Pre-existing mutations can lead to drug resistance in HIV virus [with video]

HIV treatment nowadays works well, unless drug resistance evolves. To prevent the evolution of drug resistance, it is important to know the origin of the responsible mutations. We combined models from evolutionary biology with data from clinical trials to determine the origin of drug resistance mutations in patients with failed treatment. The analysis depends on the following idea: if pre-existing mutations are important, then the risk of treatment failure due to resistance must be highest when pre-existing mutations can still play a role, which is shortly after the start of treatment. We found that, indeed, the risk of treatment failure is highest when treatment is recently started or restarted after a treatment interruption, showing that the responsible drug resistance mutations typically originate before treatment is started or during interruptions of treatment. We propose ways to reduce the risk of evolution of drug resistance.

HFSP Long-Term Fellow Pleuni Pennings
authored on Mon, 11 June 2012

Based on a press release issued by Harvard University

In a critical step that may lead to more effective HIV treatments, Harvard scientists have found pre-existing mutations in a small number of HIV patients. These mutations can cause the virus to develop resistance to the drugs used to slow its progression.

The finding is particularly important because, while researchers have long known HIV can develop resistance to some drugs, it was not understood whether the virus relied on pre-existing mutations to develop resistance, or if it waits for those mutations to occur. By shedding new light on how resistance evolves, the study, reported in online journal PLoS Computational Biology opens the door to the development of new, more effective treatments.

Pennings collected her data from 26 clinical trials. Patients were treated with a typical combination of NNRTI drugs, which helps block the virus from multiplying. She found that the virus is more likely to develop resistance shortly after the start of treatment or when treatment is restarted following an interruption of a week or more. However, it is less likely to develop resistance later on and when patients do not interrupt treatment.

“In order to prevent the evolution of resistance, we need to know where the resistance mutations are coming from, it was exciting to realize data from clinical trials could help us solve this puzzle,” Pennings said. “If we understand how the virus develops resistance, we can think of new ways to prevent it.”

This finding suggests that pre-existing mutations are behind the virus’ drug resistance, and that resistance which develops early in treatment is likely the result of pre-existing mutations. Resistance that develops later is tied to mutations in the virus that occur after treatment began.

Pennings adds “It was great to see that models from evolutionary biology could be used to understand data from HIV studies. Once I had the data, it was surprisingly easy to find that resistance evolves due to pre-existing mutations in 6% of patients who start NNRTI based treatment. For the other 94% of the patients, they have a risk of approximately 2-3% per year that resistance evolves. As an evolutionary biologist, I am excited to know these numbers, but the immediate next step is to think about how to reduce these numbers to zero.”

While the study holds out hope for the future development of more effective HIV treatments, Pennings emphasized that data used in the study came from trials, which exclusively included patients receiving NNRTI or unboosted protease inhibitor treatments. It is unclear whether the results can be generalized to other treatments and to patients who are not enrolled in clinical trials.

Standing genetic variation and the evolution of drug resistance in HIV from Pleuni Pennings on Vimeo.


Standing Genetic Variation and the Evolution of Drug Resistance in HIV. Pleuni Simone Pennings. PLoS Comput Biol8(6):e1002527. doi:10.1371/journal.pcbi.1002527.

PLoS link

The Scientist link