Not everyone exposed to the influenza virus become ill, and while the exact reasons behind such variability have not yet been fully elucidated, scientists have identified a number of biomarkers predictive of who will experience the attendant symptoms.
The problem, however, is that predictions based on the variety of known biomarkers can only be made after infection has already taken place, but prior to the appearance of symptoms.
Now, a group of researchers from Stanford University have discovered a new, blood-based biomarker — a gene called KLRD1, which is expressed by antiviral cells — which could do a much better job.
“There is huge variability in who gets the flu each year. We wanted to understand what immune factors might play a role in why people get sick. We hypothesized that there may be an immune state that protects from infection upon exposure and reduces susceptibility,” said co-author on the study Erika Bongen.
In the study, people with higher expression of KLRD1 were found to be much less prone to catching the flu, most likely due to higher killer cell activity in their immune systems.
First, Bongen and her colleagues took blood samples from 52 healthy volunteers to gauge the volume of immune cells in their blood, and measured the expression of over 20,000 individual genes.
Then, once the subjects were infected, researchers found that volunteers who did not get sick had more natural killer cells prior to infection, and also significantly higher expression of the KLRD1.
“Since influenza is major health problem, there is a great deal of work focused on understanding the immune response, developing better vaccines, and creating new drugs,” said Bongen.
Given the importance of killer cells in combating influenza, future endeavours could focus on developing vaccines or drugs capable of boosting immune activity.
While the study did validate its findings in a completely independent cohort, it also used gene expression in a relatively small number of samples. “We need to confirm our findings in a large cohort. Also, our results are a strong association. The next step is to find the mechanism behind it,” concluded co-author Purvesh Khatri.
The study was published in the journal Genome Medicine on 14 June 2018.