Abstract
BackgroundCardiomyopathies (CM) are heterogeneous group of genetic disorders, specifically damage the heart muscles that leads to the progression of many clinical symptoms such as congestive heart failure (CHF). Dilated Cardiomyopathy (DCM) is the most common cause of heart failure. This study focuses on genetic variations in DCM, which is chronic, generally nonreversible heart muscles disease characterized by heart chamber dilation mostly left ventricle and decreased systolic efficiency. MethodologyThis study includes two parts, First we identified 100 genes associated with DCM using deep literature survey. Genetic variants were extracted from 1000 Genome Project (1000 GP), ExAC and Simon Genome Diversity project, for the identification of deleterious variants using in silico prediction tools followed by population genetic differentiation. In Second part, we examined 21,469 patients related to cardiac diseases. Of these, 100 DCM patients were recruited for the identification of rare pathogenic variants rs143187236 in MYOM3 and an INDEL rs36212066 in MYBPC3 using ARMS-PCR and validation through Sanger sequencing. ResultsWe identified 1658, 15,058 and 461 deleterious variants in 1000 GP, ExAC and Simon Genomes project respectively predicted by both SIFT and PolyPhen2 prediction tools. Clinvar database revealed 10, 69 and one pathogenic and likely pathogenic variants associated with DCM in 1000 GP, ExAC and Simon genome. Population genetic differentiation analysis revealed South Asian populations are closely related to European and American while highly differentiated to East Asian and African populations. ARMS-PCR and Sanger sequencing data of enlisted DCM patients showed that rs143187236 in MYOM3 was found in heterozygous state in three patients while rs36212066 in MYBPC3 was not detected in studied patients. ConclusionBased on bioinformatics analysis and investigation of deleterious variants through Sanger sequencing, it is deduced that large sample size is necessary for further detection of variants that will aid in the early diagnosis of DCM.
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