Novel serologic biomarkers provide accurate estimates of recent Plasmodium falciparum exposure for individuals and communities.


Helb, DA; Tetteh, KK; Felgner, PL; Skinner, J; Hubbard, A; Arinaitwe, E; Mayanja-Kizza, H; Ssewanyana, I; Kamya, MR; Beeson, JG; Tappero, J; Smith, DL; Crompton, PD; Rosenthal, PJ; Dorsey, G; Drakeley, CJ; Greenhouse, B; (2015) Novel serologic biomarkers provide accurate estimates of recent Plasmodium falciparum exposure for individuals and communities. Proceedings of the National Academy of Sciences of the United States of America, 112 (32). E4438-47. ISSN 0027-8424 DOI: https://doi.org/10.1073/pnas.1501705112

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Abstract

: Tools to reliably measure Plasmodium falciparum (Pf) exposure in individuals and communities are needed to guide and evaluate malaria control interventions. Serologic assays can potentially produce precise exposure estimates at low cost; however, current approaches based on responses to a few characterized antigens are not designed to estimate exposure in individuals. Pf-specific antibody responses differ by antigen, suggesting that selection of antigens with defined kinetic profiles will improve estimates of Pf exposure. To identify novel serologic biomarkers of malaria exposure, we evaluated responses to 856 Pf antigens by protein microarray in 186 Ugandan children, for whom detailed Pf exposure data were available. Using data-adaptive statistical methods, we identified combinations of antibody responses that maximized information on an individual's recent exposure. Responses to three novel Pf antigens accurately classified whether an individual had been infected within the last 30, 90, or 365 d (cross-validated area under the curve = 0.86-0.93), whereas responses to six antigens accurately estimated an individual's malaria incidence in the prior year. Cross-validated incidence predictions for individuals in different communities provided accurate stratification of exposure between populations and suggest that precise estimates of community exposure can be obtained from sampling a small subset of that community. In addition, serologic incidence predictions from cross-sectional samples characterized heterogeneity within a community similarly to 1 y of continuous passive surveillance. Development of simple ELISA-based assays derived from the successful selection strategy outlined here offers the potential to generate rich epidemiologic surveillance data that will be widely accessible to malaria control programs.<br/>

Item Type: Article
Faculty and Department: Faculty of Infectious and Tropical Diseases > Dept of Immunology and Infection
Faculty of Infectious and Tropical Diseases > Dept of Clinical Research
Research Centre: Malaria Centre
PubMed ID: 26216993
Web of Science ID: 359285100015
URI: http://researchonline.lshtm.ac.uk/id/eprint/2255457

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