High-throughput assay optimization and statistical interpolation of rubella-specific neutralizing antibody titers

Abstract

Rubella remains a social and economic burden due to the high incidence of congenital rubella syndrome (CRS) in some countries. For this reason, an accurate and efficient high-throughput measure of antibody response to vaccination is an important tool. In order to measure rubella-specific neutralizing antibodies in a large cohort of vaccinated individuals, a high-throughput immunocolorimetric system was developed. Statistical interpolation models were applied to the resulting titers to refine quantitative estimates of neutralizing antibody titers relative to the assayed neutralizing antibody dilutions. This assay, including the statistical methods developed, can be used to assess the neutralizing humoral immune response to rubella virus and may be adaptable for assessing the response to other viral vaccines and infectious agents.

FIG 1

Distribution of initial NT₅₀ values, estimated as the first dilution that resulted in a 50% reduction in observed activity from the positive control. Rubella virus-specific neutralizing antibodies were measured in 2,091 vaccinated subjects using a high-throughput ICA. The broad spectrum of observed NT₅₀ (0 to 1,600) demonstrates that there is a large range in the levels of neutralizing antibodies in vaccinated cohorts.

FIG 2

Distribution of interpolated NT₅₀ values, estimated via the loess-based interpolation approach. Rubella virus-specific neutralizing antibodies were interpolated for 2,090 vaccinated subjects, using a high-throughput ICA. This distribution agrees with that generated by the uninterpolated values, with the exception that fewer interpolated values were estimated to be less than a titer of 1:25.

FIG 3

Box plots of NT₅₀ values, estimated via the loess-based interpolation approach, within categories of initial NT₅₀ values, estimated without interpolation. A high degree of agreement is reflected between the two methods, as the box plots of the interpolated values demonstrate tight distributions within uninterpolated NT₅₀ values and they increase in a regular pattern as a function of the uninterpolated NT₅₀ values.

FIG 4

Scatter plot demonstrating the association between IgG levels calculated using a rubella virus-specific EIA and the interpolated values obtained from our high-throughput ICA for 732 participants with both measurements. Open circles represent the assay results from both assays, measured for each individual, and r_s is the IgG/NT₅₀ Spearman rank correlation coefficient. Although agreement between the two methods decreases with increasing antibody levels and the interpolated NT₅₀ values have a somewhat higher lower limit of detection, the correlation coefficient of 0.76 suggests a strong correspondence between results from the two assay methods.