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Systems pharmacology–based integration of human and mouse data for drug repurposing to treat thoracic aneurysms
Jens Hansen, … , Francesco Ramirez, Ravi Iyengar
Jens Hansen, … , Francesco Ramirez, Ravi Iyengar
Published June 6, 2019
Citation Information: JCI Insight. 2019;4(11):e127652. https://doi.org/10.1172/jci.insight.127652.
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Research Article Therapeutics

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

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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 (Fbn1mgR/mgR mice) predicted that subcellular pathways associated with reduced muscle contractility are key TAA determinants that could be targeted with the GABAB receptor agonist baclofen. Systemic administration of baclofen to Fbn1mgR/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 Fbn1mgR/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.

Authors

Jens Hansen, Josephine Galatioto, Cristina I. Caescu, Pauline Arnaud, Rhodora C. Calizo, Bart Spronck, Sae-Il Murtada, Roshan Borkar, Alan Weinberg, Evren U. Azeloglu, Maria Bintanel-Morcillo, James M. Gallo, Jay D. Humphrey, Guillaume Jondeau, Catherine Boileau, Francesco Ramirez, Ravi Iyengar

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Figure 1

DEG analyses correlate defective muscle contractility with TAA progression in MFS mice and patients.

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DEG analyses correlate defective muscle contractility with TAA progressi...
Volcano plots of DEGs in (A) aortas of MFS mice sacrificed at P16 (n = 3 mutant mice and n = 3 WT mice) and (B) aortic SMCs of MFS patients aged between 22 and 32 years (n = 3 MFS patients and n = 3 non-MFS organ transplant donors). The log2 of fold change is plotted against the negative log10 of the P value; blue/green dots indicate significantly downregulated genes, and orange dots indicate significantly upregulated genes. Dots above the horizontal gray line indicate genes whose minus log10(P value) was calculated as infinity (since its P value was below the lowest number that is supported by Cuffdiff and therefore given as zero). Blue/orange or green/orange numbers give total counts of significantly down- or upregulated genes in mouse and human samples, respectively. Top-ranked (according to P values) SCPs related to muscle contractility (blue or green boxes) from GO enrichment analysis of mouse aorta (C) or human SMC (D) downregulated genes. Integration of the enrichment results into GO-SCP topology identifies 2 muscle contractility-related subnetworks (E) that have 5 SCPs in common. SPCs predicted to be downregulated in MFS aortas and human aortic SMCs are in blue and green, respectively, and intermediate SCPs are in white. Solid lines connect parents with their children processes (“is_a” or “part_of” GO relationship), dashed lines indicate regulatory relationships (“regulates” GO relationship). Regulatory SCPs are visualized as rectangles, all other SCPs as circles. Identity of network components can be found in Supplemental Table 5.

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