Natural History of Malaria Infections During Early Childhood in Twins

Abstract

Background: The frequency and clinical presentation of malaria infections show marked heterogeneity in epidemiological studies. However, deeper understanding of this variability is hampered by the difficulty in quantifying all relevant factors. Here, we report the history of malaria infections in twins, who are exposed to the same in utero milieu, share genetic factors, and are similarly exposed to vectors.

Methods: Data were obtained from a Malian longitudinal birth cohort. Samples from 25 twin pairs were examined for malaria infection and antibody responses. Bayesian models were developed for the number of infections during follow-up.

Results: In 16 of 25 pairs, both children were infected and often developed symptoms. In 8 of 25 pairs, only 1 twin was infected, but usually only once or twice. Statistical models suggest that this pattern is not inconsistent with twin siblings having the same underlying infection rate. In a pair with discordant hemoglobin genotype, parasite densities were consistently lower in the child with hemoglobin AS, but antibody levels were similar.

Conclusions: By using a novel design, we describe residual variation in malaria phenotypes in naturally matched children and confirm the important role of environmental factors, as suggested by the between-twin pair heterogeneity in malaria history.

Keywords: hemoglobin S; infection; malaria; pathogenesis; twins.

Figure 1.

Falciparum infections during early childhood for 8 twin pairs. In each panel, smear results (parasite counts per 300 white blood cells [WBCs]) for the 2 twins in the pair are represented by blue and red lines. Hemoglobin type and ID numbers are indicated in the upper left corner. Circles represent time points when smears were performed; black squares, clinical episodes. Orange shaded areas represent the transmission season (July–December). To facilitate visualization of low-density infections, infections with <100 parasites per 300 WBCs are represented by stars. Groups defined in the text are shown on the top right corner in each panel. Pairs in group 1 were subcategorized in those with similar parasite levels during infection (group 1a) and those with discordant levels (group 1b), in which the twin with highest parasitemia had ≥1 smear with parasite counts ≥5-fold the maximum count of her or his sibling. Group 2 corresponds to pairs in which only 1 twin had infection. Group 3 includes pairs with discordant hemoglobin S mutation status. Note that here only the 2 pairs in each group with the longest follow-up are presented (the same information is shown for all twin pairs in Supplementary Figure 1). In group 3, only individuals with AA genotype had hyperparasitemia (here defined as > 3750 parasites per 300 WBC; see also Supplementary Figure 3). Clinical episodes in which only nonfalciparum parasites were detected are represented by black squares that are not linked to the plot lines and whose y-axis coordinate is defined by the nonfalciparum parasitemia.

Figure 2.

Results of statistical models on the number of malaria infections. A, We fit 3 count data models: a Poisson model, which assumes the same incidence parameter for all individuals; a negative binomial model, which allows for additional variability in the incidence but does not explicitly allow for the clustering of children within pairs; and a hierarchical Poisson model, which allows the incidence parameter to vary between pairs of twins but not within pairs. The y-axis represents the number of infections (black circles) during the follow-up of children, grouped in pairs (x-axis); red stars indicate children with hemoglobin AS genotype. For each child, posterior predictive distributions are presented for the 3 models discussed above; the different degrees of transparency of the colors represent different posterior intervals: 2.5–97.5, 25–75, 40–60. While the Poisson model (orange) does not fit the data well, data are consistent with both the negative binomial (green) and the hierarchical Poisson (purple) models. Of note, we also fit a Poisson model that included as covariate birth before versus after August 2013, when follow-up frequency changed (see Supplementary Figure 4). B, Estimated rate of infection, per month (x-axis; posterior median and 95% interval), based on the hierarchical Poisson model, presented for each of the 25 twin pairs (y-axis). Note that the rate in pair 5 is estimated to be relatively high, owing to infection detection during the relatively short follow-up of this pair. The ordering of this panel, from higher to lower y-axis coordinates, corresponds to the same ordering, from left to right, in A.

Figure 3.

Numbers of clinical malaria episodes for twins in the same pair (x- and y-axes). Red circles represent pairs with discordant hemoglobin S status; in these pairs, twin 2 (y-axis) is the AS child. Noise was added to x- and y-coordinates so that circles for pairs with similar coordinates do not fully overlap.

Figure 4.

Levels of antibodies (y-axes) against the malaria antigens apical membrane antigen 1 (AMA-1; gray lines) and merozoite surface protein 1 (MSP-1; green lines). As in Figure 1, each panel presents data for a twin pair. The ordering of the panels in the same in both figures; continuous and dashed lines represent data from the twins represented with red and blue lines, respectively, in Figure 1. Blue and red circles, in the lower half of each panel, indicate the timing (x-axes) of positive smears. Black crosses on the serological measurements represent serological samples coinciding with smear-positive results. Of note, there were twins in whom a high humoral response developed despite low cumulative parasite burden. Note that, as for Figure 1, only data for the twin pairs in each group with the longest follow-up are shown; similar data for all twin pairs are shown in Supplementary Figure 6. Hemoglobin type and ID numbers are indicated in the upper left corner. Abbreviation: OD, optical density at 450 nm.