Department of Infectious Disease Epidemiology, Bernhard Nocht Institute for Tropical Medicine, Bernhard Nocht Str. 74, 20359, Hamburg, Germany.
German Centre for Infection Research (DZIF), Hamburg-Lübeck-Borstel-Riems, Hamburg, Germany.
Sci Rep. 2020 Dec 3;10(1):21168. doi: 10.1038/s41598-020-78155-y.
A better understanding of disease-specific biomarker profiles during acute infections could guide the development of innovative diagnostic methods to differentiate between malaria and alternative causes of fever. We investigated autoantibody (AAb) profiles in febrile children (≤ 5 years) admitted to a hospital in rural Ghana. Serum samples from 30 children with a bacterial bloodstream infection and 35 children with Plasmodium falciparum malaria were analyzed using protein microarrays (Protoplex Immune Response Assay, ThermoFisher). A variable selection algorithm was applied to identify the smallest set of AAbs showing the best performance to classify malaria and bacteremia patients. The selection procedure identified 8 AAbs of which IFNGR2 and FBXW5 were selected in repeated model run. The classification error was 22%, which was mainly due to non-Typhi Salmonella (NTS) diagnoses being misclassified as malaria. Likewise, a cluster analysis grouped patients with NTS and malaria together, but separated malaria from non-NTS infections. Both current and recent malaria are a risk factor for NTS, therefore, a better understanding about the function of AAb in disease-specific immune responses is required in order to support their application for diagnostic purposes.
更好地了解急性感染期间特定于疾病的生物标志物谱，可以指导开发创新的诊断方法，以区分疟疾和发热的其他原因。我们研究了在加纳农村一家医院住院的发热儿童（≤5 岁）的自身抗体（AAb）谱。使用蛋白质微阵列（Protoplex 免疫反应分析，ThermoFisher）分析了 30 名细菌性血流感染患儿和 35 名恶性疟原虫疟疾患儿的血清样本。应用变量选择算法来确定表现最佳的最小一组 AAb，以对疟疾和菌血症患者进行分类。选择过程确定了 8 种 AAb，其中 IFNGR2 和 FBXW5 在重复模型运行中被选中。分类错误为 22%，主要是由于非伤寒沙门氏菌（NTS）诊断被误诊为疟疾。同样，聚类分析将 NTS 和疟疾患者分为一组，但将疟疾与非 NTS 感染分开。当前和近期的疟疾都是 NTS 的风险因素，因此，需要更好地了解 AAb 在特定于疾病的免疫反应中的功能，以支持其在诊断目的中的应用。
