Will this year’s flu vaccine protect you? The answer is hidden in your blood

Flu vaccines save lives in the United States every year. These vaccines are good for protecting the population from Graves flu infections, but not all people receive the same level of protection.

“Some people have incredibly strong answers to annual flu vaccines, and some people do not react at all,” said Tal Einav, Ph.D., assistant professor of the Bodman family at the Jolla Institute For Immunology (LJI) and member of the LJI’s Center for Vaccine Innovation.

EINAV and his colleagues have developed an automatic learning model to analyze massive data sets from several flu studies against flu. Researchers use this tool to resolve a great mystery of science: can we predict who will be a low vaccine answering machine or a strong vaccine answering machine?

The research team shared their results in a recent ebiomicine study. They used their automatic learning model to identify trends through 20,000 antibodies of antibodies from the flu in 1997 and 2021. “From this point of view, with all these data sets, you can start exploring the vaccine’s response in a fundamentally new way,” explains Einav, who was the main author of the study.

The researchers discovered that the best way to predict a person’s response to a next flu vaccine (containing the influenza strain currently in circulation) is to measure their immune response to the influenza vaccine used the previous year – and the previous year – and the previous year.

In fact, the responses of a person with anterior influenza strains are a better predictor of the future responses than the age of a person, sex, geographic location or the dose of vaccine they receive.

“Many studies have shown that age has an effect. We have just shown that this is a very small effect, while you can get much better forecasts with antibodies that can be measured from your blood,” said Einav.

Your blood remembers

The influenza virus acquires a few changes each year, so that researchers do not tend to linger on the response of a person with past influf steuvas. Instead, the researchers consider the response to the strains currently in circulation.

The new LJI study shows the importance of looking back over time.

When a person obtains a vaccine or undergoes a viral infection, their body produces specialized immune cells and antibodies. Some of these immune cells and antibodies remain for years to provide long -term protection against the disease.

Scientists can measure the strength of this “memory” of the immune system by examining antibodies or titles in a person’s blood. Antibody titles are fascinating because they act as a kind of historic disc of what your immune system has encountered during your lifetime.

Because the flu lifts quickly – and the influenza vaccine formulations change every year – scientists can distinguish between your antibody response to this year, from last year or even earlier. By measuring all these strains, researchers can assemble a reliable chronological recording of the immune responses of a person with the flu of each year.

“The blood does not forget,” explains Einav.

The “signature” of a strong vaccine answering machine

The researchers found that strong respondents in the vaccine had “shredded” antibodies which would be raised in one year, low compared to the tension of the previous year, again from the previous year, and continue in this way. On a chronology, these peaks create a regular motif which resembles a row of shark teeth, where each peak indicates a strong response to this specific flu deformation.

Einav says that these annual fluctuations are a useful “signature” of a high alert immune system. “Powerful speakers tended to have these shredded peaks,” said Einav.

Antibody titles seemed very different in weak responders, whose chronology plots tended to be smoother. Some weak stakeholders have had antibodies that have more frequently reached platforms over the years. Their antibody response against this year’s influenza strain tends to be similar to their response to the strain of next year.

“However, when the virus evolves the following year and the vaccine changes, these individuals tend to respond to dismay,” explains Einav.

Although these results are held in more than 20 flu seasons, the researchers also tested their automatic learning model on four recent vaccine studies that they conducted in 2022 and 2023. These studies included data from a wide range of participants in the Jolla study, in California, as well as in Athens, GA, who received one of the three types of influenza vaccines.

The model was true. Regardless of a person’s demography, or his type of vaccine, his response as antibodies to current and past influenza strains was the best predictor to know if they would be weak or strong answers.

What it means for annual flu photos

Now LJI researchers wonder: How can we help weak responders?

“There are several types of flu vaccines you can get,” said Einav. “We want to know if people could react better or worse if you give them a different vaccine formulation.”

Einav and his colleagues are now looking for markers of the immune system that could show whether some vaccine formulations can stimulate the reactions of immune cells in weak responders. This work is an important step towards more personalized and effective vaccines.

“Our hope is to be able to provide for each person what will be their answer for each different vaccine,” explains Einav.

In addition, Einav adds that this study was possible thanks to the multiple research groups of the whole country sharing their data. “There are very generous researchers there, and I really congratulate their efforts. We all want our harshly won data to help improve things for all of us, and that’s exactly what we do when we publish our data,” says Einav. “We cannot even imagine the discoveries and applications that groups will make in the coming years using these data sets.”

Additional authors of the study, “draw pre -vacinated antibody titles on several variants of the H3N2 influenza to provide the post-vaccination response”, included Hannah Stacey, Michael A. Carlock, James D. Allen, Hannah B. Hanley, Shane Crotty and Ted M. Ross.