A network-based approach to identify deregulated pathways and drug effects in metabolic syndrome

Karla Misselbeck, Silvia Parolo (), Francesca Lorenzini, Valeria Savoca, Lorena Leonardelli, Pranami Bora, Melissa J. Morine, Maria Caterina Mione, Enrico Domenici () and Corrado Priami ()
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Karla Misselbeck: Centre for Computational and Systems Biology (COSBI)
Silvia Parolo: Centre for Computational and Systems Biology (COSBI)
Francesca Lorenzini: University of Trento
Valeria Savoca: University of Trento
Lorena Leonardelli: Centre for Computational and Systems Biology (COSBI)
Pranami Bora: Centre for Computational and Systems Biology (COSBI)
Melissa J. Morine: Centre for Computational and Systems Biology (COSBI)
Maria Caterina Mione: University of Trento
Enrico Domenici: Centre for Computational and Systems Biology (COSBI)
Corrado Priami: Centre for Computational and Systems Biology (COSBI)

Nature Communications, 2019, vol. 10, issue 1, 1-14

Abstract: Abstract Metabolic syndrome is a pathological condition characterized by obesity, hyperglycemia, hypertension, elevated levels of triglycerides and low levels of high-density lipoprotein cholesterol that increase cardiovascular disease risk and type 2 diabetes. Although numerous predisposing genetic risk factors have been identified, the biological mechanisms underlying this complex phenotype are not fully elucidated. Here we introduce a systems biology approach based on network analysis to investigate deregulated biological processes and subsequently identify drug repurposing candidates. A proximity score describing the interaction between drugs and pathways is defined by combining topological and functional similarities. The results of this computational framework highlight a prominent role of the immune system in metabolic syndrome and suggest a potential use of the BTK inhibitor ibrutinib as a novel pharmacological treatment. An experimental validation using a high fat diet-induced obesity model in zebrafish larvae shows the effectiveness of ibrutinib in lowering the inflammatory load due to macrophage accumulation.

Date: 2019
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DOI: 10.1038/s41467-019-13208-z

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