Researchers create search engines linking diseases and observable traits


Imagine this scenario: A patient presents to a doctor with a constellation of symptoms and physical traits that at first glance do not lead to an obvious diagnosis. Perhaps the patient has facial abnormalities and heart symptoms, as well as other issues with the skeleton and joints. The provider suspects that these symptoms are related to an illness due to an underlying genetic mutation, but is unsure of where to look.


A screenshot of the new search engine functionality
Enter PhenCards, a new data resource and search engine created by researchers at Children’s Hospital of Philadelphia (CHOP) that links existing biomedical knowledge to observable human traits, also known as phenotypes. Pulling data from dozens of existing databases related to phenotypes, genetics, drug development, NIH funding and more, PhenCards allows researchers to focus on potential diagnoses, causal genetic pathways, and collaborators who are already studying the disease or similar diseases.

“Providing all of this data on a single web server will allow clinicians, researchers and genetic counselors to add new layers of information to previously limited genetic studies and make more informed clinical decisions,” said Kai Wang, PhD, Associate Professor of Pathology and Laboratory Medicine at CHOP and lead author of the article describing the new search engine. “We sincerely hope that with the participation of researchers and the community, we can add even more useful knowledge to our web server.”

PhenCards allows users to search by a single phenotypic trait – cleft palate, for example, or by pasting in the text of a fully anonymized clinical note, from which phenotypic terms are extracted by the search engine. The program’s disease prediction algorithm ranks the most likely associated diseases and provides information on potential candidate genes and pathways, ongoing clinical trials, and potential collaborators and funders for future research. The site is particularly useful for rare diseases, for which information may be limited.

“PhenCards gives researchers the best possible chance of identifying a disease by comparing its phenotypic traits to similar diseases and even providing new candidate genes,” said the first author James M. Havrilla, a bioinformatics scientist in Wang’s lab. “Our goal is to provide both a one-stop shop and a sustainable, continuously updated resource that will allow us to deepen our understanding of human health and rare and common diseases.”

Learn more about PhenCards in Finders paper, published in Genome Medicine.

/ CHOP press release. This material is from the original organization and may be ad hoc in nature, edited for clarity, style and length. View full here.

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