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Spatial correlation between the presence of genetic variants in sarcomeric genes and hereditary cardiomyopathy: using next generation sequencing to reevaluate genotype and phenotype relationships

Grant number: 15/07953-9
Support type:Scholarships abroad - Research Internship - Post-doctor
Effective date (Start): November 02, 2015
Effective date (End): November 01, 2016
Field of knowledge:Biological Sciences - Genetics - Human and Medical Genetics
Principal researcher:Alexandre da Costa Pereira
Grantee:Júlia Daher Carneiro Marsiglia
Supervisor abroad: Cristine E. Seidman
Home Institution: Instituto do Coração Professor Euryclides de Jesus Zerbini (INCOR). Hospital das Clínicas da Faculdade de Medicina da USP (HCFMUSP). Secretaria da Saúde (São Paulo - Estado). São Paulo , SP, Brazil
Research place: Harvard University, Boston, United States  
Associated to the scholarship:14/15256-3 - Spatial correlation between the presence of genetic variants in sarcomeric genes and hereditary cardiomyopathy: using next generation sequencing to reevaluate genotype and phenotype relationships, BP.PD

Abstract

Cardiomyopathies encompass a clinically and genetically heterogeneous group of the heart muscle diseases. They are defined by the presence of an abnormal structure resulting in myocardial systolic and/or diastolic dysfunction, in the absence of isquemic disease or abnormal conditions of hemodynamic loading. In children and adolescents, cardiomyopathies can have severe consequences, with up to 40% of patients progressing to death or heart transplantation in five years. Idiopathic dilated cardiomyopathy is characterized by left ventricle (LV) dilatation and systolic dysfunction that usually leads to a late-stage congestive heart failure being most responsible for cardiac transplantation in adults and children in the absence of any disease or environmental aggression while hypertrophic cardiomyopathy is characterized by an asymmetric LV hypertrophy without dilatation and histologic disarray of myocardial fibers. It is the leading cause of sudden death in young athletes and has prevalence in the general population of 1:500. Molecular diagnosis emerged in the clinical scenario with a promise to improve the understanding of the diseases, but studies demonstrate that various cardiomyopathies have a gene overlapping and there is not a clear relationship between genotype and phenotype. With the development of next-generation sequencing platforms, genetic studies have become faster, cheaper and viable but since so much data was generated, that leaded to another problem. In many patients, several potentially pathogenic variants were found, making harder the understanding of genetic factors. Thus, there is a need to find reliable mechanisms for assessing the impact of each variant in the gene. Ideally, family segregation analysis and functional assays may help to elucidate the problem, but are not always available or feasible. We suggest that the correlation of clinical data with genotype, combined with in silico programs of protein changes prediction can help direct genetic evaluation. Thus, with this project we intend to evaluate if the location of the variants found in the proposed genes determines what disease the patient will develop, and evaluate whether there is an additive effect of mutations on the severity of the clinical presentation. (AU)

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