9-tetradecenoic acid, respectively.Our data-driven approach based on measured metabolite levels and genetic associations as well as information from public resources can be used alone or together with methods utilizing spectral patterns as a complementary, automated and powerful method to characterize unknown metabolites.
Ämnesord
- MEDICIN OCH HÄLSOVETENSKAP -- Medicinska och farmaceutiska grundvetenskaper -- Cell- och molekylärbiologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Basic Medicine -- Cell and Molecular Biology (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Medicinteknik -- Medicinsk laboratorie- och mätteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Medical Engineering -- Medical Laboratory and Measurements Technologies (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Bioinformatik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Bioinformatics (hsv//eng)
- NATURVETENSKAP -- Kemi -- Analytisk kemi (hsv//swe)
- NATURAL SCIENCES -- Chemical Sciences -- Analytical Chemistry (hsv//eng)
Nyckelord
- Biochemical pathway prediction
- Metabolic network reconstruction
- Metabolite identification
- Non-targeted metabolomics
- Reaction prediction
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- art (ämneskategori)
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Till lärosätets databas
- Av författaren/redakt...
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Quell, Jan D.
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Römisch-Margl, W ...
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Colombo, Marco
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Krumsiek, Jan
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Evans, Anne M.
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Mohney, Robert
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visa fler...
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Salomaa, Veikko
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De Faire, Ulf
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Groop, Leif C.
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Agakov, Felix
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Looker, Helen C.
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McKeigue, Paul M ...
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Colhoun, Helen M ...
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Kastenmüller, Ga ...
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visa färre...
- Om ämnet
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- MEDICIN OCH HÄLSOVETENSKAP
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MEDICIN OCH HÄLS ...
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och Medicinska och f ...
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och Cell och molekyl ...
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- TEKNIK OCH TEKNOLOGIER
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TEKNIK OCH TEKNO ...
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och Medicinteknik
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och Medicinsk labora ...
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- NATURVETENSKAP
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NATURVETENSKAP
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och Data och informa ...
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och Bioinformatik
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- NATURVETENSKAP
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NATURVETENSKAP
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och Kemi
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och Analytisk kemi
- Artiklar i publikationen
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Journal of Chrom ...
- Av lärosätet
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Lunds universitet
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Karolinska Institutet