Roddy Walsh

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

The paper evaluates the clinical validity of heterozygous ALPK3 loss-of-function variants as a cause of hypertrophic cardiomyopathy, finding strong gene-disease association with reduced penetrance.

This study evaluates polygenic scores for hypertrophic cardiomyopathy (HCM) in the general population and clinical settings, showing increased risk with higher scores and potential for clinical application.

The paper identifies a rare non-coding enhancer variant in SCN5A associated with Brugada syndrome in Thailand, showing it disrupts a transcription factor binding site and reduces sodium current.

The paper structures evidence on inheritance, allelic requirement, and variant classes for inherited cardiac conditions to improve variant filtering in genomic testing.

This paper introduces Paralogue Annotation, a method using homologous protein variants to predict disease-causing missense variants with high precision.

This study examines the clinical impact of rare variants in HCM-associated genes in the UK Biobank, finding that pathogenic variants are linked to increased cardiovascular risk and subclinical phenotypes, while non-pathogenic variants show minimal effect.

The paper identifies a frameshift variant in MYH7 associated with HCM in an Egyptian cohort, revealing a new pathogenic mechanism involving distal PTC escape from NMD.

The paper curates and classifies genetic evidence for dilated cardiomyopathy (DCM), identifying 19 genes with strong or moderate evidence and highlighting gaps in understanding.

This study identifies genetic overlaps and distinct variant classes in LVNC compared to DCM and HCM, revealing both shared and unique genetic mechanisms.

The paper describes the EHVol study, a genomic database of 391 Egyptian healthy volunteers to improve representation in global genomic databases and aid in variant interpretation for North African populations.

This paper introduces CardioBoost, a disease-specific variant classifier for inherited cardiac conditions, showing improved accuracy in predicting pathogenicity compared to genome-wide tools.

The paper quantifies variant pathogenicity in hypertrophic cardiomyopathy using etiological fraction, increasing actionable variant detection by 14-20%.

The paper responds to a critique of their variant filtering method, demonstrating its robustness and highlighting the benefits of using high-resolution variant frequencies for clinical genome interpretation.

CardioClassifier is a decision-support tool for inherited cardiac conditions that improves variant interpretation by integrating disease-specific annotations and case data.

The paper presents a statistical framework to filter candidate disease-causing variants using high-resolution variant frequencies, reducing the number of variants under consideration and reclassifying some as pathogenic.

The paper reassesses the pathogenicity of Mendelian genes by comparing rare variation frequencies between cardiomyopathy cases and large reference datasets, identifying false positives and overly conservative variant assessments.