The burden of Plasmodium falciparum malaria is greatest in young children and pregnant women (World Health Organisation, 2019). Among women with lifelong malaria exposure, pregnant women have increased susceptibility to malaria, and complications include maternal mortality, severe maternal anemia, miscarriage and stillbirth, and impaired fetal growth or prematurity leading to low birth weight delivery (Steketee et al., 2001; Guyatt and Snow, 2001; Desai et al., 2007; Moore et al., 2017a; Moore et al., 2017b). The prevalence, intensity, and consequences of infection decline with increasing gravidity (Guyatt and Snow, 2001).

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). VAR2CSA is a unique 350 kDa protein that is a member of the P. falciparum erythrocyte membrane protein 1 (PfEMP1) family of variant surface antigens (VSA). PfEMP1s are encoded by var genes and are composed of multiple Duffy binding-like (DBL) domains and cysteine-rich interdomain regions (CIDR). VAR2CSA has six DBL domains, with CSA adhesion being strongly associated with the DBL2 domain, which is present in the N-terminal region of the protein (Doritchamou et al., 2013). Two constructs based on this region have entered clinical trials as vaccine candidates to prevent placental malaria (Mordmüller et al., 2019; Sirima et al., 2020).

Antibodies to VAR2CSA, in its native form on IE or expressed as recombinant protein, develop in a parity-dependent manner, block adhesion to CSA, and opsonize IE for phagocytosis by monocytic cells (Fried et al., 1998; Ricke et al., 2000; Salanti et al., 2004; Keen et al., 2007). Some studies report associations between measures of single antibody features and protection from malaria complications such as placental infection, impaired fetal growth, prematurity, or anemia (Duffy and Fried, 2003; Staalsoe et al., 2004; Feng et al., 2009). However, identifying targets and features of protective antibody responses to malaria is challenging because exposure to infection is accompanied by the production of antibody to many parasite antigens, only a fraction of which contributes to protective immunity (Crompton et al., 2010). The large size and multidomain structure of VAR2CSA adds complexity to the identification of targets and features of protective immune response. In a recent systematic review, antibody responses to VAR2CSA were often correlated with exposure to placental malaria, rather than protection from infection (Cutts et al., 2020), although some studies indicate an association between antibody to IE and protection from low birth weight in subsets of pregnant women (Duffy and Fried, 2003; Staalsoe et al., 2004; Feng et al., 2009).

To identify antibody responses that protect women from placental malaria, an alternative approach that examines multiple antibody features and controls for exposure may be needed. Placental malaria mostly occurs when antigenic variation (Roberts et al., 1992) leads to a parasite that has infected a pregnant woman, expressing VAR2CSA. These parasites can flourish by sequestering in the placenta in women who lack VAR2CSA-specific immunity (Hviid, 2004). By contrast, some pregnant women with peripheral blood infection remain free of placental malaria, and we postulate that these women have antibody responses that specifically protect them against VAR2CSA and placental malaria.

Antibody measures towards the IE have traditionally focused on the quantity of bound antibodies and their ability to inhibit IE binding to CSA (Cutts et al., 2020), but there is increasing interest in how antibodies that recognize IE engage with innate immune cells and activate complement (Aitken et al., 2020), which are both determined by biophysical features of the Fab and Fc regions of antibody (reviewed in Arnold and Chung, 2018). In recent years, detailed functional and biophysical characterization of antibody responses has led to the identification of specific antibody determinants that correlate with vaccine-induced protection from HIV (Chung et al., 2015), control of latent tuberculosis infection (Lu et al., 2016), transplacental transfer of antibody (Martinez et al., 2019; Jennewein et al., 2019), and correlates of vaccine-induced protection in human malaria challenge models (Suscovich et al., 2020). This approach, which has been termed systems serology, is well suited to placental malaria because there is a clear relationship between a single antigen (VAR2CSA) and a specific pathology (the sequestration of parasites in the placenta, reviewed in Ataíde et al., 2014).

The objective of this study was develop a prognostic model using antibody features to identify women protected from placental malaria. In this prospective study, we identified features, functions, and targets of naturally acquired antibody to VAR2CSA that contribute to protection against placental malaria. Pregnant Papua New Guinean women who were participating in a trial of intermittent preventive treatment against malaria (Unger et al., 2015) were categorized at delivery as currently uninfected, having placental malaria, or having a non-placental infection. Using plasma samples collected at enrollment in mid-pregnancy, we performed extensive profiling of antibody responses to VAR2CSA recombinant proteins and IEs expressing VAR2CSA. Machine learning techniques revealed that 6 of 169 antibody features measured mid-pregnancy were able to discriminate between women who had placental malaria and non-placental infection at delivery with high accuracy. Five of the six leading antibody features we found were related to inhibition of placental sequestration and/or opsonization for phagocytic clearance.

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 net-regularized regression and PLSDA to identify those antibody features that protect pregnant women with P. falciparum infection from placental malaria. The combination of a prospective study design and a systems serology approach provided an unbiased way to identify the key features of the antibody response to VAR2CSA that mediates protection. Using this approach, 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. The antibody features identified fell into broad functional groups: antibody that blocks placental binding of IEs and opsonizing antibody that result in phagocytic clearance of IEs (see Figure 6 for a schematic of mechanisms of protection of the six selected antibody features).

Figure 6

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We hypothesized that pregnant women who had P. falciparum peripheral blood parasitemia at delivery but who did not have placental sequestration were protected from placental malaria by antibody immunity targeting VAR2CSA, and we sought to determine the characteristics of this protective antibody response. We frequency matched groups on participant characteristics such as gravidity and urban or rural residence to minimize confounding by these variables that are known to affect exposure and immunity. Antibody features at enrollment did not differ between women with placental malaria and those who were uninfected at delivery, but they did differ between infected women with and without placental malaria at delivery.

Unlike previously published studies (Aitken et al., 2010; Fried et al., 2018), the inclusion of an infected group without placental malaria allowed us to accurately control for exposure to the parasite at the time point of outcome. The lack of differences in antibody features between the non-infected and placental malaria groups was quite striking and mirrors previous observations (reviewed by Cutts et al., 2020). It may in part be attributable to the heterogeneous nature of the non-infected group, which probably includes both women who are exposed but protected by antibody and women who have not been exposed to malaria in pregnancy and therefore lack pregnancy-specific antibodies. It is possible that the non-infected group is protected by antibodies towards other antigens. That differences were seen only when comparing the two infected groups, clearly highlighting the importance for controlling for exposure when studying antibody responses and protection from malaria. In Cameroon, multigravid women studied in early pregnancy who did not go on to have placental malaria had a greater breadth and intensity of antibody responses to DBL domains than those with placental malaria at delivery (Tutterrow et al., 2012), and higher avidity antibodies to full-length VAR2CSA, suggesting that a broad, high-affinity IgG response to DBL proteins may also correlate with protection.

In this study, fitting the ENLR model to resampled subsets of data allowed us to rank antibody features by their selection frequency. We generated a ranking of the 20 most frequently selected features, and then used PLSDA to determine a minimal set of antibody features that classify the pregnant women with a high accuracy. These six features were selected by ENLR more than 70% of the time, and the inclusion of these six features in the PLSDA showed an ability to accurately distinguish 86% of the women in the two groups. Notably this ability to distinguish the two groups did not increase if more than six features were included in the model. The six antibody features that best distinguished the groups were all more common in women with non-placental infection, and they included previously identified and novel responses.

Among the features we identified as associated with protection against placental malaria were adhesion inhibition and cytophilic antibodies that mediate ADCP of IE. The ability to block IE binding to CSA has been associated with protection against placental malaria, maternal anemia, low birth weight, or prematurity in subsets of pregnant women (Duffy and Fried, 2003; Ndam et al., 2015). IgG1 and IgG3 antibody responses to VAR2CSA are dominant and mediate opsonic clearance of IE (Tebo et al., 2002; Elliott et al., 2005a; Megnekou et al., 2005; Keen et al., 2007; Damelang et al., 2019). ADCP using THP-1 cells has been correlated with protection from malaria or its complications in pregnant women and in adults (reviewed in Teo et al., 2016). ADNP of IE, which has not previously been systematically studied in malaria immunity, also correlated with placental infection status. Antibodies that block adhesion and mediate ADCP by THP-1 cells or ADNP are important correlates of protection that should be included in future studies of naturally acquired and vaccine-induced antibody to malaria in pregnancy.

Although only 11% of features measured antibody to IE, four of the six top antibody features involved assays using IE. Similarly, both features towards recombinant proteins involved the DBL2 domain, which is the principal DBL domain involved in placental adhesion. The overrepresentation of both IE and DBL2 in the selected features supports the notion that antibody features directed towards functionally important targets are key to protection from placental malaria.

Novel features identified using the system serology approach include the antibody feature IgA2. Of note, IgA2 levels in serum are generally low (most serum IgA is IgA1) (Macpherson et al., 2008). Interestingly a recent study looking for correlates of malaria protection from vaccine-induced immunity also identified IgA2 as a variable that helped predict those protected from P. falciparum infection (Suscovich et al., 2020). IgA2 can elicit myeloid cell effector functions, including opsonic phagocytosis (mediated by FcαRI) (Breedveld and van Egmond, 2019), and as it recognized the CSA binding DBL domain DBL2, it may also inhibit IE binding to CSA. However, since IgA2 levels in serum are low, we hypothesize that rather than being directly involved in protection IgA2 might instead be a marker of a protective antibody response. Further investigation of VAR2CSA-specific B cells and whether a protective response is associated with increased IgA2 is warranted.

Our analysis suggests that features determined by measuring antibody to VAR2CSA-expressing IE are important indicators of protection from placental malaria. Four features measured antibody to IE using representatives of the dominant 3D7-like and FCR3-like clades (Patel et al., 2017; Benavente et al., 2018) whose N-terminal regions are used in two VAR2CSA-based pregnancy malaria vaccines (Sirima et al., 2020; Mordmüller et al., 2019). While three of these four assays targeted FCR3 or the isogenic CS2 parasite line, studies of global diversity in VAR2CSA to date have included few sequences from Papua New Guinea (Benavente et al., 2018), and the relative importance of immunity to specific clades may vary by region. Vaccination offered limited heterologous protection (Sirima et al., 2020), and it is unclear whether effective naturally acquired protective immunity needs to target multiple clades or different clades in different regions.

Antibody responses to VAR2CSA domains serve as excellent markers of exposure to malaria in pregnant women (Cutts et al., 2020), but few were selected as correlates of protection in our analysis. This may reflect the fact that the responses to different VARCSA domains were generally highly correlated, as revealed by their clustering together in the center of our network analysis, or it might be because of the longevity of antibody that promotes ADCP of IE compared to that of antibody responses to recombinant proteins (Teo et al., 2014; Teo et al., 2015; Chandrasiri et al., 2014). Antibody to VAR2CSA recombinant proteins, and particularly to specific VAR2CSA peptides, appears to be a good correlate of exposure and transmission intensity (Fonseca et al., 2019), but these responses appear to be less useful as correlates of protection.

The correlation network showed close correlations between different antibody responses to recombinant DBL domains (which are predominantly located in the central cluster) but the protective antibody features were dispersed, suggesting that distinct pathways contribute to the development of protection against placental malaria. The analysis of functions identified in the selected features further supports this, with most protected women (and few unprotected women) having significant antibody that promoted both binding inhibition to CSA and phagocytosis; however, no consistent pattern of antibody functions in protected women was seen. Similar associations have been seen in the relationships between antibody features and protection from viral pathogens, and there is a growing awareness that polyfunctional antibody responses, rather than a single functional correlate, contribute to protection from disease (Gunn et al., 2018; Chung et al., 2014). None of the antibody features targeted more than one variant of the protein or parasite strain. One possible explanation is that epitopes recognized by antibodies mediating each function may vary between strains (as suggested by Doritchamou et al., 2019). This could in turn mean that protective functional features could vary with different populations (as there is variation in global distribution of the different VAR2CSA domain clades; Benavente et al., 2018). Future studies should ideally include multiple VAR2CSA clades and study diverse populations.

We used systems serology to identify protective features of the naturally acquired antibody response to VAR2CSA, a PfEMP1 variant that is specifically associated with placental malaria, complementing a recent study that used systems serology to identify functional antibody correlates of vaccine-induced immunity, in subjects vaccinated with RTS,S (Suscovich et al., 2020). A systems serology approach could also be used to identify the characteristics of protective immunity to other malaria syndromes, such as cerebral malaria, which is often associated with a subset of PfEMP1s that are potential vaccine candidates (reviewed in Jensen et al., 2020). It will be important to determine whether protective features of the cerebral malaria-associated PfEMP1 antibody response analogous to the ones that we identified in this study can be identified.

We were interested in measuring antibodies to placental binding parasites and defined placental malaria by the detection of IE in the placenta by histology because previous studies have shown that these are the infections associated with adverse pregnancy outcomes (Menendez et al., 2000; Rogerson et al., 2003). Ring stage parasites in the peripheral blood will circulate through the placenta, and, in some cases, these could be detected by PCR of placental blood; however, we did not consider these submicroscopic infections as placental malaria as they were not shown to be sequestering there.

Study strengths include the application of 169 novel and established assays; minimal missing predictor and no missing outcome data, the ability to control for exposure with the identification of pregnant women with P. falciparum infection with, and without, placental malaria; the prospective study design; and the use of native antigens on IEs to complement the data we acquired using recombinant protein. Together, this allowed us to discover the determinants of naturally acquired protective immunity. Weaknesses include the lack of inclusion of full-length VAR2CSA in our Luminex and bead-based assays, and an imbalance in numbers between women with parasitemia but no placental infection relative to the other groups. Samples from all women in the former group were selected for this study (and statistical analysis controlled for this imbalance between groups), but this group is relatively rare, with placental infection in the absence of peripheral infection being substantially more common (Desai et al., 2007). High levels of collinearity between some variables make it difficult to dissect out individual protective responses. Demonstration that our selected variables correlate with lack of placental malaria in other cohorts would further strengthen the findings. Antibody glycosylation (Lu et al., 2016) is an additional feature that could be included in future studies.

The present study identified leading candidate antibody features that mediate naturally acquired protection from placental malaria and demonstrated we could use these features to identify women in this cohort protected from placental malaria with high accuracy (though this should be validated in a second cohort). Our results suggest that multiple pathways exist that lead to the development of protective immunity against placental malaria. Next steps will include validating this set of features in other sample sets from different geographical settings and also determining whether these antibody features predict protection from adverse pregnancy outcomes such as low birth weight. The immune responses identified are relevant to further development of pregnancy malaria-specific therapies such as vaccines or monoclonal antibodies and possibly to the identification of protective antibody against malaria in non-pregnant populations. Multiple antibody functions and characteristics may be required to develop robust protective immunity to placental malaria.

Dataset used for Figures 1–6 has been uploaded to Dryad: doi:10.5061/dryad.wpzgmsbkx.

All antibody feature data has been deposited in Dryad.

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Author details

1. Elizabeth H Aitken

   Department of Medicine, University of Melbourne, the Doherty Institute, Melbourne, Australia

   Contribution

   Conceptualization, Data curation, Formal analysis, Supervision, Funding acquisition, Investigation, Visualization, Methodology, Writing - original draft, Project administration, Writing - review and editing

   Contributed equally with

   Timon Damelang and Amaya Ortega-Pajares

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-2677-6208

2. Timon Damelang

   Department of Microbiology and Immunology, University of Melbourne, the Doherty Institute, Melbourne, Australia

   Contribution

   Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - review and editing

   Contributed equally with

   Elizabeth H Aitken and Amaya Ortega-Pajares

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-6150-4435

3. Amaya Ortega-Pajares

   Department of Medicine, University of Melbourne, the Doherty Institute, Melbourne, Australia

   Contribution

   Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - review and editing

   Contributed equally with

   Elizabeth H Aitken and Timon Damelang

   Competing interests

   No competing interests declared

4. Agersew Alemu

   Department of Medicine, University of Melbourne, the Doherty Institute, Melbourne, Australia

   Contribution

   Validation, Investigation, Methodology

   Competing interests

   No competing interests declared

5. Wina Hasang

   Department of Medicine, University of Melbourne, the Doherty Institute, Melbourne, Australia

   Contribution

   Supervision, Validation, Investigation, Methodology, Project administration

   Competing interests

   No competing interests declared

6. Saber Dini

   Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia

   Contribution

   Data curation, Formal analysis, Investigation, Visualization, Methodology, Writing - review and editing

   Competing interests

   No competing interests declared

7. Holger W Unger

   1. Department of Medicine, University of Melbourne, the Doherty Institute, Melbourne, Australia
   2. Department of Obstetrics and Gynaecology, Royal Darwin Hospital, Darwin, Australia
   3. Menzies School of Health Research, Darwin, Australia

   Contribution

   Data curation, Writing - review and editing

   Competing interests

   No competing interests declared

8. Maria Ome-Kaius

   Walter and Eliza Hall Institute of Medical Research, Parkville, Australia

   Contribution

   Data curation

   Competing interests

   No competing interests declared

9. Morten A Nielsen

   Centre for Medical Parasitology, Department of Microbiology and immunology, University of Copenhagen, Copenhagen, Denmark

   Contribution

   Resources, Methodology, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-2668-4992

10. Ali Salanti

    1. Centre for Medical Parasitology, Department of Microbiology and immunology, University of Copenhagen, Copenhagen, Denmark
    2. Department of Infectious Disease, Copenhagen University Hospital, Copenhagen, Denmark

    Contribution

    Resources, Writing - review and editing

    Competing interests

    No competing interests declared

11. Joe Smith

    1. Seattle Children’s Research Institute, Seattle, United States
    2. Department of Pediatrics, University of Washington, Seattle, United States

    Contribution

    Resources, Writing - review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-7915-6360

12. Stephen Kent

    Department of Microbiology and Immunology, University of Melbourne, the Doherty Institute, Melbourne, Australia

    Contribution

    Resources, Supervision, Writing - review and editing

    Competing interests

    No competing interests declared

13. P Mark Hogarth

    1. Seattle Children’s Research Institute, Seattle, United States
    2. Immune Therapies Group, Centre for Biomedical Research, Burnet Institute, Melbourne, Australia
    3. Department of Clinical Pathology, University of Melbourne, Melbourne, Australia
    4. Department of Immunology and Pathology, Monash University, Melbourne, Australia

    Contribution

    Resources, Writing - review and editing

    Competing interests

    No competing interests declared

14. Bruce D Wines

    1. Immune Therapies Group, Centre for Biomedical Research, Burnet Institute, Melbourne, Australia
    2. Department of Clinical Pathology, University of Melbourne, Melbourne, Australia
    3. Department of Immunology and Pathology, Monash University, Melbourne, Australia

    Contribution

    Resources, Writing - review and editing

    Competing interests

    No competing interests declared

15. Julie A Simpson

    Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia

    Contribution

    Formal analysis, Supervision, Methodology, Writing - review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-2660-2013

16. Amy Chung

    Department of Microbiology and Immunology, University of Melbourne, the Doherty Institute, Melbourne, Australia

    Contribution

    Conceptualization, Resources, Supervision, Funding acquisition, Methodology, Project administration, Writing - review and editing

    Contributed equally with

    Stephen J Rogerson

    Competing interests

    No competing interests declared

17. Stephen J Rogerson

    Department of Medicine, University of Melbourne, the Doherty Institute, Melbourne, Australia

    Contribution

    Conceptualization, Resources, Supervision, Funding acquisition, Methodology, Writing - original draft, Project administration, Writing - review and editing

    Contributed equally with

    Amy Chung

    For correspondence

    sroger@unimelb.edu.au

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0003-4287-1982

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