Koenraad Devriendt

The paper demonstrates that integrating CNV detection into exome sequencing analysis improves diagnostic yield for developmental disorders in the DDD-Africa cohort by 8.3% without additional costs.

The paper analyzes cfDNA methylome and fragmentome profiles from healthy individuals to identify cell-type and demographic signatures influencing cfDNA characteristics.

The paper identifies WAPL as a novel cohesinopathy gene and driver of a genomic disorder, showing its role in developmental delay and other anomalies through clinical, in vitro, and in vivo analyses.

A randomized trial compares genome sequencing to standard of care in diagnosing developmental disorders, finding higher diagnostic yield with genome sequencing.

This study demonstrates that nanopore sequencing can detect episignatures in developmental disorders, matching microarray results and identifying pathogenic variants.

The paper investigates the mechanisms behind the high incidence of 22q11.2 deletion syndrome by analyzing recombination events and paralogous structures in LCR22 regions.

This paper identifies loss-of-function variants in ZFHX3 as a cause of syndromic intellectual disability and describes its role in chromatin remodeling and DNA methylation.

The paper introduces an AI-driven method that uses facial images to prioritize exome data, achieving 99% top-10 accuracy in identifying disease-causing genes.

The paper identifies NOTCH1 variants as a major genetic contributor to non-syndromic Tetralogy of Fallot, with 6% of patients carrying deleterious variants.