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Immune system development varies according to age, location, and anemia in African children

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Science Translational Medicine  05 Feb 2020:
Vol. 12, Issue 529, eaaw9522
DOI: 10.1126/scitranslmed.aaw9522
  • Fig. 1 No changes to blood leukocyte subsets are detected 1 month after third vaccination.

    (A) The timeline for vaccinations and blood sampling during the vaccine trial follow-up period. The three vaccination groups are shown (R3R, R3C, and C3C). Vaccinations are shown in blue (R = RTS,S; C = Comparator). Comparator vaccine differed between age groups (Menjugate for infants, Verorab for children). Red numbers indicate the month of follow-up at which blood samples were collected. (B) The distribution of participant age (in months) at each of the blood sampling time points for Tanzanian children (n = 414 total samples). Nonmetric multidimensional scaling (NMDS) for Tanzanian children at blood sample 3 (C) or blood sample 21 (D) based on the 336 tSNE clusters and vaccine group (B3: R3R and R3C, n = 63; comparator, n = 17; B21: C3C, n = 18; R3C, n = 39; R3R, n = 44). Samples from R3R and R3C groups were combined at B3 because identical vaccines had been received. The frequencies of 336 tSNE clusters (E) (as a proportion of each subpopulation) or 70 manually gated cell subsets for each participant (F) (as a percentage of all leukocytes) were compared between vaccine groups at B0 and B3 and within groups at B3 relative to B0 (all = all Tanzanian children, n = 80). Between-group comparisons were analyzed with the Mann-Whitney test, and B0 versus B3 used paired data and Wilcoxon signed-rank test. The −log10 P value is plotted for each cluster or subset (FDR adjusted for multiple comparisons). tSNE clusters (G) or manual gated cell subsets (H) were compared within vaccine group at B21 and in all children (pairwise) at B21 relative to B0. In (E) to (H), any population with an adjusted P value of less than 0.01 were deemed significantly different; the dashed lines indicate Padj = 0.01.

  • Fig. 2 Dynamic development of memory B and T cells occurs between 6 months and 2 years of age.

    (A) The age (in months) of infant and children age groups from Mozambique during study follow-up. Red box indicates the B3 samples (n = 37 infants, n = 52 children). (B) NMDS for children and infants at B3 based on the 336 tSNE clusters, with the coordinates for each dimension compared by Mann-Whitney test. (C) Heatmap showing the manually gated cell subsets (as a percentage of all leukocytes) with an FDR-adjusted P value of less than 0.001 between children and infants at B3 by Mann-Whitney test. Cell types are shown as rows, and each column represents an individual participant. Rows and columns were clustered using Euclidean distance, and the cell subset frequency was converted to z-scores. Individuals without any missing values are shown (n = 22 infants, n = 30 children). (D) The contribution of sample age group and sex to the cell type variance as determined from linear regression models, shown as a boxplot summary of the 33 cell types shown in (C) (n = 89 samples). (E) Representative cell type frequencies (as a percentage of parent population) for infants and children, with a P value from Mann-Whitney test (FDR adjusted for 70 subsets; n = 37 infants, n = 52 children). (F) Anti-HBV.S or anti-CSP IgG titer [B3 − B0 arbitrary units (AU)] from a cohort of RTS,S vaccinated participants from Mozambique (n = 198 infants, n = 137 children), with a P value from Mann-Whitney test. The 336 tSNE clusters (G) or 70 manually gated cell subsets (H) were compared between infants and children at B3, B21, and B32, and the −log10 FDR-adjusted P value is shown, with dashed lines indicating Padj = 0.01.

  • Fig. 3 Dynamic changes of the immune landscape during early childhood.

    (A) The age in months of Tanzanian children at blood samples throughout the follow-up period (n = 414 in total). (B) NMDS for children at B0 (n = 78) and B32 (n = 109) based on the 336 tSNE clusters, with the coordinates for each dimension compared by Mann-Whitney test. Colors correspond to time point (B0, white; B32, black). (C) Heatmap of cell subsets that were significantly different between B0 and B32 in Tanzanian children (P < 0.0001 and conditional R2 > 0.25), with the frequency predicted from LMER models shown normalized to week 20 frequency. P values for the effect of sex and age determined by ANOVA of LMER models after FDR adjustment are shown in gray boxes, and the marginal and conditional R2 of LMER model are shown in purple for each cell subset. n.s., not significant. (D) The frequency of four representative cell subsets (as a percentage of parent population) plotted against age for each sample, with LMER modeling (red lines). Marginal R2 and P value for fit of LMER models shown in boxes above each plot.

  • Fig. 4 Blood gene expression signatures reflect innate and adaptive immune cell changes during early childhood.

    (A) The age (in months) of the Tanzanian children at blood samples B0 and B32 for which RNA-seq was performed. Dots represent individual samples, B0 (n = 21) and B32 (n = 9). (B) Hierarchical clustering of 2146 differentially expressed (DE) genes between B0 and B32 (1148 up-regulated at B0, 1008 up-regulated at B32). Significantly different genes had an FDR-adjusted P value of <0.01 from DESeq2 and an FDR-adjusted P value of <0.05 from the intensity-difference test and were clustered using Euclidean distance. Each column represents an individual sample, and genes are shown as rows. Enriched blood transcriptional modules (BMTs) at (C) B0 and (D) B32, represented as colored circles with annotations as text. Colors and connecting lines show gene sets with related genes, and summary are terms shown in text boxes. BTMs enriched from within all expressed genes (17,607) with an enrichment score greater than 1.5 or less and −0.5 and an FDR-adjusted P value of <0.01 (Kolmorogov-Smirnov test) are shown. (E) A stylized representation of the multi-omics factor analysis (MOFA) modeling, which was built using 5000 most variable genes from RNA-seq and 61 immune cell types measured by flow cytometry for 27 samples (19 B0, 8 B32) and reduces these 5061 parameters to latent factors (LFs). (F) The percentage of total variance (R2) in the MOFA model explained by flow cytometry or RNA-seq datasets. (G) Scatter plot showing the distribution of samples by the first two LFs determined by MOFA modeling. Each sample shown is as a circle (B0, white; B32, black). The percentage of total variance and the contribution of flow and RNA to each factor are indicated in the axes labels. (H) The correlation between the age in weeks for each sample and the sum of values for LF1 and LF2 (factor sum; B0, white; B32, black). Linear regression fit shown by the red line, and R2 and P value from Pearson correlation are shown. The proportional loading for the 12 cell types with the strongest contribution to (I) LF1 or (K) LF2 are shown. The P values (−log10 FDR-adjusted) for BTMs that were significantly enriched (P adjusted < 0.05) among genes identified by (J) LF1 and (L) LF2 and corresponding enrichment scores. (I to L) Color and symbol representing the direction of loading or enrichment in factor space (blue, negative; red, positive).

  • Fig. 5 Comparison of Tanzanian and Dutch children reveals that age and location are linked with changes in the immune landscape.

    (A) The age in months for Tanzanian samples relative to Dutch cohort. The green box indicates the 20- to 125-week age range used for age-matched LMER modeling, with 176 total samples from 102 Tanzanian children and 748 total samples from 504 Dutch children. The purple box represents the birth to 414-week age range used for immune trajectory building. (B) Cell subsets that were measured in both cohorts and were significantly altered with age in either cohort are shown as the frequency predicted from LMER models, normalized to the Tanzanian cohort week 20 levels. P values determined by ANOVA for the effect of sex and location (Tanzanian or Dutch cohorts) and for the interaction between age and location are shown in gray boxes, with FDR adjustment. (C) The frequency (percentage of B cells, CD4, or CD8 T cells) of representative cell subsets are shown from 20 to 125 weeks of age for the Tanzanian (gray) and Dutch samples (blue). Solid lines represent respective LMER models, with P values from ANOVA for location, age, and sex effects shown in boxes below (FDR adjusted for the 19 of cell subsets). (D) Diffusion map dimensionality reduction of Dutch and Tanzanian samples using scaled cellular frequencies and the diffusion-pseudotime algorithm. Each dot represents a sample, color represents the pseudotime output values, and the red arrow indicates the direction of the trajectory that starts with the Dutch newborn samples. First panel shows all samples used for building the trajectory (421 total samples from 157 Tanzania children, 1801 total samples from 1119 Dutch children), and second and third panels show Dutch and Tanzanian samples in the 20- to 125-week age range, respectively, used in LMER models in (B) and (C). The correlation coefficients (R2) for the 18 cell types that significantly correlated with the pseudotime are shown as colored boxes. (E) The distribution of naïve and memory B cell frequencies along the diffusion map trajectory are shown for 2222 samples, with color representing the scaled cell type frequency. (F) Age (in weeks) and (G) corresponding pseudotime age for samples in the 20- to 125-week age range shown in (D), with P values determined by Mann-Whitney test.

  • Fig. 6 Childhood immune development is influenced by location within Africa.

    (A) NMDS for children at B0 from Tanzania (n = 78) and Mozambique (n = 30) based on the 336 tSNE clusters, with the coordinates for each dimension compared by Mann-Whitney test. (B) Heatmap showing manually gated cell subsets (as a percentage of all leukocytes) with an FDR-adjusted P value of less than 0.01 between each site at B0 by Mann-Whitney test. Cell types are shown as rows, and each column represents an individual sample. Rows and columns were clustered using Euclidean distance, and the cell subset frequency was converted to z-scores (Mozambique, n = 19; Tanzania, n = 86). (C) The 336 tSNE clusters or 70 manually gated cell subsets were compared between samples from Tanzania and Mozambique at B0, B3, B21, and B32 by Mann-Whitney test. The −log10 FDR-adjusted P value is shown, with the dashed line indicating Padj = 0.01. (D) Representative cell type frequencies for each site (as a percentage of parent population), with a P value from Mann-Whitney test (FDR adjusted for 70 subsets). (E) The increase in anti-HBV.S or anti-CSP IgG (B3 − B0 AU) at B3 (B3 − B0) from a larger cohort of RTS,S-vaccinated participants from each site (Mozambique, n = 137; Tanzania, n = 123), with a P value from Mann-Whitney test. (F) The age of children for immunophenotyping samples from each site (Tanzania, n = 33; Mozambique, n = 94). (G) The contribution of sample age, sex, and country (Tanzania or Mozambique) to the cell type variance as determined from linear regression models, shown as a boxplot summary of the 31 cell types shown in (B). (H) Weight and (I) height (z-scores, age-adjusted according to global reference values) for each site (Tanzania, n = 359; Mozambique, n = 974). (J) Blood hemoglobin concentration (g/dl) for each site, with dashed lines representing the various disease categories (Tanzania, n = 359; Mozambique, n = 974).

  • Fig. 7 Anemia is linked to changes in immunophenotype and iron availability directly impacts B cell biology.

    (A) The age of anemic [hemoglobin (<8.5 g/dl), n = 43] and nonanemic [hemoglobin (>10.5 g/dl), n = 52] from Tanzania and Mozambique at B0. Black squares indicate samples where RNA-seq was performed on whole PBMCs in addition to immunophenotyping. (B) Hierarchical clustering of 376 DE genes between anemic (n = 6) and nonanemic (n = 8) Tanzanian children. Significantly different genes had an FDR-adjusted P value of <0.01 from DESeq2 and an FDR-adjusted P value of <0.05 from the intensity-difference test and were clustered using Euclidean distance. Each column represents an individual sample, and genes are shown as rows. Enriched BMTs in (C) anemic and (D) nonanemic children, represented as colored circles with annotations as text. Colors and connecting lines show gene sets with related genes, and summary terms are shown in text boxes. BTMs enriched from within all expressed genes (17,607) with an enrichment score greater than 1.5 or less and −0.5 and an FDR-adjusted P value of <0.01 (Kolmorogov-Smirnov test) are shown. (E) The contribution of sample age, anemia status, and sex to the cell type variance as determined from linear regression models. Representative cell subset frequencies that were significantly different between anemic and nonanemic children at (F) B0 (nonanemic, n = 52; anemic, n = 43) and (G) B21 (nonanemic, n = 99; anemic, n = 20), with a P value from Mann-Whitney test. (H to M) Purified B cells from U.K. adults were stained with CellTraceViolet and incubated in culture media with interleukin-21 and CD40L (CM) for 5 days. Some cultures were supplemented with either apo-transferrin (APO) throughout or with ciclopirox olamine (CPX) after 24 hours of culture. (H) The percentage and number of live B cells at days 0 and 5 in CM, APO, and CPX culture conditions. (I) Representative histogram of cell trace violet on day 5 (black, CM; red, APO; blue, CPX) and (J) the percentage of cells that have undergone one or more divisions on day 5. (K) Plasmablast gating strategy (live IgDCD27+CD38+IRF4+ B cells). (L) The percentage of plasmablasts and fold change (FC) relative to CM alone. (M) The concentration of IgG in culture supernatants as measured by ELISA and fold change relative to CM culture conditions. (H to M) P values were determined using Holm-Sidak’s multiple comparison testing, except for fold change analyses for which a one-sample t test was used. Representative of three independent experiments with six to eight U.K. adult blood samples.

Supplementary Materials

  • stm.sciencemag.org/cgi/content/full/12/529/eaaw9522/DC1

    Fig. S1. Pregating of cell types for tSNE.

    Fig. S2. Gating hierarchy panel 1.

    Fig. S3. Gating hierarchy panel 2.

    Fig. S4. Representative flow plots panel 1.

    Fig. S5. Representative flow plots panel 2.

    Fig. S6. No vaccine-induced changes are detectable 1 month after vaccination.

    Fig. S7. Strong correlations observed within related cell types.

    Fig. S8. Cell subset frequency correlations between baseline and B3 time points.

    Fig. S9. Cell subset frequency correlations between baseline and B32 time points.

    Fig. S10. Anti-CSP and anti-HBV.S IgG titers before and after vaccination in infants and children from Mozambique.

    Fig. S11. Distribution of participant age along the diffusion-pseudotime trajectory.

    Fig. S12. Anti-CSP and anti-HBV.S IgG titers before and after vaccination in children from Tanzania and Mozambique.

    Fig. S13. Dose-dependent toxicity of ciclopirox olamine on B cells in culture.

    Fig. S14. Highly reproducible flow cytometry data between experiments.

    Table S1. Participant characteristics.

    Table S2. Consolidated Standards of Reporting Trials table.

    Table S3. Antibody panels.

    Table S4. Manually gated cell subset definitions panel 1.

    Table S5. Manually gated cell subset definitions panel 2.

    Data file S1. Differentially expressed genes between B0 and B32.

    Data file S2. Differentially expressed genes between anemic and nonanemic children.

    Data file S3. Plasmablast differentiation assay raw data.

  • The PDF file includes:

    • Fig. S1. Pregating of cell types for tSNE.
    • Fig. S2. Gating hierarchy panel 1.
    • Fig. S3. Gating hierarchy panel 2.
    • Fig. S4. Representative flow plots panel 1.
    • Fig. S5. Representative flow plots panel 2.
    • Fig. S6. No vaccine-induced changes are detectable 1 month after vaccination.
    • Fig. S7. Strong correlations observed within related cell types.
    • Fig. S8. Cell subset frequency correlations between baseline and B3 time points.
    • Fig. S9. Cell subset frequency correlations between baseline and B32 time points.
    • Fig. S10. Anti-CSP and anti-HBV.S IgG titers before and after vaccination in infants and children from Mozambique.
    • Fig. S11. Distribution of participant age along the diffusion-pseudotime trajectory.
    • Fig. S12. Anti-CSP and anti-HBV.S IgG titers before and after vaccination in children from Tanzania and Mozambique.
    • Fig. S13. Dose-dependent toxicity of ciclopirox olamine on B cells in culture.
    • Fig. S14. Highly reproducible flow cytometry data between experiments.
    • Table S1. Participant characteristics.
    • Table S2. Consolidated Standards of Reporting Trials table.
    • Table S3. Antibody panels.
    • Table S4. Manually gated cell subset definitions panel 1.
    • Table S5. Manually gated cell subset definitions panel 2.

    [Download PDF]

    Other Supplementary Material for this manuscript includes the following:

    • Data file S1 (.csv format). Differentially expressed genes between B0 and B32.
    • Data file S2 (.csv format). Differentially expressed genes between anemic and nonanemic children.
    • Data file S3 (Microsoft Excel format). Plasmablast differentiation assay raw data.

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