Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2024 Sep 12;22(1):388.
doi: 10.1186/s12916-024-03604-8.

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

Isobel S Walker  1 , Saber Dini  2 , Elizabeth H Aitken  3   4 , Timon Damelang  4 , Wina Hasang  3 , Agersew Alemu  3 , Anja T R Jensen  5 , Janavi S Rambhatla  1   4 , D Herbert Opi  1   6   7 , Michael F Duffy  1   4 , Eizo Takashima  8 , Visopo Harawa  9 , Takafumi Tsuboi  10 , Julie A Simpson  2 , Wilson Mandala  11 , Terrie E Taylor  12   13 , Karl B Seydel  12   13 , Amy W Chung  4 , Stephen J Rogerson  14   15
Affiliations

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

Isobel S Walker et al. BMC Med. .

Abstract

Background: 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.

Methods: 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.

Results: 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).

Conclusions: 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.

Keywords: Plasmodium falciparum; Africa; Antibody; Immunity; Malawi.

PubMed Disclaimer

Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Individual antibody features to recombinant proteins compared between cerebral and uncomplicated malaria. A All individuals, B children under 49 months, C children 49 months and older. X-axis represents the magnitude of difference (log2 transformed) between the geometric mean antibody levels of the cerebral and uncomplicated malaria groups. Vertical lines at log2(2) and log2(0.50) indicate a twofold elevation in uncomplicated malaria or cerebral malaria, respectively. Y-axis represents − log10 transformed p value from Welch’s t-test comparison of cerebral and uncomplicated malaria. Horizontal line indicates log10(0.05) threshold of statistical significance, and there were no adjustments for multiple comparisons. DBL Duffy binding like domain, CIDR cysteine-rich interdomain region, a α, b β, d δ, e ε, g γ, z ζ
Fig. 2
Fig. 2
Multivariate analysis to select a minimum combination of features that best distinguishes between cerebral and uncomplicated malaria. A combination of elastic net regularized logistic regression (ENLR) and partial least squares (PLS) regression was used. A Odds ratio of antibody features from 5000 repeats of tenfold cross validated ENLR models, in order of selection frequency (top 20 most selected variables are shown). Features with median odds ratio greater than 1 represents responses associated with increased odds of uncomplicated malaria and features with median odds ratio less than 1 are associated with increased odds of cerebral malaria. B Performance of PLS model after addition of features (x-axis) in order of ENLR selection frequency (left to right), as measured by AUROC from 5000 repeats of tenfold cross validated PLS regression. Black line shows AUROC for all children, red line shows the accuracy of classifying children with cerebral malaria only, and blue line the accuracy of classifying children with uncomplicated malaria only. Vertical dashed line represents point at which the addition of one or two more features does not significantly increase the AUROC which occurs at seven features (referred to as the “selected features”). C Performance of PLS regression models using only the seven selected features from ENLR (87% median, 80–96% IQR), compared to randomly selected combinations of seven features (50% median, 40–65% IQR). AUROC corresponds to 5000 repeats of tenfold cross validated PLS regression models. AUROC area under the receiver operating characteristic curve. Box plots show median and interquartile range (IQR) and whiskers show points within Q1 − 1.5*IQR and Q3 + 1.5*IQR. DBL Duffy binding like domain, CIDR cysteine-rich interdomain region, a α, b β, d δ, e ε, g γ, z ζ
Fig. 3
Fig. 3
Antibody features associated with protection from cerebral malaria and their correlation with one another. A Distribution of seven selected features in children with cerebral malaria (red) and uncomplicated malaria (blue). MFI readouts were log(x + 1) transformed, mean centered, and scaled to 1 standard deviation (z-score). Box plots show median and interquartile range (IQR) and whiskers show IQR + 1.5*IQR. Horizontal bars represent Welch’s t-test comparison with p value shown. B Spearman correlation of features that appeared in > 70% of ENLR model iterations, including the seven selected features, using non-transformed MFI values. DBL Duffy binding like domain, CIDR cysteine-rich interdomain region, a α, b β, d δ, e ε, g γ, z ζ. *p value < 0.05, **p value < 0.01, ***p value < 0.001
Fig. 4
Fig. 4
Antibody-dependent neutrophil phagocytosis and THP-1 cell phagocytosis of ICAM-1 binding IE. A Neutrophil phagocytosis of 3D7VAR04 ICAM-1 + EPCR co-binding IE and B IT4VAR13 ICAM-1 + CD36 co-binding IE. Mean responses from two neutrophil donors shown. C THP-1 cell phagocytosis of 3D7VAR04 ICAM-1 + EPCR co-binding IE and D IT4VAR13 ICAM-1 + CD36 co-binding IE. IE were opsonized with plasma from Malawian children with cerebral or uncomplicated malaria, or healthy Melbourne donors (Melbourne control). Y-axis (% phagocytosis) represents percentage of neutrophils or THP-1 cells associated with DHE stained IE, relative to a positive control serum. Boxes represent median and interquartile range (IQR) from Q1 to Q3, and whiskers range from (Q1 − 1.5*IQR) to (Q3 + 1.5*IQR). Medians (horizontal bars) were compared by Wilcoxon rank sum test and associated p values are shown
See this image and copyright information in PMC

Similar articles

See all similar articles

References

    1. World malaria report 2023. World Health Organization. 2023. https://www.who.int/teams/global-malaria-programme/reports.
    1. Taylor TE, Fu WJ, Carr RA, Whitten RO, Mueller JS, Fosiko NG, et al. Differentiating the pathologies of cerebral malaria by postmortem parasite counts. Nat Med. 2004;10:143–5. 10.1038/nm986 - DOI - PubMed
    1. Rask TS, Hansen DA, Theander TG, Pedersen AG, Lavstsen T. Plasmodium falciparum erythrocyte membrane protein 1 diversity in seven genomes - divide and conquer. PLoS Comput Biol. 2010;6: e1000933. 10.1371/journal.pcbi.1000933 - DOI - PMC - PubMed
    1. Lavstsen T, Gilbert MTP, Willerslev E, Baraka V, Theander TG, Marquard AM, et al. Plasmodium falciparum erythrocyte membrane protein 1 domain cassettes 8 and 13 are associated with severe malaria in children. Proc Natl Acad Sci. 2012;109:e1791–800. 10.1073/pnas.1120455109 - DOI - PMC - PubMed
    1. Kessler A, Dankwa S, Bernabeu M, Harawa V, Danziger SA, Duffy F, et al. Linking EPCR-binding PfEMP1 to brain swelling in pediatric cerebral malaria. Cell Host Microbe. 2017;22:601-614.e5. 10.1016/j.chom.2017.09.009 - DOI - PMC - PubMed

Publication types

Substances

LinkOut - more resources