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

  1. Elizabeth H Aitken
  2. Timon Damelang
  3. Amaya Ortega-Pajares
  4. Agersew Alemu
  5. Wina Hasang
  6. Saber Dini
  7. Holger W Unger
  8. Maria Ome-Kaius
  9. Morten A Nielsen
  10. Ali Salanti
  11. Joe Smith
  12. Stephen Kent
  13. P Mark Hogarth
  14. Bruce D Wines
  15. Julie A Simpson
  16. Amy W Chung
  17. Stephen J Rogerson  Is a corresponding author
  1. Department of Medicine, University of Melbourne, the Doherty Institute, Australia
  2. Department of Microbiology and Immunology, University of Melbourne, the Doherty Institute, Australia
  3. Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Australia
  4. Department of Obstetrics and Gynaecology, Royal Darwin Hospital, Australia
  5. Menzies School of Health Research, Australia
  6. Walter and Eliza Hall Institute of Medical Research, Australia
  7. Centre for Medical Parasitology, Department of Microbiology and immunology, University of Copenhagen, Denmark
  8. Department of Infectious Disease, Copenhagen University Hospital, Denmark
  9. Seattle Children’s Research Institute, United States
  10. Department of Pediatrics, University of Washington, United States
  11. Immune Therapies Group, Centre for Biomedical Research, Burnet Institute, Australia
  12. Department of Clinical Pathology, University of Melbourne, Australia
  13. Department of Immunology and Pathology, Monash University, Australia
Research Article
Cite this article as: eLife 2021;10:e65776 doi: 10.7554/eLife.65776
6 figures, 2 tables and 6 additional files

Figures

Figure 1 with 2 supplements
Individual antibody features to recombinant VAR2CSA Duffy binding-like (DBL) domain proteins measured by multiplex comparing women with placental malaria at delivery to (A) non-infected women and (B) women with non-placental infection.

Fold-change (log2 transformed), characterizing the magnitude of difference between the antibody levels of two groups (x-axis), is plotted against the -log10 p-value, characterizing the statistical significance of the difference (y-axis). The vertical dotted lines (log2(2) and log2(0.5)) mark a threshold for a twofold change, and the horizontal dotted lines (log10(0.05)) mark the statistical significance threshold (p≤0.05, Welch’s t-test). Antibody features beyond the thresholds are shown in blue and labeled.

Figure 1—figure supplement 1
Diagram of the Plasmodium falciparum erythrocyte membrane protein 1 (PfEMP1) VAR2CSA on the surface of the infected erythrocyte.

DBL2, which is involved in binding to chondroitin sulfate A, is highlighted in light purple. DBL: Duffy binding-like domain; ID: interdomain region; TM: transmembrane segment; ATS: acid terminal segment.

Figure 1—figure supplement 2
Flow chart of data acquisition and analysis.

NPI: non-placental infection; PM: placental malaria; NI: non-infected; IE: infected erythrocyte; PLSDA: partial least squares discriminant analysis.

Figure 2 with 1 supplement
Antibody features that are influential in distinguishing between malaria-infected women with and without placental infection identified by the elastic net-regularized logistic regression model.

Resampling (5000 repeats of 10-fold cross-validation) was used to obtain the selection frequencies and the odds ratios. (A) The top 20 antibody features are ranked in ascending order of selection frequency. (B) Boxplots of the estimated odds ratios, an odds ratio >1 indicates the antibody feature is positively associated with non-placental infection at delivery. Boxplots are median, IQR, whiskers (the lowest data point that falls between Q1 and 1.5 * Q1 IQR, the highest data point that falls between Q3 and 1.5 * Q3 IQR). IQR: interquartile range.

Figure 2—figure supplement 1
Selection frequencies estimated across all α values {0, 0.25, 0.5, 0.75 1} using the resampling of elastic net-regularized logistic regression.

See section Identification of key antibody features.

Figure 3 with 1 supplement
Selecting a minimal set of antibody features by partial least squares discriminant analysis (PLSDA).

(A) Performance of PLSDA at classifying women as having placental malaria (PM) or non-placental infection (NPI) when the features (ranked by selection frequency using the elastic net; Figure 2) are added one by one to the model from highest to lowest rank (500 repeats of 10-fold cross-validation were performed to estimate accuracy for each model). The three lines represent the accuracy of classification of all women in the cohort (black), those with NPI (blue), and those with PM (red). The vertical dashed line denotes the cutoff beyond which the accuracy does not change significantly by adding more antibody features (used for selecting the minimal set of features). (B) Comparing the performance of the elastic net-regularized logistic regression (ENLR) + PLSDA applied on the original data of the top six variables (rightmost boxplot) with two permutation tests (null cases): (1) the PLSDA model was fitted to six randomly selected antibody features and the performance was computed for 500 repeats of 10-fold cross-validation resampling; (2) 100 datasets were generated by randomly permuting the group labels (PM and NPI) and the same analysis performed for the original dataset (i.e., building PLSDA models using the top six frequently selected antibody features found by resampling of elastic net) was repeated for each dataset. (C) Segregation of women with NPI (blue) and PM (red) using the scores of the two components of the PLSDA model with data from the selected six antibody features. The background colors show the predicted classification of the women for all the possible score values in the depicted range. (D) Feature loadings on the components of the PLSDA of the six selected antibody features (see Figure 3—source data 1 for more details about the factor loadings and group prediction using the PLSDA). Boxplots are median, IQR, whiskers (the lowest data point that falls between Q1 and 1.5 * Q1 IQR, the highest data point that falls between Q3 and 1.5 * Q3 IQR). IQR: interquartile range; AUROC: area under the receiver operating characteristic curve.

Figure 3—source data 1

Partial least squares discriminant analysis (PLSDA) prediction model.

A PLSDA model with two components and using the six selected antibody features can be formed for prediction of the group of the pregnant women. The estimated loading factors of the model for the two components (shown in Figure 3) are listed here. The softmax technique was used to normalize the scores for each class (placental malaria and non-placental infection) that works as the probability of an observation belonging to a certain class (Kuhn, 2008). The predicted class is the one with the largest model prediction or, equivalently, the largest class probability.

https://cdn.elifesciences.org/articles/65776/elife-65776-fig3-data1-v3.docx
Figure 3—figure supplement 1
Accuracy of partial least squares discriminant analysis (PLSDA) at classifying women as having placental malaria or non-placental infection when the features (ranked by selection frequency using the elastic net; Figure 2) are added one by one to the model from highest to lowest rank (500 repeats of 10-fold cross-validation were performed to estimate accuracy for each model).

The three lines represent the accuracy of classification of all women in the cohort (black), those with non-placental infection (blue), and those with placental malaria (red). The vertical dashed line denotes the cutoff beyond which the accuracy does not change significantly by adding more antibody features (used for selecting the minimal set of features).

Figure 4 with 1 supplement
Correlation network of antibody features.

Correlation network of all antibody features in both women with non-placental infection and those with placental malaria. The six selected antibody features do not cluster together. Antibody features with similar functions (denoted by the same letter) tend to correlate with each other. Blue: positive correlation; red: negative correlation; line width and closeness of variables increase with increasing correlation coefficients; only significant correlations (after Bonferroni correction for multiple comparisons) are shown. Selected antibody features identified by elastic net are highlighted and labeled. See supplementary file 3 for a full list of feature names.

Figure 4—figure supplement 1
Correlation matrix of the six selected antibody features from women with non-placental infection at delivery and women with placental malaria.

Color and size of dots represent estimates of the correlation coefficient (r) (the further the correlation coefficient from 0 the larger the dot).

Distribution of antibody features in women with non-placental infection (NPI) and placental malaria (PM).

(A–F) Levels of each of the selected antibody features in individual women in the two groups (G) No single antibody feature was present in all individuals with NPI (or was absent in all those with PM). Errors bars are mean (SD), p-values derived from Welch’s t-test. IE: infected erythrocyte; Z-score: distribution of the features was centered and scaled to have zero mean and a standard deviation of 1.

The six selected antibody features may protect women from placental malaria by (A) inhibiting infected red blood cells from binding chondroitin sulfate A (CSA) and sequestering in the placenta and/or (B) promoting phagocytosis of infected red blood cells by monocytes and/or neutrophils.

Selected features that may inhibit placental sequestration include IgG3 to the whole infected red blood cell and IgG3 and IgA2 to VAR2CSA's CSA binding domain DBL2. Selected features that may promote parasite clearance by antibody dependent phagocytosis include IgG3 to the whole infected red blood cell and to DBL2, IgA2 to DBL2, and neutrophil and monocyte phagocytosis of whole infected red blood cells. ADNP: antibody-dependent neutrophil phagocytosis; ADCP: antibody-dependent cellular phagocytosis; VAR2CSA: a parasite protein expressed on the surface of the infected red blood cell, made up of Duffy binding-like domains (DBL).

Tables

Table 1
Clinical characteristics of the three groups of pregnant women at the time of antibody feature measurement at enrollment (14–26 weeks’ gestation) and also at delivery.
Non-infected at deliveryPlacental malaria at deliveryNon-placental infection at delivery
N = 50N = 50N = 27
Enrollment
Mean age (years), SD24.55.324.05.023.14.4
Residence, N (%)
Rural37(74.0)38(76.0)18(66.7)
Non-rural13(26.0)12(24.0)9(33.3)
Ethnicity, N (%)
Sepik6(12.0)11(22.0)3(11.1)
Madang/Morobe39(78.0)30(60.0)22(81.5)
Highlander3(6.0)5(10.0)1(3.7)
Other2(4.0)4(8.0)1(3.7)
Formal schooling, N (%)46(92.0)46(92.0)25(92.6)
Smoking, N (%)9(18.0)11(22.0)6(22.2)
Betel nut user, N (%)†41(82.0)41(82.0)24(88.9)
Alcohol, N (%)2(4.0)2(4.0)2(7.4)
Gravidity, N (%)
Primigravidae26(52.0)29(58.0)14(51.9)
Secundigravidae8(16.0)7(14.0)8(29.6)
Multigravidae16(32.0)14(28.0)5(18.5)
IPTp regime, N (%)
SPCQ27(54.0)30(60.0)18(66.7)
SPAZ23(46.0)20(40.0)9(33.3)
Mean gestational age (days), SD145.931.4147.531.3152.219.8
Mean maternal weight (kg), SD*54.713.153.58.254.17.4
Mean maternal height (cm), SD154.35.9154.66.9154.46.0
Bed net use, N (%)34(68.0)40(80.0)21(77.8)
Hb (g/dL), mean SD9.71.29.32.09.41.2
Light microscopy positive for Pf, N (%)2(4.0)4(8.0)4(14.8)
PCR positive for Pf, N (%)4(8.0)5(10.0)5(18.5)
Delivery
Placenta
light microscopy positive for Pf, N (%)
0(0)50(100)0(0)
Peripheral blood light microscopy positive for Pf, N (%)0(0)10(20)13(48.2)
Peripheral blood PCR positive for Pf, N (%)0(0)13(26)21(77.8)
Placental blood PCR positive for Pf, N (%)§1(2.0)10(20)10(37.04)
Birthweight (g), SD306254628275012840416
Gestation at delivery (days), SD278182791628013
Mean Hb (g/dL), SD10.129.51.910.21.4
  1. * One participant with missing data on betel nut use in placental malaria.

    One participant with missing data on weight in the non-infected group.

  2. Missing Hb data, five in non-infected group, four in placental malaria group, and two in the non-placental infection group.

    § Missing placental PCR data in five non-infected, eight placental malaria, and four non-placental infection women.

  3. One participant with missing data on gestation length at delivery in the non-infected group.

    SD: standard deviation; Hb: hemoglobin; PCR: polymerase chain reaction; IPTp: intermittent preventive treatment in pregnancy; SPAZ: sulfadoxine pyrimethamine-azithromycin; SPCQ: sulfadoxine pyrimethamine-chloroquine.

Appendix 1—key resources table
Reagent type (species) or resourceDesignationSource or referenceIdentifiersAdditional information
Strain, strain background (Plasmodium falciparum, CS2)CS2Chandrasiri et al., 2014
Strain, strain background (Plasmodium falciparum, 3D7)3D7Chandrasiri et al., 2014Selected for chondroitin sulfate A (CSA) adhesion
Strain, strain background (Plasmodium falciparum, FCR3)FCR3Nielsen and Salanti, 2015Selected for CSA adhesion (parent of CS2)
Strain, strain background (Plasmodium falciparum, NF54)NF54Nielsen and Salanti, 2015Selected for CSA adhesion
(parent of 3D7)
Biological sample (Homo sapiens)PlasmaUnger et al., 2015
Biological sample (Homo sapiens)Primary monocytesThis paperFreshly isolated cells (see Materials and methods – Primary leukocytes)
Biological sample (Homo sapiens)Primary neutrophilsThis paperFreshly isolated cells (see Materials and methods – Primary leukocytes)
Biological sample (Homo sapiens)Primary NK cellsThis paperFreshly isolated cells (see Materials and methods – Primary leukocytes)
Cell line (Homo sapiens)THP1Ataíde et al., 2010RRID:CVCL_0006Monocytic cell line
Peptide, recombinant proteinDBL1-7G8Avril et al., 2011MV-1398Parasite line 7G8
Peptide, recombinant proteinDBL2(ID1-ID2a)-FCR3Doritchamou et al., 2016MV1942Parasite line FCR3
Peptide, recombinant proteinDBL2(ID1-ID2a)-FCR3Mordmüller et al., 2019Parasite line FCR3
Peptide, recombinant proteinDBL2-isolateDoritchamou et al., 2016MV 1940Parasite isolate 1010
Peptide, recombinant proteinDBL3- FCR3Nielsen et al., 2009MP1028Parasite line FCR3
Peptide, recombinant proteinDBL3- 7G8Avril et al., 2011MV-1914Parasite line 7G8
Peptide, recombinant proteinDB4-FCR3Fried et al., 2018MP2369Parasite line FCR3
Peptide, recombinant proteinDBL4-isolateDoritchamou et al., 2016MV1700Parasite isolate I 0711
Peptide, recombinant proteinDBL5-3D7Avril et al., 20111218Parasite line 3D7
Peptide, recombinant proteinDBL5-7G8Avril et al., 20111269Parasite line 7G8
Peptide, recombinant proteinDBL5-isolateDoritchamou et al., 2016MV 1749Parasite isolate I 0466
Peptide, recombinant proteinDBL6-IT4Avril et al., 2011MV-1137Parasite line IT4
Peptide, recombinant proteinMSP-1Barua et al., 2019
Biological sample (Plasmodium falciparum)Schizont extractBarua et al., 2019
AntibodyGoat anti-human IgG (polyclonal)Mabtech3820-4-250(1:2000)
AntibodyMouse anti-human IgG-PE (polyclonal)SouthernBiotech9040-09
RRID:AB_2796601
(1:77)
AntibodyMouse anti-human IgG1-PE (monoclonal)SouthernBiotech9052-09
RRID:AB_2796621
(1:77)
AntibodyMouse anti-human IgG2-PE (monoclonal)SouthernBiotech9070-09
RRID:AB_2796639
(1:77)
AntibodyMouse anti-human IgG3-PE (monoclonal)SouthernBiotech9210-09
RRID:AB_2796701
(1:77)
AntibodyMouse anti-human IgG4-PE (monoclonal)SouthernBiotech9200-09
RRID:AB_2796693
(1:77)
AntibodyMouse anti-human IgA1-PE (monoclonal)SouthernBiotech9130-09
RRID:AB_2796656
(1:77)
AntibodyMouse anti-human IgA2-PE (monoclonal)SouthernBiotech9140-09
RRID:AB_2796664
(1:77)
AntibodyMouse anti-human IgM-PE (monoclonal)SouthernBiotech9020-09
RRID:AB_2796577
(1:77)
AntibodyRabbit anti-human IgG (polyclonal)DAKOA0425(1:100)
AntibodyMouse anti-human IgG1 HP6069 (monoclonal)Merck Millipore411451(1:50)
AntibodyMouse anti-human IgG2 HP6002 (monoclonal)Merck MilliporeMAB1308(1:50)
AntibodyMouse anti-human IgG3
HP6050
(monoclonal)
SigmaI7260.2ml(1:50)
AntibodyMouse anti-human IgG4
HP6023
(monoclonal)
Merck MilliporeMAB1312-K(1:50)
AntibodyGoat anti-mouse IgG AlexaFluor 647 (polyclonal)Life TechnologiesA-21235
RRID:AB_2535804
(1:500)
AntibodyDonkey anti-rabbit 647 (polyclonal)Life TechnologiesA-31573
RRID:AB_2536183
(1:500)
Peptide, recombinant proteinC1qMP Biomedicals80295-33-61.3 µg/ml
Peptide, recombinant proteinFcγRIR&D Systems1257-FC
Peptide, recombinant proteinFcγRIIaWines et al., 2016
Peptide, recombinant proteinFcγRIIIaWines et al., 2016
Peptide, recombinant proteinFcγRIIIbR&D Systems1875 CD
AntibodyMouse anti-human CD16-Brilliantviolet 605
(monoclonal)
BD563172(1:50)
AntibodyMouse anti-human CD56-Brilliantultraviolet 737
(monoclonal)
BD347344(1:800)
AntibodyMouse anti-human CD3-peridinin-chlorophyll-protein
(monoclonal)
BD552127(1:200)
AntibodyMouse anti-human IFNγ-PE
(monoclonal)
BD554701(1:200)
AntibodyMouse anti-human TNFα-BV-785
(monoclonal)
BioLegend502947
RRID:AB_2565857
(1:200)
Software, algorithmR software, caret packageR software
Kuhn, 2008
Software, algorithmR software, glmnet packageR software
Zou and Hastie, 2005
Software, algorithmR software, PLS packageR software
Mevik and Wehrens, 2007
Software, algorithmR software, mixOmics packageR software
Rohart et al., 2017
Software, algorithmR software, qgraph packageR software
Epskamp et al., 2012
Commercial assay or kitEasySep Direct Human Neutrophil Isolation KitSTEMCELL Technologies19666
Commercial assay or kitRosetteSep Human Monocyte Enrichment CocktailSTEMCELL Technologies15068
Commercial assay or kitRosetteSep Human NK Enrichment CocktailSTEMCELL Technologies15065
Commercial assay or kitMelon Gel purification kitsThermo Fisher Scientific45212
Commercial assay or kitEZ-link Sulfo NHS-LC-Biotin kitThermo Fisher Scientific24520
OtherBio-Plex magnetic carboxylated microspheresBio-Rad#MC100xx-01
OtherStreptavidin-PESouthernBiotech7105-09

Additional files

Supplementary file 1

Recombinant VAR2CSA DBL domain proteins used to measure antibody features.

https://cdn.elifesciences.org/articles/65776/elife-65776-supp1-v3.docx
Supplementary file 2

Univariate analysis non-infected vs. placental malaria and non-placental infection vs. placental malaria.

https://cdn.elifesciences.org/articles/65776/elife-65776-supp2-v3.docx
Supplementary file 3

Antibody feature code, name, and description.

https://cdn.elifesciences.org/articles/65776/elife-65776-supp3-v3.docx
Supplementary file 4

Table 1: Association between selected antibody features and graviditya in 77 women (women with placental malaria or non-placental infection at delivery) and Table 2: univariate analysis of selected antibody features placental malaria v non-placental infection, in women uninfected at enrollment.

https://cdn.elifesciences.org/articles/65776/elife-65776-supp4-v3.docx
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