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. 2011 Mar;84(3):397-401.
doi: 10.4269/ajtmh.2011.10-0450.

African Burkitt lymphoma: age-specific risk and correlations with malaria biomarkers

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African Burkitt lymphoma: age-specific risk and correlations with malaria biomarkers

Benjamin Emmanuel et al. Am J Trop Med Hyg. 2011 Mar.

Abstract

African Burkitt lymphoma is an aggressive B-cell, non-Hodgkin lymphoma linked to Plasmodium falciparum malaria. Malaria biomarkers related to onset of African Burkitt lymphoma are unknown. We correlated age-specific patterns of 2,602 cases of African Burkitt lymphoma (60% male, mean ± SD age = 7.1 ± 2.9 years) from Uganda, Ghana, and Tanzania with malaria biomarkers published from these countries. Age-specific patterns of this disease and mean multiplicity of P. falciparum malaria parasites, defined as the average number of distinct genotypes per positive blood sample based on the merozoite surface protein-2 assessed by polymerase chain reaction, were correlated and both peaked between 5 and 9 years. This pattern, which was strong and consistent across regions, contrasted parasite prevalence, which peaked at 2 years and decreased slightly, and geometric mean parasite density, which peaked between 2 and 3 years and decreased sharply. Our findings suggest that concurrent infection with multiple malaria genotypes may be related to onset of African Burkitt lymphoma.

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Figures

Figure 1.
Figure 1.
Characteristics of African Burkitt lymphoma cases correlated with Plasmodium falciparum malaria mean multiplicity of infection, prevalence, and geometric mean parasite density. A and B, Percentage of African Burkitt lymphoma cases by age and mean multiplicity of P. falciparum malaria parasites, defined as the average number of distinct genotypes per positive blood sample based on the merozoite surface protein-2 assessed by polymerase chain reaction, in Ghana and Tanzania. C and D, Percentage of African Burkitt lymphoma cases per age, prevalence of P. falciparum malaria, and geometric mean parasite density in the general population in Ghana and Tanzania., Age group intervals for the cases were plotted according to the age groups used in the malaria papers.

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