Date Published: June 18, 2015
Publisher: Public Library of Science
Author(s): Jörg Bartel, Jan Krumsiek, Katharina Schramm, Jerzy Adamski, Christian Gieger, Christian Herder, Maren Carstensen, Annette Peters, Wolfgang Rathmann, Michael Roden, Konstantin Strauch, Karsten Suhre, Gabi Kastenmüller, Holger Prokisch, Fabian J. Theis, Michael Inouye
Abstract: 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.
Partial Text: Blood is a connective tissue, which not only ensures nutrient and oxygen supply of all organs of the human body, but also the communication between them. Among the variety of key tasks performed by blood are immunological functions through white blood cells. Due to its diverse functionality, blood is heterogeneous and complex in its composition. Besides cellular constituents, which can be roughly divided into red and white blood cells, blood mainly consists of plasma. Plasma represents the aqueous phase containing proteins, peptides, signaling molecules and steroid hormones, but also other metabolites (e.g. carbohydrates, amino acids and lipids) which are consumed and released by the organs. This unique composition of blood, agglomerating both metabolic and transcriptional variation carrying molecular signatures of system-wide processes, together with its minimally invasive accessibility, makes blood a widely used system for integrative biomedical research [1,2].
We constructed a global network model across two levels of biological information by integrating cross-sectional omics data from a large-scale population cohort. The dataset was based on circulating metabolites from plasma and transcriptional variation derived from whole blood. This analysis exploited the naturally-occurring variation caused by genetic variation, environmental and behavioral influences from a natural population over multiple layers of organization. Such an approach was recently referred to as ‘systems genetics’, enabling the systematic exploration of information flow between the different biological scales .