Prof. Hertz and his colleagues take a computational and wet lab approach to studying systems immunology within the context of vaccines and diseases. More specifically, Dr. Hertz is interested in the immune response following infection or vaccination within the context of immune history and memory – how do previous infections and exposure in the world affect how your immune system will react?
The adaptive immune system uses a diverse set of pattern detectors to identify and eliminate pathogens and pathogen-infected cells. During the course of an infection, the immune system focuses its response on a small fraction of the thousands of potential targets in a phenomenon known as immunodominance. Understanding the mechanisms that govern this is crucial for, among other things, designing vaccines. It is a result of a large number of factors including immunological history, antigen processing and presentation, viral load and kinetics of viral expression, and host genetics.
Immunological memory exists as an internal representation of an individual’s immune response. Thus, the questions become what and how can we learn from a person’s immune history and memory to better predict how they will respond to an infection? For example, herpes (HSV-2) is a risk factor for HIV, and people who test positive for cytomegalovirus (CMV) have a stronger response to influenza. Why is this? Why can two people can react so differently to the same infection? And why are some people protected by vaccines but others aren’t? Ultimately, this comes down to the question of, how does a child’s or person’s immune system develop as they walk through the world?
Using a combination of our self-designed antigen microarrays and computational modeling the lab’s Dr. Hertz and his colleagues aim to provide answers to these questions by creating a baseline representation of an individual’s immune system and using it to compare and contrast post-vaccination or infection responses. Thus far, their research has shown that these are closely linked, the former being able to act as an accurate prediction of the latter.
Developing this work beyond academic research will provide valuable information to, for example, physicians – in determining whether medication or vaccination is required or would even be effective– and clinicians performing vaccine trials – helping to explain why a specific new vaccine may be effective for some subjects but not for others.