CirculationGenetic & Genomic MedicinePeer-reviewed journal article
Arrhythmia variant associations and reclassifications in the eMERGE-III sequencing study
Andrew Michael GlazeriD, Giovanni DavogusttoiD, Christian M. Shaffer, Carlos G. VanoyeiD, Reshma R. DesaiiD, Eric H. Farber‐EgeriD, Ozan DikilitasiD, Ning ShangiD, Jennifer A. PachecoiD, Tao YangiD, Ayesha MuhammadiD, Jonathan D. MosleyiD, Sara L. Van DriestiD, Quinn Stanton WellsiD, Lauren Lee Shaffer, Olivia R. Kalash, Yuko WadaiD, Harris T. BlandiD, Zachary T. YonedaiD, Devyn MitchelliD, Brett M. KronckeiD, Iftikhar J. KulloiD, Gail Pairitz JarvikiD, Adam S. Gordon, Eric Berg LarsoniD, , Dan M. RodeniD
Abstract
In 21,846 eMERGE-III participants, sequencing 10 arrhythmia syndrome disease genes identified 123 individuals with pathogenic or likely pathogenic (P/LP) variants. Compared to non-carriers, P/LP carriers had a significantly higher burden of arrhythmia phenotypes in their electronic health records (EHRs). Fifty one participants had variant results returned. Eighteen of these 51 participants had inherited arrhythmia syndrome diagnoses (primarily long QT syndrome), and 11/18 of these diagnoses were made only after variant results were returned. After in vitro functional evaluation of 50 variants of uncertain significance (VUS), we reclassified 11 variants: 3 to likely benign and 8 to P/LP. As large numbers of people are sequenced, the disease risk from rare variants in arrhythmia genes can be assessed by integrating genomic screening, EHR phenotypes, and in vitro functional studies.
- organism: human
- assay: whole-exome sequencing
- research focus: variant effect prediction
- approach: statistical model
- Citations
- 44
- FWCI
- 7.04
- Field percentile
- top 2%
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