“We found that a type of immune cell called a natural killer cell was consistently low at baseline in individuals who got infected,” Bongen said. Those who had a higher proportion of natural killer cells had better immune defenses and fought off illness.
“So we asked, ‘What are the genes that represent natural killer cells?’ And there turned out to be this one gene, KLRD1, that seemed to be a good target,” Bongen said.
Old data, new tricks
KLRD1, when expressed, manifests as a receptor on the surface of natural killer cells. KLRD1 is basically a counting chip. When the score was tallied, Khatri saw that, on the whole, those whose immune cells consisted of 10-13 percent natural killers did not succumb to the flu, whereas those whose natural killer cells fell short of 10 percent wound up ill. It’s a fine line, Khatri said, but the distinction between the groups is quite clear: Everyone who had 10 percent or more natural killer cells stood strong against the infection and showed no symptoms.
Khatri said his findings could help health professionals understand who’s at the highest risk for flu infection. “If, for example, there’s a flu epidemic going on, and Tamiflu supplies are limited, this data could help identify who should be prophylactically treated first,” Khatri said.
Khatri emphasizes that for now, the link between KLRD1 levels and influenza susceptibility is only an association. The next step, he said, is to find the mechanism.
“It will be crucial to understand the role of natural killer cells’ protection so that we can potentially leverage that in designing better flu vaccines,” he said. “Since we see that natural killer cells are protective across different strains, maybe that would be a path to a universal flu vaccine.”
More broadly, Khatri said that this research exemplifies the power of “data repurposing.”
“Our work shows how you can use data that exists from previous studies to answer questions that those studies alone would not have been able to answer,” Khatri said. “But by aggregating the data, we were able to find a signal across both studies and use that to discover something new.”
Khatri is a member of Stanford Bio-X and the Stanford Child Health Research Institute.
The study was supported by the National Institutes of Health (grants 5K12HL120001-02, U19-AI110491 and R01 AI125197-01), the Donald E. and Delia B. Baxter Foundation, the Henry Gustav Floren Trust, a gift from Elizabeth F. Alder and the Bill and Melinda Gates Foundation.
Stanford’s departments of Medicine and of Biomedical Data Science also supported the work.