Whole genome sequencing of families diagnosed with cardiac channelopathies reveals structural variants missed by whole exome sequencing.
J Hum Genet
; 2024 Jun 18.
Article
en En
| MEDLINE
| ID: mdl-38890497
ABSTRACT
Cardiac channelopathies are a group of heritable disorders that affect the heart's electrical activity due to genetic variations present in genes coding for ion channels. With the advent of new sequencing technologies, molecular diagnosis of these disorders in patients has paved the way for early identification, therapeutic management and family screening. The objective of this retrospective study was to understand the efficacy of whole-genome sequencing in diagnosing patients with suspected cardiac channelopathies who were reported negative after whole exome sequencing and analysis. We employed a 3-tier analysis approach to identify nonsynonymous variations and loss-of-function variations missed by exome sequencing, and structural variations that are better resolved only by sequencing whole genomes. By performing whole genome sequencing and analyzing 25 exome-negative cardiac channelopathy patients, we identified 3 pathogenic variations. These include a heterozygous likely pathogenic nonsynonymous variation, CACNA1CNM_000719exon19c.C2570Gp. P857R, which causes autosomal dominant long QT syndrome in the absence of Timothy syndrome, a heterozygous loss-of-function variation CASQ2NM_001232.4c.420+2T>C classified as pathogenic, and a 9.2 kb structural variation that spans exon 2 of the KCNQ1 gene, which is likely to cause Jervell-Lange-Nielssen syndrome. In addition, we also identified a loss-of-function variation and 16 structural variations of unknown significance (VUS). Further studies are required to elucidate the role of these identified VUS in gene regulation and decipher the underlying genetic and molecular mechanisms of these disorders. Our present study serves as a pilot for understanding the utility of WGS over clinical exomes in diagnosing cardiac channelopathy disorders.
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01-internacional
Base de datos:
MEDLINE
Idioma:
En
Revista:
J Hum Genet
Asunto de la revista:
GENETICA MEDICA
Año:
2024
Tipo del documento:
Article
País de afiliación:
India