Genetic variant annotation scores in congenital long QT syndrome.

Arwa YounisChristopher BodurianDan E ArkingNicola Luigi BragazziChadi TabajaWojciech ZarebaScott McNittMehmet K AktasBronislava PolonskyCoeli M LopesNona SotoodehniaPeter J KudenchukIlan Goldenberg

Published in: Annals of noninvasive electrocardiology : the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc (2023)

In congenital LQTS patients, well-established algorithms (CADD, SIFT, REVEL, and PolyPhen-2) were able to identify the majority of the causal variants as pathogenic. However, the scores did not predict clinical outcomes. These results indicate that mutation location/functional assays are essential for accurate interpretation of the risk associated with LQTS mutations.

Keyphrases

end stage renal disease
newly diagnosed
machine learning
ejection fraction
copy number
peritoneal dialysis
prognostic factors
high resolution
high throughput
genome wide
deep learning
drug induced