Pharmacologic management of Duchenne muscular dystrophy: target identification and preclinical trials

Abstract

Duchenne muscular dystrophy (DMD) is an X-linked human disorder in which absence of the protein dystrophin causes degeneration of skeletal and cardiac muscle. For the sake of treatment development, over and above definitive genetic and cell-based therapies, there is considerable interest in drugs that target downstream disease mechanisms. Drug candidates have typically been chosen based on the nature of pathologic lesions and presumed underlying mechanisms and then tested in animal models. Mammalian dystrophinopathies have been characterized in mice (mdx mouse) and dogs (golden retriever muscular dystrophy [GRMD]). Despite promising results in the mdx mouse, some therapies have not shown efficacy in DMD. Although the GRMD model offers a higher hurdle for translation, dogs have primarily been used to test genetic and cellular therapies where there is greater risk. Failed translation of animal studies to DMD raises questions about the propriety of methods and models used to identify drug targets and test efficacy of pharmacologic intervention. The mdx mouse and GRMD dog are genetically homologous to DMD but not necessarily analogous. Subcellular species differences are undoubtedly magnified at the whole-body level in clinical trials. This problem is compounded by disparate cultures in clinical trials and preclinical studies, pointing to a need for greater rigor and transparency in animal experiments. Molecular assays such as mRNA arrays and genome-wide association studies allow identification of genetic drug targets more closely tied to disease pathogenesis. Genes in which polymorphisms have been directly linked to DMD disease progression, as with osteopontin, are particularly attractive targets.

Keywords: Duchenne muscular dystrophy; animal models; drug development; genome wide association studies; golden retriever muscular dystrophy; mRNA arrays; mdx mouse; preclinical studies.

Figure 1

The canine dystrophin protein (Ensembl protein ID ENSCAFP00000031637), along with mutation information for seven dog breeds known to exhibit DMD-linked muscular dystrophy. CH indicates calponin homology domains, which are actin-binding. WWP indicates the WW domain, which binds proline-rich polypeptides and is the primary interaction site for dystrophin and dystroglycan. EF indicates members of the EF-hand family; this domain stabilizes the dystrophin-dystroglycan complex. ZNF represents a putative zinc-binding domain, ZnF_ZZ, which is present in dystrophin-like proteins and may bind to calmodulin. All 79 exons are represented. Exons and protein domains are depicted approximately to scale. Insertion and deletion mutations are shown above the exons. Arrows at the bottom of the figure indicate point mutations. Reprinted by permission from Bentham Science Publishers: Current Genomics. Comparative genomics of X-linked muscular dystrophies: The golden retriever model, 14:330–342, © 2013.

Figure 2

Homozygous female GRMD dog (Jelly) at 6 years of age. Note the characteristic plantigrade stance, most noticeably carpal hyperextension and glossal hypertrophy.

Figure 3

Tetanic force in prednisone-treated GRMD dogs. Note the reverse pattern for extension and flexion. For extension (A), a trend for increased force at 1 mg/kg becomes significant at 2 mg/kg. Flexion is similar (B) but values are decreased. *p < 0.05 compared with normal. Data are from Liu et al. 2004.

Figure 4

The histologic appearance of normal canine muscle (A) is contrasted with characteristic progressive histopathologic lesions of GRMD (B–D). (B) Several myofibers are swollen/hypercontracted (hyalin necrosis), and two myofibers are mineralized (calcified). The endomysial space is relatively normal. (C) Two small groups of myofibers have undergone necrosis and there is an associated inflammatory cell infiltrate. The endomysial space is mildly expanded. (D) The endomysial space is markedly expanded due to both fibrosis and fatty deposition. Individual myofibers are enlarged and many have central nuclei. H&E stain and 20 × original magnification for all.

Figure 5

Heat map depicting supervised hierarchical clustering in GRMD dogs. A total of 485 genes correlated with OPN expression in 72 mRNA expression profiles from normal and GRMD CS, long digital extensor (LDE), and vastus lateralis (VL) muscles (Nghiem et al. 2013) at 4 to 9 weeks and 6 months. All mRNA profiles were correlated with OPN mRNA expression, and the top correlated genes (r ≥ 0.9; p ≤ 0.001; 485 genes) are depicted here. Note that the OPN-correlated genes (1) have minimal to no expression in normal muscle profiles, (2) increase in expression with age in GRMD profiles, (3) increase in expression in the more affected GRMD muscles at the respective time point, and (4) are variably expressed even within muscles.

Figure 6

NF-κB inhibitors tested in mdx mice. Inhibition of the NF-κB pathway, utilizing mechanisms illustrated here, has shown phenotypic benefit in the mdx mouse (also see Table 3).

Figure 7

Data from GWAS and gene expression microarrays help to identify trends that provide important clues for drug development. Panels A and B illustrate that the same gene (“Gene A”) may have distinct effects on a particular biomarker (here, force) in different muscles (“Muscles A and B”). (A) Expression of Gene A positively correlates with force values in GRMD and normal (unaffected) dogs. (B) Expression of Gene A only minimally correlates with force values (if at all), though higher values are still clearly found in unaffected dogs. Therefore, Gene A expression levels are distinct in the two different muscles from which RNA was extracted. This suggests that Gene A could be considered as a therapeutic target in Muscle A but not Muscle B.

Figure 8

Criteria proposed by Plenge et al. (2013) to apply genetic findings to target validation in human disease. These criteria generally fit with the role that OPN plays in DMD disease pathogenesis. Reprinted by permission from Macmillan Publishers Ltd: Nature Reviews Drug Discovery. Validating therapeutic targets through human genetics, 12:581–594, © 2013.