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The human blood metabolome-transcriptome interface.

PLoS Genet. 11:e1005274 (2015)
Verlagsversion DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
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.
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GAC Icb_Latent Causes Icb_metabo Icb_MIMOmics
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Gene-coexpression Network; Peripheral-blood; Mendelian Randomization; Cholesterol-metabolism; Cardiovascular-disease; Cell-activation; Plant Biology; B-cells; Expression; Pathway
ISSN (print) / ISBN 1553-7390
e-ISSN 1553-7404
Zeitschrift PLoS Genetics
Quellenangaben Band: 11, Heft: 6, Seiten: , Artikelnummer: e1005274 Supplement: ,
Verlag Public Library of Science (PLoS)
Verlagsort San Francisco
Begutachtungsstatus