Using Systems Biology and Mathematical Modeling Approaches in the Discovery of Therapeutic Targets for Spinal Muscular Atrophy

  • Matthew E. R. ButchbachEmail author
Part of the Advances in Neurobiology book series (NEUROBIOL, volume 21)


Systems biology uses a combination of experimental and mathematical approaches to investigate the complex and dynamic interactions with a given system or biological process. Systems biology integrates genetics, signal transduction, biochemistry and cell biology with mathematical modeling. It can be used to identify novel pathways implicated in diseases as well as to understand the mechanisms by which a specific gene is regulated. This review describes the development of mathematical models for the regulation of an endogenous modifier gene, SMN2, in spinal muscular atrophy—an early-onset motor neuron disease that is a leading genetic cause of infant mortality worldwide—by cAMP signaling. These mathematical models not only can aid in understanding how SMN2 expression is regulated but they can also be used to examine the best ways to manipulate cAMP signaling to maximally increase SMN2 expression. These models will lead to the development of therapeutic strategies for treating SMA. This systems biology approach can also be applied to other neurological diseases, particularly those in which a disease-causing gene or a modifier gene has been identified.


Spinal muscular atrophy Drug discovery SMN2 Ordinary differential equations Gene expression Mathematical modeling 



Adenylate cyclase


Cyclic AMP


Cyclic nucleotide phosphodiesterase


cAMP-response element


CRE binding protein


Dibutyryl cAMP


Enzyme-linked immunosorbent assay


Exonic splicing enhancer


Full length SMN


G protein-coupled receptor


Insulin-like growth factor 1 receptor


Ordinary differential equation


Partial differential equation


cAMP-dependent protein kinase


Protein phosphatase 2A


Spinal muscular atrophy


Survival motor neuron 1


Survival motor neuron 2


SMN lacking exon 7


Single nucleotide variant



This work was supported by an Institutional Development Award (IDeA) from the National Institute of General Medical Sciences of the National Institutes of Health (P30GM114736) and by the Nemours Foundation.

Conflict of Interest

The author declares no conflict of interest.


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© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Center for Applied Clinical Genomics, Nemours Biomedical ResearchNemours/Alfred I. duPont Hospital for ChildrenWilmingtonUSA
  2. 2.Center for Pediatric Research, Nemours Biomedical ResearchNemours/Alfred I. duPont Hospital for ChildrenWilmingtonUSA
  3. 3.Department of PediatricsThomas Jefferson UniversityPhiladelphiaUSA
  4. 4.Department of Biological SciencesUniversity of DelawareNewarkUSA

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