THE URGENCY OF GENETIC VERIFICATION OF NON-COMPACTION CARDIOMYOPATHY IN CHILDREN: CLINICAL CASES

Autor: Nataliya A. Sdvigova, Elena N. Basargina, Dmitry V. Ryabtsev, Kirill V. Savostyanov, Alexander A. Pushkov, Natalia V. Zhurkova, Grigory V. Revunenkov, Olga P. Zharova
Jazyk: English<br />Russian
Rok vydání: 2018
Předmět:
Zdroj: Вопросы современной педиатрии, Vol 17, Iss 2, Pp 157-165 (2018)
Druh dokumentu: article
ISSN: 1682-5527
1682-5535
DOI: 10.15690/vsp.v17i2.1883
Popis: Background. Non-compaction cardiomyopathy is a group of genetically heterogeneous, poorly studied myocardial diseases with a variety of clinical manifestations (from asymptomatic course to progressive systolic dysfunction with symptoms of chronic heart failure, arrhythmias, and thromboembolic complications). Considering the variety of genetic disorders associated with the development of noncompaction cardiomyopathy, genetic verification of the diagnosis is important for determining the prognosis and conducting genetic counselling of families with cases of the disease.Description of the Clinical Case. The article presents two clinical observations of a severe course of non-compaction cardiomyopathy with remodeling of the heart cavities according to the dilated phenotype. In order to clarify the disease etiology, a molecular genetic study was conducted using the method of direct automatic sequencing with the analysis of targeted regions of 404 genes which mutations are described in hereditary diseases of the heart and blood vessels. After verifying the mutation (in the ACTC1 and MYBPC3 genes), we performed a search for the detected nucleotide substitution in the venous blood samples of parents and in one case — in the fetal DNA sample. The mode of inheritance has been determined; the probability of recurrence of the disease in siblings in subsequent pregnancies has been estimated.Conclusion. The description of clinical cases shows the importance of genetic verification of the diagnosis in patients with non-compaction cardiomyopathy for determining the disease prognosis and developing an algorithm for monitoring relatives of a proband.
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