David R FitzPatrick

This study uses whole genome sequencing to identify causative variants in mutation-negative Cornelia de Lange Syndrome patients, finding novel genes and regulatory regions involved.

The paper uses deep mutational scanning to quantify PAX6:DNA binding and predict clinical outcomes of variants, finding most pathogenic mutations affect DNA binding.

This paper creates a human embryonic limb cell atlas using single-cell and spatial transcriptomics, identifying novel cell populations and developmental patterns.

The paper identifies SMC3 loss-of-function variants associated with variable growth and developmental features, including some unexpected phenotypes like bone marrow failure and leukemia.

The paper uses optic vesicle organoids to study gene expression and chromatin changes during eye field specification, identifying key transcription factors and regulatory elements.

EyeG2P improves diagnostic genomic testing efficiency for inherited ophthalmic disorders by increasing precision while maintaining high sensitivity.

The paper identifies mosaic chromosomal alterations in children with developmental disorders using SNP array data from the DDD study, finding that many are tissue-specific and undetectable in blood.

IMPROVE-DD integrates multiple phenotype data sources to improve variant evaluation in developmental disorders, showing better diagnostic accuracy and fewer false positives.

This study identifies a critical genomic region on the X chromosome linked to anophthalmia in mice but finds no clear causative mutation, suggesting regulatory changes may underlie the phenotype.

The paper reports diagnostic outcomes from a large-scale genomic study of developmental disorders, identifying factors that influence diagnostic success.

This paper provides recommendations for interpreting non-coding variants in clinical settings, adapting existing guidelines to account for their role in disease.

The paper describes the formation of the Gene Curation Coalition to standardize gene-disease validity terminology and create a unified database for curated gene-disease assertions.

The paper develops automated methods to extract phenotypic features from literature to improve disease modeling for developmental disorders, showing increased accuracy over manual curation.

The paper identifies mutational biases at germline regulatory sites, showing increased structural variants and insertions at transcription factor binding sites, with implications for evolution and disease.

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 rare CRE variants associated with X-linked intellectual disability by combining sequencing, functional assays in zebrafish and mice, and phenotypic analysis.

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 identifies de novo variants in fetal brain enhancers linked to intellectual disability by analyzing genomic data from affected individuals and their parents.

VEP-G2P filters genomic variants for diagnostic purposes, showing higher sensitivity but lower precision for de novo and inherited variants, with significant background noise in controls.

This paper identifies ITPA mutations causing a lethal infantile dilated cardiomyopathy with Martsolf syndrome features and describes the molecular consequences of ITPase deficiency.

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 identifies 9 novel genetic loci, including low-frequency variants in TP53, associated with head circumference and intracranial volume in up to 46,000 individuals.

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.