A novel FGD1 mutation in a family with Aarskog-Scott syndrome and predominant features of congenital joint contractures

A novel truncating variant in the FGD1 gene associated with Aarskog-Scott syndrome in a family previously diagnosed with Tel Hashomer camptodactyly

Tel Hashomer camptodactyly syndrome is a long-known entity characterized by camptodactyly with muscular hypoplasia, skeletal dysplasia, and abnormal palmar creases. Currently, the genetic basis for this disorder is unknown, thus there is a possibility that this clinical presentation may be contained within another genetic diagnosis. Here, we present a multiplex family with a previous clinical diagnosis of Tel Hashomer camptodactyly syndrome. Whole exome sequencing and pedigree-based analysis revealed a novel hemizygous truncating variant c.269_270dup (p.Phe91Alafs*34) in the FGD1 gene (NM_004463.3) in all three symptomatic patients, congruous with a diagnosis of Aarskog-Scott syndrome. Our report adds to the limited data on Aarskog-Scott syndrome, and emphasizes the importance of unbiased comprehensive molecular testing toward establishing a diagnosis for genetic syndromes with unknown genetic basis.

PhenCards: a data resource linking human phenotype information to biomedical knowledge

We present PhenCards ( https://phencards.org ), a database and web server intended as a one-stop shop for previously disconnected biomedical knowledge related to human clinical phenotypes. Users can query human phenotype terms or clinical notes. PhenCards obtains relevant disease/phenotype prevalence and co-occurrence, drug, procedural, pathway, literature, grant, and collaborator data. PhenCards recommends the most probable genetic diseases and candidate genes based on phenotype terms from clinical notes. PhenCards facilitates exploration of phenotype, e.g., which drugs cause or are prescribed for patient symptoms, which genes likely cause specific symptoms, and which comorbidities co-occur with phenotypes.

The Prevalence of Clinical Features in Patients with Aarskog-Scott Syndrome and Assessment of Genotype-Phenotype Correlation: A Systematic Review

Aarskog–Scott syndrome is a genetically and clinically heterogeneous rare condition caused by a pathogenic variant in the FGD1 gene. A systematic review was carried out to analyse the prevalence of clinical manifestations found in patients, as well as to evaluate the genotype-phenotype correlation. The results obtained show that clinical findings of the craniofacial, orthopaedic, and genitourinary tract correspond to the highest scores of prevalence. The authors reclassified the primary, secondary, and additional criteria based on their prevalence. Furthermore, it was possible to observe, in accordance with previous reports, that the reported phenotypes do not present a direct relation to the underlying genotypes.

Phen2Gene: rapid phenotype-driven gene prioritization for rare diseases

Human Phenotype Ontology (HPO) terms are increasingly used in diagnostic settings to aid in the characterization of patient phenotypes. The HPO annotation database is updated frequently and can provide detailed phenotype knowledge on various human diseases, and many HPO terms are now mapped to candidate causal genes with binary relationships. To further improve the genetic diagnosis of rare diseases, we incorporated these HPO annotations, gene-disease databases and gene-gene databases in a probabilistic model to build a novel HPO-driven gene prioritization tool, Phen2Gene. Phen2Gene accesses a database built upon this information called the HPO2Gene Knowledgebase (H2GKB), which provides weighted and ranked gene lists for every HPO term. Phen2Gene is then able to access the H2GKB for patient-specific lists of HPO terms or PhenoPacket descriptions supported by GA4GH (http://phenopackets.org/), calculate a prioritized gene list based on a probabilistic model and output gene-disease relationships with great accuracy. Phen2Gene outperforms existing gene prioritization tools in speed and acts as a real-time phenotype-driven gene prioritization tool to aid the clinical diagnosis of rare undiagnosed diseases. In addition to a command line tool released under the MIT license (https://github.com/WGLab/Phen2Gene), we also developed a web server and web service (https://phen2gene.wglab.org/) for running the tool via web interface or RESTful API queries. Finally, we have curated a large amount of benchmarking data for phenotype-to-gene tools involving 197 patients across 76 scientific articles and 85 patients' de-identified HPO term data from the Children's Hospital of Philadelphia.