Phenotype-Based High-Throughput Classification of Long QT Syndrome Subtypes Using Human Induced Pluripotent Stem Cells

Abstract

Summary: For long QT syndrome (LQTS), recent progress in genome-sequencing technologies enabled the identification of rare genomic variants with diagnostic, prognostic, and therapeutic implications. However, pathogenic stratification of the identified variants remains challenging, especially in variants of uncertain significance. This study aimed to propose a phenotypic cell-based diagnostic assay for identifying LQTS to recognize pathogenic variants in a high-throughput manner suitable for screening. We investigated the response of LQT2-induced pluripotent stem cell (iPSC)-derived cardiomyocytes (iPSC-CMs) following IKr blockade using a multi-electrode array, finding that the response to IKr blockade was significantly smaller than in Control-iPSC-CMs. Furthermore, we found that LQT1-iPSC-CMs and LQT3-iPSC-CMs could be distinguished from Control-iPSC-CMs by IKs blockade and INa blockade, respectively. This strategy might be helpful in compensating for the shortcomings of genetic testing of LQTS patients. : The methods presented by the authors allowed recognition of long QT syndrome (LQTS) subtypes 1, 2, and 3 using specific ion-channel current blockade with a combination of patient-derived iPSCs and a multi-electrode array system. This strategy might potentially compensate for the shortcomings of genetic testing for LQTS, especially in patients who have variants of unknown significance or no identified mutations. Keywords: long QT syndrome, induced pluripotent stem cell, phenotype-based diagnosis, multi-electrode array, genome editing