Corona Virus Covid-19 Medical Vaccine Concept.
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Vaccination could be made more effective with personalization, according to a new study led by University of Michigan (U-M) researchers. This international team also identified a particular antibody-related gene that predicts, at a population level, whether boosting to produce more antibodies will be effective for increasing innate immune responses.

The study explored how people respond differently to conventional boosting, which reexposes the immune system to the virus (or some portion of it) to increase antibody concentration.

“What’s most interesting with this work is the concept of personalized variability and understanding direct links between vaccine responses and different genes people have,” said Kelly Arnold, U-M assistant professor of biomedical engineering and senior author of the paper, which was published this week in Frontiers in Immunology.

In some people, an increase in antibody concentration may not matter as much because their immune receptors aren’t as good at sticking to the antibodies—i.e. they have a lower affinity. As a result, someone can have a good antibody count and still have a poor immune response. So, how can vaccination be made more effective?

“Depending on your genetic background, we’ve found that vaccine boosting may be more or less effective in activating certain innate immune functions,” Arnold said. “And in some people, where boosting the concentrations of antibodies was ineffective, being able to change the affinity of antibodies could be the more successful route. Though this is still a theoretical concept and not yet possible in practice.”

Using data from the RV144 HIV vaccine trial, these investigators mapped the landscape of IgG-FcγRIIIa complex formation predicted post-vaccination for three different IgG1 allotypes and two different FcγRIIIa polymorphisms.

IgG antibodies form complexes with Fc receptors (FcRs) to activate Fc-mediated immune functions. Genetic variation in both IgGs and FcRs can alter IgG-FcR complex formation through changes in binding affinity and concentration.

Arnold’s team, working with partners in Australia, Thailand and the U.S., created a computer model to determine how different genetic factors influence innate immune responses induced by vaccine boosting. It uses data and plasma samples obtained by the University of Melbourne from the only moderately protective HIV vaccine trial to date.

The plasma samples from trial participants showed the amount and type of antibodies produced after vaccination.

Their model shows how specific vaccine interventions could be applied to maximize IgG-FcγRIIIa complex formation in people of different genetic backgrounds. Individuals with the G1m1,17 and G1m1,3 allotypes were predicted to be more responsive to vaccine adjuvant strategies that increase antibody FcγRIIIa affinity (e.g. glycosylation modifications). Those with the G1m-1,3 allotype were predicted to be more responsive to vaccine boosting regimens that increase IgG1 antibody titers (concentration).

“In a mixed population of people, we’ve also shown how one specific genotype would drive whether that population was responsive to changes in antibody concentrations expected from traditional boosting,” Arnold said.

Modeling showed that, in a gene that encodes the IgG1 antibody, different variations can predict how effective boosting will be in a given population. The HIV trial showed that increasing antibody levels in some people resulted in no change in the innate immune functions evaluated.

“What that tells us is that in populations with certain genetic variations, traditional boosting methods to increase antibody concentrations may not be as effective at improving innate immune functions,” Arnold said.

Last year, Arnold’s team utilized data from the same trial to highlight why certain vaccines influence people differently. In the future, both studies could lead to new design principles for vaccines that take an individual’s personalized characteristics into account.

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