PLoS ONE (Jan 2018)
Sera selected from national STI surveillance system shows Chlamydia trachomatis PgP3 antibody correlates with time since infection and number of previous infections.
Abstract
BackgroundSeroprevalence surveys of Chlamydia trachomatis (CT) antibodies are promising for estimating age-specific CT cumulative incidence, however accurate estimates require improved understanding of antibody response to CT infection.MethodsWe used GUMCAD, England's national sexually transmitted infection (STI) surveillance system, to select sera taken from female STI clinic attendees on the day of or after a chlamydia diagnosis. Serum specimens were collected from laboratories and tested anonymously on an indirect and a double-antigen ELISA, both of which are based on the CT-specific Pgp3 antigen. We used cross-sectional and longitudinal descriptive analyses to explore the relationship between seropositivity and a) cumulative number of chlamydia diagnoses and b) time since most recent chlamydia diagnosis.Results919 samples were obtained from visits when chlamydia was diagnosed and 812 during subsequent follow-up visits. Pgp3 seropositivity using the indirect ELISA increased from 57.1% (95% confidence interval: 53.2-60.7) on the day of a first-recorded chlamydia diagnosis to 89.6% (95%CI: 79.3-95.0) on the day of a third or higher documented diagnosis. With the double-antigen ELISA, the increase was from 61.1% (95%CI: 53.2-60.7) to 97.0% (95%CI: 88.5-99.3). Seropositivity decreased with time since CT diagnosis on only the indirect assay, to 49.3% (95%CI: 40.9-57.7) two or more years after a first diagnosis and 51.9% (95%CI: 33.2-70.0) after a repeat diagnosis.ConclusionSeropositivity increased with cumulative number of infections, and decreased over time after diagnosis on the indirect ELISA, but not on the double-antigen ELISA. This is the first study to demonstrate the combined impact of number of chlamydia diagnoses, time since diagnosis, and specific ELISA on Pgp3 seropositivity. Our findings are being used to inform models estimating age-specific chlamydia incidence over time using serial population-representative serum sample collections, to enable accurate public health monitoring of chlamydia.