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Iqbal-et-al_2018_Comparison of metabolite networks from four German population-based studies.pdf 1,29MB
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1000 Titel
  • Comparison of metabolite networks from four German population-based studies
1000 Autor/in
  1. Iqbal, Khalid |
  2. Dietrich, Stefan |
  3. Wittenbecher, Clemens |
  4. Krumsiek, Jan |
  5. Kühn, Tilman |
  6. Lacruz, Maria Elena |
  7. Kluttig, Alexander |
  8. Prehn, Cornelia |
  9. Adamski, Jerzy |
  10. von Bergen, Martin |
  11. Kaaks, Rudolf |
  12. Schulze, Matthias B. |
  13. Boeing, Heiner |
  14. Floegel, Anna |
1000 Erscheinungsjahr 2018
1000 LeibnizOpen
1000 Art der Datei
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2018-07-02
1000 Erschienen in
1000 Quellenangabe
  • 47(6): 2070-2081
1000 FRL-Sammlung
1000 Copyrightjahr
  • 2018
1000 Lizenz
1000 Verlagsversion
  • http://dx.doi.org/10.1093/ije/dyy119 |
1000 Ergänzendes Material
  • https://academic.oup.com/ije/article/47/6/2070/5047840#supplementary-data |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • BACKGROUND: Metabolite networks are suggested to reflect biological pathways in health and disease. However, it is unknown whether such metabolite networks are reproducible across different populations. Therefore, the current study aimed to investigate similarity of metabolite networks in four German population-based studies. METHODS: One hundred serum metabolites were quantified in European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam (n = 2458), EPIC-Heidelberg (n = 812), KORA (Cooperative Health Research in the Augsburg Region) (n = 3029) and CARLA (Cardiovascular Disease, Living and Ageing in Halle) (n = 1427) with targeted metabolomics. In a cross-sectional analysis, Gaussian graphical models were used to construct similar networks of 100 edges each, based on partial correlations of these metabolites. The four metabolite networks of the top 100 edges were compared based on (i) common features, i.e. number of common edges, Pearson correlation (r) and hamming distance (h); and (ii) meta-analysis of the four networks. RESULTS: Among the four networks, 57 common edges and 66 common nodes (metabolites) were identified. Pairwise network comparisons showed moderate to high similarity (r = 63–0.96, h = 7–72), among the networks. Meta-analysis of the networks showed that, among the 100 edges and 89 nodes of the meta-analytic network, 57 edges and 66 metabolites were present in all the four networks, 58–76 edges and 75–89 nodes were present in at least three networks, and 63–84 edges and 76–87 edges were present in at least two networks. The meta-analytic network showed clear grouping of 10 sphingolipids, 8 lyso-phosphatidylcholines, 31 acyl-alkyl-phosphatidylcholines, 30 diacyl-phosphatidylcholines, 8 amino acids and 2 acylcarnitines. CONCLUSIONS: We found structural similarity in metabolite networks from four large studies. Using a meta-analytic network, as a new approach for combining metabolite data from different studies, closely related metabolites could be identified, for some of which the biological relationships in metabolic pathways have been previously described. They are candidates for further investigation to explore their potential role in biological processes.
1000 Sacherschließung
lokal Biological pathways
lokal Gaussian graphical models
lokal Metabolomics
lokal Reproducibility
lokal Network analysis
lokal Meta-analysis
1000 Fachgruppe
  1. Medizin |
  2. Gesundheitswesen |
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. http://orcid.org/0000-0002-3312-4259|https://frl.publisso.de/adhoc/creator/RGlldHJpY2gsIFN0ZWZhbg==|https://frl.publisso.de/adhoc/creator/V2l0dGVuYmVjaGVyLCBDbGVtZW5z|https://frl.publisso.de/adhoc/creator/S3J1bXNpZWssIEphbg==|https://frl.publisso.de/adhoc/creator/S8O8aG4sIFRpbG1hbg==|https://frl.publisso.de/adhoc/creator/TGFjcnV6LCBNYXJpYSBFbGVuYQ==|https://frl.publisso.de/adhoc/creator/S2x1dHRpZywgQWxleGFuZGVy|https://frl.publisso.de/adhoc/creator/UHJlaG4sIENvcm5lbGlh|https://frl.publisso.de/adhoc/creator/QWRhbXNraSwgSmVyenk=|https://frl.publisso.de/adhoc/creator/dm9uIEJlcmdlbiwgTWFydGlu|https://frl.publisso.de/adhoc/creator/S2Fha3MsIFJ1ZG9sZg==|https://frl.publisso.de/adhoc/creator/U2NodWx6ZSwgTWF0dGhpYXMgQi4=|https://frl.publisso.de/adhoc/creator/Qm9laW5nLCBIZWluZXI=|https://frl.publisso.de/adhoc/creator/RmxvZWdlbCwgQW5uYQ==
1000 Förderer
  1. German Federal Ministry of Education and Research (BMBF) |
  2. State of Brandenburg |
  3. German Research Foundation (DFG) |
  4. Martin Luther University of Halle-Wittenberg |
  5. Federal Employment Office |
  6. Ministry of Education and Cultural Affairs of Saxony-Anhalt |
1000 Fördernummer
  1. -
  2. -
  3. -
  4. FKZ 14/41; FKZ 16/19; FKZ 28/21
  5. -
  6. MK-CARLA-MLU-2011
1000 Förderprogramm
  1. -
  2. -
  3. -
  4. Wilhelm-Roux Programme
  5. -
  6. -
1000 Dateien
  1. Iqbal-et-al_2018_Comparison of metabolite networks from four German population-based studies
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer German Federal Ministry of Education and Research (BMBF) |
    1000 Förderprogramm -
    1000 Fördernummer -
  2. 1000 joinedFunding-child
    1000 Förderer State of Brandenburg |
    1000 Förderprogramm -
    1000 Fördernummer -
  3. 1000 joinedFunding-child
    1000 Förderer German Research Foundation (DFG) |
    1000 Förderprogramm -
    1000 Fördernummer -
  4. 1000 joinedFunding-child
    1000 Förderer Martin Luther University of Halle-Wittenberg |
    1000 Förderprogramm Wilhelm-Roux Programme
    1000 Fördernummer FKZ 14/41; FKZ 16/19; FKZ 28/21
  5. 1000 joinedFunding-child
    1000 Förderer Federal Employment Office |
    1000 Förderprogramm -
    1000 Fördernummer -
  6. 1000 joinedFunding-child
    1000 Förderer Ministry of Education and Cultural Affairs of Saxony-Anhalt |
    1000 Förderprogramm -
    1000 Fördernummer MK-CARLA-MLU-2011
1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6411703.rdf
1000 Erstellt am 2018-12-10T15:41:07.208+0100
1000 Erstellt von 266
1000 beschreibt frl:6411703
1000 Bearbeitet von 266
1000 Zuletzt bearbeitet Fri Dec 14 12:49:41 CET 2018
1000 Objekt bearb. Fri Dec 14 12:49:40 CET 2018
1000 Vgl. frl:6411703
1000 Oai Id
  1. oai:frl.publisso.de:frl:6411703 |
1000 Sichtbarkeit Metadaten public
1000 Sichtbarkeit Daten public
1000 Gegenstand von

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