STANFORD, Calif. Scientists at the Stanford University School of Medicine have devised a software algorithm that could enable a common laboratory device to virtually separate a whole-blood sample into its different cell types and detect medically important gene-activity changes specific to any one of those cell types.
In a study to be published online March 7 in Nature Methods, the scientists reported that they had successfully used the new technique to pinpoint changes in one cell type that flagged the likelihood of kidney-transplant recipients rejecting their new organs. Without the software, these gene-activity flags would have gone unnoticed. The authors believe that the use of the new algorithm may have applications beyond kidney rejection, allowing doctors to better identify the onset of cancers, genetic disorders and a variety of other problems.
The lab device, called a microarray, is a standard research tool. But until the development of this algorithm, scientists and physicians have not been able to use it to derive such medically useful information from whole-blood samples. Part of the problem is that the information is obscured by the whole-blood samples' complex, multiple-component composition.
"Drawing blood is one of the most common diagnostic tests in clinical practice," said one of the investigators, Atul Butte, MD, PhD, assistant professor of pediatrics and of medical informatics. "We'd love to be able to use microarrays to find changes in the blood that indicate trouble somewhere in the body. But distinguishing one type of cell from another can be critical to doing that."
Butte is a senior author of the paper, along with Mark Davis, PhD, director of the Stanford Institute for Immunity, Transplantation and Infection. The two lead authors are postdoctoral scholar Shai Shen-Orr, PhD, and Robert Tibshirani, PhD, professor of health research and policy and of statistics.
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|Contact: Bruce Goldman|
Stanford University Medical Center