Recent advances in understanding congenital myopathies.
Gianina RavenscroftRobert J Bryson-RichardsonKristen J NowakNigel G LaingPublished in: F1000Research (2018)
By definition, congenital myopathy typically presents with skeletal muscle weakness and hypotonia at birth. Traditionally, congenital myopathy subtypes have been predominantly distinguished on the basis of the pathological hallmarks present on skeletal muscle biopsies. Many genes cause congenital myopathies when mutated, and a burst of new causative genes have been identified because of advances in gene sequencing technology. Recent discoveries include extending the disease phenotypes associated with previously identified genes and determining that genes formerly known to cause only dominant disease can also cause recessive disease. The more recently identified congenital myopathy genes account for only a small proportion of patients. Thus, the congenital myopathy genes remaining to be discovered are predicted to be extremely rare causes of disease, which greatly hampers their identification. Significant progress in the provision of molecular diagnoses brings important information and value to patients and their families, such as possible disease prognosis, better disease management, and informed reproductive choice, including carrier screening of parents. Additionally, from accurate genetic knowledge, rational treatment options can be hypothesised and subsequently evaluated in vitro and in animal models. A wide range of potential congenital myopathy therapies have been investigated on the basis of improved understanding of disease pathomechanisms, and some therapies are in clinical trials. Although large hurdles remain, promise exists for translating treatment benefits from preclinical models to patients with congenital myopathy, including harnessing proven successes for other genetic diseases.
Keyphrases
- genome wide
- skeletal muscle
- late onset
- clinical trial
- genome wide identification
- end stage renal disease
- bioinformatics analysis
- healthcare
- ejection fraction
- randomized controlled trial
- muscular dystrophy
- type diabetes
- newly diagnosed
- dna methylation
- prognostic factors
- risk assessment
- autism spectrum disorder
- climate change
- stem cells
- social media
- big data
- deep learning
- artificial intelligence
- double blind
- study protocol
- mass spectrometry
- high speed
- atomic force microscopy