A systems serology approach to identifying key antibody correlates of protection from cerebral malaria in Malawian children

IF 7 1区 医学 Q1 MEDICINE, GENERAL & INTERNAL
Isobel S. Walker, Saber Dini, Elizabeth H. Aitken, Timon Damelang, Wina Hasang, Agersew Alemu, Anja T. R. Jensen, Janavi S. Rambhatla, D. Herbert Opi, Michael F. Duffy, Eizo Takashima, Visopo Harawa, Takafumi Tsuboi, Julie A. Simpson, Wilson Mandala, Terrie E. Taylor, Karl B. Seydel, Amy W. Chung, Stephen J. Rogerson
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Abstract

Plasmodium falciparum erythrocyte membrane protein 1 (PfEMP1) proteins are expressed on the surface of infected erythrocytes, mediating parasite sequestration in the vasculature. PfEMP1 is a major target of protective antibodies, but the features of the antibody response are poorly defined. In Malawian children with cerebral or uncomplicated malaria, we characterized the antibody response to 39 recombinant PfEMP1 Duffy binding like (DBL) domains or cysteine-rich interdomain regions (CIDRs) in detail, including measures of antibody classes, subclasses, and engagement with Fcγ receptors and complement. Using elastic net regularized logistic regression, we identified a combination of seven antibody targets and Fc features that best distinguished between children with cerebral and uncomplicated malaria. To confirm the role of the selected targets and Fc features, we measured antibody-dependent neutrophil and THP-1 cell phagocytosis of intercellular adhesion molecule-1 (ICAM-1) and endothelial protein C (EPCR) co-binding infected erythrocytes. The selected features distinguished between children with cerebral and uncomplicated malaria with 87% accuracy (median, 80–96% interquartile range) and included antibody to well-characterized DBLβ3 domains and a less well-characterized CIDRγ12 domain. The abilities of antibodies to engage C1q and FcγRIIIb, rather than levels of IgG, correlated with protection. In line with a role of FcγRIIIb binding antibodies to DBLβ3 domains, antibody-dependent neutrophil phagocytosis of ICAM-1 and EPCR co-binding IE was higher in uncomplicated malaria (15% median, 8–38% interquartile range) compared to cerebral malaria (7%, 30–15%, p < 0.001). Antibodies associated with protection from cerebral malaria target a subset of PfEMP1 domains. The Fc features of protective antibody response include engagement of FcγRIIIb and C1q, and ability to induce antibody-dependent neutrophil phagocytosis of infected erythrocytes. Identifying the targets and Fc features of protective immunity could facilitate the development of PfEMP1-based therapeutics for cerebral malaria.
采用系统血清学方法确定马拉维儿童脑疟疾防护的关键抗体相关因素
恶性疟原虫红细胞膜蛋白 1(PfEMP1)蛋白表达于受感染的红细胞表面,介导寄生虫在血管中的固着。PfEMP1 是保护性抗体的一个主要靶点,但抗体反应的特征尚不明确。在马拉维患有脑疟疾或无并发症疟疾的儿童中,我们详细描述了针对 39 个重组 PfEMP1 Duffy 结合样(DBL)结构域或富半胱氨酸结构域间区(CIDR)的抗体反应,包括抗体类别、亚类以及与 Fcγ 受体和补体的接触情况。利用弹性网正则逻辑回归,我们确定了七个抗体靶点和 Fc 特征的组合,它们是区分脑疟疾患儿和非并发疟疾患儿的最佳方法。为了证实所选靶点和 Fc 特征的作用,我们测量了抗体依赖性中性粒细胞和 THP-1 细胞对细胞间粘附分子-1(ICAM-1)和内皮细胞蛋白 C(EPCR)共同结合的受感染红细胞的吞噬作用。所选特征区分脑型疟疾和无并发症疟疾患儿的准确率为87%(中位数,80-96%四分位数间范围),包括特征明确的DBLβ3结构域抗体和特征不明确的CIDRγ12结构域抗体。抗体接合 C1q 和 FcγRIIIb 的能力,而不是 IgG 的水平,与保护作用相关。与 FcγRIIIb 结合 DBLβ3 结构域的抗体的作用相一致的是,与脑型疟疾(7%,30-15%,p < 0.001)相比,无并发症疟疾中 ICAM-1 和 EPCR 共同结合 IE 的抗体依赖性中性粒细胞吞噬率更高(中位数为 15%,四分位数间范围为 8-38%)。与脑型疟疾保护相关的抗体针对的是 PfEMP1 结构域的一个子集。保护性抗体反应的 Fc 特征包括 FcγRIIIb 和 C1q 的参与,以及诱导抗体依赖性中性粒细胞吞噬受感染红细胞的能力。确定保护性免疫的靶点和 Fc 特征有助于开发基于 PfEMP1 的脑疟疾疗法。
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来源期刊
BMC Medicine
BMC Medicine 医学-医学:内科
CiteScore
13.10
自引率
1.10%
发文量
435
审稿时长
4-8 weeks
期刊介绍: BMC Medicine is an open access, transparent peer-reviewed general medical journal. It is the flagship journal of the BMC series and publishes outstanding and influential research in various areas including clinical practice, translational medicine, medical and health advances, public health, global health, policy, and general topics of interest to the biomedical and sociomedical professional communities. In addition to research articles, the journal also publishes stimulating debates, reviews, unique forum articles, and concise tutorials. All articles published in BMC Medicine are included in various databases such as Biological Abstracts, BIOSIS, CAS, Citebase, Current contents, DOAJ, Embase, MEDLINE, PubMed, Science Citation Index Expanded, OAIster, SCImago, Scopus, SOCOLAR, and Zetoc.
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