Assessment of drug resistance mutations in plasma and peripheral blood mononuclear cells at different plasma viral loads in patients receiving HAART

Abstract

Background: HIV drug resistance mutations both in peripheral blood mononuclear cells (PBMCs) and plasma have the ability to influence the outcome of highly active antiretroviral therapy for HIV patients. PBMCs harbor archival proviral DNA, are a major source of HIV and also underdo latent infection during suppressive HAART.

Objectives: The main objectives of this study were to assess whether specific viral load groups are better predictors of drug resistance and to examine the utility of PBMCs for drug resistance testing during HAART.

Study design: Patients were grouped into a plasma panel comprising of 100 patients and a PBMC/plasma panel of 45 patients. These two groups were further divided according to plasma viral load (low, medium and high). Therapy naive patients were also included. Resistance to protease and reverse transcriptase inhibitors was assessed in each group over different viral load categories.

Results: Our data indicated that in addition to plasma, PBMCs also are a reliable predictor of drug resistance. Drug resistance mutations analyzed from each panel demonstrated that intermediate and high viral loads were strong indicators of drug resistance in both the plasma and PBMC compartments. Despite this, a significant portion of patients with high viral loads showed reduced levels of drug resistance indicating that factors including poor compliance, drug pharmacokinetics and host genetic factors are also likely to contribute to therapy failure. A significant degree of resistance to NRTI and PI resistance was found in treatment-naive individuals, demonstrating the transmission of circulating drug resistant HIV-1 variants.

Conclusions: Our data emphasize the need for stronger pharmacokinetic evaluation during HAART, especially for patients with intermediate or high plasma viremia. The utility of PBMCs as an alternative source of resistance profiling was also demonstrated, and this approach may benefit the assessment of future drug regimens for HIV-infected patients.