“Sentinel” Antibodies May Predict How Well Vaccines Boost the Immune System

Vaccines are an important tool in the fight against infectious diseases like COVID-19, but their benefits are not shared equally. That’s because some people get a greater boost to their immune systems after vaccination than others. The reasons for this are often unclear. Most previous studies have looked at how the body responds to vaccination for clues to this conundrum. In a new paper, published in Cell Press Blue, researchers instead used AI to look for clues in the body before a vaccine is given.¹

The research team found that key “sentinel” antibodies, produced in response to previous infections, predicted strong or weak responses to COVID-19 vaccination. The researchers hope that the study could point the way toward vaccine strategies that can anticipate responses and help people prepare accordingly.

“What our study found is that certain biomarkers, when analyzed with AI, can predict who is likely to respond well to a vaccine, even before they receive it. This suggests that some people may be more immune-ready than others,” said Joshua LaBear, a molecular scientist at Arizona State University and coauthor of the new study, in a statement.

The Fingerprints of Vaccination Response

The scientists tracked 4,089 people before and after COVID-19 vaccination. At each time point, researchers measured levels of 185 antibodies in the participants’ blood. These antibodies are produced in response to a range of antigens, including those from SARS-CoV-2 as well as those from other disease-causing microbes and those produced in response to antigens made by the body itself that are linked to autoimmune disease.

The trial had recruited both healthy volunteers and those with conditions where the immune system is weakened, such as people with multiple myeloma and transplant patients. These latter groups had generally weaker responses to vaccination, as expected. But there was no clear rule. Some patients with conditions that should have blunted their immune responses were no different from healthy volunteers. Roughly 5–6 percent of the healthy group produced only weak vaccine responses. So, the researchers dug into the antibody signatures that predicted strong or weak responses.

They found that when pre-existing antibodies against common disease antigens, like those from respiratory syncytial virus, human respovirus 3, and Staphylococcus aureus, were present before vaccination, both healthy and immunosuppressed volunteers produced strong responses to COVID-19 vaccination. The researchers called these “sentinel” antibodies that acted as proxy measures for the underlying strength of a participant’s immune responses.

The researchers then used AI to build a model that would attempt to predict vaccine response based on a global antibody profile before getting a jab. This model identified people who would later mount a weak antibody response after vaccination. Once again, antibodies against microbes like S. aureus were the biggest contributors to the strength of these predictions.

The researchers hope that, if validated in larger groups of volunteers and patients, their model could serve as an adjunct to vaccination, helping doctors identify those who may not respond to a vaccine as expected and need additional booster doses. The AI approach may also help predict responses to vaccines against diseases other than COVID-19, although further testing is needed. The solution to the puzzle of vaccine responses may have been inside us all along.