Abstract
BackgroundMalaria antigen-specific antibodies and polymorphisms in host receptors involved in antibody functionality have been associated with different outcomes of Plasmodium falciparum infections. Thus, to identify key prospective malaria antigens for vaccine development, there is the need to evaluate the associations between malaria antibodies and antibody dependent host factors with more rigorous statistical methods. In this study, different statistical models were used to evaluate the predictive performance of malaria-specific antibodies and host gene polymorphisms on P. falciparum infection in a longitudinal cohort study involving Ghanaian children.MethodsModels with different functional forms were built using known predictors (age, sickle cell status, blood group status, parasite density, and mosquito bed net use) and malaria antigen-specific immunoglobulin (Ig) G and IgG subclasses and FCGR3B polymorphisms shown to mediate antibody-dependent cellular functions. Malaria antigens studied were Merozoite surface proteins (MSP-1 and MSP-3), Glutamate Rich Protein (GLURP)-R0, R2, and the Apical Membrane Antigen (AMA-1). The models were evaluated through visualization and assessment of differences between the Area Under the Receiver Operating Characteristic Curve and Brier Score estimated by suitable internal cross-validation designs.ResultsThis study found that the FCGR3B-c.233C>A genotype and IgG against AMA1 were relatively better compared to the other antibodies and FCGR3B genotypes studied in classifying or predicting malaria risk among children.ConclusionsThe data supports the P. falciparum, AMA1 as an important malaria vaccine antigen, while FCGR3B-c.233C>A under the additive and dominant models of inheritance could be an important modifier of the effect of malaria protective antibodies.
Highlights
Malaria antigen-specific antibodies and polymorphisms in host receptors involved in antibody functionality have been associated with different outcomes of Plasmodium falciparum infections
It has recently been shown that interaction between naturally acquired antibodies to Plasmodium falciparum and polymorphisms in host FCGR3B gene, encoding the Fc Gamma Receptor IIIB (FcγRIIIB) plays a key role in immunity against malaria [4]
It is quite plausible that the long delay in attaining an effective malaria vaccine may partly be due to inadequacies of traditional statistical approaches used in malaria immuno-epidemiological studies to determine the performance of predictors in classifying or predicting malaria risk [7,8,9,10]
Summary
Malaria antigen-specific antibodies and polymorphisms in host receptors involved in antibody functionality have been associated with different outcomes of Plasmodium falciparum infections. A robust malaria risk prediction model based on epidemiological predictors may contribute to finding possible answers to the question of which parasite antigens and host factors should be the main research focus in the efforts to find optimal control strategies and vaccines. This is important as the number of malaria-specific antibodies and host gene polymorphisms found to be associated with clinical malaria have increased significantly over the past few years [3] but with little impact on malaria control. To assess the performance of the models, this study used Brier scores and area under the receiver operating characteristic curve (AUROC) through appropriate bootstrap cross-validation design
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