Treating Duchenne Muscular Dystrophy: The Promise of Stem Cells, Artificial Intelligence, and Multi-Omics

Abstract

Muscular dystrophies are chronic and debilitating disorders caused by progressive muscle wasting. Duchenne muscular dystrophy (DMD) is the most common type. DMD is a well-characterized genetic disorder caused by the absence of dystrophin. Although some therapies exist to treat the symptoms and there are ongoing efforts to correct the underlying molecular defect, patients with muscular dystrophies would greatly benefit from new therapies that target the specific pathways contributing directly to the muscle disorders. Three new advances are poised to change the landscape of therapies for muscular dystrophies such as DMD. First, the advent of human induced pluripotent stem cells (iPSCs) allows researchers to design effective treatment strategies that make up for the gaps missed by conventional "one size fits all" strategies. By characterizing tissue alterations with single-cell resolution and having molecular profiles for therapeutic treatments for a variety of cell types, clinical researchers can design multi-pronged interventions to not just delay degenerative processes, but regenerate healthy tissues. Second, artificial intelligence (AI) will play a significant role in developing future therapies by allowing the aggregation and synthesis of large and disparate datasets to help reveal underlying molecular mechanisms. Third, disease models using a high volume of multi-omics data gathered from diverse sources carry valuable information about converging and diverging pathways. Using these new tools, the results of previous and emerging studies will catalyze precision medicine-based drug development that can tackle devastating disorders such as DMD.

Keywords: Duchenne muscular dystrophy; artificial intelligence; cardiomyopathy; drug testing; iPSC disease modeling; single-cell technology.

Figure 1

Schematic of the approaches to broaden the therapeutics available to DMD patients. Patient-derived or genome-edited iPSCs provide a human model for disease specific modeling of various cell types and benefits from previous knowledge using the mdx mouse. Newer experimental technologies are detailing the intricacies of complex phenotypes. Next-generation computational tools are enabling high-dimensional analysis of multi-omics data. This figure was created with BioRender.com.

Figure 2

Sample meta-analysis from an A.I. driven therapeutics platform. (A) Summary of some of the top gene targets associated to DMD. (B) Summary of some of the top compounds associated to DMD for therapy. The evidence for classifying these molecules as the top targets is gleaned from various public databases plus the funding and publications landscape using PandaOmics (http://pandaomics.com/).