title: Probabilistic networks of blood metabolites in healthy subjects as indicators of latent cardiovascular risk.
abstract: The complex nature of the mechanisms behind cardiovascular diseases prevents the detection of latent early risk conditions. Network representations are ideally suited to investigate the complex interconnections between the individual components of a biological system that underlies complex diseases. Here, we investigate the patterns of correlations of an array of 29 metabolites identified and quantified in the plasma of 864 healthy blood donors and use a systems biology approach to define metabolite probabilistic networks specific for low and high latent cardiovascular risk. We adapted methods based on the likelihood of correlation and methods from information theory and combined them with resampling techniques. Our results show that plasma metabolite networks can be defined that associate with latent cardiovascular disease risk. The analysis of the networks supports our previous finding of a possible association between cardiovascular risk and impaired mitochondrial activity and highlights post-translational modifications (glycosilation and oxidation) of lipoproteins as a possible target-mechanism for early detection of latent cardiovascular risk.
authors.affiliation: Laboratory of Systems and Synthetic Biology, Wageningen University and Research Center , Dreijenplein 10, 6703 HB Wageningen, The Netherlands.
authors.forename: Edoardo
authors.initials: E
authors.lastname: Saccenti
authors.forename: Maria
authors.initials: M
authors.lastname: Suarez-Diez
authors.forename: Claudio
authors.initials: C
authors.lastname: Luchinat
authors.forename: Claudio
authors.initials: C
authors.lastname: Santucci
authors.forename: Leonardo
authors.initials: L
authors.lastname: Tenori
mesh_terms: D000328:Adult; D002318:Cardiovascular Diseases / Q000097:blood* / Q000453:epidemiology; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D011336:Probability; D012307:Risk Factors
keywords: amino acids; arginine; blood low molecular weight metabolite; cardiovascular risk; correlation networks; metabolomics; mutual information; post-translational modifications; systems biology