The Human Blood Metabolome-Transcriptome Interface

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.

Oxidative Stress and Inflammation Induced by Environmental and Psychological Stressors: A Biomarker Perspective

“…(27)), and broader implication in pathways identified by cross-omics analysis (13,142). Additionally, a comprehensive survey focused on the role of metabolome studies in characterising oxidative studies was previously published by Liu et al (90).…”

Metabolomics in epidemiology: from metabolite concentrations to integrative reaction networks

“…Carnitine transferase also featured in a recent landmark investigation of the metabolome-transcriptome interface in the KORA F4 study 78 . This study generated a pathway-level interaction network of gene ontologies and metabolic pathways, together with transcription factor binding enrichment analysis, to identify diverse regulatory interactions, network motifs and signatures associated with HDL cholesterol and triglyceride levels 78 . The same study also replicated the co-expression and diverse metabolic relationships of the core LL module.…”

“…In addition, individual gene transcript analysis identified carnitine palmitoyl transferase A1 ( CPTA1 ) and carnitine/acylcarnitine translocase ( SLC25A20 ) associations with circulating free fatty acids 76 . Carnitine transferase also featured in a recent landmark investigation of the metabolome-transcriptome interface in the KORA F4 study 78 . This study generated a pathway-level interaction network of gene ontologies and metabolic pathways, together with transcription factor binding enrichment analysis, to identify diverse regulatory interactions, network motifs and signatures associated with HDL cholesterol and triglyceride levels 78 .…”

The Expressed Genome in Cardiovascular Diseases and Stroke: Refinement, Diagnosis, and Prediction: A Scientific Statement From the American Heart Association

“…This would include meta-analysis of results from different analytical platforms to increase sample sizes and generalizability of results and increased open data sharing. Other possible future directions for cardiovascular investigators using metabolomics are increased efforts at data integration, for example, combining metabolomics with genomics 119 or transcriptomics 120 to use different data layers for improved biological understanding of pathways leading to cardiovascular diseases.…”