Differential expression pattern of co-inhibitory molecules on CD4+ T cells in uncomplicated versus complicated malaria

Abstract

The immune response of malaria patients is a main factor influencing the clinical severity of malaria. A tight regulation of the CD4⁺ T cell response or the induction of tolerance have been proposed to contribute to protection from severe or clinical disease. We therefore compared the CD4⁺ T cell phenotypes of Ghanaian children with complicated malaria, uncomplicated malaria, asymptomatic Plasmodium falciparum (Pf) infection or no infection. Using flow cytometric analysis and automated multivariate clustering, we characterized the expression of the co-inhibitory molecules CTLA-4, PD-1, Tim-3, and LAG-3 and other molecules implicated in regulatory function on CD4⁺ T cells. Children with complicated malaria had higher frequencies of CTLA-4⁺ or PD-1⁺ CD4⁺ T cells than children with uncomplicated malaria. Conversely, children with uncomplicated malaria showed a higher proportion of CD4⁺ T cells expressing CD39 and Granzyme B, compared to children with complicated malaria. In contrast, asymptomatically infected children expressed only low levels of co-inhibitory molecules. Thus, different CD4⁺ T cell phenotypes are associated with complicated versus uncomplicated malaria, suggesting a two-sided role of CD4⁺ T cells in malaria pathogenesis and protection. Deciphering the signals that shape the CD4⁺ T cell phenotype in malaria will be important for new treatment and immunization strategies.

Figure 1

Higher proportions of PD-1⁺ and CTLA-4⁺ CD4⁺ T cells in children with complicated malaria. Blood samples from patients and controls were ex vivo analyzed for the expression of PD-1, intracellular CTLA-4, LAG-3, and Tim-3 on CD4⁺ T cells by flow cytometry. Box plots demonstrating expression of PD-1 (A), CTLA-4 (B), LAG-3 (C), and Tim-3 (D) in all four study groups. Statistical differences are shown according to One-way ANOVA with Tukey’s Multiple Comparison Test.

Figure 2

Identification of differing cell signatures between children with uncomplicated and complicated malaria using automated hierarchical clustering. (A) CITRUS with group PAMR analysis (R implementation of Prediction Analysis for Microarrays) of PD-1, CTLA-4, LAG-3 and Tim-3 expression of samples from children with complicated (IP) and uncomplicated (OP) malaria. Differing clusters are highlighted in red (centre) and categorized into cluster group I (purple) and cluster group II (pink) (centre). Within each cluster group, clusters are numbered. Four parameter clustering of OP and IP samples demonstrating individual parameter expression intensities of PD-1, CTLA-4, LAG-3 and Tim-3 (outer graphs). Cv.1se was used with a 10 fold cross validation and error rate of 30%. (B) Each line represents a numbered cluster defined in A. Abundance of cells within the identified differing clusters in the OP and IP groups. The dots represent samples within the groups. (C) Intensity of the expression of co-inhibitory molecules within the differing clusters. Expression of the specific molecules within the total amount of cells is shown in grey, expression within the specific cluster is shown in red.

Figure 3

Uncomplicated malaria is associated with a higher expression of CD69, CD39, and Granzyme B on CD4⁺ T cells. Blood samples from patients and controls were ex vivo analyzed for the expression of CD38, CD69, CD39, and intracellular Ki-67 and Granzyme B on CD4⁺ T cells by flow cytometry. Box plots demonstrating expression of CD38, CD69, Ki-67, CD39, and Granzyme B on CD4⁺ T cells. Potential statistically significant differences were determined by One-way ANOVA with Tukey’s Multiple Comparison Test. (CD38, CD39, CD69, and GrzB: HC n = 39; AS n = 40; OP n = 27; IP n = 31; Ki67: HC n = 37; AS n = 40; OP n = 19; IP n = 31).

Figure 4

Levels of plasma cytokines do not differ between the outpatient and inpatient group. Plasma samples from patients and controls were ex vivo analyzed for the presence of cytokines by LEGENDplex. Scatter plots showing levels of Interferon (IFN)-γ, Interleukin-6 (IL-6), IL-10, IL-2, IL-17F, IL-17A and Tumor necrosis factor (TNF)-α in the four study groups. One-way ANOVA with Tukey’s Multiple Comparison Test was conducted to determine potential statistical differences. (HC n = 38; AS n = 39; OP n = 29; IP n = 32).