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High Prevalence of Genetic Alterations in Infantile-Onset Cardiomyopathy

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摘要 Background and Method:The genetic cause of infantile-onset cardiomyopathy is rarely investigated.Here,we conducted whole exome sequencing(WES)and mitochondrial DNA(mtDNA)sequencing in eight patients with infantile-onset cardiomyopathy to identify genetic variations.Result:Among these patients,two(25%)had dilated cardiomyopathy(DCMP),two(25%)had left ventricular non-compaction(LVNC),and four(50%)had hypertrophic cardiomyopathy(HCMP).Except four patients identified prenatally,the remaining patients presented at a median age of 85.5 days.WES identified genetic variants in a total of seven(87.5%)patients and mtDNA sequencing in the other case.TPM1 and MYH7 variants were identified in the two patients with DCMP;MYH11 and MYLK2 variants in the two patients with LVNC;HRAS,BRAF,and MYH7 variants in three patients with HCMP;and MT-ND1 variant in one patient with HCMP having high blood lactic acid levels.Among the eight variants,four were classified as pathogenic or likely-pathogenic according to the American College of Medical Genetics(ACMG)guidelines,and the remaining were identified as variants of unknown significance(VUSs).Three pathogenic mutations were de novo,whereas four(likely-pathogenic or VUSs)were inherited from a respective parent,excluding one variant where parental testing was unavailable,questioning whether these inherited variants are disease-causing.Three patients died before 3 months of age.Conclusion:Genomic studies,such as WES with additional mtDNA sequencing,can identify a genetic variant in high proportions of patients with infantile-onset cardiomyopathy.The clinical implication of the parentally inherited variant needs to be assessed in a larger patient and family cohort with a longitudinal follow-up.
出处 《Congenital Heart Disease》 SCIE 2021年第4期397-410,共14页 先天性心脏病(英文)
基金 This work was supported by an Institute for Information and Communications Technology Promotion(IITP)grant funded by the Korean government(MSIT)(2018-0-00861,Intelligent SW Technology Development for Medical Data Analysis).
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