Abstract MP264: Heterogeneous Distribution Of Mutations In Myosin Binding Protein-c Paralogs

Rationale: Myosin binding protein-C ( MYBPC ) is a sarcomeric protein which regulates the force of contraction in striated muscles. Mutations in the MYBPC family of genes, slow skeletal( MYBPC1 ), fast skeletal ( MYBPC2 ) and cardiac ( MYBPC3 ) can result in cardiac and skeletal myopathies, yet their evolutionary pattern, pathogenicity and impact on MYBPC structure remain to be elucidated. Objective: To assess conserved and epigenetic patterns of MYBPC family mutations. Methods and Results: Leveraging a machine learning approach, the Genome Aggregation Database (gnomAD) provided 12353, 6227 and 5279 variants in MYBPC1 , MYBPC2 and MYBPC3 genes, respectively, followed by analysis with the Ensembl variant effector predictor. Missense variants comprised 62-68% of total variants in which the first and second nucleotide (nt) positions in the codons were highly altered, with G/A substitution nt substitution the most predominant. Arginine was the most mutated amino acid, important because most disease-causing mutations in MYBPC are arginine in origin. Domains C5 and C6of MYBPC were found to be hotspots for most mutations in the MYBPC family. A high percentage of truncated mutations in MYBPC3 cause cardiomyopathies. Arginine and glutamate were the top hits in MYBPC1 and MYBPC3, respectively, and tryptophan and tyrosine were the most common among the three paralogs changing to premature stop codons and causing protein truncations at the carboxy terminus. Conclusion: A heterogeneous epigenetic pattern was identified among the three MYBPC paralogs. Genomic databases using machine learning approaches can be used to diagnose and design therapeutics to treat muscle disorders caused by MYBPC mutations.