The study, published this month in Public Library of Science (PLoS), represents the collaborative work of Yale School of Medicine, Applied Biosystems, and Celera Diagnostics. TAAs occur in the part of the aorta that passes through the chest. They can become huge without causing symptoms. In fact, only one in 20 patients has symptoms before internal rupture occurs—making advance detection key to treatment. Once the aneurysm ruptures, a person can go into shock and die from internal bleeding.
Currently detection of these aneurysms is made by relatively expensive tests such as a chest X-ray or CT scan—typically when a patient is being evaluated for other conditions.
"A standardized blood-based test capable of detecting individuals at risk for aneurysm disease would represent a major advance in clinical care," said John Elefteriades, M.D., section chief of cardiothoracic surgery. "This study indicates we may be able to develop such a test."
In this study Elefteriades and his colleagues took blood samples from 58 persons diagnosed with TAA disease and 36 spouses who did not have the disease. Using a gene expression profiling technology, they identified a 41-gene signature in blood cells that distinguishes TAA patients from those without the disease.
The gene expression signature and the prediction model were identified using a complete workflow of instruments, reagents, and software from Applied Biosystems. These signature genes were further validated using TaqMan® real-time PCR assays. The accuracy rate in various analyses is 78 percent to 85 percent.
"It has become increasingly evident that the immune system plays a pivotal role in the development of aortic aneurysms," Elefteriades said. "We thus hypothesized that gene expression patterns in peripheral blood cells may reflect TAA disease status."
The next step, which the researchers say is underway, is validation in real-time clinical studies. The investigative team is also interested in determining if abdominal aneurysms share a similar RNA signature, and if the RNA can predict rupture or dissection of an aneurysm.
Source: YALE University