Research ArticleMalaria

Antigen-stimulated PBMC transcriptional protective signatures for malaria immunization

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Science Translational Medicine  13 May 2020:
Vol. 12, Issue 543, eaay8924
DOI: 10.1126/scitranslmed.aay8924
  • Fig. 1 Study design for the identification of signatures of protection.

    (A) Samples from a chemoprophylaxis and sporozoite (CPS) immunization clinical trial (9) and (B) the RTS,S/AS01E vaccine phase 3 clinical trial (3) were used. The CPS trial involved immunization of malaria-naïve adult volunteers by bites from P. falciparum (Pf)–infected mosquitoes during chloroquine (CQ) chemoprophylaxis. Three groups of volunteers received three different doses of bites from infected mosquitoes. After infectious challenge, 17 of 24 volunteers were protected from infection. Blood samples were collected at baseline (before immunization) and 5 months after the last dose (after immunization). Children and infants from three different African countries in the RTS,S/AS01 phase 3 trial received three doses of the RTS,S vaccine or a comparator vaccine 1 month apart and were followed up for detection of clinical malaria episodes. Samples from 50 volunteers who had malaria (nonprotected) and 205 volunteers who did not have any malaria episode (protected) were selected. Blood samples were collected at baseline for children and 1 month after third vaccine dose for children and infants. (C) Previously cryopreserved PBMCs were stimulated in vitro with circumsporozoite protein (CSP) peptide pool or P. falciparum–infected red blood cells (PfRBCs) and their respective background controls, dimethyl sulfoxide (DMSO), and uninfected red blood cells (uRBCs). Gene expression was measured by microarrays. (D) Differential gene expression analysis using linear regression models, and subsequently, GSEA was performed. Microarray data were also used for protein network–based models. Proteins behaving differently in the models were down-selected using data science methods, leading to identification of pre- and postimmunization signatures of protection, consisting of three to five proteins, with accuracies of >70%. TPMS, Therapeutic Performance Mapping System.

  • Fig. 2 Transcriptional responses associated with CPS immunogenicity and protection.

    Each square represents a blood transcription module (BTM). The color shading indicates normalized enrichment scores obtained by GSEA analysis for BTMs. Assignment of a BTM to a high-level annotation group is illustrated by a colored sidebar. GSEA, CAMERA, and Tmod were run with genes ranked by (A) the expression of postimmunization (Post) relative to preimmunization (Pre) and (B) protected relative to nonprotected individuals for CSP and PfRBC recall stimulations after and before immunization. Modules that did not reach the significance cutoff of an FDR q value of 0.1 in all three enrichment methods or a minimum of 10 matched genes were eliminated. Modules without annotation are not shown. Modules that represent common associations of both immunogenicity and protection at postimmunization are highlighted with a circle for CSP recall responses and triangle for PfRBC recall responses, and filled symbols indicate that enrichment had the same direction, whereas empty symbols indicate that enrichment had the opposite direction. AP-1, activator protein-1; MHC, major histocompatibility complex; ECM, extracellular matrix.

  • Fig. 3 Fold-change gene expression in CPS volunteers for genes from BTMs negatively enriched upon immunization and positively enriched in protected compared to unprotected immunized volunteers.

    Charts show the log2 fold change expression upon PfRBC stimulation relative to uRBC background for genes that are found in the leading edge of enrichment in the GSEA analysis in each represented module: (A) BTM “myeloid cell–enriched receptors and transporters (M4.3),” (B) BTM “regulation of antigen presentation and immune response (M5),” (C) BTM “enriched in monocytes (M11.0),” and (D) BTM “TLR and inflammatory signaling (M16).” Different colored lines represent volunteers before immunization (green) and CPS immunized protected (pink) and unprotected (blue) volunteers.

  • Fig. 4 Transcriptional responses associated with RTS,S/AS01 immunogenicity and protection in RTS,S/AS01 and comparator vaccinees.

    Each square represents a BTM. The color shading indicates normalized enrichment scores obtained by GSEA analysis for BTMs. Assignment of a BTM to a high-level annotation group is illustrated by a colored sidebar. GSEA, CAMERA, and Tmod were run with genes ranked by the expression of (A) RTS,S/AS01E vaccinees (after immunization) relative to comparator vaccinees and (B) protected relative to nonprotected individuals in RTS,S/AS01E and comparator vaccinees for CSP recall stimulations and (C) for PfRBC recall stimulations. Modules that did not reach the significance cutoff of FDR q value of 0.1 in all three enrichment methods or a minimum of 10 matched genes were eliminated. Modules without annotation are not shown. Modules that represent common associations of both immunogenicity and protection are highlighted with a circle for CSP recall responses and a triangle for PfRBC recall responses, filled symbols when enrichment had the same direction, and empty symbols when enrichment had the opposite direction.

  • Fig. 5 Higher fold change gene expression in protected than unprotected RTS,S vaccinees for genes from BTM related to IFN signatures and monocytes.

    Charts show the log2 fold change of genes upon CSP recall stimulation related to DMSO background for genes that are found in the leading edge of enrichment in the GSEA analysis in the BTMs related to (A) IFN signatures (M67, M75, M111.1, M127, and M150) and (B) the genes contributing to enrichment of the BTM “enriched in monocytes (II) (M11.0).” Different colored lines represent comparator vaccinees (green), protected (pink), and unprotected (blue) RTS,S/AS01E vaccinees.

  • Fig. 6 Validation of signatures of protection.

    (A) Samples for validation were obtained from a CPS trial in malaria-naïve adults that used chloroquine (CQ) and mefloquine (MQ) and a separate group of children and infants from two different African countries from the RTS,S phase 3 trial. PBMCs were similarly stimulated in vitro with CSP peptide pool and DMSO, or in only CPS samples, PfRBC, and uRBC. Gene expression was measured by qRT-PCR from about 70 genes involved in the signatures of protection of each immunization strategy and that were selected on the basis of Greedy algorithms. Normalized qRT-PCR data and data science methods were used to validate 32 and 37 previously identified signatures for CPS and RTS,S, respectively. Predictive mathematical models were developed using artificial neural network (ANN) and LOO cross-validation (LOOCV) for three selected signatures. (B) Potential mechanisms by which the genes of the three selected validated signatures may confer protection against malaria. Order of signatures: CPS preimmunization signature, CPS postimmunization signature, and RTS,S postimmunization signature. Purple and orange nodes indicate genes that belong to the signature (purple and orange represent up-regulated and down-regulated genes, respectively). White nodes indicate genes participating in the mode of action of the signature. Broken-lined nodes contain more than one gene, all of them acting in the mode of action in the same way. Purple arrows show activation, whereas orange lines show inhibition. NFAC1, nuclear factor of activated T-cells, cytoplasmic 1; VWF, von willebrand factor. VEGFA, vascular endothelial growth factor A. (C) ROC curves predicting malaria protection (based on the qRT-PCR validation data) for the selected CPS pre- and postimmunization and RTS,S postvaccination signatures of protection.

  • Table 1 Signatures of protection induced by CPS and RTS,S/AS01E identified from mathematical network models based on the transcriptional data.

    Time pointAge groupAntigenSignature of
    protection
    Generalization
    capability
    Accuracy
    CPS
    PostimmunizationAdultsCSP/DMSOF2, CXCL10, and KL87.50%87.50%
    AdultsPfRBC/uRBCHSPA8, CALR, and
    CXCL16
    70.83%70.83%
    AdultsCSP/DMSO and PfRBC/uRBCF2RL2, IL-3RA, and
    GNA11
    81.25%93.75%
    PreimmunizationAdultsCSP/DMSOCSF2, NFkBIE,
    TNFRSF11B, and
    ITGA2
    87.50%100%
    AdultsPfRBC/uRBCPTK2, TGF-β3, and
    HSPA8
    70.83%70.83%
    AdultsCSP/DMSO and PfRBC/uRBCCACNA2D2,
    CACNA1F, ITGB7,
    ARHGDIB, and KCNB1
    77.08%89.58%
    Pre- and
    postimmunization
    AdultsCSP/DMSOIL-7, ADRA2B, and
    F2RL2
    89.58%93.75%
    RTS,S/AS01E
    PostimmunizationInfantsCSP/DMSOGNAT 3, SGK1, and
    TLR4
    80%86.67%
    InfantsPfRBC/uRBCTLR4, P85B, and
    SH2B2
    82.69%88.46%
    ChildrenCSP/DMSOERBB2, PRLR, and
    FAK2
    80.49%92.68%
    ChildrenPfRBC/uRBCJAK2, NCAM1,
    VCAM1, CNTFR, and
    GNA11
    80.65%100%
    Infants and childrenCSP/DMSOITB1, CASP6, and IL-1879.29%83.57%
    Infants and childrenPfRBC/uRBCM3K7, IL-3, FCG2A,
    and CBLC
    80%90%
    ChildrenCSP/DMSO and PfRBC/uRBCGNAT3, SGK1, and
    TLR4
    81.94%84.72%
    PreimmunizationChildrenPfRBC/uRBCTR10A, CCNE2,
    ADA2A, SRC, and
    IL-12B
    79.49%100%
    ChildrenCSP/DMSOTLR4, WASL, and P85B81.13%86.79%
    ChildrenCSP/DMSO and PfRBC/uRBCTLR4, P85B, SH2B2,
    MAP2K7, and IKKB
    78.79%87.88%

Supplementary Materials

  • stm.sciencemag.org/cgi/content/full/12/543/eaay8924/DC1

    Materials and Methods

    Fig. S1. Experimental design and sample sizes.

    Fig. S2. CPS study profile and sample flow chart.

    Fig. S3. RTS,S study profile and sample flow chart.

    Fig. S4. PCA of CPS gene expression data.

    Fig. S5. Heatmaps and unsupervised hierarchical clustering in gene expression after cell stimulation for all CPS immunized volunteers.

    Fig. S6. PCA of RTS,S/AS01E gene expression data.

    Fig. S7. Heatmaps and unsupervised hierarchical clustering in gene expression after cell stimulation for all RTS,S and comparator vaccinees.

    Fig. S8. Frequencies of leukocyte subsets after resting of PBMCs.

    Table S1. Predictive models obtained by artificial neural networks.

    Table S2. Validation qRT-PCR values and prediction results for the selected CPS preimmunization signature of protection.

    Table S3. Validation qRT-PCR values and prediction results for the selected CPS postimmunization signature of protection.

    Table S4. Validation qRT-PCR values and prediction results for the selected RTS,S/AS01E postimmunization signature of protection.

    Data file S1. Gene lists differential gene expression CPS immunogenicity and protection.

    Data file S2. Gene list correlations PfRBC FC and CPS outcomes and frequencies of gene ontology biological processes terms and BTMs of genes correlated with CPS outcomes.

    Data file S3. Gene lists differential gene expression RTS,S/AS01E immunogenicity and protection.

    Data file S4. Summary of GSEA and differential gene expression results.

    Data file S5. Summary of GSEA and WGCNA results.

    Data file S6. Selected genes for validation for CPS and RTS,S/AS01E.

    Data file S7. Postvalidation signatures of protection with accuracy data for CPS and RTS,S/AS01.

    Data file S8. CSP 15-mer peptides, corresponding to CSP region of RTS,S and predicted CD4+ and CD8+ T cell epitopes.

    Data file S9. Comparisons and limma contrasts.

    Data file S10. Gene list for validation.

    References (98133)

  • The PDF file includes:

    • Materials and Methods
    • Fig. S1. Experimental design and sample sizes.
    • Fig. S2. CPS study profile and sample flow chart.
    • Fig. S3. RTS,S study profile and sample flow chart.
    • Fig. S4. PCA of CPS gene expression data.
    • Fig. S5. Heatmaps and unsupervised hierarchical clustering in gene expression after cell stimulation for all CPS immunized volunteers.
    • Fig. S6. PCA of RTS,S/AS01E gene expression data.
    • Fig. S7. Heatmaps and unsupervised hierarchical clustering in gene expression after cell stimulation for all RTS,S and comparator vaccinees.
    • Fig. S8. Frequencies of leukocyte subsets after resting of PBMCs.
    • Table S1. Predictive models obtained by artificial neural networks.
    • Table S2. Validation qRT-PCR values and prediction results for the selected CPS preimmunization signature of protection.
    • Table S3. Validation qRT-PCR values and prediction results for the selected CPS postimmunization signature of protection.
    • Table S4. Validation qRT-PCR values and prediction results for the selected RTS,S/AS01E postimmunization signature of protection.
    • References (98133)

    [Download PDF]

    Other Supplementary Material for this manuscript includes the following:

    • Data file S1 (.zip format). Gene lists differential gene expression CPS immunogenicity and protection.
    • Data file S2 (Microsoft Excel format). Gene list correlations PfRBC FC and CPS outcomes and frequencies of gene ontology biological processes terms and BTMs of genes correlated with CPS outcomes.
    • Data file S3 (.zip format). Gene lists differential gene expression RTS,S/AS01E immunogenicity and protection.
    • Data file S4 (Microsoft Excel format). Summary of GSEA and differential gene expression results.
    • Data file S5 (Microsoft Excel format). Summary of GSEA and WGCNA results.
    • Data file S6 (Microsoft Excel format). Selected genes for validation for CPS and RTS,S/AS01E.
    • Data file S7 (Microsoft Excel format). Postvalidation signatures of protection with accuracy data for CPS and RTS,S/AS01.
    • Data file S8 (Microsoft Excel format). CSP 15-mer peptides, corresponding to CSP region of RTS,S and predicted CD4+ and CD8+ T cell epitopes.
    • Data file S9 (Microsoft Excel format). Comparisons and limma contrasts.
    • Data file S10 (Microsoft Excel format). Gene list for validation.

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