New tool to link symptoms with potential genetic causes developed at HudsonAlpha

A new tool released this week by a team of researchers at the HudsonAlpha Institute for Biotechnology, a nonprofit genetics and genomics research institute in Huntsville, Ala., aims to change the way doctors diagnose challenging genetic disorders by working the problem from a new angle. It can help researchers improve their understanding of the role of genetics in complicated health puzzles.

Matt Holt, PhD, and Brandon Wilk; researchers under the direction of Liz Worthey, PhD, director of the software development and informatics lab, developed PyxisMap to transform the way clinicians narrow down the list of genetic variants that may be responsible for a patient’s condition.

Worthey explains, “After a genome is sequenced, analysts have to sift through the data to determine which of the millions of variants are causing disease in a particular patient.”

PyxisMap collects the symptoms of a patient in the form of free text or ordered lists, then runs the extracted terms against a data structure containing relationships between these symptoms (or phenotype terms) and genes and variants in order to rank these genomic regions based on disease associations. Importantly, the tool is able to use the most up to date information by incorporating the latest data from academic journals, meaning the software doesn’t solely rely on disease databases that can often be months out of date in a field that changes daily.

That’s a new approach from Worthey’s last tool, CODICEM, which focused on studying the likely impact of genetic variants that were identified in patients. Focusing on the variant data alone leaves potentially hundreds of variants for the clinical analysts to review. Although these variants have been prioritized because of characteristics that make them seem deleterious, the vast majority turn out to be wholly unrelated to the patient’s symptoms.

Now, by attacking the problem from both axes, genomic researchers and clinicians should have an even greater chance of quickly identifying the genetic variant or variants causing the patient’s condition. Worthey notes, “By combining both the variant impact analysis and the phenotype ranking tools, you can quickly begin to understand exactly what is causing an individual patient’s disease.”

Improving that diagnostic process can dramatically impact the lives of patients, as many of them have searched for an explanation for their rare ailments for years. Even just identifying a potentially pathogenic variant within a gene can finally start these patients on a path toward effective treatment.

Worthey’s team debuted the tool at Intelligent Systems for Molecular Biology (ISMB) conference in Chicago. The tool is already being used to dramatically improve the effectiveness and efficiency of the WGS diagnostic process in order to provide accurate diagnoses.