Comparative evaluation of plasma biomarkers of Schistosoma haematobium infection in endemic populations from Burkina Faso

Abstract

Infection with Schistosoma haematobium causes urogenital disease associated with organ disfunction, bleeding, pain, and higher susceptibility to infections and cancer. Timely and accurate diagnosis is crucial for prompt and appropriate treatment as well as surveillance efforts, and the use of plasma biomarkers offers important advantages over parasitological examination of urine, including increased sensitivity and the possibility to use the same specimen for multiple investigations. The present study aims to evaluate the diagnostic performance of different plasma biomarkers in endemic populations from Burkina Faso, West Africa. Schistosoma spp. Circulating Anodic Antigen (CAA), cell free S. haematobium DNA (cfDNA), class M and G antibodies against S. haematobium Soluble Worm Antigen Preparation (SWAP) and Soluble Egg Antigen (SEA) were measured in 406 plasma samples. Results of each biomarker test were compared to those of CAA, a Composite Reference Standard (CRS) and Latent Class Analysis (LCA). An identical proportion of positive samples (29%) was observed as a result of CAA and cfDNA testing, with a substantial agreement (84%, Cohen k = 0.62) between the results of the two tests, and a comparable agreement with the results of CRS and LCA. A higher positivity was observed, as expected, as a result of specific antibody testing (47%-72%), with IgG showing a higher agreement than IgM with the three references. Also, higher IgG levels were observed in current vs past infection, and ROC analysis identified optimal cutoff values for improved testing accuracy. This study provides compelling evidence that can inform the choice of the most appropriate diagnostic plasma biomarker for urogenital schistosomiasis in endemic areas, depending on the purpose, context, and available resources for testing. Either CAA or cfDNA testing can be used for the diagnosis of patients and for epidemiological investigations, even in absence of urine filtration microscopy, whereas anti-SWAP or anti-SEA IgG can be employed for surveillance and integrated monitoring of control interventions against poverty-associated diseases.

Fig 1. CAA and cfDNA positivity according to the breadth of the antibody response to S. haematobium antigens.

The figure shows the proportion of subjects showing results to CAA (blue) and cfDNA (green) testing according to the breadth of the antibody response to S. haematobium antigens. Bars represent proportion and whiskers represent the standard error of the proportion.

Fig 2. Proportion of cfDNA negative results according to CAA levels.

The figure shows the proportion of negative results according to CAA levels, i.e. concentration ranges (level 0 = 0–9 pg/ml range; level 1 = 10–99 pg/ml range; level 2 = 100–999 pg/ml range; level 3 = 1000–9999 pg/ml range; level 4≥10000pg/ml). Bars represent proportion and whiskers represent the standard error of the proportion.

Fig 3. Cutoff levels of anti-SWAP and anti-SEA IgG and diagnostic performance compared to Circulating Anodic Antigen.

The figure shows the plot of sensitivity (blue) and specificity (red) compared to Circulating Anodic Antigen for each cutoff value of anti-SWAP IgG (left panel) and anti-SEA IgG (right panel). The grey vertical line indicates the analytical cutoff.

Fig 4. Distribution of anti-SWAP and anti-SEA IgG levels according to Circulating Anodic Antigen positivity.

The figure shows the boxplot distribution of anti-SWAP (left panel) and anti-SEA (right panel) IgG levels according to Circulating Anodic Antigen (CAA) positivity (negative subjects, Neg; positive subjects; Pos). The horizontal line represents the 50% percentile (median), the box lower and upper limits represent the 25% and 75% percentiles respectively, and lower and upper whiskers represent the 5% and 95% percentiles respectively, while the dots are outliers of the distribution.

Fig 5. Correlation of anti-SWAP and anti-SEA IgG levels with Circulating Anodic Antigen concentration.

The figure shows scatterplots illustrating the correlation of anti-SWAP IgG levels (log fOD; left panel) and anti-SEA IgG levels (log fOD; right panel) with CAA concentration (log pm/ml). Dots represent actual data points, the line represent the fitted data, and the grey area represent the 95% confidence interval of the fitted line.

Fig 6. Sensitivity and specificity of S. haematobium plasma biomarkers compared to Circulating Anodic Antigen, Composite Reference Standard and Latent Class Analysis.

The figure shows forest plots of sensitivity (blue) and specificity (red) of different S. haematobium plasma biomarkers compared to Circulating Anodic Antigen (CAA, left panel), Composite Reference Standard (CRS, mid panel) and Latent Class Analysis (LCA, right panel). Dots represent the estimate and whiskers represent the 95% CI of the estimate.