Giuseppe Gallone

The paper investigates the role of rare inherited coding variants in developmental disorders by analyzing family and case/control data, finding significant burdens of damaging variants and estimating their population attributable risk.

The paper evaluates CNV detection from exome sequencing in the DDD study, finding it has higher sensitivity than low-resolution CMA and comparable sensitivity to exon-resolution CMA.

The paper identifies genetic and chemotherapeutic causes of germline hypermutation by analyzing genome-wide sequences of families with rare genetic diseases.

TADA prioritizes pathogenic CNVs using functional annotations and machine learning, achieving high AUC scores for deletions and duplications.

InDelible detects cryptic structural variants in exome sequencing data, improving diagnostic yield for developmental disorders by identifying variants missed by standard methods.

The paper identifies non-coding variants upstream of MEF2C causing severe developmental disorder through three distinct loss-of-function mechanisms, showing their diagnostic importance in existing exome datasets.

The paper analyzes X-linked coding variation in developmental disorders, finding similar rates in males and females and estimating pathogenicity of inherited variants.

The paper integrates healthcare and research exome sequences to identify 28 novel developmental disorder-associated genes using a simulation-based statistical test.

The paper identifies 299 new genes associated with developmental disorders using exome data from 31,058 trios and finds many more likely remain undiscovered.

The paper identifies retrotransposition events in developmental disorders using exome sequencing data from the DDD study and shows their evolutionary constraints.

The paper analyzes exome sequencing data to assess the contribution of splice site mutations to developmental disorders and estimates their pathogenicity and underrepresentation in public databases.

The paper estimates the contribution of recessive coding variants to developmental disorders using exome data from 7,448 families, finding low prevalence in European ancestry but higher in Pakistani ancestry.

The paper shows that common genetic variants contribute to risk and clinical variation in severe neurodevelopmental disorders, even in individuals with known monogenic diagnoses.

The paper identifies de novo mutations in fetal-brain active regulatory elements as a cause of 1-3% of neurodevelopmental disorders in patients without coding variants.

The paper identifies genetic variants affecting vitamin D receptor binding and links them to autoimmune diseases.