Novel Biomarkers May Predict Likelihood, Timing of HIV Viral Rebound, Remission


Investigators have identified metabolic and glycomic signatures in blood samples of post-treatment controllers, a rare population of HIV-infected individuals who can naturally sustain viral suppression after antiretroviral therapy (ART). The findings of this study, published in Nature Communications, could provide non-invasive biomarkers that predict the likelihood and duration of HIV remission following treatment interruption.

Clinical trials focusing on the eradication of HIV infection require patients to undergo analytical treatment interruption (ATI). HIV remains undetectable during ART, making ATI necessary to evaluate the experimental strategies.

In the vast majority of cases, viral loads increase within days or weeks of treatment interruption, and patients must be carefully monitored, according to the study. There are currently no simple, non-invasive methods available to monitor viral rebound following ATI. According to the investigators, biomarkers that predict how long a patient can remain off ART are urgently needed to improve the safety of ATI.

The study used blood samples from 2 cohorts of patients who participated in previous clinical trials. The first was a group of 24 HIV-infected individuals who underwent an open-ended ATI without concurrent immunoregulatory agents. The second was a group of 74 individuals from 6 AIDS Clinical Trial Group (ACTG) clinical studies evaluating different vaccines and immunotherapies, which included 27 participants identified as post-treatment controllers.

“We analyzed one of the largest sets of samples ever studied from post-treatment controllers, who don't experience viral rebound after ART interruption,” said Mohamed Abdel-Mohsen, PhD, assistant professor in The Wistar Institute Vaccine & Immunotherapy Center, in a press release. “This condition is extremely rare and provides very important insights into what a functional HIV cure looks like. Analyzing the blood of these individuals, we identified promising biomarker signatures that may fast-track future HIV cure trials and treatments. These biomarkers also provide us with insights on how post-treatment controllers restrain infection and how we can design novel HIV curative strategies to recapitulate this promising phenotype in the millions of HIV-infected individuals worldwide.”

The investigators initially performed metabolomic analyses on the Philadelphia cohort samples, identifying a select set of metabolites linked to inflammation whose pre-ATI levels are associated with time to viral rebound. In-vitro virus reactivation assays confirmed these observations, and the team then extended the metabolomic analysis to the larger cohort.

In these tests, the researchers also included glycomic studies to measure the levels of sugar-bound proteins. Because this cohort contained both post-treatment controllers and non-controllers, the investigators could confirm their observations through direct comparisons of these 2 groups. Through the use of machine learning, they combined the identified biomarkers and created 2 models that could predict the likelihood and timing of viral rebound with 95% and 74% accuracy, respectively.

“A growing body of research applies metabolomics and glycomics methods for the unbiased discovery of biomarkers associated with clinical conditions,” said Leila Giron, PhD, postdoctoral fellow in the Abdel-Mohsen lab, in the release. “We are among the first to apply this strategy in the context of ATI to analyze 2 carefully selected and well characterized groups of individuals, including a rare population of post-treatment controllers.”


Blood-based biomarkers may predict HIV remission after stopping antiretroviral therapy [news release]. EurekAlert; June 29, 2021. Accessed June 30, 2021.

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