Rare Disease and Phenotyping

Rare neurological disease research depends on computable phenotype descriptions, cross-database disease classifications, and standardised data exchange to aggregate the small patient numbers that characterise this domain.

Standards and ontologies

HPO (Human Phenotype Ontology) and ORDO (Orphanet Rare Disease Ontology) are the primary phenotyping standards for rare neurological disease, used to describe clinical features and disease entities in a computable form. MP (Mammalian Phenotype Ontology) is the model-organism counterpart to HPO, co-maintaining a cross-species mapping with it so that mouse and rat phenotype data can be matched to human disease phenotypes for model discovery and disease-gene prediction. MONDO harmonises disease classifications across ICD-10, OMIM, and ORDO into a unified disease hierarchy, enabling cross-database querying and dataset integration. Phenopackets (the GA4GH Phenopacket Schema) is the standard for computable genotype-phenotype data exchange, capturing HPO phenotypic features, diagnoses, and variant data in a single structured package. GA4GH develops and maintains both VRS and Phenopackets as part of its rare disease and clinical genomics framework.

Data archives

ClinVar is the NCBI (National Center for Biotechnology Information) reference database for variant pathogenicity classifications, aggregating submissions from clinical laboratories worldwide and assigning consensus classifications based on submitted evidence. ClinGen expert panels cover hereditary neurological diseases and provide the highest evidence tier in ClinVar, with curated gene-disease validity and variant pathogenicity classifications used by neurogenetics laboratories globally. BBMRI-ERIC promotes Phenopackets and OMOP CDM for cross-biobank discoverability across European biobank networks.

For the clinical data models and interoperability infrastructure that connect rare disease phenotyping to health data platforms, see Health. For variant formats and sequence archives, see Genomics.