Detection of recent HIV-1 infection using a new limiting-antigen avidity assay: potential for HIV-1 incidence estimates and avidity maturation studies

Abstract

Background: Accurate and reliable laboratory methods are needed for estimation of HIV-1 incidence to identify the high-risk populations and target and monitor prevention efforts. We previously described a single-well limiting-antigen avidity enzyme immunoassay (LAg-Avidity EIA) to detect recent HIV-1 infection.

Methods: We describe here further optimization and characterization of LAg-Avidity EIA, comparing it to the BED assay and a two-well avidity-index (AI) EIA. Specimen sets included longitudinal sera (n = 393), collected from 89 seroconverting individuals from 4 cohorts representing 4 HIV-1 subtypes, and sera from AIDS patients (n = 488) with or without TB co-infections from 3 different cohorts. Ninety seven HIV-1 positive specimens were purchased commercially. The BED assay, LAg-Avidity EIA, AI-EIA and HIV serology were performed, as needed.

Results: Monitoring quality control specimens indicated high reproducibility of the LAg-Avidity EIA with coefficient of variation of <10% in the dynamic range. The LAg-Avidity EIA has an overall mean duration of recency (ω) of 141 days (95% CI 119-160) at normalized optical density (ODn) cutoff of 1.0, with similar ω in different HIV-1 subtypes and populations (132 to 143 days). Antibody avidity kinetics were similar among individuals and subtypes by both the LAg-Avidity EIA and AI-EIA compared to the HIV-IgG levels measured by the BED assay. The false recent rate among individuals with AIDS was 0.2% with the LAg-Avidity EIA, compared to 2.9% with the BED assay. Western blot profiles of specimens with increasing avidity confirm accurate detection of recent HIV-1 infections.

Conclusions: These data demonstrate that the LAg-Avidity EIA is a promising assay with consistent ω in different populations and subtypes. The assay should be very useful for 1) estimating HIV-1 incidence in cross-sectional specimens as part of HIV surveillance, 2) identifying risk factors for recent infections, 3) measuring impact of prevention programs, and 4) studying avidity maturation during vaccine trials.

Figure 1. Antibody avidity maturation post-seroconversion as measured by LAg-Avidity EIA in individuals from 4 cohorts representing different geographic locations and subtype infections: Amsterdam and Trinidad cohorts (subtype B; left), Kenya cohort (subtypes A and D; middle), and Ethiopia cohort (subtype C; right).

Each line represents a single individual with sequential specimens collected over time post-seroconversion (X-axis; note that scale is different in panel C due to longer follow up).

Figure 2. Comparative HIV antibody kinetics following seroconversion as detected by the BED assay (left), LAg-Avidity EIA (middle), and Avidity Index-EIA (right) among 89 seroconverting individuals (subtypes A ,B, C & D).

The BED assay measures increasing proportion of HIV-specific IgG in total IgG, while LAg-Avidity EIA and AI-EIA measure increasing avidity of HIV antibody. Both LAg-Avidity EIA and AI-EIA use multi-subtype gp41 recombinant protein, rIDR-M, and pH 3.0 dissociation buffer to distinguish recent and long-term HIV infections.

Figure 3. A) Increase in duration of mean recency (solid line) of LAg-Avidity EIA with varying cutoffs from 0.5 to 2.0 ODn.

The 95% confidence interval is shown by dotted lines. The numbers shown represent mean duration of recency, ω, at each cutoff. B) Empirical frequency distribution of duration of recency at cutoff of 1.0 for LAg-Avidity EIA.

Figure 4. A) Comparative OD or ODn values of a cross-sectional specimen set tested with Genetics Systems HIV-1/HIV-2 Plus O EIA and LAg-Avidity EIA.

Specimens are arranged in ascending ODn on LAg-Avidity EIA to represent avidity maturation since seroconversion; a horizintal line at 1.0 indicates cut-off for recent and long-term classification. Only first 35 specimens are shown for clarity. B) Corresponding HIV-1 Western blot banding profile of first 32 specimens showing increase in number and intensity of bands typical of antibody maturation. For the purpose of incidence estimation, vertical arrow indicates cutoff; recent infections = left of the arrow, long-term infections = right of the arrow.