Effect of Natural and ARV-induced Viral Suppression and Viral Breakthrough on Anti-HIV Antibody Proportion and Avidity in Patients with HIV-1 Subtype B Infection
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Background: Viral suppression and viral breakthrough impact the humoral immune response to HIV infection. We evaluated the impact of viral suppression and viral breakthrough on results obtained with two cross-sectional HIV incidence assays.
Methods: All samples were collected from adults in the US who were HIV infected for >2 years. Samples were tested with the BED capture enzyme immunoassay (BED-CEIA) which measures the proportion of IgG that is HIV-specific, and with an antibody avidity assay based on the Genetic Systems 1/2+ O ELISA. We tested 281 samples: (1) 30 samples from 18 patients with natural control of HIV-1 infection known as elite controllers or suppressors (2) 72 samples from 18 adults on antiretroviral therapy (ART), with 1 sample before and 2-6 samples after ART initiation, and (3) 179 samples from 20 virally-suppressed adults who had evidence of viral breakthrough receiving ART (>400 copies/ml HIV RNA) and with subsequent viral suppression.
Results: For elite suppressors, 10/18 had BED-CEIA values <0.8 normalized optical density units (OD-n) and these values did not change significantly over time. For patients receiving ART, 14/18 had BED-CEIA values that decreased over time, with a median decrease of 0.42 OD-n (range 0.10 to 0.63)/time point receiving ART. Three patterns of BED-CEIA values were observed during viral breakthrough: (1) values that increased then returned to pre-breakthrough values when viral suppression was re-established, (2) values that increased after viral breakthrough, and (3) values that did not change with viral breakthrough.
Conclusions: Viral suppression and viral breakthrough were associated with changes in BED-CEIA values, reflecting changes in the proportion of HIV-specific IgG. These changes can result in misclassification of patients with long-term HIV infection as recently infected using the BED-CEIA, thereby influencing a falsely high value for cross-sectional incidence estimates.
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