Data integration and network analysis workflow for the blood metabolome-transcriptome interface (BMTI).

A: We analyzed fasting serum metabolomics and whole blood transcriptomics data from 712 samples of the KORA F4 cohort. After preprocessing and filtering, a cross-correlation matrix between 440 distinct metabolites and 16,780 unique, gene-mapped probes was calculated. The correlation matrix was transformed into a bipartite network by applying a statistical significance threshold. B: Scientific literature was screened for biological evidence for the strongest metabolite-mRNA associations. All correlating metabolite-mRNA pairs contained in the human metabolic model Recon2 were systematically evaluated with respect to their distance in the metabolic pathway network. C: Aggregated z-scores for each functional annotation were calculated. A pathway interaction network (PIN) was then constructed via cross-correlation of scores between pairs of functional annotations. D: For each metabolite contained in the BMTI, we investigated the promoter regions of associated transcripts for shared regulatory signatures. Similarly, shared regulatory signatures within and between metabolic pathways were examined. As a final step, we identified specific regulatory motifs in the BMTI. E: Both BMTI and the PIN were integrated with the results from an association analysis to the three intermediate physiological traits (HDL-C, LDL-C and TG).