Human immunodeficiency virus (HIV), the precursor to acquired immunodeficiency syndrome (AIDS), has long confounded medical researchers attempting to find a cure.

Now, researchers in the Nutritional Immunology and Molecular Medicine Laboratory (NIMML) at Virginia Tech's Biocomplexity Institute have developed a computational model that might help.

HIV affects approximately 36.7 million people worldwide and 1.2 million in the U.S. Current treatments involve lifelong, expensive treatments with side effects and drug resistance issues.

In addition to being difficult to treat, HIV leaves the body open to many other co-infections, such as tuberculosis or human papillomavirus (HPV). HPV is the most common sexually transmitted infection in the United States, and is therefore a great risk to HIV patients and those with compromised immunity. In addition, HPV co-infection leads to higher incidences of oropharyngeal cancers and other tumors.

Understanding the interactions between these HIV and HPV within immunocompromised patients is key to finding proper treatments and therapies that will address the co-infection. NIMML has developed a computational model that describes the interactions between HIV and HPV.

“NIMML has built computational and mathematical models of unprecedented scalability (trillions of interactions) and resolution (from molecules to cells, to tissues to systems). Like our previous modeling work, simulations using the new model enable a better-informed path to precision medicine interventions during co-infection with HIV and HPV,” said Josep Bassaganya-Riera, director of NIMML and corresponding author of the study.

“The limited clinical information about treatment and prevention options against HPV in HIV-infected individuals led us to employ modeling approaches to investigate the co-infection,” said Meghna Verma, a Ph.D. student at NIMML and co-author of the study. “We can use the model simulations to determine how HIV-directed therapeutics … can help halt the HPV-related issues in co-infected individuals.”

Mathematical models are essential to assess both the progression of co-infection and the affect of timing on treatments and therapies. The antiretroviral therapy used for HIV also sped up the resolution of HPV infection, an unforeseen consequence prior to instigation of the model.

“Though the combined antiretroviral therapy does not interfere with HPV replication, it indirectly strengthened the immune response against HPV by restoring proper immune function,” said Stanca Ciupe, associate professor in mathematics at Virginia Tech and co-corresponding author on the study.

The first of its kind, the model shows that if antiretrovirals are applied at the proper time, HPV infections will eventually decline as protective immune responses are restored. For immunocompromised patients, such information could relieve one of the constant struggles they face — dealing with co-infections and the side effects of the treatments necessary to fight them.

Published by Tiffany Trent, February 09, 2017
Tags: Biosystems to Computing