BSO-AD: An Ontology for Representing and Harmonizing Behavioral Social Knowledge in ADRD
Objective: RD (BSO-AD) to represent and integrate BSFs with respect to ADRD. Material and Methods: BSO-AD was developed following established ontology design principles, prioritizing reuse of existing ontology elements to ensure semantic interoperability. It was built upon the Social Determinants of Health Ontology (SDoHO) and the Drug-Repurposing Oriented Alzheimer's Disease Ontology (DROADO). BSF-related classes were enriched with ICD-10-CMZ55-Z65 codes and ADRD-related classes with AD-Onto. Relationships between BSFs and ADRD were derived through literature mining. Ontology quality was evaluated through Hootation-based expert review and an LLM-assisted framework assessing structural coverage and semantic coherence. Results: BSO-AD contains 2,275 classes, 153 object properties, and 49 data properties. Expert review demonstrated strong rational agreement (0.95), with disagreements resolved through discussion. LLM-based evaluation showed high category coverage rates (≥ 0.97) and robust semantic alignment with the relevant literature (average completeness = 0.79; conciseness = 0.94). Discussion and Conclusion: BSO-AD is, to our knowledge, the first ontology to systematically represent BSFs and hierarchically model their interrelationships in ADRD. It establishes a semantic backbone for computational analysis and knowledge integration. The LLM-assisted evaluation framework demonstrates the feasibility of scalable, automated ontology assessment.
Authors
- Avanti Bhandarkar (ORCID: https://orcid.org/0000-0002-9297-5029)
- Yutong Hu (ORCID: https://orcid.org/0000-0001-5339-3782)
- Na Zhao
- Cui Tao
- FANG LI
- Rakesh Kumar
- Haifang Li
- Weiguo Cao
- Isaac Heath Clark
- Yue Yu
Institutions
- Emory University (US)
- Mayo Clinic in Florida (US)
Publication Details
- Journal
- medRxiv
- Published
- 2026-03-31
- DOI
- https://doi.org/10.64898/2026.03.30.26349756
- Primary Topic
- Biomedical Text Mining and Ontologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Institute of Mental Health