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Duchenne muscular dystrophy: High-resolution melting curve analysis as an affordable diagnostic mutation scanning tool in a South African cohort


AI Esterhuizen
JM Wilmshurst
RG Goliath
LJ Greenberg

Abstract

Background. Duchenne/Becker muscular dystrophy (D/BMD) is an X-linked recessive muscle disorder affecting 1/3 500 live male births worldwide. Up to 70% of all D/BMD cases are caused by exonic deletions or duplications routinely identified in diagnostic laboratories worldwide. The remaining patients harbour other sequence alterations for which testing availability is limited owing to the expense of interrogating the large DMD gene. Genetic screening for D/BMD in South Africa currently includes multiple ligase-dependent probe amplification (MLPA) for exonic deletions and duplications and linkage analysis. No genetic testing for small mutations in the DMD gene is offered, leaving a third of D/BMD families without genetic closure. The advent of potential mutation-specific therapies for DMD necessitates comprehensive testing protocols.
Objective. To investigate the effectiveness and affordability of high-resolution melting curve analysis (hrMCA) for detection of small/point mutations in the DMD gene, for possible inclusion into the local public health-funded diagnostic service.
Methods. DNA from 24 patients who had previously tested deletion-negative with multiplex polymerase chain reaction (mPCR) was analysed by MLPA and hrMCA.
Results. MLPA revealed eight previously undetected exonic rearrangements: five deletions and three duplications. HrMCA of the remaining samples revealed three nonsense, four frameshifts, one splice-site, one missense and one single-base substitution in the Dp427promoter/ exon1 of the DMD gene. In addition, 41 polymorphisms and three changes of uncertain significance were detected.
Conclusion. These findings identify hrMCA as an affordable and effective mutation scanning tool for incorporation into the local diagnostic setting, allowing for better genetic counselling of more DMD families and selection of potential candidates for future therapies.


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eISSN: 2078-5135
print ISSN: 0256-9574