Modelling primaquine-induced haemolysis in G6PD deficiency

  1. James Watson  Is a corresponding author
  2. Walter RJ Taylor
  3. Didier Menard
  4. Sim Kheng
  5. Nicholas J White
  1. Mahidol University, Thailand
  2. Institut Pasteur du Cambodge, Cambodia
  3. National Center for Parasitology, Entomology and Malaria Control, Cambodia

Abstract

Primaquine is the only drug available to prevent relapse in vivax malaria. The main adverse effect of primaquine is erythrocyte age and dose dependent acute haemolytic anaemia in individuals with glucose-6-phosphate dehydrogenase deficiency (G6PDd). As testing for G6PDd is often unavailable this limits the use of primaquine for radical cure. A compartmental model of the dynamics of red blood cell production and destruction was designed to characterise primaquine-induced haemolysis using a holistic Bayesian analysis of all published data and was used to predict a safer alternative to the currently recommended once weekly 0.75mg/kg regimen for G6PDd. The model suggests that a step-wise increase in daily administered primaquine dose would be relatively safe in G6PDd. If this is confirmed then were this regimen to be recommended for radical cure patients would not require testing for G6PDd in areas where G6PD Viangchan or milder variants are prevalent.

Article and author information

Author details

  1. James Watson

    Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
    For correspondence
    jwatowatson@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5524-0325
  2. Walter RJ Taylor

    Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
    Competing interests
    The authors declare that no competing interests exist.
  3. Didier Menard

    Unité d'Epidémiologie Moléculaire du Paludisme, Institut Pasteur du Cambodge, Phnom Penh, Cambodia
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1357-4495
  4. Sim Kheng

    National Center for Parasitology, Entomology and Malaria Control, Phnom Penh, Cambodia
    Competing interests
    The authors declare that no competing interests exist.
  5. Nicholas J White

    Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1897-1978

Funding

Wellcome

  • James Watson
  • Walter RJ Taylor
  • Nicholas J White

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

Reviewing Editor

  1. Prabhat Jha, Saint Michael's Hospital, Canada

Version history

  1. Received: November 10, 2016
  2. Accepted: January 31, 2017
  3. Accepted Manuscript published: February 3, 2017 (version 1)
  4. Version of Record published: February 28, 2017 (version 2)

Copyright

© 2017, Watson 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.

Metrics

  • 1,836
    views
  • 318
    downloads
  • 39
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. James Watson
  2. Walter RJ Taylor
  3. Didier Menard
  4. Sim Kheng
  5. Nicholas J White
(2017)
Modelling primaquine-induced haemolysis in G6PD deficiency
eLife 6:e23061.
https://doi.org/10.7554/eLife.23061

Share this article

https://doi.org/10.7554/eLife.23061

Further reading

    1. Computational and Systems Biology
    2. Epidemiology and Global Health
    Javier I Ottaviani, Virag Sagi-Kiss ... Gunter GC Kuhnle
    Research Article

    The chemical composition of foods is complex, variable, and dependent on many factors. This has a major impact on nutrition research as it foundationally affects our ability to adequately assess the actual intake of nutrients and other compounds. In spite of this, accurate data on nutrient intake are key for investigating the associations and causal relationships between intake, health, and disease risk at the service of developing evidence-based dietary guidance that enables improvements in population health. Here, we exemplify the importance of this challenge by investigating the impact of food content variability on nutrition research using three bioactives as model: flavan-3-ols, (–)-epicatechin, and nitrate. Our results show that common approaches aimed at addressing the high compositional variability of even the same foods impede the accurate assessment of nutrient intake generally. This suggests that the results of many nutrition studies using food composition data are potentially unreliable and carry greater limitations than commonly appreciated, consequently resulting in dietary recommendations with significant limitations and unreliable impact on public health. Thus, current challenges related to nutrient intake assessments need to be addressed and mitigated by the development of improved dietary assessment methods involving the use of nutritional biomarkers.

    1. Cancer Biology
    2. Computational and Systems Biology
    Marie Breeur, George Stepaniants ... Vivian Viallon
    Research Article

    Untargeted metabolomic profiling through liquid chromatography-mass spectrometry (LC-MS) measures a vast array of metabolites within biospecimens, advancing drug development, disease diagnosis, and risk prediction. However, the low throughput of LC-MS poses a major challenge for biomarker discovery, annotation, and experimental comparison, necessitating the merging of multiple datasets. Current data pooling methods encounter practical limitations due to their vulnerability to data variations and hyperparameter dependence. Here, we introduce GromovMatcher, a flexible and user-friendly algorithm that automatically combines LC-MS datasets using optimal transport. By capitalizing on feature intensity correlation structures, GromovMatcher delivers superior alignment accuracy and robustness compared to existing approaches. This algorithm scales to thousands of features requiring minimal hyperparameter tuning. Manually curated datasets for validating alignment algorithms are limited in the field of untargeted metabolomics, and hence we develop a dataset split procedure to generate pairs of validation datasets to test the alignments produced by GromovMatcher and other methods. Applying our method to experimental patient studies of liver and pancreatic cancer, we discover shared metabolic features related to patient alcohol intake, demonstrating how GromovMatcher facilitates the search for biomarkers associated with lifestyle risk factors linked to several cancer types.