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Systems pharmacology-based integration of human and mouse data for drug repurposing to treat thoracic aneurysms

Authors :
Cristina I. Caescu
Francesco Ramirez
Roshan Borkar
Jay D. Humphrey
Guillaume Jondeau
Bart Spronck
Pauline Arnaud
Evren U. Azeloglu
Jens Hansen
Alan D. Weinberg
Maria Bintanel-Morcillo
Sae-Il Murtada
Ravi Iyengar
Catherine Boileau
James M. Gallo
Rhodora Cristina Calizo
Josephine Galatioto
Source :
JCI INSIGHT, 4(11):027652. American Society for Clinical Investigation
Publication Year :
2019

Abstract

Marfan syndrome (MFS) is associated with mutations in fibrillin-1 that predispose afflicted individuals to progressive thoracic aortic aneurysm (TAA) leading to dissection and rupture of the vessel wall. Here we combined computational and experimental approaches to identify and test FDA-approved drugs that may slow or even halt aneurysm progression. Computational analyses of transcriptomic data derived from the aortas of MFS patients and MFS mice (Fbn1(mgR/mgR) mice) predicted that subcellular pathways associated with reduced muscle contractility are key TAA determinants that could be targeted with the GABA(B) receptor agonist baclofen. Systemic administration of baclofen to Fbn1(mgR/mgR) mice validated our computational prediction by mitigating arterial disease progression at the cellular and physiological levels. Interestingly, baclofen improved muscle contraction–related subcellular pathways by upregulating a different set of genes than those downregulated in the aorta of vehicle-treated Fbn1(mgR/mgR) mice. Distinct transcriptomic profiles were also associated with drug-treated MFS and wild-type mice. Thus, systems pharmacology approaches that compare patient- and mouse-derived transcriptomic data for subcellular pathway–based drug repurposing represent an effective strategy to identify potential new treatments of human diseases.

Details

Language :
English
ISSN :
23793708
Database :
OpenAIRE
Journal :
JCI INSIGHT, 4(11):027652. American Society for Clinical Investigation
Accession number :
edsair.doi.dedup.....dcc854adf7edabc91dc15990a05ecbe9