The Human Blood Metabolome-Transcriptome Interface

PLoS Genet. 2015 Jun 18;11(6):e1005274. doi: 10.1371/journal.pgen.1005274. eCollection 2015 Jun.


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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Fasting / blood*
  • Female
  • Gene Regulatory Networks*
  • Genome, Human
  • Humans
  • Male
  • Metabolome*
  • Middle Aged
  • Transcriptome*

Grant support

JK is supported by a grant from the Helmholtz Postdoctoral Programme, “Initiative and Networking Fund”. CG is supported by a grant of the RFBR (Russian Foundation for Basic Research)-Helmholtz Joint Research Group. KSu is supported by Biomedical Research Program funds at Weill Cornell Medical College in Qatar, a program funded by the Qatar Foundation. The KORA Augsburg studies were financed by the Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany and supported by grants from the German Federal Ministry of Education and Research (BMBF). Part of this work was financed by the German National Genome Research Network (NGFN). In addition, this work was partly supported within the Munich Center of Health Sciences (MC Health) as part of LMUinnovativ. Moreover, the research leading to these results has received funding from the European Union's Seventh Framework Programme [FP7-Health-F5-2012] under grant agreement n° 305280 (MIMOmics) and grant agreement n° 277984, (TIRCON). Further support for this study was obtained by a grant from the German Federal Ministry of Education and Research [BMBF Förderkennzeichen 01GI0922] to D.Z.D (German Center for Diabetes Research DZD e.V.). Parts of this work was funded by the European Research Council (starting grant 'LatentCauses'), by the Ministry of Science and Research of the State of North Rhine-Westphalia (MIWF NRW) and the German Federal Ministry of Health (BMG). Additional support was obtained from the German Federal Ministry of Education and Research (BMBF; National Genome Network NGFNplus Atherogenomics, 01GS0834). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.