XXXX Genotype-Cardiac Phenotype Correlations in @entity1555 Using Cardiac Magnetic Resonance Imaging.

@entity1 @entity296 @entity1555 @entity4714 @entity299 @entity17416 @entity1002
UNASSIGNED: @entity1555 are caused by mutations in @entity4714 . Cardiac manifestations vary broadly, making prognosis difficult. Current @entity4714 genotype-cardiac phenotype correlations are limited. For skeletal muscle, the reading-frame rule suggests in-frame mutations tend to yield milder phenotypes. We performed @entity4714 genotype-cardiac phenotype correlations using a protein-effect model and cardiac magnetic resonance imaging. A translational model was applied to @entity1 -specific deletion, indel, and nonsense mutations to predict exons and protein domains present within truncated @entity4714 protein. @entity1 were dichotomized into predicted present and predicted absent groups for exons and protein domains of interest. Development of @entity296 (represented by late gadolinium enhancement [LGE]) and depressed @entity1002 ( @entity1002 ) were compared. @entity1 (n  = 274) with predicted present @entity17416 ( @entity17416 ), C-terminal domain (CTD), and both the N-terminal actin-binding and cysteine-rich domains (ABD1  + @entity17416 ) had a decreased risk of LGE and trended toward greater freedom from LGE. @entity1 with predicted present CTD (exactly the same as those with in-frame mutations) and ABD1  + @entity17416 trended toward decreased risk of and greater freedom from depressed @entity1002 . In conclusion, genotypes previously implicated in altering the @entity299 phenotype were not significantly related to LGE and depressed @entity1002 . @entity1 with predicted present @entity17416 , CTD/in-frame mutations, and ABD1  + @entity17416 trended toward milder cardiac phenotypes, suggesting that the reading-frame rule may be applicable to the cardiac phenotype. Genotype-phenotype correlations may help predict the  cardiac phenotype for dystrophinopathic @entity1 and guide future therapies.
