Abstract
BackgroundNumerous inflammation-related pathways have been shown to play important roles in atherogenesis. Rapid and efficient assessment of the relative influence of each of those pathways is a challenge in the era of “omics” data generation. The aim of the present work was to develop a network model of inflammation-related molecular pathways underlying vascular disease to assess the degree of translatability of preclinical molecular data to the human clinical setting.MethodsWe constructed and evaluated the Vascular Inflammatory Processes Network (V-IPN), a model representing a collection of vascular processes modulated by inflammatory stimuli that lead to the development of atherosclerosis.ResultsUtilizing the V-IPN as a platform for biological discovery, we have identified key vascular processes and mechanisms captured by gene expression profiling data from four independent datasets from human endothelial cells (ECs) and human and murine intact vessels. Primary ECs in culture from multiple donors revealed a richer mapping of mechanisms identified by the V-IPN compared to an immortalized EC line. Furthermore, an evaluation of gene expression datasets from aortas of old ApoE-/- mice (78 weeks) and human coronary arteries with advanced atherosclerotic lesions identified significant commonalities in the two species, as well as several mechanisms specific to human arteries that are consistent with the development of unstable atherosclerotic plaques.ConclusionsWe have generated a new biological network model of atherogenic processes that demonstrates the power of network analysis to advance integrative, systems biology-based knowledge of cross-species translatability, plaque development and potential mechanisms leading to plaque instability.
Highlights
Numerous inflammation-related pathways have been shown to play important roles in atherogenesis
Current challenges in the analysis of transcriptomics datasets based on functional annotation or pathway maps (e.g. Gene ontology, KEGG) [10,11] reside on the forward reasoning assumption that differential expression of genes is directly related to differential protein activity
Vascular Inflammatory Processes Network (V-IPN) construction and biological integration: description of modular framework and boundaries To capture the diverse array of biological processes involved in the development of atherosclerotic plaques, the V-IPN network model was constructed using a modular approach that represents key processes related to vascular inflammation and atherogenesis
Summary
Numerous inflammation-related pathways have been shown to play important roles in atherogenesis. The aim of the present work was to develop a network model of inflammation-related molecular pathways underlying vascular disease to assess the degree of translatability of preclinical molecular data to the human clinical setting. Current challenges in the analysis of transcriptomics datasets based on functional annotation or pathway maps (e.g. Gene ontology, KEGG) [10,11] reside on the forward reasoning assumption that differential expression of genes is directly related to differential protein activity. Subsequent mapping of HYPs to network models that recreate the biology of interest (e.g., atherogenesis) offers a mechanistically integrated evaluation and interpretation of gene expression data captured in large datasets. Unlike direct network mapping of gene expression data, a network-based HYP evaluation approach allows translating experimentally-determined molecular changes as measurable network perturbations that can be compared between different datasets
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