Brian R Omondi1,2, Michelle K Muthui1, William I Muasya1, Benedict Orindi1, Ramadhan S Mwakubambanya2, Teun Bousema3, Chris Drakeley4, Kevin Marsh1,5, Philip Bejon1,5, Melissa C Kapulu1,5. 1. Department of Biosciences, KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya. 2. Department of Biochemistry and Molecular Biology, Egerton University, Nakuru, Kenya. 3. Department of Medical Microbiology, Radboud University Medical Centre, Nijmegen, Netherlands. 4. Department of Infection Biology, London School of Hygiene & Tropical Medicine, London, United Kingdom. 5. Centre for Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, United Kingdom.
Abstract
Background: Malaria caused by Plasmodium falciparum remains a serious global public health challenge especially in Africa. Interventions that aim to reduce malaria transmission by targeting the gametocyte reservoir are key to malaria elimination and/or eradication. However, factors that are associated with gametocyte carriage have not been fully explored. Consequently, identifying predictors of the infectious reservoir is fundamental in the elimination campaign. Methods: We cultured P. falciparum NF54 gametocytes (to stage V) and prepared crude gametocyte extract. Samples from a total of 687 participants (aged 6 months to 67 years) representing two cross-sectional study cohorts in Kilifi, Kenya were used to assess IgG antibody responses by ELISA. We also analyzed IgG antibody responses to the blood-stage antigen AMA1 as a marker of asexual parasite exposure. Gametocytemia and asexual parasitemia data quantified by microscopy and molecular detection (QT-NASBA) were used to determine the relationship with antibody responses, season, age, and transmission setting. Multivariable logistic regression models were used to study the association between antibody responses and gametocyte carriage. The predictive power of the models was tested using the receiver operating characteristic (ROC) curve. Results: Multivariable logistic regression analysis showed that IgG antibody response to crude gametocyte extract predicted both microscopic (OR=1.81 95% CI: 1.06-3.07, p=0.028) and molecular (OR=1.91, 95% CI: 1.11-3.29, p=0.019) P. falciparum gametocyte carriage. Antibody responses to AMA1 were also associated with both microscopic (OR=1.61 95% CI: 1.08-2.42, p=0.020) and molecular (OR=3.73 95% CI: 2.03-6.74, p<0.001) gametocytemia. ROC analysis showed that molecular (AUC=0.897, 95% CI: 0.868-0.926) and microscopic (AUC=0.812, 95% CI: 0.758-0.865) multivariable models adjusted for gametocyte extract showed very high predictive power. Molecular (AUC=0.917, 95% CI: 0.891-0.943) and microscopic (AUC=0.806, 95% CI: 0.755-0.858) multivariable models adjusted for AMA1 were equally highly predictive. Conclusion: In our study, it appears that IgG responses to crude gametocyte extract are not an independent predictor of gametocyte carriage after adjusting for AMA1 responses but may predict gametocyte carriage as a proxy marker of exposure to parasites. Serological responses to AMA1 or to gametocyte extract may facilitate identification of individuals within populations who contribute to malaria transmission and support implementation of transmission-blocking interventions.
Background: Malaria caused by Plasmodium falciparum remains a serious global public health challenge especially in Africa. Interventions that aim to reduce malaria transmission by targeting the gametocyte reservoir are key to malaria elimination and/or eradication. However, factors that are associated with gametocyte carriage have not been fully explored. Consequently, identifying predictors of the infectious reservoir is fundamental in the elimination campaign. Methods: We cultured P. falciparum NF54 gametocytes (to stage V) and prepared crude gametocyte extract. Samples from a total of 687 participants (aged 6 months to 67 years) representing two cross-sectional study cohorts in Kilifi, Kenya were used to assess IgG antibody responses by ELISA. We also analyzed IgG antibody responses to the blood-stage antigen AMA1 as a marker of asexual parasite exposure. Gametocytemia and asexual parasitemia data quantified by microscopy and molecular detection (QT-NASBA) were used to determine the relationship with antibody responses, season, age, and transmission setting. Multivariable logistic regression models were used to study the association between antibody responses and gametocyte carriage. The predictive power of the models was tested using the receiver operating characteristic (ROC) curve. Results: Multivariable logistic regression analysis showed that IgG antibody response to crude gametocyte extract predicted both microscopic (OR=1.81 95% CI: 1.06-3.07, p=0.028) and molecular (OR=1.91, 95% CI: 1.11-3.29, p=0.019) P. falciparum gametocyte carriage. Antibody responses to AMA1 were also associated with both microscopic (OR=1.61 95% CI: 1.08-2.42, p=0.020) and molecular (OR=3.73 95% CI: 2.03-6.74, p<0.001) gametocytemia. ROC analysis showed that molecular (AUC=0.897, 95% CI: 0.868-0.926) and microscopic (AUC=0.812, 95% CI: 0.758-0.865) multivariable models adjusted for gametocyte extract showed very high predictive power. Molecular (AUC=0.917, 95% CI: 0.891-0.943) and microscopic (AUC=0.806, 95% CI: 0.755-0.858) multivariable models adjusted for AMA1 were equally highly predictive. Conclusion: In our study, it appears that IgG responses to crude gametocyte extract are not an independent predictor of gametocyte carriage after adjusting for AMA1 responses but may predict gametocyte carriage as a proxy marker of exposure to parasites. Serological responses to AMA1 or to gametocyte extract may facilitate identification of individuals within populations who contribute to malaria transmission and support implementation of transmission-blocking interventions.
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