A researcher with the University of Kentucky's Sanders-Brown Center on Aging is part of a team who worked to identify genetic variants more accurately in genomic regions known to be involved in disease. In the fields of molecular biology and genetics, a genome is all genetic information for an organism. The basis of the study was that the repetitive nature and complexity of some medically relevant genes pose a challenge to accurately analyze in a clinical setting. The study was recently published in Nature Biotechnology.
"There are many medically relevant genes that are still difficult to accurately resolve for disease diagnosis," Mark Ebbert, Ph.D., assistant professor in the UK College of Medicine. "This new benchmark can help clinical labs and physicians ensure they are identifying genetic variants in these challenging regions."
Ebbert says through their research they identified clear errors in the current human reference genome that is used to identify disease-relevant genetic variants, which prevents clinical labs and physicians from accurately identifying certain variants. They also developed a method to accurately identify variants in these medically relevant genes that increases their ability to identify disease-relevant genetic variants from 8% to 100% (for these genes).
The improvements to this system make it possible to more accurately identify these variants, perhaps providing a clear diagnosis and genetic explanation for some patients that otherwise could not be diagnosed.
"It will absolutely impact patient care and the public," said Ebbert. "Without clear diagnosis and genetic explanation, physicians may not know how to proceed with treatment, and patients are left with questions that cannot be answered. This study will help close that gap for more patients."
Research reported in this publication was supported by the National Institute of General Medical Sciences of the National Institutes of Health under Award Number R35GM138636. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
