Both inflammatory and regulatory cytokine responses to malaria are blunted with increasing age in highly exposed children

Abstract

Background: Young children are at greatest risk for malaria-associated morbidity and mortality. The immune response of young children differs in fundamental ways from that of adults, and these differences likely contribute to the increased susceptibility of children to severe malaria and to their delayed development of immunity. Elevated levels of pro-inflammatory cytokines and chemokines in the peripheral blood during acute infection contribute to the control of parasitaemia, but are also responsible for much of the immunopathology seen during symptomatic disease. Clinical immunity to malaria may depend upon the ability to regulate these pro-inflammatory responses, possibly through mechanisms of immunologic tolerance. In order to explore the effect of age on the immune response to malaria and the development of clinical immunity, cytokines and chemokines were measured in the plasma of children at day 0 of an acute malaria episode and during convalescence.

Results: Younger children presenting with acute malaria exhibited much higher levels of TNF, IL2, and IL6, as well as increased Th1 associated chemokines IP10, MIG, and MCP1, compared to older children with acute malaria. Additionally, the regulatory cytokines IL10 and TNFRI were dramatically elevated in younger children compared to older children during acute infection, indicating that regulatory as well as pro-inflammatory cytokine responses are dampened in later childhood.

Conclusions: Together these data suggest that there is a profound blunting of the cytokine and chemokine response to malaria among older children residing in endemic settings, which may be due to repeated malaria exposure, intrinsic age-based differences in the immune response, or both.

Keywords: Age; Cytokines; Immunity; Malaria; Tolerance.

Fig. 1

Plasma inflammatory (a) and regulatory (b) cytokine responses to malaria across age groups. Data are presented as scatter plots across age groups and timepoints. Boxes represent medians and whiskers represent the IQR of each group. Significant differences across age groups were assessed by Wilcoxon rank sum and the Wilcoxon sign-rank test was used for pairwise comparisons between timepoints. Only P values < 0.05 are shown. *Denotes p values that are not statistically significant (P > 0.0125) after Bonferroni multiple comparisons testing. Samples below the limit of detection are shown at the lower limit of detection. Only cytokines for which > 7% of samples were above the limit of detection appear in the figure

Fig. 2

IFNγ responses to malaria across age groups by ELISA. Data are presented as scatter plots across age groups and timepoints. Boxes represent medians and whiskers represent the IQR of each group. The dashed horizontal line marks the lower limit of detection for the assay

Fig. 3

Association between regulatory cytokines and parasitaemia. Spearman’s rank correlation was used to detect associations between plasma levels of IL10 and sTNFRI and parasite density. Parasite density and IL10 concentrations were log transformed, sTNFRI concentrations were square root transformed

Fig. 4

Pro-inflammatory/regulatory cytokine ratios across age groups. Data are presented as scatter plots across age groups and timepoints. Boxes represent medians and whiskers represent the IQR of each group. Significant differences across age groups were assessed by Wilcoxon rank sum

Fig. 5

Plasma inflammatory (a) and regulatory (b) chemokine responses to malaria across age groups. Data are presented as scatter plots across age groups and timepoints. Boxes represent medians and whiskers represent the IQR of each group. Significant differences across age groups were assessed by Wilcoxon rank sum and the Wilcoxon sign-rank test was used for pairwise comparisons between timepoints. Only P values < 0.05 are shown. *Denotes p-values that are not statistically significant (P > 0.0125) after Bonferroni multiple comparisons testing. Samples below the limit of detection are shown at the lower limit of detection. Only chemokines for which > 7% of samples were above the limit of detection appear in the figure