January 19, 2018

New Duke research could make HIV incidence tracking faster, cheaper

The Chronicle | By Claire Xiao | 01/18/2018

Researchers at the Duke Human Vaccine Institute have recently developed a tool that more accurately discerns new HIV infections from long-standing ones.

Their strategy involved searching patient samples for antibodies, the proportions or components of which might differ based on whether patients are facing recent or long-standing infections. The newer method is more accurate in its intended measurements compared to existing tools and also requires less samples for population-level inferences, explained Georgia Tomaras, director of research at DHVI and senior author of the study. She added that these advances, collectively, could save governments and NGOs tracking HIV incidence time and money.

Tomaras noted that their tool is premised on the idea that the body's immune system continually adapts to HIV upon infection.

“HIV mutates in the body. There is a cat-and-mouse game where the immune system is now evolving to try to catch up with the virus and at the same time [the immune system] is maturing,” she said.

When the body is first infected with HIV, the immune system is capable of recognizing different components of the HIV virus, Tomaras noted. This dynamic is reflected in the antibodies that are produced by the body to combat the pathogen, which can change and become better adapted over time. Eventually, the body's immune response learns to better recognize HIV, leading to an increasingly stronger interaction between the antibody and the HIV antigen that the antibody is targeting.

Because HIV also can mutate within the body, antibodies which might be more abundant at the early stages of infection could also become less or more prevalent later in a patient's lifespan, she added.

Armed with this knowledge, the team examined samples from HIV-infected individuals to assess relative proportions of antibodies in patients.

“[The samples] are from HIV-infected individuals from all over the world. People who are either recently infected or have been infected for a long time—what we call chronically infected. Additionally, we looked at samples from people who are on antiretroviral therapy as well as those who are not," Tomaras said, referring to a class of drugs which can also put further pressure on the virus to evolve.

The samples were from patients who had been infected as recently as a couple weeks to 10 or 15 years, added Kelly Seaton, associate research laboratory manager at DHVI and lead author of the study. This combination allowed them to compare the antibody profiles of patients recently infected from those with long-standing infections.

Seaton explained that the technology used to run the experiment involved a type of bead that would bind to antigens specific to HIV, which then enabled the researchers to then search for antibodies in patient samples. One benefit of this method, she added, was that they could now search for multiple antibody types at the same time.

When researchers ran the experiment, they identified varying numbers of antibodies between different patients. These results were then processed in a statistical model developed by Nathan Vandergrift, associate professor of medicine, and Wes Rountree, a principal biostatistician at the Duke Human Vaccine Institute.

Based on the proportion of four naturally occurring biomarkers—the specific antibodies in the sample—the resulting assay was able to more accurately classify recent infections. In the future, the team might also integrate other combinations of markers in addition to those four.

The new tool can ultimately track hotspots of HIV infections or measure the effectiveness of certain vaccination trials.

“This tool enables us to keep pace with the current epidemic," Tomaras said. "The field has changed and antiretroviral therapy is now used for HIV prevention as well as for treatment of HIV infected people.

Because the new tool can distinguish the antibodies from the circulating antiretroviral therapy in the body, the test more accurately classifies someone who has antiretroviral therapy in their system.

“Our tool is more accurate at identifying recent versus long-standing infections in people taking ART,” Seaton said. “And will enable identification of the best prevention methods against HIV in different populations.”