It could contribute in the future to a new vaccine paradigm that takes into account the specific traits of the individual, potentially enabling HIV vaccinations and better flu protection.
The U-M Assistant Professor of Biomedical Engineering and the author of the paper of a recent study published in Cell Reports Medicine Kelly Arnold stated: “Different persons vary by number and type of antibodies they make.
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“They have various sequence data in anticorps and immune receptor molecules that lead them to bind unpredictably, depending on their genes.
“That situation is difficult for researchers to understand based on experiments. And that’s why this computational model has been so valuable. We can make personalized models for different people that take all of these different factors into account.”
Vaccines can function in two ways: either by sending anticorps neutralizing the virus to bind, and avoiding the infection of cells, or by stimulating adaptive immune cells to destroy pathogenic agents. First of all, the activation of the immune cells can compensate for the fact that the anticorps are not always the right combination to the virus, for relative status viruses like measles, but viruses such as HIV and influenza.
The problem is that, as indicated in the study released in Cell Reports Medicine, the kind and number of antibodies could have a distinct effect on immune cell activation.
Experts have checked various surveys and data that provide a fact that in most cases the vaccines have proven effective and created a higher level of antibodies. This prevents the infection as soon as the virus enters the body and even if there is an infection one does not have to face serious health issues. It will be like the common cold only and one can recover in a few days.
Melissa Lemke, a candidate for the U-M Ph.D. in biomedical engineering and the study researcher explained, “There is unpredictability in both the viral population and its people through rapidly changing viruses such as HIV and flu. “That implies we will require a range of feasible solutions, which can match the health status, sex, age and genetic background of any person to protect everyone against a variety of virus mutations, to the same degree.”
The U-M model uses data from the only marginally protective HIV vaccination test to date acquired from the University of Melbourne. The model analyzed the type and amount of antibodies produced after vaccination by plasma samples from the study participants — primarily blood samples minus red blood cells. When a pathogen and immune cells are binding an antibody, it’s a signal for a pathogen to be destroyed by the immune cell.
The model projected that increasing antibiotic levels would not generally activate immune cells for all people. The rise of these antibodies can lead to conclusions in some patients gaining, doing nothing for others but potentially lowering immune activity in others, depending on the basic levels of antibody and genetic makeup of the subject.
The U-M team evaluates 30 persons and selects the eight who are most likely to bind their immune cell receptors using antibodies created by the vaccine, with the 8 most likely to react correctly.
Then the Melbourne team conducted trials to supplement plasma samples with antibodies and HIV viruses. Antibodies, pathogens, and immune systems, which signal activity to destroy viruses, have been forecast to respond by five- to seven-fold increases in immune complexes.
Non-responders, meanwhile, have shown an increase in inflammatory cells only 1.3 times. This demonstrates that the preparation of antibodies that interact well with the virus is not necessarily sufficient to protect the vaccine—immune cells must also bind with the antibodies.