Age and Sex Effects on Plasma Metabolite Association Networks in Healthy Subjects

• Published in: Journal of proteome research Vol. 17; no. 1; pp. 97 - 107
• Main Authors: Vignoli, Alessia, Tenori, Leonardo, Luchinat, Claudio, Saccenti, Edoardo
• Format: Journal Article
• Language: English
• Published: United States American Chemical Society 05.01.2018
• Subjects: Adolescent; Adult; Age Factors; Aged; amino acids; biochemical pathways; Blood - metabolism; blood donors; differential network analysis; Female; Healthy Volunteers; Humans; ketone bodies; Male; Metabolic Networks and Pathways; metabolism; metabolomics; Metabolomics - methods; Middle Aged; Multivariate Analysis; network inference; NMR; phenotype; precision medicine; proteome; Sex Factors; Young Adult; NMR; metabolism; network inference; differential network analysis; metabolomics
• ISSN: 1535-3893; 1535-3907; 1535-3907
• DOI: 10.1021/acs.jproteome.7b00404

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.