Analytical approaches for antimalarial antibody responses to confirm historical and recent malaria transmission: an example from the Philippines
Analytical approaches for antimalarial antibody responses to confirm historical and recent malaria transmission: an example from the Philippines
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用于确认历史和近期疟疾传播的抗疟抗体反应的分析方法：来自菲律宾的例子
DOI：
10.1101/2022.06.16.22276488
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发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Macalinao M
中科院分区：
文献类型：
--
作者：
Macalinao M
随着各国接近消灭疟疾，评估疟疾流行地区的传播状况变得越来越具有挑战性。血清学可以提供强大的估计疟疾传播强度，多重血清学检测允许同时评估最近和历史的疟疾exposure.MethodsHere的标记，我们评估了不同的统计和机器学习方法，用于分析多重疟疾特异性抗体反应数据，分类最近和历史的接触恶性疟原虫和间日疟原虫。为了评估这些方法，我们利用了来自菲律宾卫生机构的调查（n = 9132）样本，在那里我们量化了来自3个不同传播强度的地点的8个恶性疟原虫和6个间日疟原虫特异性抗原的抗体应答。在测试的模型中，使用4种血清学标志物（PfGLURP R2、Etramp5.Ag1、GEXP 18和PfMSP 119）的机器学习（ML）方法（随机森林模型）对巴拉望的恶性疟原虫近期感染（AUC：0.9591，CI 0.9497-0.9684）的预测优于单个抗原血清阳性。尽管ML方法没有改善间日疟原虫感染的预测，ML分类证实了西方民都洛和巴丹岛最近没有暴露于恶性疟原虫和间日疟原虫。为了预测历史恶性疟原虫和间日疟原虫传播，基于累积暴露标记物AMA 1和MSP 119的血清阳性率和血清转换率在3个地点显示了可靠的趋势。还强调了利用多重抗体反应的机器学习模型的潜在用途，以改善对旨在消除疟疾的国家的疟疾传播状况的评估。这项工作还为监测菲律宾疟疾流行地区的风险提供了基线抗体数据。
BackgroundAssessing the status of malaria transmission in endemic areas becomes increasingly challenging as countries approach elimination. Serology can provide robust estimates of malaria transmission intensities, and multiplex serological assays allow for simultaneous assessment of markers of recent and historical malaria exposure.MethodsHere, we evaluated different statistical and machine learning methods for analyzing multiplex malaria-specific antibody response data to classify recent and historical exposure toPlasmodium falciparumandPlasmodium vivax. To assess these methods, we utilized samples from a health-facility based survey (n = 9132) in the Philippines, where we quantified antibody responses against 8P. falciparumand 6P. vivax-specific antigens from 3 sites with varying transmission intensity.FindingsMeasurements of antibody responses and seroprevalence were consistent with the 3 sites' known endemicity status. Among the models tested, a machine learning (ML) approach (Random Forest model) using 4 serological markers (PfGLURP R2, Etramp5.Ag1, GEXP18, and PfMSP119) gave better predictions forP. falciparumrecent infection in Palawan (AUC: 0.9591, CI 0.9497–0.9684) than individual antigen seropositivity. Although the ML approach did not improveP. vivaxinfection predictions, ML classifications confirmed the absence of recent exposure toP. falciparumandP. vivaxin both Occidental Mindoro and Bataan. For predicting historicalP. falciparumandP. vivaxtransmission, seroprevalence and seroconversion rates based on cumulative exposure markers AMA1 and MSP119showed reliable trends in the 3 sites.InterpretationOur study emphasizes the utility of serological markers in predicting recent and historical exposure in a sub-national elimination setting, and also highlights the potential use of machine learning models using multiplex antibody responses to improve assessment of the malaria transmission status of countries aiming for elimination. This work also provides baseline antibody data for monitoring risk in malaria-endemic areas in the Philippines.FundingNewton Fund, Philippine Council for Health Research and Development, UK Medical Research Council.
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影响因子：
4.1
作者：
Sepúlveda N;Stresman G;White MT;Drakeley CJ
通讯作者：
Drakeley CJ
影响因子：
3
作者：
Niass O;Saint-Pierre P;Niang M;Diop F;Diouf B;Faye MM;Sarr FD;Faye J;Diagne N;Sokhna C;Trape JF;Perraut R;Tall A;Diongue AK;Toure Balde A
通讯作者：
Toure Balde A
血清学揭示了南非东北部恶性疟原虫传播的异质性：消除疟疾的影响。
影响因子：
3
作者：
Biggs J;Raman J;Cook J;Hlongwana K;Drakeley C;Morris N;Serocharan I;Agubuzo E;Kruger P;Mabuza A;Zitha A;Machaba E;Coetzee M;Kleinschmidt I
通讯作者：
Kleinschmidt I
影响因子：
3.1
作者：
TAYLOR, RR;SMITH, DB;RILEY, EM
通讯作者：
RILEY, EM
影响因子：
4.8
作者：
Collins, Christine R.;Withers-Martinez, Chrislaine;Blackman, Michael J.
通讯作者：
Blackman, Michael J.