Craniosynostosis Syndromes Ontology (CSO)
Abstract: Craniosynostosis syndromes (CSs) are patterns of anomalies that mainly affect anatomical structures of the head and the neck. Treatment of these conditions involves surgical, medical and behavioral interventions associated with high costs in terms of health care, emotional disturbance and social exclusion both for the individual and the family. The accurate recognition and phenotypic description of pathognomonic clinical signs that uniquely identify various CFSs is fundamental for effective diagnosis, treatment, determination of prognosis, and genetic counseling.
The low prevalence of these related syndromes presents several diagnostic challenges. These challenges are complicated by overlap between the sets of signs associated with various syndromes and the involvement of diverse organ systems with varying disease presentation due to incomplete penetrance, somatic mosaicism and variable expression.
Continuing advances in human genetics provide further challenges and opportunities. Although the number of reported syndromes grows from year to year, corresponding increases in molecular and genetic understanding offer the potential for genetic testing to diagnose CSs (potentially even pre-natally), target therapies, and inform genetic counseling. Appropriately designed informatics tools will play a critical role in realizing these clinical advances. Systems that provide integrated views of phenotypic and genotypic information about low prevalence syndromes, relevant anatomical structures, and descriptions of specific abnormalities that define clinical phenotypes will help clinicians interpret otherwise inaccessible resources and achieve better outcomes.
Here, we propose an Ontology that provides specific and formal representation of the clinical signs of CSs, highlighting the altered anatomy and the qualities that define the syndromes, with a particular focus on pathognomonic features. In doing so, this Ontology overcomes the semantic heterogeneity, provides a shared understanding of molecular and clinical information, and establishes a source of data interpretable by humans and by computer programs.