Clusters of genes within human aortas appear to predict risk for atherosclerosis

Duke University Medical Center researchers have identified specific clusters of genes within human aortas that appear to predict with great specificity which patients may be at highest risk for developing atherosclerosis, as well as the severity of the disease.

For the researchers, this is an important first of many steps toward developing highly individualized approaches to identifying and treating atherosclerosis that are tailored to and informed by a patient's unique genetic make-up.

Atherosclerosis is a disorder marked by the thickening and clogging of blood vessels, which over time can deprive the heart of necessary oxygen and nutrients. While factors such as diet, smoking, cholesterol levels and inactivity are important in the development of atherosclerosis, the researchers said that heredity plays a crucial role in how the body responds to these environmental factors.

"Instead of trying to find a specific gene that might be implicated in the development atherosclerosis, we took the novel approach of trying identify clusters of genes that may help us better understand the progression of the disease," said Duke cardiologist David Seo, M.D. The results of the Duke research are scheduled to appear in the October 2004 issue of the journal Arteriorsclerosis, Thrombosis and Vascular Biology and are published early on-line at http://atvb.ahajournals.org.

"In a complex disorder like atherosclerosis, it is not likely that only one gene is involved, but many different ones that interact with each other," said Seo.

Specifically, the researchers found that their new model could predict with 93.5 percent accuracy the extent of atherosclerosis. It could also predict with 93.6 percent accuracy the location of atherosclerotic lesions.

"This study is the foundation of future research and was absolutely critical study in demonstrating that we can indeed refine genomic techniques to address the risk for complex disorders like atherosclerosis," said cardiologist Pascal Goldschmidt, M.D., senior member of the research team and chairman of Duke's Department of Medicine.

"After seeing the results of this study, I am extremely encouraged that at some point after further research we will be able to help fulfill the promise of personalized medicine," Goldschmidt. "This would not have been possible without the collaborations across this institution, as well as the support of the National Institutes of Health."

For their experiments, the research collected more than 60 fresh aorta samples from humans whose hearts had been harvested for organ transplantation. The aorta, the body's largest artery, takes blood ejected from the heart and distributes it throughout the body via smaller arteries. The samples ranged from healthy to severely diseased.

The researchers then "mapped" not only the degree of atherosclerotic plaque development, but also the locations of the plaque within the aorta. Location of the plaque is an important indicator of disease susceptibility, the researchers said, because atherosclerosis tends to progress toward the heart.

Once the samples were mapped by defined segments, the researches then performed a DNA microarray, or gene chip, analysis of each region. Using this new technique, researchers can quickly screen more than 12,500 known genes, searching for those that are "turned on," or are expressing themselves.

In terms of severity of disease, the researchers found a cluster of 208 genes that predicted severe disease in 29 out of 31 (93.5 percent) tissues samples, and a cluster of 28 genes that predicted location of disease in 59 out of 63 samples (93.6 percent).

In general, many of the genes found within the clusters were known to researchers, although there was very little overlap between genes identified in the severity and locations groups. The genes in the severity cluster tended to be involved in the inflammation process, while those related to susceptibility tend to mediate cellular responses that occur prior to the inflammatory process.

"While the methods we used to identify these genes do not have immediate clinical applications, they do play an important role in identifying genes for further study," Seo said. "The identification of these genes advances our understanding of the biological pathways relevant to atherosclerosis.

"Many of these genes are likely to be implicated in the disease process and may become targets of future therapies," Seo continued. "By identifying variants within these genes, we may be able to identify combinations of such variants that when taken together with known clinical risk factors, may lead to new prognostic and diagnostic tools for cardiovascular disease."

The research team plans further studies in animal mouse models of atherosclerosis to further refine their techniques. Since it is not practical to test samples of aortas in living patients, the also researchers hope to develop a way to correlate their findings in the aorta with possible markers in circulating blood.