Phenogenon: Gene to phenotype associations for rare genetic diseases

• DOI: 10.1371/journal.pone.0230587
• Publication Date: 2020-04-09T17:30:45Z
• Authors: Nikolas Pontikos; Cian Murphy; Ismail Moghul; Gavin Arno; Kaoru Fujinami; Yu Fujinami; Dayyanah Sumodhee; Susan Downes; Andrew Webster; Jing Yu
• Keywords: 0301 basic medicine; Genotype; Science; Skin Diseases; Cohort Studies; Nail Diseases; 03 medical and health sciences; Rare Diseases; 3-Oxo-5-alpha-Steroid 4-Dehydrogenase; Gene Frequency; Databases, Genetic; Retinal Dystrophies; Humans; Genetic Predisposition to Disease; Genetic Association Studies; Monomeric GTP-Binding Proteins; 0303 health sciences; Q; R; Genetic Diseases, Inborn; Computational Biology; High-Throughput Nucleotide Sequencing; Membrane Proteins; 3. Good health; DNA-Binding Proteins; Phenotype; Medicine; Research Article; Transcription Factors

As high-throughput sequencing is increasingly applied to the molecular diagnosis of rare Mendelian disorders, a large number of patients with diverse phenotypes have their genetic and phenotypic data pooled together to uncover new gene-phenotype relations. We introduce Phenogenon, a statistical tool that combines, Human Phenotype Ontology (HPO) annotated patient phenotypes, gnomAD allele population frequency, and Combined Annotation Dependent Depletion (CADD) score for variant pathogenicity, in order to jointly predict the mode of inheritance and gene-phenotype associations. We ran Phenogenon on our cohort of 3,290 patients who had undergone whole exome sequencing. Among the top associations, we recapitulated previously known, such as "SRD5A3-Abnormal full-field electroretinogram-recessive" and "GRHL2 -Nail dystrophy-recessive", and discovered one potentially novel, "RRAGA-Abnormality of the skin-dominant". We also developed an interactive web interface available at https://phenogenon.phenopolis.org to visualise and explore the results.