Developing a multivariate prediction model of antibody features associated with protection of malaria-infected pregnant women from placental malaria.

Elizabeth H Aitken,Morten A Nielsen,Holger W Unger,Ali Salanti,Joe Smith,Agersew Alemu,Amaya Ortega-Pajares,Julie A Simpson,Wina Hasang,Amy W Chung,P Mark Hogarth,Bruce D Wines,Stephen J Rogerson,Timon Damelang,Maria Ome-Kaius,Stephen Kent,Saber Dini

doi:10.7554/elife.65776

Abstract

Plasmodium falciparum causes placental malaria, which results in adverse outcomes for mother and child. P. falciparum-infected erythrocytes that express the parasite protein VAR2CSA on their surface can bind to placental chondroitin sulfate A. It has been hypothesized that naturally acquired antibodies towards VAR2CSA protect against placental infection, but it has proven difficult to identify robust antibody correlates of protection from disease. The objective of this study was to develop a prediction model using antibody features that could identify women protected from placental malaria. We used a systems serology approach with elastic net-regularized logistic regression, partial least squares discriminant analysis, and a case-control study design to identify naturally acquired antibody features mid-pregnancy that were associated with protection from placental malaria at delivery in a cohort of 77 pregnant women from Madang, Papua New Guinea. The machine learning techniques selected 6 out of 169 measured antibody features towards VAR2CSA that could predict (with 86% accuracy) whether a woman would subsequently have active placental malaria infection at delivery. Selected features included previously described associations with inhibition of placental binding and/or opsonic phagocytosis of infected erythrocytes, and network analysis indicated that there are not one but multiple pathways to protection from placental malaria. We have identified candidate antibody features that could accurately identify malaria-infected women as protected from placental infection. It is likely that there are multiple pathways to protection against placental malaria. This study was supported by the National Health and Medical Research Council (Nos. APP1143946, GNT1145303, APP1092789, APP1140509, and APP1104975).

Highlights

The burden of Plasmodium falciparum malaria is greatest in young children and pregnant women (World Health Organisation, 2019)
We used a systems serology approach to broadly characterize antibody responses to the VAR2CSA protein that mediates protection from placental malaria. This involved measuring a wide range of antibody features to this protein followed by employing the machine learning techniques elastic netregularized regression and Partial least squares discriminant analysis (PLSDA) to identify those antibody features that protect pregnant women with P. falciparum infection from placental malaria
We identified six antibody features of 169 tested, which were able to correctly differentiate, on average, 86% of the pregnant women with placental malaria and non-placental infection

Summary

Introduction

The burden of Plasmodium falciparum malaria is greatest in young children and pregnant women (World Health Organisation, 2019). The susceptibility of pregnant women to P. falciparum malaria is in part due to the ability of infected erythrocytes (IEs) to sequester in the maternal blood spaces of the placenta (Rogerson et al, 2007), where IEs that express VAR2CSA adhere to chondroitin sulfate A (CSA), a glycosaminoglycan chain on syndecan-1 expressed by the placental syncytiotrophoblast (Salanti et al, 2004; Ayres Pereira et al, 2016). P. falciparum-infected erythrocytes that express the parasite protein VAR2CSA on their surface can bind to placental chondroitin sulfate A. The objective of this study was to develop a prediction model using antibody features that could identify women protected from placental malaria. Methods: We used a systems serology approach with elastic net-regularized logistic regression, partial least squares discriminant analysis, and a case-control study design to identify naturally acquired antibody features mid-pregnancy that were associated with protection from placental malaria at delivery in a cohort of 77 pregnant women from Madang, Papua New Guinea. Selected features included previously described associations with inhibition of placental binding and/or opsonic phagocytosis of infected

Objectives

Results

Conclusion