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Computational discovery of therapeutic candidates for preventing preterm birth
Brian L. Le, … , David K. Stevenson, Marina Sirota
Brian L. Le, … , David K. Stevenson, Marina Sirota
Published February 13, 2020
Citation Information: JCI Insight. 2020;5(3):e133761. https://doi.org/10.1172/jci.insight.133761.
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Research Article Reproductive biology Therapeutics

Computational discovery of therapeutic candidates for preventing preterm birth

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Abstract

Few therapeutic methods exist for preventing preterm birth (PTB), or delivery before completing 37 weeks of gestation. In the US, progesterone (P4) supplementation is the only FDA-approved drug for use in preventing recurrent spontaneous PTB. However, P4 has limited effectiveness, working in only approximately one-third of cases. Computational drug repositioning leverages data on existing drugs to discover novel therapeutic uses. We used a rank-based pattern-matching strategy to compare the differential gene expression signature for PTB to differential gene expression drug profiles in the Connectivity Map database and assigned a reversal score to each PTB-drug pair. Eighty-three drugs, including P4, had significantly reversed differential gene expression compared with that found for PTB. Many of these compounds have been evaluated in the context of pregnancy, with 13 belonging to pregnancy category A or B — indicating no known risk in human pregnancy. We focused our validation efforts on lansoprazole, a proton-pump inhibitor, which has a strong reversal score and a good safety profile. We tested lansoprazole in an animal inflammation model using LPS, which showed a significant increase in fetal viability compared with LPS treatment alone. These promising results demonstrate the effectiveness of the computational drug repositioning pipeline to identify compounds that could be effective in preventing PTB.

Authors

Brian L. Le, Sota Iwatani, Ronald J. Wong, David K. Stevenson, Marina Sirota

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Figure 2

Gene expression heatmap and protein-interaction connectivity of category A/B therapeutic drug hits.

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Gene expression heatmap and protein-interaction connectivity of category...
(A) Differential gene expression heatmap of sPTB meta-analysis and 10 computationally identified drugs in pregnancy categories A or B. Each row corresponds to a gene (sorted top to bottom from most downregulated to most upregulated in sPTB relative to term births). A rank-based coloring scheme was used. The sPTB meta-analysis differential gene expression signature ranked the 115 downregulated genes (blue) and the 44 upregulated genes (red) separately. The 10-drug gene expression profiles were ordered from left to right by reversal score (most negative to least negative), with all 159 genes ranked from 1–159 (blue-red). Bluer color corresponds to more downregulated genes, and redder color corresponds to more upregulated genes. Bolded drugs (metformin, folic acid, clotrimazole, and progesterone) have been observed in past studies to have some efficacy in the prevention of PTB. (B) Drug-protein interactions for the 10 drug hits according to DrugBank.

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