Andrew Michael Glazer

The paper investigates E-rich domain variants of RBM20, showing they reduce protein abundance and cause splicing defects, but are not rescued by RBM20 overexpression.

The paper develops a multidimensional assay to assess variant effects in MYBPC3, reclassifying variants and uncovering disease mechanisms in hypertrophic cardiomyopathy.

This study identifies rare and low-frequency non-coding variants at the SCN5A locus associated with Brugada syndrome using whole-genome sequencing and functional assays.

The paper maps the functional landscape of KCNQ1 variants to identify pathogenic and benign variants, revealing their impact on arrhythmia risk and ion channel mechanisms.

The paper uses automated patch clamp data to reclassify SCN5A variants in Brugada Syndrome, improving variant classification and penetrance stratification.

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.

This paper introduces ParSE-seq, a multiplexed assay to assess splice-altering variants, showing high correlation between experimental and computational predictions.

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

The paper validates an in vitro SCN5A Brugada Syndrome assay to reclassify variants of uncertain significance as pathogenic or benign.

The paper identifies a novel SCN5A variant, E171Q, that creates a gating pore current by neutralizing a negative charge in the S2 helix, leading to MEPPC and altered voltage dependence.

This study maps the functional effects of thousands of KCNE1 variants using high-throughput methods, identifying loss-of-function and loss-of-surface expression variants and showing concordance with electrophysiological and computational data.

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 shows that most SCN5A missense loss-of-function variants cause dominant negative effects and are associated with higher Brugada Syndrome risk.

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

Neptune delivers structured genomic data to EHR systems through customizable reports and variant reanalysis, supporting over 15,000 clinical reports.

This study reclassifies SCN5A variants using high-throughput patch clamping, finding most variants of uncertain significance are either benign or pathogenic.

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.

The paper performs a deep mutational scan of SCN5A variants to assess their functional impact, identifying 40 gain and 33 loss of function variants with high accuracy.

The paper develops a Bayesian method to estimate penetrance of disease-associated variants using sparse data and applies it to SCN5A variants in Brugada syndrome.

The paper identifies HFE E168Q as a novel pathogenic variant associated with hereditary hemochromatosis using Phenotype Risk Scores and validates its mechanism through experimental assays.