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  • Review Article
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Is it time for genetic modifiers to predict prognosis in Duchenne muscular dystrophy?

Nature Reviews Neurology volume 19, pages 410–423 (2023)Cite this article

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Abstract

Patients with Duchenne muscular dystrophy (DMD) show clinically relevant phenotypic variability, despite sharing the same primary biochemical defect (dystrophin deficiency). Factors contributing to this clinical variability include allelic heterogeneity (specific DMD mutations), genetic modifiers (trans-acting genetic polymorphisms) and variations in clinical care. Recently, a series of genetic modifiers have been identified, mostly involving genes and/or proteins that regulate inflammation and fibrosis — processes increasingly recognized as being causally linked with physical disability. This article reviews genetic modifier studies in DMD to date and discusses the effect of genetic modifiers on predicting disease trajectories (prognosis), clinical trial design and interpretation (inclusion of genotype-stratified subgroup analyses) and therapeutic approaches. The genetic modifiers identified to date underscore the importance of progressive fibrosis, downstream of dystrophin deficiency, in driving the disease process. As such, genetic modifiers have shown the importance of therapies aimed at slowing this fibrotic process and might point to key drug targets.

Key points

  • Clinically relevant variability in disease severity and progression is observed in Duchenne muscular dystrophy (DMD) and can be explained by allelic heterogeneity within the DMD locus (‘cis’ modifiers) and polymorphisms in different loci (‘trans’ modifiers).

  • Understanding the bases of clinical variability is important for patient and family counselling and prognosis, clinical trial design and the identification of therapeutic targets.

  • The main identified modifiers influence inflammation and fibrotic replacement, highlighting the central role of these processes in DMD and the importance of addressing them pharmacologically.

  • Modifier genes and proteins might become targets for therapeutic modulation themselves, predict responsiveness to treatments or enable precise subgroup analyses in clinical trials.

  • Future developments in the field include the identification of novel modifiers by genome mapping in large, deeply phenotyped cohorts and the development of multilocus interaction models.

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Fig. 1: Schematic representation of the downstream consequences of dystrophin deficiency in skeletal muscle.
Fig. 2: Schematic representation of ‘cis-acting’ genetic modifiers.
Fig. 3: The main ‘trans-acting’ genetic modifiers and their effects on inflammatory and profibrotic pathways.

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Acknowledgements

E.P. and L.B. are part of the European Reference Network (ERN) for neuromuscular diseases and wish to acknowledge funding from the Cariparo foundation (Progetti di Eccellenza 2017).

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Authors and Affiliations

  1. Department of Neurosciences (DNS), University of Padova, Padova, Italy

    Luca Bello & Elena Pegoraro

  2. School of Pharmacy and Pharmaceutical Sciences, Binghamton University (State University of New York), Binghamton, NY, USA

    Eric P. Hoffman

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  2. Eric P. Hoffman
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The authors contributed equally to all aspects of the article.

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Correspondence to Elena Pegoraro.

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Competing interests

L.B. reports honoraria (speaker, advisory boards) from PTC Therapeutics, Sarepta Therapeutics, Edgewise Therapeutics, Epirium Bio and research funding from PTC Therapeutics. E.P.H. reports salary support from Reveragen and AGADA Biosciences. E.P. reports personal fees from Sarepta, grants and non-financial support from Santhera, personal fees and non-financial support from PTC Pharmaceuticals, non-financial support from Genzyme and personal fees from Roche, outside the submitted work.

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Nature Reviews Neurology thanks Marianela Schiava, who co-reviewed with Michela Guglieri, and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Review criteria

L.B., E.P.H. and E.P. carried out independent literature searches using PubMed for published articles on genetic modifiers in Duchenne muscular dystrophy, with the following keywords: ‘Duchenne AND genetic modifiers’, ‘Duchenne AND genotype’. All results describing findings from human patients were considered for inclusion in the article. Abstracts were not considered. No time period restrictions or language restrictions utilized in the search criteria.

Related links

BGee database: https://bgee.org/

GTEx database: https://gtexportal.org/home/

Glossary

Allelic heterogeneity

When patients with a single gene disorder show multiple different types of mutations in the specific gene involved in the disorder.

Cis-acting genetic modifiers

Mutations in disease-causing genes that are expected to give rise to a ‘typical’ phenotype for the disease of interest (for example, out-of-frame mutations in the DMD gene expected to give rise to a severe DMD phenotype), but that, in some cases, is associated with milder or more severe phenotypes, because of complex molecular mechanisms (for example, out-of-frame deletion of exon 45 of the DMD gene allowing low-level expression of internally deleted dystrophin owing to endogenous skipping of exon 44).

GWASs

Genome-wide association studies, in which millions of genetic polymorphisms throughout the human genome are studied for association with a human trait (such as clinical severity in DMD).

Non-null (leaky)

The protein product of the mutated gene is detectable, often at low levels, and with only partly retained biochemical function.

Null

The protein product of the mutated gene is not detectable.

Trans-acting genetic modifiers

Genetic variations in genes remote from a disease-causing gene, which typically show a high degree of polymorphism in the general population and significantly alter the phenotypic manifestations of the disease, by affecting molecular pathways in the disease pathophysiology.

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Bello, L., Hoffman, E.P. & Pegoraro, E. Is it time for genetic modifiers to predict prognosis in Duchenne muscular dystrophy?. Nat Rev Neurol 19, 410–423 (2023). https://doi.org/10.1038/s41582-023-00823-0

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