PuSH - Publication Server of Helmholtz Zentrum München: Plasma and serum metabolite association networks: Comparibility within and between studies using NMR and MS profiling.

Navigation

Home

Deutsch

Research

Advanced Search

Browse by ...

... Journal

... Publication Type

... Research Data

... Publication Year

Publication overview

Support & Contact

Contact persons

Help

Data protection

Suarez-Diez, M.* ; Adam, J. ; Adamski, J. ; Chasapi, S.A.* ; Luchinat, C.* ; Peters, A. ; Prehn, C. ; Santucci, C.* ; Spyridonidis, A.* ; Spyroulias, G.A.* ; Tenori, L.* ; Wang-Sattler, R. ; Saccenti, E.*

Plasma and serum metabolite association networks: Comparibility within and between studies using NMR and MS profiling.

J. Proteome Res. 16, 2547-2559 (2017)

Postprint

DOI

	Open Access Green

Abstract
Metrics
Extra information

Blood is one of the most used biofluids in metabolomics studies, and the serum and plasma fractions are routinely used as a proxy for blood itself. Here we investigated the association networks of an array of 29 metabolites identified and quantified via NMR in the plasma and serum samples of two cohorts of ∼1000 healthy blood donors each. A second study of 377 individuals was used to extract plasma and serum samples from the same individual on which a set of 122 metabolites were detected and quantified using FIA–MS/MS. Four different inference algorithms (ARANCE, CLR, CORR, and PCLRC) were used to obtain consensus networks. The plasma and serum networks obtained from different studies showed different topological properties with the serum network being more connected than the plasma network. On a global level, metabolite association networks from plasma and serum fractions obtained from the same blood sample of healthy people show similar topologies, and at a local level, some differences arise like in the case of amino acids.

Altmetric

Additional Metrics?

[➜Log in]

Edit extra informations Login

Publication type Article: Journal article

Document type Scientific Article

Corresponding Author

Keywords blood; correlations; differential network analysis; low molecular weight metabolites; mutual information; network inference; network topology; plasma; serum; Transfer-rna Synthetases; Metabolomics Data; Cardiovascular Risk; Escherichia-coli; Inference; Disease; Spectroscopy; Metabonomics; Stability; Analytes

ISSN (print) / ISBN 1535-3893

e-ISSN 1535-3907

Journal Journal of Proteome Research

Quellenangaben Volume: 16, Issue: 7, Pages: 2547-2559

Publisher American Chemical Society (ACS)

Publishing Place Washington

Non-patent literature Publications

Reviewing status Peer reviewed

Institute(s) Institute of Epidemiology II (EPI2)
Molekulare Endokrinologie und Metabolismus (MEM)