Staff Publications

Staff Publications

  • external user (warningwarning)
  • Log in as
  • language uk
  • About

    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

    We have a manual that explains all the features 

Record number 532046
Title Age and Sex Effects on Plasma Metabolite Association Networks in Healthy Subjects
Author(s) Vignoli, Alessia; Tenori, Leonardo; Luchinat, Claudio; Saccenti, Edoardo
Source Journal of Proteome Research 17 (2018)1. - ISSN 1535-3893 - p. 97 - 107.
DOI https://doi.org/10.1021/acs.jproteome.7b00404
Department(s) Systems and Synthetic Biology
VLAG
Publication type Refereed Article in a scientific journal
Publication year 2018
Keyword(s) differential network analysis - metabolism - metabolomics - network inference - NMR
Abstract In the era of precision medicine, the analysis of simple information like sex and age can increase the potential to better diagnose and treat conditions that occur more frequently in one of the two sexes, present sex-specific symptoms and outcomes, or are characteristic of a specific age group. We present here a study of the association networks constructed from an array of 22 plasma metabolites measured on a cohort of 844 healthy blood donors. Through differential network analysis we show that specific association networks can be associated with sex and age: Different connectivity patterns were observed, suggesting sex-related variability in several metabolic pathways (branched-chain amino acids, ketone bodies, and propanoate metabolism). Reduction in metabolite hub connectivity was also found to be associated with age in both sex groups. Network analysis was complemented with standard univariate and multivariate statistical analysis that revealed age- and sex-specific metabolic signatures. Our results demonstrate that the characterization of metabolite-metabolite association networks is a promising and powerful tool to investigate the human phenotype at a molecular level.
Comments
There are no comments yet. You can post the first one!
Post a comment
 
Please log in to use this service. Login as Wageningen University & Research user or guest user in upper right hand corner of this page.