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Mitchell, D. W.

Publications and source records attributed to Mitchell, D. W..

4 recordsLinked to original sources

EFP Analyzer: A fast, accurate, and easy-to-teach program for analyzing Extracellular Field Potentials from iPSC-derived cardiomyocytes

RationaleInduced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) are an emerging model for determining drug effects and modeling disease. Specialized devices can generate Extracellular Field Potential (EFP) measurements from these cells, analogous to the ventricular complex of the electrocardiogram. ObjectiveThe objective of this study was to develop an easy-to-use, easy-to-teach, reproducible software tool to measure EFPs. Methods-ResultsWe present the EFP-Analyzer (EFPA), a semi-automized analyzer for EFP traces, which identifies and averages beats, identifies landmarks, and calculates intervals. We evaluated the tool in an analysis of 358 EFP traces from 22 patient-derived lines. We analyzed spontaneously beating iPSC-CMs, as well as optically paced iPSC-CMs through channelrhodopsin. We developed stringent quality criteria and measured EFP intervals, including Field Potential Duration (FPD). FPD from optically paced iPSC-CMs were shorter than those of spontaneously beating iPSC-CMs (283.7.0{+/-}54.2 vs. 293.0{+/-}47.5, p: 0.32, respectively). We further analyzed the usability and data replicability of EFPA through an inter-intra observer analysis. Correlation coefficient for inter-reader tangent and threshold measurements for these FPD ranged between r: 0.93-1.00. Bland-Altman plots comparing inter observer results for spontaneously beating and paced iPSC-CMs showed 95% limits of agreement (-13.6 to 19.4ms and -13.2 to 15.3ms, respectively). The EFP-analyzer could accurately detect FPD prolongation due to drug (moxifloxacin) or pathogenic loss of function mutations (CACNA1C N639T). This program is available for download at https://github.com/kroncke-lab/EFPA. The instructions will be available at the same listed website under the README section of the Github main page. ConclusionsThe EFP-Analyzer tool is a useful tool that enables the efficient use of iPSC-CMs as a model to study drug effects and disease.

pharmacology and toxicology↗

Functional Assays Reclassify Suspected Splice-Altering Variants of Uncertain Significance in Mendelian Channelopathies

BackgroundRare protein-altering variants in SCN5A, KCNQ1, and KCNH2 are major causes of Brugada Syndrome (BrS) and the congenital Long QT Syndrome (LQTS). While splice-altering variants lying outside 2-bp canonical splice sites can cause these diseases, their role remains poorly described. ObjectiveWe implemented two functional assays to assess 12 recently reported putative splice-altering variants of uncertain significance (VUS) and 1 likely pathogenic (LP) variant without functional data observed in BrS and LQTS probands. MethodsWe deployed minigene assays to assess the splicing consequences of 10 variants. Three variants incompatible with the minigene approach were introduced into control induced pluripotent stem cells (iPSCs) by CRISPR genome editing. We differentiated cells into iPSC-derived cardiomyocytes (iPSC-CMs) and studied splicing outcomes by reverse transcription-polymerase chain reaction (RT-PCR). We used the American College of Medical Genetics and Genomics functional assay criteria (PS3/BS3) to reclassify variants. ResultsWe identified aberrant splicing, with presumed disruption of protein sequence, in 8/10 variants studied using the minigene assay and 1/3 studied in iPSC-CMs. We reclassified 9 VUS to LP, 1 VUS to Likely Benign, and 1 LP variant to pathogenic. ConclusionsFunctional assays reclassified splice-altering variants outside canonical splice sites in BrS- and LQTS-associated genes.

genetics↗

A Massively Parallel Trafficking Assay Accurately Predicts Loss of Channel Function in KCNH2 Variants

High throughput genomics has greatly facilitated identification of genetic variants. However, determining which variants contribute to disease causation is challenging with more than half of all missense variants now classified as variants of uncertain significance (VUS). A VUS leaves patients and their clinicians unable to utilize the variant information in clinical decision-making. In long QT syndrome type 2, KCNH2 channel function is directly associated with disease presentation. Therefore, functional phenotyping of KCNH2 variants can provide direct evidence to aid variant classification. Here, we investigated the expression of all codon variants in exon 2 of KCNH2 using a massively parallel trafficking assay and for a subset of 458 single nucleotide variants compared the results with peak tail current density and gating using automated patch clamp electrophysiology. Trafficking could correctly classify loss of peak tail current density variants with an AUC reaching 0.94 compared to AUCs of 0.75 to 0.8 for in silico variant classifiers. We suggest massively parallel trafficking assays can provide prospective and accurate functional assessment for all missense variants in KCNH2 and most likely many other ion channels and membrane proteins.

biophysics↗

High-throughput discovery of trafficking-deficient variants in the cardiac potassium channel KCNH2

BackgroundKCHN2 encodes the KV11.1 potassium channel responsible for IKr, a major repolarization current during the cardiomyocyte action potential. Variants in KCNH2 that decrease IKr can cause Type 2 Long QT syndrome, usually due to mistrafficking to the cell surface. Accurately discriminating between variants with normal and abnormal trafficking would help clinicians identify and treat individuals at risk of a major cardiac event. The volume of reported non-synonymous KCNH2 variants preclude the use of conventional electrophysiologic methods for functional study. ObjectiveTo report a high-throughput, multiplexed screening method for KCNH2 genetic variants capable of measuring the cell surface abundance of hundreds of missense variants in KCNH2. MethodsWe develop a method to quantitate KCNH2 variant trafficking on a pilot region of 11 residues in the S5 helix, and generate trafficking scores for 220/231 missense variants in this region. ResultsFor 5/5 variants, high-throughput trafficking scores validated when tested in single variant flow cytometry and confocal microscopy experiments. We additionally compare our results with planar patch electrophysiology and find that loss-of-trafficking variants do not produce IKr, but that some variants which traffic normally may still be functionally compromised. ConclusionsHere, we describe a new method for detecting trafficking-deficient variants in KCNH2 in a multiplexed assay. This new method accurately generates trafficking data for variants in KCNH2 and can be readily extended to all residues in Kv11.1 and to other cell surface proteins. CLINICAL IMPLICATIONSHundreds of KCNH2 variants have been observed to date, and thousands more will be found as clinical and population sequencing efforts become increasingly widespread. The major mechanism of KV11.1 loss of function is misfolding and failure to traffic to the cell surface. Deep mutational scanning of KCNH2 trafficking is a scalable, high-throughput method that can help identify new loss of function variants and decipher the large number of KCNH2 variants being found in the population.

genetics↗