C/VDdb: A multi-omics expression profiling database for a knowledge-driven approach in cardiovascular disease (CVD)

Abstract

The cardiovascular disease (C/VD) database is an integrated and clustered information resource that covers multi-omic studies (microRNA, genomics, proteomics and metabolomics) of cardiovascular-related traits with special emphasis on coronary artery disease (CAD). This resource was built by mining existing literature and public databases and thereafter manual biocuration was performed. To enable integration of omic data from distinct platforms and species, a specific ontology was applied to tie together and harmonise multilevel omic studies based on gene and protein clusters (CluSO) and mapping of orthologous genes (OMAP) across species. CAD continues to be a leading cause of death in the population worldwide, and it is generally thought to be an age-related disease. However, CAD incidence rates are now known to be highly influenced by environmental factors and interactions, in addition to genetic determinants. With the complexity of CAD aetiology, there is a difficulty in research studies to elucidate general elements compared to other cardiovascular diseases. Data from 92 studies, covering 13945 molecular entries (4353 unique molecules) is described, including data descriptors for experimental setup, study design, discovery-validation sample size and associated fold-changes of the differentially expressed molecular features (p-value<0.05). A dedicated interactive web interface, equipped with a multi-parametric search engine, data export and indexing menus are provided for a user-accessible browsing experience. The main aim of this work was the development of a data repository linking clinical information and molecular differential expression in several CVD-related traits from multi-omics studies (genomics, transcriptomics, proteomics and metabolomics). As an example case of how to query and identify data sets within the database framework and concomitantly demonstrate the database utility, we queried CAD-associated studies and performed a systems-level integrative analysis.