The Human Blood Metabolome-Transcriptome Interface

Biological systems consist of multiple organizational levels all densely interacting with each other to ensure function and flexibility of the system. simultaneous analysis of cross-sectional multi-omics data from large population studies is a powerful tool to comprehensively characterize the underlying molecular mechanisms on a physiological scale. in this study,we systematically analyzed the relationship between fasting serum metabolomics and whole blood transcriptomics data from 712 individuals of the german kora f4 cohort. correlation-based analysis identified 1,109 significant associations between 522 transcripts and 114 metabolites summarized in an integrated network,the ‘human blood metabolome-transcriptome interface’ (bmti). bidirectional causality analysis using mendelian randomization did not yield any statistically significant causal associations between transcripts and metabolites. a knowledge-based interpretation and integration with a genome-scale human metabolic reconstruction revealed systematic signatures of signaling,transport and metabolic processes,i.e. metabolic reactions mainly belonging to lipid,energy and amino acid metabolism. moreover,the construction of a network based on functional categories illustrated the cross-talk between the biological layers at a pathway level. using a transcription factor binding site enrichment analysis,this pathway cross-talk was further confirmed at a regulatory level. finally,we demonstrated how the constructed networks can be used to gain novel insights into molecular mechanisms associated to intermediate clinical traits. overall,our results demonstrate the utility of a multi-omics integrative approach to understand the molecular mechanisms underlying both normal physiology and disease. © 2015 bartel et al.