Researchers use artificial intelligence to analyze blood antibody patterns and better understand why people respond differently to vaccines
Researchers at Arizona State University used artificial intelligence to analyze patterns of antibodies found in the blood, focusing on understanding why vaccine responses differ from one person to another.
The team analyzed 8,687 blood samples from 4,089 participants, including healthy individuals as well as people with conditions or receiving treatments that may weaken the immune system, such as AIDS, multiple myeloma, cancer, inflammatory bowel disease and organ transplants.
Artificial intelligence reads the immune fingerprint (Pexels)
The study included antibodies targeting 185 antigens, including SARS-CoV-2 as well as common viruses and bacteria.
The researchers analyzed these data to create an "immune fingerprint" for each person, then compared it with their response to the COVID-19 vaccine.
The results showed that some of these pre-existing antibodies were associated with a stronger vaccine response. Among what the researchers called "sentinel antibodies," other antibodies that target common microbes also stood out, including Staphylococcus aureus, respiratory syncytial virus (RSV) and Human respirovirus 3.
The model found that combining these indicators could help predict who might have a strong or weak response following vaccination.
Notably, health status alone was not sufficient to explain the differences between individuals. While some groups with weakened immune systems were indeed more likely to have a weak response, some individuals showed a strong response, while around 5 to 6% of healthy people had a weak response to the vaccine.
This suggests that immune preparedness may be more complex than simply classifying a person as healthy or immunocompromised.
The importance of using artificial intelligence lies in its ability to analyze a large number of indicators simultaneously and identify connections that are difficult to detect through traditional methods.
The study suggests that information already present in the blood could potentially be used to estimate a person's response in advance.
Predicting responses before vaccination may change the future of prevention (Pexels)
This approach could eventually pave the way for more personalized vaccination, as it could help identify people who may need additional doses, closer monitoring or other preventive strategies if their effectiveness is proven.
However, these findings do not mean that "AI" is currently capable of determining the right vaccine for each person. Further studies are still needed to validate the findings in other populations and with different vaccines before this technology can be adopted in medical practice.
In this way, the study offers a new vision for preventive medicine: first, reading the "immune fingerprint" present in the blood, and then using this information to understand how the body is prepared to respond to a vaccine.
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