What is a Phenopacket?

The Phenopacket Schema represents an open standard for sharing disease and phenotype information to improve our ability to understand, diagnose, and treat both rare and common diseases. A Phenopacket links detailed phenotype descriptions with disease, patient, and genetic information, enabling clinicians, biologists, and disease and drug researchers to build more complete models of disease (see Disease for the distinction between disease and phenotypic feature). The standard is designed to encourage wide adoption and synergy between the people, organizations and systems that comprise the joint effort to address human disease and biological understanding.

While great strides have been made in exchange formats for sequence and variation data (e.g. Variant Call Format) and the GA4GH Variation Representation Specification), complementary standards for phenotypes and environment are urgently needed. For individuals with rare and undiagnosed diseases, broad adoption and appropriate utilization of these standards could improve the speed and accuracy of diagnosis by promoting quicker, more comprehensive, and accurate exchange of information relevant for research and medical care. The development of a clinical phenotype data exchange standard is both necessary and timely. It is necessary because study sizes of well over 100,000 patients are thought to be required to effectively assess the role of rare variation in common disease or to discover the genomic basis for a substantial portion of Mendelian diseases. It is timely because studies of this power are now becoming financially and technologically tractable.

Phenotypic abnormalities of individuals are currently described in diverse places in diverse formats: publications, databases, health records, and even in social media. We propose that these descriptions a) contain a minimum set of fields and b) get transmitted alongside genomic sequence data, such as in VCF, between clinics, authors, journals, and data repositories. The structure of the data in the exchange standard will be optimized for integration from these distributed contexts. The implementation of such a system will allow the sharing of phenotype data prospectively, as well as retrospectively. Increasing the volume of computable data across a diversity of systems will support large-scale computational disease analysis using the combined genotype and phenotype data.

The terms ‘disease’ and ‘phenotype’ are often conflated. The Phenopackets schema uses phenotypic feature to refer to a phenotypic feature, such as Arachnodactyly, that is the component of a disease, such as Marfan syndrome. The Phenopacket proposed here is designed to support deep phenotyping, a process wherein individual components of each phenotype are observed and documented. The phenoptypes may be constitutional or those related to a sample (such as from a biopsy).