Devyn Mitchell

This study links polygenic scores for QT interval to changes in Kv11.1 protein interactions in hiPSC-CMs, revealing connections between genetic variants and endocytic trafficking mechanisms.

The paper uses patient-derived iPSC-CMs to show that polygenic scores influence cardiac electrophysiology and drug response in Long QT Syndrome.

The paper evaluates RYR2-CPVT missense variants using Bayesian penetrance analysis and finds it outperforms existing tools.

The paper introduces EFP-Analyzer, a software tool for analyzing extracellular field potentials from iPSC-derived cardiomyocytes, showing it accurately measures intervals and detects drug or mutation effects.

The paper generates hiPSC lines from patients with extreme polygenic scores for QT interval to study LQTS genetic and cellular complexity.

This paper evaluates how functional variant data and penetrance estimates improve risk stratification for LQTS in KCNH2 missense variant carriers.

The paper uses functional assays to reclassify splice-altering variants in Brugada Syndrome and Long QT Syndrome genes, identifying pathogenic and benign classifications.

The paper identifies pathogenic variants in arrhythmia genes in eMERGE-III participants and reclassifies variants of uncertain significance using functional studies.

This paper introduces a high-throughput method to screen KCNH2 variants for trafficking defects, validating it with multiple assays and showing its utility for identifying loss-of-function variants.