Immunomics-guided discovery of serum and urine antibodies for diagnosing urogenital schistosomiasis: a biomarker identification study

Pearson, Mark S., Tedla, Bemnet A., Mekonnen, Gebeyaw G., Proietti, Carla, Becker, Luke, Nakajima, Rie, Jasinskas, Al, Doolan, Denise L., Amoah, Abena S., Knopp, Stefanie, Rollinson, David, Ali, Said M., Kabole, Fatma, Hokke, Cornelis H., Adegnika, Akim A., Field, Matt A., van Dam, Govert, Corstjens, Paul L.A.M., Mduluza, Takafira, Mutapi, Francisca, Oeuvray, Claude, Greco, Beatrice, Chaiyadet, Sujittra, Laha, Thewarach, Cai, Pengfei, McManus, Donald P., Bottazzi, Maria Elena, Felgner, Philip L., Sotillo, Javier, and Loukas, Alex (2021) Immunomics-guided discovery of serum and urine antibodies for diagnosing urogenital schistosomiasis: a biomarker identification study. The Lancet Microbe, 2 (11). e617-e626.

[img]
Preview
PDF (Published Version) - Published Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (1MB) | Preview
View at Publisher Website: https://doi.org/10.1016/s2666-5247(21)00...
 
23


Abstract

Background: Sensitive diagnostics are needed for effective management and surveillance of schistosomiasis so that current transmission interruption goals set by WHO can be achieved. We aimed to screen the Schistosoma haematobium secretome to find antibody biomarkers of schistosome infection, validate their diagnostic performance in samples from endemic populations, and evaluate their utility as point of care immunochromatographic tests (POC-ICTs) to diagnose urogenital schistosomiasis in the field.

Methods: We did a biomarker identification study, in which we constructed a proteome array containing 992 validated and predicted proteins from S haematobium and screened it with serum and urine antibodies from endemic populations in Gabon, Tanzania, and Zimbabwe. Arrayed antigens that were IgG-reactive and a select group of antigens from the worm extracellular vesicle proteome, predicted to be diagnostically informative, were then evaluated by ELISA using the same samples used to probe arrays, and samples from individuals residing in a low-endemicity setting (ie, Pemba and Unguja islands, Zanzibar, Tanzania). The two most sensitive and specific antigens were incorporated into POC-ICTs to assess their ability to diagnose S haematobium infection from serum in a field-deployable format.

Findings: From array probing, in individuals who were infected, 208 antigens were the targets of significantly elevated IgG responses in serum and 45 antigens were the targets of significantly elevated IgG responses in urine. Of the five proteins that were validated by ELISA, Sh-TSP-2 (area under the curve [AUC]serum=0·98 [95% CI 0·95–1·00]; AUCurine=0·96 [0·93–0·99]), and MS3_01370 (AUCserum=0·93 [0·89–0·97]; AUCurine=0·81 [0·72–0·89]) displayed the highest overall diagnostic performance in each biofluid and exceeded that of S haematobium-soluble egg antigen in urine (AUC=0·79 [0·69–0·90]). When incorporated into separate POC-ICTs, Sh-TSP-2 showed absolute specificity and a sensitivity of 75% and MS3_01370 showed absolute specificity and a sensitivity of 89%.

Interpretation: We identified numerous biomarkers of urogenital schistosomiasis that could form the basis of novel antibody diagnostics for this disease. Two of these antigens, Sh-TSP-2 and MS3_01370, could be used as sensitive, specific, and field-deployable diagnostics to support schistosomiasis control and elimination initiatives, with particular focus on post-elimination surveillance.

Item ID: 72409
Item Type: Article (Research - C1)
ISSN: 2666-5247
Copyright Information: © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license.
Funders: National Health and Medical Research Council (NHMRC)
Projects and Grants: NHMRC Senior Principal Research Fellowship (number APP1117504)
Date Deposited: 16 Feb 2022 01:56
FoR Codes: 32 BIOMEDICAL AND CLINICAL SCIENCES > 3204 Immunology > 320404 Cellular immunology @ 50%
31 BIOLOGICAL SCIENCES > 3102 Bioinformatics and computational biology > 310208 Translational and applied bioinformatics @ 50%
SEO Codes: 20 HEALTH > 2001 Clinical health > 200101 Diagnosis of human diseases and conditions @ 100%
Downloads: Total: 23
Last 12 Months: 13
More Statistics

Actions (Repository Staff Only)

Item Control Page Item Control Page