The 2020 NHGRI Strategic plan highlights the need for facilitating data and resource interoperability for advancing genomic research and promoting data reuse. The Human Disease Ontology (DO) Knowledgebase will provide a sustainable approach for linking the growing bodies of information related to core datasets across genomic and proteomic resources, as interoperable genomic resources enable precision medicine and knowledge dissemination. The DO plays a key role in disease knowledge organization, representation, and standardization, serving as a reference framework for multiscale biomedical data integration and analysis across thousands of clinical, biomedical and computational researchers and genomic resources around the world. Expanding the DO’s disease data and models for complex diseases will provide a comprehensive network of disease to disease relationships (DO’s diseasome) that represents a disease feature similarity network for clinical differential diagnosis exploration. We will deepen our knowledge and understanding of the interrelationships between genomics and the social and environmental factors that influence human health. We will deliver an increasingly comprehensive view of the roles and relationships of genomic variation, biomolecules, environmental drivers and regulatory elements on biological processes, and address the need for genomics training in the clinical workforce. We will build beyond the current set of coordinating genomic resources, offering increasingly automated approaches for aggregating and linking disease metadata in a scalable and cost-effective manner. The DO Knowledgebase will expand content, capacity to support the development of genomic data science and machine learning/artificial intelligence (ML/AI) methods. The overall goal of this proposal is to facilitate the linking of disease data via the DO’s diseaseome across broadly useful biomedical, clinical genomic, proteomic and epigenomic resources, to drive innovative machine learning research and to provide a resource for optimizing clinical care. The DO serves as the de facto standard for disease etiology across biomedical data repositories. Conservatively, based on available resource statistics, terms from the DO have been annotated to over 1.5 million biomedical data elements and citations, a 10x increase in the past 5 years. Our proposed aims position us well for providing a comprehensive disease resource for the genomic community. We have identified three main areas of improvement in the DO Knowledgebase to achieve our goals: (1) aggregating disease information across genomic resources, modeling complex disease and defining the disease environmental exposome; (2) automating the DO’s production workflow, enabling federated resource querying, producing a multi-lingual DO and dissemination of ML/AI ready datasets; (3) maintaining and expanding the DO’s collaborations, establishing a clinical training nosology program and convening topical focus groups.

PUBLIC HEALTH RELEVANCE. The overall goal of this proposal is to develop a comprehensive network of disease-to-disease relationships to facilitate linking of data across broadly useful genomic and proteomic resources via the Human Disease Ontology (DO) Knowledgebase. Success of this study will address a significant barrier in data interoperability between these disparate resources. Ultimately, the DO’s large-scale integration of disease knowledge into a hierarchical classification framework will aid researchers in better understanding alternative mechanisms of disease, thus driving innovative machine learning approaches, optimizing clinical care and making disease-related data Findable, Accessible, Interoperable, and Reusable (FAIR).