"Our approach represents a simple, yet powerful and important new tool for medical research and may serve as a catalyst for future blood-based disease diagnostics," wrote the authors, who hail from Dartmouth, Oregon State University, the University of Minnesota, and the University of CaliforniaSan Francisco, as well as Brown. Several authors worked with Kelsey at Brown during the research.
They describe the technique and its analytical methods in deep mathematical detail in another paper published in May in BMC Bioinformatics. They also report experiments that included analyses of the leukocyte mix of noncancer conditions such as Down syndrome and obesity.
The paper found many examples of differences between the immune cell mix of healthy controls and people with specific illnesses. For example, obese African Americans had an estimated increase in granulocyte leukocytes of about 12 percentage points. People with Down syndrome, had 4.8 percentage points fewer B cells. For head and neck cancer, they noted a 10.4 percentage point drop in CD4+ T-lymphocytes.
"Any disease that has an immune-cell mediated component to it would have applicability," Kelsey said.
In both papers, the authors said they expect that the technique will be applied in clinical and research efforts.
"Our approach provides a completely novel tool for the study of the immune profiles of diseases where only DNA can be accessed," the authors wrote in Cancer Epidemiology Biomarkers and
|Contact: David Orenstein|