Quantification of anti-parasite and anti-disease immunity to malaria as a function of age and exposure

  1. Isabel Rodriguez-Barraquer  Is a corresponding author
  2. Emmanuel Arinaitwe
  3. Prasanna Jagannathan
  4. Moses R Kamya
  5. Phillip J Rosenthal
  6. John Rek
  7. Grant Dorsey
  8. Joaniter Nankabirwa
  9. Sarah G Staedke
  10. Maxwell Kilama
  11. Chris Drakeley
  12. Isaac Ssewanyana
  13. David L Smith
  14. Bryan Greenhouse
  1. University of California, San Francisco, United States
  2. Infectious Diseases Research Collaboration, Uganda
  3. Stanford University, United States
  4. Makerere University College of Health Sciences, Uganda
  5. Infectious Diseases Resarch Collaboration, Uganda
  6. London School of Hygiene and Tropical Medicine, United Kingdom
  7. University of Washington, United States

Abstract

Fundamental gaps remain in our understanding of how immunity to malaria develops. We used detailed clinical and entomological data from parallel cohort studies conducted across the malaria transmission spectrum in Uganda to quantify the development of immunity against symptomatic P. falciparum as a function of age and transmission intensity. We focus on: anti-parasite immunity (i.e; ability to control parasite densities) and anti-disease immunity (i.e; ability to tolerate higher parasite densities without fever). Our findings suggest a strong effect of age on both types of immunity, not explained by cumulative-exposure. They also show an independent effect of exposure, where children living in moderate/high transmission settings develop immunity faster as transmission increases. Surprisingly, children in the lowest transmission setting appear to develop immunity more efficiently than those living in moderate transmission settings. Anti-parasite and anti-disease immunity develop in parallel, reducing the probability of experiencing symptomatic malaria upon each subsequent P. falciparum infection.

Data availability

All the data used for these analyses as well as the R code used to reproduce the main study findings are available at https://github.com/isabelrodbar/immunity. Complete data from the 3 cohort studies are available at the CliEpiDB website (https://clinepidb.org/ce/app/record/dataset/DS_0ad509829e).

Article and author information

Author details

  1. Isabel Rodriguez-Barraquer

    Department of Medicine, University of California, San Francisco, San Francisco, United States
    For correspondence
    isabel.rodriguez-barraquer@ucsf.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6784-1021
  2. Emmanuel Arinaitwe

    Infectious Diseases Research Collaboration, Kampala, Uganda
    Competing interests
    The authors declare that no competing interests exist.
  3. Prasanna Jagannathan

    Department of Medicine, Stanford University, Stanford, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6305-758X
  4. Moses R Kamya

    Department of Medicine, Makerere University College of Health Sciences, Kampala, Uganda
    Competing interests
    The authors declare that no competing interests exist.
  5. Phillip J Rosenthal

    Department of Medicine, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. John Rek

    Infectious Diseases Research Collaboration, Kampala, Uganda
    Competing interests
    The authors declare that no competing interests exist.
  7. Grant Dorsey

    Department of Medicine, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. Joaniter Nankabirwa

    Infectious Diseases Resarch Collaboration, Kampala, Uganda
    Competing interests
    The authors declare that no competing interests exist.
  9. Sarah G Staedke

    London School of Hygiene and Tropical Medicine, London, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  10. Maxwell Kilama

    Infectious Diseases Research Collaboration, Kampala, Uganda
    Competing interests
    The authors declare that no competing interests exist.
  11. Chris Drakeley

    London School of Hygiene and Tropical Medicine, London, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4863-075X
  12. Isaac Ssewanyana

    Infectious Diseases Research Collaboration, Kampala, Uganda
    Competing interests
    The authors declare that no competing interests exist.
  13. David L Smith

    Institute of Health Metrics and Evaluation, University of Washington, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4367-3849
  14. Bryan Greenhouse

    Department of Medicine, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.

Funding

National Institutes of Health (2U19AI089674)

  • Isabel Rodriguez-Barraquer
  • Emmanuel Arinaitwe
  • Prasanna Jagannathan
  • Moses R Kamya
  • Phillip J Rosenthal
  • John Rek
  • Grant Dorsey
  • Joaniter Nankabirwa
  • Sarah G Staedke
  • Maxwell Kilama
  • Chris Drakeley
  • Isaac Ssewanyana
  • David L Smith
  • Bryan Greenhouse

Bill and Melinda Gates Foundation (OPP1110495)

  • David L Smith

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Human subjects: The study protocol was reviewed and approved by the Makerere University School of Medicine Research and Ethics Committee (Identification numbers 2011-149 and 2011-167, the Uganda National Council for Science and Technology, , the London School of Hygiene and Tropical Medicine Ethics Committee (Identification numbers 5943 and 5944), the Durham University School of Biological and Biomedical Sciences Ethics Committee (PRISM Entomology Uganda), and the University of California, San Francisco, Committee on Human Research (Identification numbers 11-05539 and 11-05995) and the Uganda National Council for Science and Technology (Identification numbers HS350 and HS-1019).. All parents/guardians were asked to provide written informed consent at the time of enrollment.

Copyright

© 2018, Rodriguez-Barraquer et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Download links

Share this article

https://doi.org/10.7554/eLife.35832

Further reading

    1. Epidemiology and Global Health
    Yuan Zhang, Dan Tang ... Xing Zhao
    Research Article

    Background:

    Biological aging exhibits heterogeneity across multi-organ systems. However, it remains unclear how is lifestyle associated with overall and organ-specific aging and which factors contribute most in Southwest China.

    Methods:

    This study involved 8396 participants who completed two surveys from the China Multi-Ethnic Cohort (CMEC) study. The healthy lifestyle index (HLI) was developed using five lifestyle factors: smoking, alcohol, diet, exercise, and sleep. The comprehensive and organ-specific biological ages (BAs) were calculated using the Klemera–Doubal method based on longitudinal clinical laboratory measurements, and validation were conducted to select BA reflecting related diseases. Fixed effects model was used to examine the associations between HLI or its components and the acceleration of validated BAs. We further evaluated the relative contribution of lifestyle components to comprehension and organ systems BAs using quantile G-computation.

    Results:

    About two-thirds of participants changed HLI scores between surveys. After validation, three organ-specific BAs (the cardiopulmonary, metabolic, and liver BAs) were identified as reflective of specific diseases and included in further analyses with the comprehensive BA. The health alterations in HLI showed a protective association with the acceleration of all BAs, with a mean shift of –0.19 (95% CI −0.34, –0.03) in the comprehensive BA acceleration. Diet and smoking were the major contributors to overall negative associations of five lifestyle factors, with the comprehensive BA and metabolic BA accounting for 24% and 55% respectively.

    Conclusions:

    Healthy lifestyle changes were inversely related to comprehensive and organ-specific biological aging in Southwest China, with diet and smoking contributing most to comprehensive and metabolic BA separately. Our findings highlight the potential of lifestyle interventions to decelerate aging and identify intervention targets to limit organ-specific aging in less-developed regions.

    Funding:

    This work was primarily supported by the National Natural Science Foundation of China (Grant No. 82273740) and Sichuan Science and Technology Program (Natural Science Foundation of Sichuan Province, Grant No. 2024NSFSC0552). The CMEC study was funded by the National Key Research and Development Program of China (Grant No. 2017YFC0907305, 2017YFC0907300). The sponsors had no role in the design, analysis, interpretation, or writing of this article.

    1. Epidemiology and Global Health
    2. Microbiology and Infectious Disease
    Bo Zheng, Bronner P Gonçalves ... Caoyi Xue
    Research Article

    Background:

    In many settings, a large fraction of the population has both been vaccinated against and infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Hence, quantifying the protection provided by post-infection vaccination has become critical for policy. We aimed to estimate the protective effect against SARS-CoV-2 reinfection of an additional vaccine dose after an initial Omicron variant infection.

    Methods:

    We report a retrospective, population-based cohort study performed in Shanghai, China, using electronic databases with information on SARS-CoV-2 infections and vaccination history. We compared reinfection incidence by post-infection vaccination status in individuals initially infected during the April–May 2022 Omicron variant surge in Shanghai and who had been vaccinated before that period. Cox models were fit to estimate adjusted hazard ratios (aHRs).

    Results:

    275,896 individuals were diagnosed with real-time polymerase chain reaction-confirmed SARS-CoV-2 infection in April–May 2022; 199,312/275,896 were included in analyses on the effect of a post-infection vaccine dose. Post-infection vaccination provided protection against reinfection (aHR 0.82; 95% confidence interval 0.79–0.85). For patients who had received one, two, or three vaccine doses before their first infection, hazard ratios for the post-infection vaccination effect were 0.84 (0.76–0.93), 0.87 (0.83–0.90), and 0.96 (0.74–1.23), respectively. Post-infection vaccination within 30 and 90 days before the second Omicron wave provided different degrees of protection (in aHR): 0.51 (0.44–0.58) and 0.67 (0.61–0.74), respectively. Moreover, for all vaccine types, but to different extents, a post-infection dose given to individuals who were fully vaccinated before first infection was protective.

    Conclusions:

    In previously vaccinated and infected individuals, an additional vaccine dose provided protection against Omicron variant reinfection. These observations will inform future policy decisions on COVID-19 vaccination in China and other countries.

    Funding:

    This study was funded the Key Discipline Program of Pudong New Area Health System (PWZxk2022-25), the Development and Application of Intelligent Epidemic Surveillance and AI Analysis System (21002411400), the Shanghai Public Health System Construction (GWVI-11.2-XD08), the Shanghai Health Commission Key Disciplines (GWVI-11.1-02), the Shanghai Health Commission Clinical Research Program (20214Y0020), the Shanghai Natural Science Foundation (22ZR1414600), and the Shanghai Young Health Talents Program (2022YQ076).