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Aligning Orphanet Classification to Identify Disease Characteristics among Rare Disease Clusters.

Sungrim Moon¹, Jessica Maine¹, Ewy Mathe¹

¹Division of Preclinical Innovation, National Center for Advancing Translational Sciences National Institutes of Health Rockville, Maryland, USA.

Proceedings. IEEE International Conference on Bioinformatics and Biomedicine

|September 12, 2025

Summary

Investigating rare disease etiologies using Orphanet classifications revealed significant links. Rare developmental defects and inborn errors of metabolism show promise for future rare disease research and drug discovery.

Keywords:

Orphanet classification disease cluster rare disease rare disease characteristics

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Area of Science:

Genetics and Genomics
Rare Diseases
Bioinformatics

Background:

Understanding rare disease etiologies is crucial for advancing research.
Facilitating basket trial design and drug repurposing requires knowledge of shared disease mechanisms.
Current classification systems may not fully capture the etiological relationships between diverse rare conditions.

Purpose of the Study:

To align clusters of rare diseases with Orphanet classifications to represent shared etiologies.
To establish a foundation for biological mechanism discovery in rare diseases.
To identify specific Orphanet categories with significant associations to rare disease clusters.

Main Methods:

Utilized linearized Orphanet categories for classification.
Connected 35 distinct clusters of rare diseases into 18 Orphanet classifications.
Performed association analysis between disease clusters and Orphanet categories.

Main Results:

Successfully linked rare disease clusters to established Orphanet classifications.
Identified significant associations between "Rare Developmental Defects During Embryogenesis" and rare disease clusters.
Found significant associations between "Rare Inborn Errors of Metabolism" and rare disease clusters.

Conclusions:

The Orphanet classification system provides a valuable framework for understanding rare disease etiologies.
Rare diseases with developmental or metabolic origins represent key areas for future research.
This etiological framework supports targeted investigation for biological mechanisms and therapeutic strategies.