Publications & Reports

Framework for Characterizing Longitudinal Antibody Response in Children After Plasmodium falciparum Infection.

Rogier E, Nace D, Dimbu PR, Wakeman B, Pohl J, Beeson JG, Drakeley C, Tetteh K, Plucinski M
Malaria Branch, Division of Parasitic Diseases and Malaria, Centers for Disease Control and Prevention, Atlanta, GA, United States.


Human Plasmodium infection produces a robust adaptive immune response. Time courses for 104 children followed for 42 days after initiation of Plasmodium falciparum chemotherapy were assayed for antibody levels to the five isotypes of human immunoglobulins (Ig) and 4 subclasses of IgG for 32 P. falciparum antigens encompassing all 4 parasite stages of human infection. IgD and IgE against these antigens were undetectable at 1:100 serum concentration, but other Ig isotypes and IgG subclasses were consistently observed against all antigens. Five quantitative parameters were developed to directly compare Ig response among isotypes and antigens: Cmax, maximum antibody level; DeltaC, difference between Cmax and the antibody level at Day 0; tmax, time in days to reach Cmax; t1/2, Ig signal half-life in days; tneg, estimated number of days until complete loss of Ig signal. Classical Ig patterns for a bloodborne pathogen were seen with IgM showing early tmax and IgG production highest among Ig isotypes. However, some unexpected trends were observed such as IgA showing a biphasic pattern for many antigens. Variability among these dynamics of Ig acquisition and loss was noted for different P. falciparum antigens and able to be compared both quantitatively and statistically. This parametrization methodology allows direct comparison of Ig isotypes produced against various Plasmodium antigens following malaria infection, and the same methodology could be applied to other longitudinal serologic studies from P. falciparum or different pathogens. Specifically for P. falciparum seroepidemiological studies, reliable and quantitative estimates regarding the IgG dynamics in human populations can better optimize modeling efforts for serological outputs.

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  • Journal: Frontiers in Immunology
  • Published: 02/03/2021
  • Volume: 12
  • Pagination: 617951