Supervised development of an integrative multi-omics molecular model in CAD.

Coronary artery disease (CAD) multi-omics data sets retrieved from C/VD regarding molecular entity type, for instance metabolite (MET), proteins (PRO) and microRNA (miRNA). Molecular entities from the studies were initially ranked by meta-analysis using a vote-counting approach (frequency assessment), in which statistical scores (p-values) were combined by implementing Fisher’s method and differential expression of molecules (fold-change) were merged through a consensus approach. Following the meta-analysis, a combinatorial integration at the systems-level of all molecular entities concerning modulation of transcriptional activity via assessment of transcription factors (TF’s), post-transcriptional regulation ascertained by microRNA-gene interactions (computationally predicted and experimentally validated), protein-protein interactions (PPI’s), evaluation of metabolic flux and regulation via association of gene-enzyme-reaction-compound and over-representation analysis of gene ontology (GO) terms and KEGG pathways. Further contextualisation of the disease model was ensured via incorporation of known CAD-gene associations sourced from the DisGeNET [44] repository.