Physiological genomics identifies genetic modifiers of long QT syndrome type 2 severity

Research output: Contribution to journalArticle

Authors

External Institution(s)

  • Heart and Vascular Research Center
  • Case Western Reserve University

Details

Original languageEnglish (US)
Pages (from-to)1043-1056
Number of pages14
JournalJournal of Clinical Investigation
Volume128
Issue number3
StatusPublished - Mar 1 2018
Peer-reviewedYes

Abstract

Congenital long QT syndrome (LQTS) is an inherited channelopathy associated with life-threatening arrhythmias. LQTS type 2 (LQT2) is caused by mutations in KCNH2, which encodes the potassium channel hERG. We hypothesized that modifier genes are partly responsible for the variable phenotype severity observed in some LQT2 families. Here, we identified contributors to variable expressivity in an LQT2 family by using induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) and whole exome sequencing in a synergistic manner. We found that iPSC-CMs recapitulated the clinical genotype-phenotype discordance in vitro. Importantly, iPSC-CMs derived from the severely affected LQT2 patients displayed prolonged action potentials compared with cells from mildly affected first-degree relatives. The iPSC-CMs derived from all patients with hERG R752W mutation displayed lower IKr amplitude. Interestingly, iPSC-CMs from severely affected mutation-positive individuals exhibited greater L-type Ca2+ current. Whole exome sequencing identified variants of KCNK17 and the GTP-binding protein REM2, providing biologically plausible explanations for this variable expressivity. Genome editing to correct a REM2 variant reversed the enhanced L-type Ca2+ current and prolonged action potential observed in iPSC-CMs from severely affected individuals. Thus, our findings showcase the power of combining complementary physiological and genomic analyses to identify genetic modifiers and potential therapeutic targets of a monogenic disorder. Furthermore, we propose that this strategy can be deployed to unravel myriad confounding pathologies displaying variable expressivity.

Citation formats

APA

Chai, S., Wan, X., Ramirez-Navarro, A., Tesar, P. J., Kaufman, E. S., Ficker, E., ... Deschênes, I. (2018). Physiological genomics identifies genetic modifiers of long QT syndrome type 2 severity. Journal of Clinical Investigation, 128(3), 1043-1056. https://doi.org/10.1172/JCI94996

Harvard

Chai, S, Wan, X, Ramirez-Navarro, A, Tesar, PJ, Kaufman, ES, Ficker, E, George, AL & Deschênes, I 2018, 'Physiological genomics identifies genetic modifiers of long QT syndrome type 2 severity', Journal of Clinical Investigation, vol. 128, no. 3, pp. 1043-1056. https://doi.org/10.1172/JCI94996