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Biology subjects

Blair, M. A.

Publications and source records attributed to Blair, M. A..

3 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↗

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↗

High-throughput reclassification of SCN5A variants

RationalePartial or complete loss of function variants in SCN5A are the most common genetic cause of the arrhythmia disorder Brugada Syndrome (BrS1). However, the pathogenicity of SCN5A variants is often unknown or disputed; 80% of the 1,390 SCN5A missense variants observed in at least one individual to date are variants of uncertain significance (VUS). The designation of VUS is a barrier to the use of sequence data in clinical care. ObjectiveWe selected 83 variants for study: 10 previously studied control variants, 10 suspected benign variants, and 63 suspected Brugada Syndrome-associated variants, selected on the basis of their frequency in the general population and in patients with Brugada Syndrome. We used high-throughput automated patch clamping to study the function of the 83 variants, with the goal of reclassifying variants with functional data. Methods and ResultsTen previously studied variants had functional properties concordant with published manual patch clamp data. All 10 suspected benign variants had wildtype-like function. 22 suspected BrS variants had loss of channel function (<10% normalized peak current) and 23 variants had partial loss of function (10-50% normalized peak current). The 73 previously unstudied variants were initially classified as likely benign (n=2), likely pathogenic (n=11), or VUS (n=60). After the patch clamp studies, 16 variants were benign/likely benign, 47 were pathogenic/likely pathogenic, and only 10 were still VUS. 8/22 loss of function variants were partially rescuable by incubation at lower temperature or pretreatment with a sodium channel blocker. Structural modeling identified likely mechanisms for loss of function including altered thermostability, and disruptions to alpha helices, disulfide bonds, or the permeation pore. ConclusionsHigh-throughput automated patch clamping enabled the reclassification of the majority of tested VUSs in SCN5A.

genetics↗