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Study Finds Expression Signature Linked to Symptoms after Flu Infection

By Andrea Anderson

NEW YORK (GenomeWeb News) – Researchers from the US and France reported online last night in PLoS Genetics that they have identified gene expression patterns that may eventually help predict which individuals will become ill following infection with influenza virus.

The team evaluated expression patterns in multiple blood samples from 17 individuals exposed to a strain of influenza A, including nine who became sick and eight who did not. Using an algorithm originally developed to find materials and patterns on the earth's surface from satellite images, the researchers were able to distinguish between gene expression patterns in individuals with or without symptoms. And in their subsequent analyses they found distinct expression patterns in the symptomatic and asymptomatic groups over time, hinting at the pathways that contribute to flu susceptibility and resistance.

"The [gene expression] patterns of resistance of those who remained healthy but still have gotten infected with the virus were quite different as compared to the patterns that we saw in those who did get sick," co-corresponding author Alfred Hero, a computational biology, bioinformatics, and biomedical engineering researcher at the University of Michigan, told GenomeWeb Daily News.

Interestingly though, he added, their results indicate that even individuals with no flu symptoms show a shift in the expression of immune and other genes as a consequence of flu exposure. "The immune response was just as active in those that remained healthy as it was in those who got sick following the exposure to the virus," he said.

Although there have been studies of gene expression and immune response to the flu virus in the past, Hero noted, most have compared individuals with flu symptoms to healthy controls from the general population who may or may not have been exposed to the virus.

For the current study, he and his team used an immune challenge approach, comparing the expression patterns in 17 otherwise healthy paid volunteers between the ages of 18 and 45 years old who were inoculated with influenza A H3N2/Wisconsin/67/2005 virus at Retroscreen Virology in the UK.

Blood samples were drawn from the study participants every six to eight hours over the span of about five and a half days following the flu exposure and the gene expression patterns in the 16 samples per individual were assessed at Expression Analysis using Affymetrix Human Genome U133A 2.0 arrays.

"The real novelty of our study was that we had people who were all exposed to the same virus at the same time and that we got to watch the immune response in their blood as measured by gene expression over the full course of the disease," Hero said.

Because researchers were unsure of some of the clinical information associated with specific samples, Hero explained, they decided to initially ignore these labels and instead relied on a label-free computational method previously used in conjunction with satellite imaging data to try to distinguish between samples from individuals who had become ill and those who had not.

"We decided to basically ignore the labels and use a method that had been previously used for imaging mineral and chemical constituents of the earth's surface that doesn't require labeling either," Hero said. "Once we made the connection, it was obvious that this tool would be ideally suited for this study."

Using this approach, they were able to track the changes in expression patterns in each individual over time, he noted. "The remarkable thing was that without any label information whatsoever, without any clinical information, we came up with a classification of the people who got sick that was spot on."

Once they had identified such differences, the researchers pooled their data into two groups — one representing study participants with flu symptoms and one without — to look for genes, pathways, and expression patterns of note in each group.

In both the symptomatic and asymptomatic groups, the researchers saw gene expression patterns consistent with an immune response to the flu virus, Hero noted, including an uptick in the expression of genes associated with early immune defense mechanisms such as pattern-recognition receptor genes.

But the expression of these early defense genes was markedly enhanced in the group that did get sick compared to the asymptomatic group. Those who became ill had also a boost in the activity of inflammation-related cytokine genes that was not detected in the flu exposed but healthy group.

"These [inflammatory] genes were not activated in the asymptomatic people who participated in the study," Hero said. "This acute inflammation pathway really distinguishes the mid- to late-infection stages of people who got sick, symptomatically ill, versus those who were able to resist the virus and throw it off."

On the other hand, the group without symptoms showed elevated expression of genes implicated in antioxidant function, cell-mediated innate immune response, stress response, and anti-inflammatory processes.

More research is needed to understand why these gene expression differences exist following flu exposure, Hero said, and for the current study the researchers did not look at genome sequence data to determine whether they could find genetic patterns associated with the expression patterns detected in those with varying vulnerability to flu.

Even so, those involved in the study say their findings may prove useful for identifying influenza infection before symptoms appear, particularly since telltale genetic signatures for acute inflammation seem to be present in the 36 hours before peak flu symptoms.

If a quick, inexpensive assay can be developed to find these expression signatures from a sample that can be taken non-invasively, Hero said, it may be possible to find and preemptively treat those who appear most likely to suffer flu symptoms. He noted that some collaborators involved in the study are currently exploring such detection strategies.

Still, Hero explained, developing ways to accurately predict disease symptoms will likely require additional studies involving a larger sample set as well as research on the gene expression response associated with exposure to other pathogens.

Based on findings so far, it appears that unraveling expression patterns involved in flu infection and other viral and bacterial exposures may also help in understanding the biological underpinnings of infection response in individuals with and without obvious symptoms.

"It also points out, importantly, that remaining asymptomatic in the face of an exposure to a virus is an active process in the immune system, and we can now begin to probe the underlying biology to resisting infection," co-corresponding author Geoff Ginsburg, director of the Duke University Institute for Genome Sciences and Policy's Center for Genomic Medicine, said in a statement.

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