Harmonising phenomics information for a better interoperability in the rare disease field

Area of Science:

• Bioinformatics
• Genomics
• Rare Diseases

Background:

• Rare diseases (RD) present diagnostic challenges due to data heterogeneity.
• Existing resources like Orphanet, ORDO, and HPO are valuable but require better integration.
• PhenoTips software facilitates structured phenotypic data capture for RD patients.

Purpose of the Study:

• To develop an integrated, RD-specific bioinformatics ecosystem for harmonized phenomic data.
• To improve interoperability of phenomic information across global databases and patient files.
• To enhance the interpretation of genomic variants for improved RD diagnostics and delineation.

Main Methods:

• Leveraging established resources: Orphanet, Orphanet Rare Disease Ontology (ORDO), and Human Phenotype Ontology (HPO).
• Utilizing PhenoTips software for structured phenotypic data capture and sharing.
• Developing a suite of optimized bioinformatics tools and ontologies.

Main Results:

• Establishment of the HIPBI-RD project, building upon key rare disease resources.
• Focus on harmonizing phenomic information storage for enhanced interoperability.
• Development of an RD-specific bioinformatics ecosystem with tools and ontologies.

Conclusions:

• The HIPBI-RD ecosystem aims to bridge genome-scale biology with a disease-centered view of human pathobiology.
• Harmonized phenomic data collection will improve the diagnostics and delineation of rare diseases.
• The project contributes to a more integrated approach for understanding and managing rare diseases.