Metabonomic, transcriptomic, and genomic variation of a population cohort

Abstract

Comprehensive characterization of human tissues promises novel insights into the biological architecture of human diseases and traits. We assessed metabonomic, transcriptomic, and genomic variation for a large population‐based cohort from the capital region of Finland. Network analyses identified a set of highly correlated genes, the lipid–leukocyte (LL) module, as having a prominent role in over 80 serum metabolites (of 134 measures quantified), including lipoprotein subclasses, lipids, and amino acids. Concurrent association with immune response markers suggested the LL module as a possible link between inflammation, metabolism, and adiposity. Further, genomic variation was used to generate a directed network and infer LL module's largely reactive nature to metabolites. Finally, gene co‐expression in circulating leukocytes was shown to be dependent on serum metabolite concentrations, providing evidence for the hypothesis that the coherence of molecular networks themselves is conditional on environmental factors. These findings show the importance and opportunity of systematic molecular investigation of human population samples. To facilitate and encourage this investigation, the metabonomic, transcriptomic, and genomic data used in this study have been made available as a resource for the research community.

Keywords

• bioinformatics
• biological networks
• integrative genomics
• metabonomics
• otranscriptomics