# Mathematical modeling and phylodynamics of HIV intrahost evolution

From the Schiffer Lab, Vaccine and Infectious Disease Division

Once a person is infected with Human Immunodeficiency Virus (HIV), the virus evolves or undergoes changes to its sequence to produce virus variants. But how do these variants differ from the original ‘parent’ virus and what drives this evolution within a person? David Swan, MS, MME, Dr. Joshua Schiffer, and Dr. Dan Reeves from the Schiffer Lab in Fred Hutchinson’s Vaccine and Infection Disease Division sought to provide insight to these questions on intrahost HIV evolution and published their findings in a recent article in PNAS.

In the United States, about 36,000 people were diagnosed as HIV positive in 2019 (HIV: Basic Statistics, CDC). HIV infection causes a chronic illness called acquired immunodeficiency syndrome (AIDS) in which a person’s adaptive immune cells, CD4+ T cells specifically, are significantly reduced. This means that a person suffering from AIDS has a weakened immune system and their ability to fight diseases is less robust. Effective management of HIV-associated disease is possible by taking a multi-drug cocktail consolidated into a single pill taken daily that works to suppress HIV-associated disease, thus restoring a person’s adaptive immune response. However, HIV integrates into the DNA of cells and remains there even with this treatment. For this reason, understanding what drives changes in the genetic code of HIV may provide insight into how this virus can be eradicated from infected individuals and aid in our understanding of how HIV causes disease.

A long-standing question in the field of virus evolution is the extent to which the immune response dictates virus adaption within an infected individual. To address this question, members of the Schiffer lab combined several datasets from human HIV infections that together included data for 1) early infection virus abundance, 2) virus sequence divergence and diversity over time, and 3) sequence data for virus genetic code integrated into human DNA – from individuals taking virus-suppressing treatments. To determine how the adaptive immune response impacts HIV evolution within a person, 24 different mathematical model variations were applied to the combined datasets to determine which models for “viral fitness” and “adaptive immunity” accurately resembled the data.