Genetic determinants of anti-malarial acquired immunity in a large multi-centre study

Abstract

Background: Many studies report associations between human genetic factors and immunity to malaria but few have been reliably replicated. These studies are usually country-specific, use small sample sizes and are not directly comparable due to differences in methodologies. This study brings together samples and data collected from multiple sites across Africa and Asia to use standardized methods to look for consistent genetic effects on anti-malarial antibody levels.

Methods: Sera, DNA samples and clinical data were collected from 13,299 individuals from ten sites in Senegal, Mali, Burkina Faso, Sudan, Kenya, Tanzania, and Sri Lanka using standardized methods. DNA was extracted and typed for 202 Single Nucleotide Polymorphisms with known associations to malaria or antibody production, and antibody levels to four clinical grade malarial antigens [AMA1, MSP1, MSP2, and (NANP)4] plus total IgE were measured by ELISA techniques. Regression models were used to investigate the associations of clinical and genetic factors with antibody levels.

Results: Malaria infection increased levels of antibodies to malaria antigens and, as expected, stable predictors of anti-malarial antibody levels included age, seasonality, location, and ethnicity. Correlations between antibodies to blood-stage antigens AMA1, MSP1 and MSP2 were higher between themselves than with antibodies to the (NANP)4 epitope of the pre-erythrocytic circumsporozoite protein, while there was little or no correlation with total IgE levels. Individuals with sickle cell trait had significantly lower antibody levels to all blood-stage antigens, and recessive homozygotes for CD36 (rs321198) had significantly lower anti-malarial antibody levels to MSP2.

Conclusion: Although the most significant finding with a consistent effect across sites was for sickle cell trait, its effect is likely to be via reducing a microscopically positive parasitaemia rather than directly on antibody levels. However, this study does demonstrate a framework for the feasibility of combining data from sites with heterogeneous malaria transmission levels across Africa and Asia with which to explore genetic effects on anti-malarial immunity.

Fig. 1

Proportion of individuals microscopically Plasmodium falciparum positive. Data shown are for the six sites for which surveys sampled across different age groups. Studies not included here include: Mali (Pongonon) where only malaria positive were included, Kenya (where only one age group was sampled) and Sudan and Sri Lanka were all negative at the time of survey.

Fig. 2

Heatmap matrix plot of correlations between logged antibody titres at each site. Pairwise correlations between logged anti-AMA1, anti-MSP1, anti-MSP2, anti-NANP, and total IgE calculated as R-squared. Strongest correlations shown in red and weakest correlations shown in yellow. Correlations of antibodies with themselves shown here in grey.

Fig. 3

Mean logged antibody titre for the five measured antibodies, for each age-group for each site. Each colour represents a different antibody while the shape of the point represents the antibody type: (triangle) for anti-merozoite, (square) for anti-sporozoite, and (circle) for total IgE.

Fig. 4

Plot for 178 SNPs with logged anti-malarial antibody levels. Values of –log₁₀ p-values plotted against chromosomal positions; only the lowest meta-analysis p-value for each SNP-antibody association is plotted. The red dotted line indicates a Bonferroni threshold p-value of 6 × 10⁻⁵. Each colour represents a different anti-malarial antibody while the shape of the point represents the genetic model of best fit for the SNP-antibody association: (circle) for additive, (triangle) for dominant, and (square) for heterozygote and (plus) for recessive. Adjusted for age, gender, microscopy result, village (>20), ethnicity (>20), sample month (>20) and study.

Fig. 5

Forest plot of the HbS (rs334) association with antibodies to AMA1, MSP1, MSP2 and NANP. Points correspond to beta values obtained from meta-analysis of results obtained from linear regression models of SNP with logged antibody levels, adjusted for relevant clinical covariates. Lines represent 95 % confidence intervals. Each colour represents a different antibody while the shape of the point represents the antibody type: (circle) for anti-merozoite and (triangle) for anti- sporozoite. Summary of meta-analysis betas obtained from combined data are represented as (square). Summary P-values: ama1 = 2.9 × 10⁻⁰⁷; msp1 = 1.2 × 10⁻⁰⁶; msp2 = 6.5 × 10⁻⁰⁷; nanp; = 0.2.