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Phenotype Data Gets Organized

03/20/2013
Sarah C.P. Williams

A new web-based system for collecting and storing phenotypes makes it easier to find commonalities between rare genetic disorders. Learn more...


At the Baylor-Johns Hopkins Center for Mendelian Genetics, researchers who are trying to pin down the genetic causes of rare disorders have a biweekly meeting to discuss new cases. Often, they’ll recall details of previous patients with similar symptoms that might inform their next steps. Connecting the dots between old and new cases mean not only remembering the patients but also sorting through hard-to-search records.

A new computer system lets scientists quickly pull information from a database of patients with rare disorders, searching by phenotypic features, keywords, or genetic mutations. Source: Bill Branson, NIH




But now, a new computer system developed by the center lets scientists quickly pull information from a database of patients with rare disorders, searching by phenotypic features, keywords, or genetic mutations. The program, called PhenoDB, aims to provide a better organization system for phenotype data not only for researchers at the center but also other geneticists around the world.

“We wanted the ability for someone to give a head to toe description of a patient, as deep as they knew, in a way that would then be searchable,” explained Ada Hamosh, the clinical director of the McKusick-Nathans Institute of Genetics Medicine at Johns Hopkins School of Medicine and first author of a new paper describing the features of the tool, published online this month in the journal Human Mutation (1). “There are no other tools that allow you to collect standardized phenotypic information,” she said.

PhenoDB is based on a set of 2900 clinical terms that describe phenotypes exhibited by a patient. They are grouped into categories so a researcher can easily zoom into the correct set of terms—if they check a box indicating abnormalities in the respiratory system, for example, a new set of phenotypic categories appear, allowing the researcher to narrow in on the symptoms.

Once they’ve gotten to the most specific phenotype, additional details can be added to a text box. Additional anonymized patient information includes family history information, a record of patient consent forms, and details on genetic tests conducted.

To test PhenoDB out, Hamosh and colleagues at Johns Hopkins and Baylor added 572 families and five research cohorts to the database and then used it for a nine month trial period. The database worked smoothly, and now they are planning to add new features, like a genetic analysis module and better pedigree mapping.

“Now, any researcher anywhere can take this package and use it,” said Hamosh. “To customize it is trivial, and to learn to use it is easy.”

Each institution or researcher using the program will only have access to their own data, but Hamosh said that in the future the database could be combined with electronic health records in a wider patient setting, allowing researchers to study phenotypes across large populations. And PhenoDB could someday contain information that can help make clinical decision making even easier—recommending tests or drugs based on a patient entry.

For now, Hamosh said, “the takeaway message is that PhenoDB is a fully integrated research tool to collect phenotypic data, genetic data, and family history data for any research project that uses whole exomes or full genomes.”

References

1. Hamosh, A., N. Sobreira, J. Hoover-Fong, V. R. Sutton, C. Boehm, F. Schiettecatte, and D. Valle. 2013. PhenoDB: A new Web-Based tool for the collection, storage, and analysis of phenotypic features. Human mutation (February).