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Albrecht, E. ; Waldenberger, M. ; Krumsiek, J. ; Evans, A.M.* ; Jeratsch, U. ; Breier, M. ; Adamski, J. ; Koenig, W.* ; Zeilinger, S. ; Fuchs, C. ; Klopp, N. ; Theis, F.J. ; Wichmann, H.-E. ; Suhre, K. ; Illig, T. ; Strauch, K. ; Peters, A. ; Gieger, C. ; Kastenmüller, G. ; Döring, A. ; Meisinger, C.

Metabolite profiling reveals new insights into the regulation of serum urate in humans.

Metabolomics 10, 141-151 (2014)
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Serum urate, the final breakdown product of purine metabolism, is causally involved in the pathogenesis of gout, and implicated in cardiovascular disease and type 2 diabetes. Serum urate levels highly differ between men and women; however the underlying biological processes in its regulation are still not completely understood and are assumed to result from a complex interplay between genetic, environmental and lifestyle factors. In order to describe the metabolic vicinity of serum urate, we analyzed 355 metabolites in 1,764 individuals of the population-based KORA F4 study and constructed a metabolite network around serum urate using Gaussian Graphical Modeling in a hypothesis-free approach. We subsequently investigated the effect of sex and urate lowering medication on all 38 metabolites assigned to the network. Within the resulting network three main clusters could be detected around urate, including the well-known pathway of purine metabolism, as well as several dipeptides, a group of essential amino acids, and a group of steroids. Of the 38 assigned metabolites, 25 showed strong differences between sexes. Association with uricostatic medication intake was not only confined to purine metabolism but seen for seven metabolites within the network. Our findings highlight pathways that are important in the regulation of serum urate and suggest that dipeptides, amino acids, and steroid hormones are playing a role in its regulation. The findings might have an impact on the development of specific targets in the treatment and prevention of hyperuricemia.
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GAC Icb_biostatistics Icb_metabo Icb_MIMOmics
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Allopurinol; Gaussian Graphical Modeling; Metabolite network; Pathway reconstruction; Purine metabolism; Uric acid; Genome-wide Association; False Discovery Rate; Xanthine-oxidase; Uric-acid; Cardiovascular-disease; Gout; Homocysteine; Aspartame; Caffeine; Metabolomics
Sprache englisch
Veröffentlichungsjahr 2014
Prepublished im Jahr 2013
HGF-Berichtsjahr 2013
ISSN (print) / ISBN 1573-3882
e-ISSN 1573-3890
Zeitschrift Metabolomics
Quellenangaben Band: 10, Heft: 1, Seiten: 141-151 Artikelnummer: , Supplement: ,
Verlag Springer
Verlagsort New York, NY
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Genetic Epidemiology (IGE)
Research Unit Molecular Epidemiology (AME)
Institute of Bioinformatics and Systems Biology (IBIS)
Institute of Epidemiology (EPI)
Institute of Experimental Genetics (IEG)
Molekulare Endokrinologie und Metabolismus (MEM)
Institute of Computational Biology (ICB)
POF Topic(s) 30501 - Systemic Analysis of Genetic and Environmental Factors that Impact Health
30505 - New Technologies for Biomedical Discoveries

30503 - Chronic Diseases of the Lung and Allergies
90000 - German Center for Diabetes Research
30201 - Metabolic Health
30202 - Environmental Health
30205 - Bioengineering and Digital Health
Forschungsfeld(er) Genetics and Epidemiology
Enabling and Novel Technologies
PSP-Element(e) G-504100-001
G-504200-001
G-503700-001
G-503900-002
G-503900-001
G-501900-061
G-505600-001
G-504000-006
G-503700-004
G-504090-001
G-504000-001
G-504200-002
G-503800-001
PubMed ID 24482632
DOI 10.1007/s11306-013-0565-2
WOS ID WOS:000330622400015
Scopus ID 84892483679
Erfassungsdatum 2013-07-23
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