Elizabeth Goldmuntz

This study examines congenital heart disease in individuals with distal 22q11.22-23 deletions, finding lower prevalence compared to proximal deletions and identifying specific cardiac anomalies.

This study uses AI to show that genome sequencing can predict adverse outcomes after congenital heart defect surgery by identifying damaging genotypes in specific genes.

The paper examines how genetic, demographic, and clinical factors interact to influence neurodevelopmental outcomes in children with single ventricle heart disease.

The paper identifies chromatin regulatory genes as genetic modifiers of conotruncal heart defects in 22q11.2 deletion syndrome and links them to sporadic congenital heart disease.

The paper identifies mosaic mutations in blood and cardiac tissue from CHD patients, finding 1% of cases have detectable mosaic variants that may contribute to congenital heart disease.

The paper introduces MEM, a method to identify deletion CNVs in WES and WGS trio data by clustering Mendelian errors, achieving high validation rates and detecting additional de novo deletions and contamination.