NATIONAL HARBOR, Maryland — One of the commonly used phrases in the rare disease community describes a patient’s “diagnostic odyssey” – a term that denotes the length of time, number of providers, frequent misdiagnoses, and emotional turmoil that accompanies the journey to obtaining an accurate diagnosis of a rare disease.
Multiple organizations, researchers, scientists, curators, authors, and clinicians have jointly contributed to the development of “Phenopackets” to combat this diagnostic odyssey and provide clinicians with precise and accurate information regarding disease characteristics.
Phenopackets link detailed phenotypic descriptions of diseases, patients, and genetic information with the intent to increase the available clinical phenotypic information for research and more accurate diagnosis of rare diseases.
Christopher Chute, MD, a Bloomberg Distinguished Professor of Health Informatics at Johns Hopkins University, Baltimore, Maryland, remarked in a video presentation at the 2021 World Orphan Drug Congress that “phenotyping is difficult to document well, so how do we systematically and concisely characterize disease manifestations in a way that can be machine readable?”
The advantage of using human phenotype ontology is the ability to formally characterize a patient’s disease manifestations in the Phenopacket structure, using up to 14,000 descriptive terms. In this way, clearer delineation between disease variants might become recognizable. Currently, “fuzzy phenotype matching” occurs when individuals have the same disease and gene affected, but not the same variant, which may hinder accurate diagnosis.
Phenopackets uses the framework of HL7 FHIR, which stands for Fast Healthcare Interoperability Resources. FHIR is a modeling language supporting Resource Oriented Architecture (ROA) to exchange healthcare information using various software such as JAVA, C++, and Python. This data may then be stored on different computer systems.
Dr. Chute asserted that “there is an aspiration to facilitate diagnostic integration using tools and resources like the Phenopacket which is bound to . . . human phenotype ontology, and leveraging the disease-manifestation relationships that are explicit in the human phenotype ontology . . . almost 200,000 associations.”
Once these descriptors of the patient’s phenotype are entered into the Phenopacket structure, precise interpretation of the data using machine reading is feasible in order to facilitate understanding and disambiguation of what is happening with a particular individual’s rare disease manifestation.
MIT Researchers Use Machine Learning to Improve DMD Drug Delivery
Widespread use of Phenopackets by model databases, medical data repositories, commercial industries, and medical journals can facilitate research and development of new modes of treatment and drug discovery, translational research, and precision medicine within the rare disease community.
One of the many organizations supporting the development of Phenopackets is the Global Alliance for Genomics and Health (GA4GH). Their intent is for Phenopackets to “accelerate progress in genomic science and human health by developing standards and framing policy for responsible genomic research.”
Dr. Chute affirmed that Phenopackets are becoming more frequently used by the rare disease community. Perhaps GA4GH’s goal is attainable, as more organizations and people recognize the benefit of a standardized, sharable means of characterizing rare disease phenotypes.
References
Impact of interoperable phenotypic clinical data for advancing research and diagnosis for rare disease: case study of Phenopackets. Presented at: World Orphan Drug Congress USA 2021: August 25, 2021; National Harbor, MD.
Phenopackets. Accessed August 25, 2021.
Sutner S. What is FHIR? Search Health IT. Accessed August 25, 2021.
