PuSH - Publikationsserver des Helmholtz Zentrums München: Gender-specific pathway differences in the human serum metabolome.

Informationen

Hinweise zu Qualitätskriterien von Zeitschriften

Open-Access-Richtlinie der Helmholtz-Gemeinschaft 2016

CC Licencences

Metriken für Publikationen

Navigation

Startseite

English

EVA: Veröffentlichen

Neuer EVA Antrag

Recherche

Erweiterte Suche

Durchblättern nach ...

... HMGU-Autoren/Konsortien

... Organisationsstruktur

... Zeitschriften

... Publikationstypen

... Forschungsdaten

... Arbeitsgruppen

... Erscheinungsjahr

Publikationen im Überblick

Statistik

HGF Fortschrittsbericht

OA Publikationen

Eintragen

Neue Publikation eintragen

Neue Publikation holen aus...

...EVA

Fehlende Publikation melden

Highlights

Suche

Hilfe & Kontakt

Ansprechpartner

Hilfe

Datenschutz

Helmholtz Open Science

Bibliometrische Indikatoren

SHERPA/RoMEO

DOAJ

Export:

Text

Endnote (RIS) BIB

BibTeX

Krumsiek, J. ; Mittelstraß, K. ; Do, K.T. ; Stückler, F. ; Ried, J.S. ; Adamski, J. ; Peters, A. ; Illig, T.* ; Kronenberg, F.* ; Friedrich, N.* ; Nauck, M.* ; Pietzner, M.* ; Mook-Kanamori, D.O.* ; Suhre, K. ; Gieger, C. ; Grallert, H. ; Theis, F.J. ; Kastenmüller, G.

Gender-specific pathway differences in the human serum metabolome.

Metabolomics 11, 1815-1833 (2015)

Verlagsversion

DOI

PMC

	Open Access Hybrid

Abstract
Metriken
Zusatzinfos

The susceptibility for various diseases as well as the response to treatments differ considerably between men and women. As a basis for a gender-specific personalized healthcare, an extensive characterization of the molecular differences between the two genders is required. In the present study, we conducted a large-scale metabolomics analysis of 507 metabolic markers measured in serum of 1756 participants from the German KORA F4 study (903 females and 853 males). One-third of the metabolites show significant differences between males and females. A pathway analysis revealed strong differences in steroid metabolism, fatty acids and further lipids, a large fraction of amino acids, oxidative phosphorylation, purine metabolism and gamma-glutamyl dipeptides. We then extended this analysis by a network-based clustering approach. Metabolite interactions were estimated using Gaussian graphical models to get an unbiased, fully data-driven metabolic network representation. This approach is not limited to possibly arbitrary pathway boundaries and can even include poorly or uncharacterized metabolites. The network analysis revealed several strongly gender-regulated submodules across different pathways. Finally, a gender-stratified genome-wide association study was performed to determine whether the observed gender differences are caused by dimorphisms in the effects of genetic polymorphisms on the metabolome. With only a single genome-wide significant hit, our results suggest that this scenario is not the case. In summary, we report an extensive characterization and interpretation of gender-specific differences of the human serum metabolome, providing a broad basis for future analyses.

Impact Factor

Scopus SNIP

Web of Science
Times Cited

Scopus
Cited By

Altmetric

3.855

1.113

104

113