Researchers Lay Groundwork for Using Bedside Genomic Analysis to Identify Patients with Post-Operative Infection

CHICAGO -- The technology that generates molecular profiles by measuring differences in the patterns of gene expression (gene microarray analysis) has helped cancer researchers to understand the biology of leukemia and lymphoma, and clinicians to diagnose breast cancer and predict response to treatment with various chemotherapeutic agents. Results from a study published in the November issue of the Journal of the American College of Surgeons (JACS) showed for the first time that the same technology can be very reliable in distinguishing infection from inflammation by determining differences in the abundance of messenger RNA in blood samples.

 We wanted to test for the first time in vivo to see whether or not blood profiles would allow us to distinguish between animals that were infected and those that were not, and the answer was yes, with a degree of accuracy on the order of 94 percent, according to J. Perren Cobb, MD, FACS, director of the Center for Critical Illness and Health Engineering at Washington University in St. Louis.

Findings from this study hold out hope that scientists could develop a bedside blood test that would greatly speed the diagnosis of infection after surgery. We would like to be able to use a simple blood test based on molecular profiles similar to what we described in this paper. From a blood sample, we would figure out whether a patient had infection and streamline the process of diagnosis, ideally by a continuous monitoring and real-time analysis process, Cobb said.

As Cobb explained, systemic infection or sepsis increases morbidity and the risk of mortality and prolongs hospitalization after surgical procedures. It is often very difficult for surgeons to differentiate between systemic inflammation due to sterile causes as opposed to infection, however, because the conditions have the same clinical and laboratory appearance: elevated temperature and increased levels of white blood cells.

The current procedure for differentiating between patients who are infected and those who are not is time-consuming. We send cultures of fluid from patients blood, sputum, or urine and try to find an infecting organism. That process is relatively insensitive. It can take up to two or three days to get results. And some bacteria are difficult to culture, so even if a culture comes back negative, we may still want to treat the patient because we dont want to miss treating infection due to one of those organisms. We hope that a bedside blood test based on molecular profiles would help us not only more accurately find patients who are infected after surgery, but also find out what they are infected with, Cobb added.

Such a test could be used not just in the surgical intensive care unit but in the emergency department or other settings where timely diagnosis of infection is important, he added. If someone came into the hospital with a cough and had a working diagnosis of pneumonia or someone came in with abdominal pain and there was suspicion of an abdominal infection, wouldnt it be wonderful if we could run a blood test in the emergency department and more accurately triage patients so they could be treated earlier with the appropriate antibiotic?

Information about the genes associated with infection could provide insights into the way the human body reacts to invading organisms and suggest new ways of treating infection. Findings from the study conducted by Cobb are consistent with other investigations that indicate there is a small number of genes that respond commonly to infection, and most of these genes have not previously been at the center of sepsis research, he said. At one level, were finding a suite of genes that are informative with regard to making a diagnosis. But as biologists, we can also say these genes are major clues to the biology of infection and the hosts response to it. If every type of infection activates these genes, then we know they must be important to the disease process, and they therefore may be new treatment targets, Cobb said.

Gene microarray analysis is a genomic technology that creates molecular profiles based on the abundance of messenger RNA associated with the genes expressed in tissue or blood samples. The approach used in the study was a survey method, which looked at the activity of thousands of genes in an attempt to cover most of the genome of the mouse and identify all the genes that might be markers of inflammation and infection.

Cobb and his associates are working to narrow down the number of genetic markers to make it practical to develop a device that would screen for signs of infection at the bedside. Already, the researchers have identified nine specific genes that are common responders to inflammation and infection in mice. Some of these genes also have been identified by other investigators in human models of infection and inflammation, lending support to Cobbs hypothesis that a small group of common inflammatory response genes may be used as novel biomarkers to show that inflammation is present. Other genes have shown promise as markers that diagnosis infection apart from inflammation, shedding light on the pathology of infection in patients.

The next series of experiments by Cobb and his associates is exploring whether gene microarray analysis can identify the type of invading organism in blood samples. Preliminary findings from those experiments indicate that genetic testing detects differences in molecular profiles based on the specific type of invading organism.

The researchers also are conducting gene microarray analysis of infection patterns in patients over time, aimed at developing novel diagnostics and prognostics. We used mouse genes to tell us about the human condition. Thats translational researchthe bedside to bench paradigmat its best. Just image what studying the human genome per se will tell us, he said.

In addition to Dr. Cobb, the research team included T. Philip Chung, MD; Jason M. Laramie, MS; Donald J. Meyer, MS; Thomas Downey, MS; Laurence HY TAM, MS; Huashi Ding, MS; Timothy G. Buchman, PhD, MD, FACS; Irene Karl, PhD; Gary D. Storno, PhD; and Richard S. Hotchkiss, MD.

This research was funded in part by the American College of Surgeons George H. A. Clowes, Jr., MD, FACS, Memorial Research Career Development Award and the National Institutes of General Medical Sciences.

Source: American College of Surgeons

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