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High <i>Plasmodium falciparum</i> longitudinal prevalence is associated with high multiclonality and reduced clinical malaria risk in a seasonal transmission area of Mali
<div><p>The effects of persistent <i>Plasmodium falciparum</i> (Pf) infection and multiclonality on subsequent risk of clinical malaria have been reported, but the relationship between these 2 parameters and their relative impacts on the clinical outcome of infection are not understood. A longitudinal cohort study was conducted in a seasonal and high-transmission area of Mali, in which 500 subjects aged 1–65 years were followed for 1 year. Blood samples were collected every 2 weeks, and incident malaria cases were diagnosed and treated. Pf infection in each individual at each time point was assessed by species-specific nested-PCR, and Pf longitudinal prevalence per person (PfLP, proportion of Pf-positive samples over 1 year) was calculated. Multiclonality of Pf infection was measured using a 24-SNP DNA barcoding assay at 4 time-points (two in wet season, and two in dry season) over one year. PfLP was positively correlated with multiclonality at each time point (all r≥0.36; all <i>P</i>≤0.011). When host factors (e.g., age, gender), PfLP, and multiclonality (at the beginning of the transmission season) were analyzed together, only increasing age and high PfLP were associated with reduced clinical malaria occurrence or reduced number of malaria episodes (for both outcomes, <i>P</i><0.001 for age, and <i>P</i> = 0.005 for PfLP). When age, PfLP and baseline Pf positivity were analyzed together, the effect of high PfLP remained significant even after adjusting for the other two factors (<i>P</i> = 0.001 for malaria occurrence and <i>P</i><0.001 for number of episodes). In addition to host age and baseline Pf positivity, both of which have been reported as important modifiers of clinical malaria risk, our results demonstrate that persistent parasite carriage, but not baseline multiclonality, is associated with reduced risk of clinical disease in this population. Our study emphasizes the importance of considering repeated parasite exposure in future studies that evaluate clinical malaria risk.</p></div
Correlation between polymorphic proportion (PmP) and <i>P</i>. <i>falciparum</i> longitudinal prevalence (PfLP).
<p>PmP positively correlates with PfLP at all 4 time-points: (A) Jun-V1 (r = 0.47, 95% confidence interval = 0.30–0.61, <i>P</i><0.001, Spearman rank correlation test); (B) Nov-V1 (r = 0.36, 0.18–0.52, <i>P</i><0.001); (C) Feb-V1 (r = 0.42, 0.15–0.63, <i>P</i> = 0.003); and (D) Apr-V1 (r = 0.39, 0.09–0.63, <i>P</i> = 0.011)</p
Cross-sectional prevalence of <i>P</i>. <i>falciparum</i> (Pf) infection and 2-week incidence of clinical malaria from June 2013 to May 2014.
<p>Left y-axis: Pf prevalence measured by nested-PCR; dark gray bars represent Pf prevalence. Right y-axis: number of clinical malaria cases recorded during each 2-week period preceding a blood sampling visit; light gray bars represent 2-week incidence. The time of visit is indicated on the x-axis, with V1 and V2 indicating the first and second blood sampling visits, respectively, for the months indicated.</p
Results of multivariate regression analysis of clinical malaria risk, including baseline Pf positivity<sup>a</sup>.
<p>Results of multivariate regression analysis of clinical malaria risk, including baseline Pf positivity<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0170948#t004fn001" target="_blank"><sup>a</sup></a>.</p
Multiclonality of <i>P</i>. <i>falciparum</i> infection at 4 time-points.
<p>(A) Distribution of complexity of infection (COI) values estimated by COIL. The proportions of individuals with COI = 1 (white), COI = 2 (light gray), and COI≥3 (dark gray) at each time-point are indicated. (B) Distribution of polymorphic proportion (PmP) values calculated from polymorphic genotypes in the 24-SNP DNA barcode. Box-and-whisker plots show median, interquartile range (IQR), and 1.5x IQR. There were no significant differences in the COI and PmP distributions among the 4 time-points as determined by Chi-squared and Kruskal-Wallis tests, respectively.</p