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Combining multiomics and drug perturbation profiles to identify muscle-specific treatments for spinal muscular atrophy
Katharina E. Meijboom, … , Caleb Webber, Melissa Bowerman
Katharina E. Meijboom, … , Caleb Webber, Melissa Bowerman
Published July 8, 2021
Citation Information: JCI Insight. 2021;6(13):e149446. https://doi.org/10.1172/jci.insight.149446.
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Research Article Muscle biology Neuroscience

Combining multiomics and drug perturbation profiles to identify muscle-specific treatments for spinal muscular atrophy

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Abstract

Spinal muscular atrophy (SMA) is a neuromuscular disorder caused by loss of survival motor neuron (SMN) protein. While SMN restoration therapies are beneficial, they are not a cure. We aimed to identify potentially novel treatments to alleviate muscle pathology combining transcriptomics, proteomics, and perturbational data sets. This revealed potential drug candidates for repurposing in SMA. One of the candidates, harmine, was further investigated in cell and animal models, improving multiple disease phenotypes, including lifespan, weight, and key molecular networks in skeletal muscle. Our work highlights the potential of multiple and parallel data-driven approaches for the development of potentially novel treatments for use in combination with SMN restoration therapies.

Authors

Katharina E. Meijboom, Viola Volpato, Jimena Monzón-Sandoval, Joseph M. Hoolachan, Suzan M. Hammond, Frank Abendroth, Olivier G. de Jong, Gareth Hazell, Nina Ahlskog, Matthew J.A. Wood, Caleb Webber, Melissa Bowerman

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Figure 4

Harmine, as predicted by CMap analyses, is able to reverse the expression of genes significantly downregulated in SMA muscle in several cellular models.

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Harmine, as predicted by CMap analyses, is able to reverse the expressio...
(A–D) C2C12, NSC-34, SMA patient fibroblasts, and control fibroblasts were treated with 25, 35, or 50 μM of harmine for 48 hours. Expression of Snrnp27 (A), Gls (B), Aspm (C), and Mcm2 (D) was assessed by qPCR and compared with untreated cells. Data are shown as a scatter plot and are represented as mean ± SEM; n = 3 independent wells, 2-way ANOVA followed by uncorrected Fisher’s least significant difference (LSD), F = 20.20 (Snrnp27), F = 90.95 (Gls), F = 14.16 (Aspm), F = 42.61 (Mcm2), df = 32 for all, *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001.

Copyright © 2022 American Society for Clinical Investigation
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