Department of Biosciences, KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya.
Department of Biochemistry and Molecular Biology, Egerton University, Nakuru, Kenya.
Front Immunol. 2021 Feb 3;11:609474. doi: 10.3389/fimmu.2020.609474. eCollection 2020.
Malaria caused by 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.
We cultured 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.
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, =0.028) and molecular (OR=1.91, 95% CI: 1.11-3.29, =0.019) gametocyte carriage. Antibody responses to AMA1 were also associated with both microscopic (OR=1.61 95% CI: 1.08-2.42, =0.020) and molecular (OR=3.73 95% CI: 2.03-6.74, <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.
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.
由 引起的疟疾仍然是一个严重的全球公共卫生挑战，尤其是在非洲。旨在通过靶向配子体库来减少疟疾传播的干预措施是疟疾消除和/或根除的关键。然而，与配子体携带相关的因素尚未得到充分探索。因此，确定传染性储库的预测因子对于消除运动至关重要。
我们培养 NF54 配子体（至第 V 期）并制备粗配子体提取物。总共使用了来自肯尼亚基利菲的两个横断面研究队列的 687 名参与者（年龄在 6 个月至 67 岁之间）的样本，通过 ELISA 评估 IgG 抗体反应。我们还分析了针对血期抗原 AMA1 的 IgG 抗体反应，作为无性寄生虫暴露的标志物。使用显微镜和分子检测（QT-NASBA）量化的配子体血症和无性寄生虫血症数据，用于确定与抗体反应、季节、年龄和传播环境的关系。使用多变量逻辑回归模型研究抗体反应与配子体携带之间的关联。使用接收者操作特征 (ROC) 曲线测试模型的预测能力。
多变量逻辑回归分析表明，粗配子体提取物的 IgG 抗体反应预测了显微镜（OR=1.81，95%CI：1.06-3.07，=0.028）和分子（OR=1.91，95%CI：1.11-3.29，=0.019）配子体携带。AMA1 的抗体反应也与显微镜（OR=1.61，95%CI：1.08-2.42，=0.020）和分子（OR=3.73，95%CI：2.03-6.74，<0.001）配子体血症均相关。ROC 分析表明，分子（AUC=0.897，95%CI：0.868-0.926）和显微镜（AUC=0.812，95%CI：0.758-0.865）经配子体提取物调整的多变量模型显示出非常高的预测能力。分子（AUC=0.917，95%CI：0.891-0.943）和显微镜（AUC=0.806，95%CI：0.755-0.858）经 AMA1 调整的多变量模型具有同等高的预测能力。
在我们的研究中，似乎 IgG 对粗配子体提取物的反应在调整 AMA1 反应后不是配子体携带的独立预测因子，但可能作为暴露于寄生虫的替代标志物预测配子体携带。针对 AMA1 或配子体提取物的血清学反应可能有助于识别人群中有助于疟疾传播的个体，并支持实施阻断传播的干预措施。
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