Evidence map›Paper›PMID 40112841›Full record

ArticleThe Lancet. Microbe2025

Selection of Plasmodium falciparum kelch13 mutations in Uganda in comparison with southeast Asia: a modelling study.

Cecile P G Meier-Scherling, Oliver J Watson, Victor Asua, Isaac Ghinai, Thomas Katairo, Shreeya Garg, Melissa D Conrad, Philip J Rosenthal, Lucy C Okell, Jeffrey A Bailey

Abstract readComparative Study
In one paragraph

Article in The Lancet. Microbe, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Mapping the prevalence of molecular markers ofmedRxiv : the preprint server for health sciences · 2025
    Article
  7. Mapping Plasmodium falciparum mutations in Africa: A critical review of emerging drug resistance and implications for malaria control.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2025
    Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Cecile P G Meier-ScherlingCenter for Computational Molecular Biology, Brown University, Providence, RI, USA.
Oliver J WatsonMedical Research Council Centre for Global Infectious Disease Analysis, Imperial College London, London, UK.
Victor AsuaInfectious Diseases Research Collaboration, Kampala, Uganda; Institute of Tropical Medicine, University of Tübingen, Tübingen, Germany.
Isaac GhinaiBig Data Institute, University of Oxford, Oxford, UK.
Thomas KatairoInfectious Diseases Research Collaboration, Kampala, Uganda.
Shreeya GargDepartment of Medicine, University of California San Francisco, San Francisco, CA, USA.
Melissa D ConradDepartment of Medicine, University of California San Francisco, San Francisco, CA, USA.
Philip J RosenthalDepartment of Medicine, University of California San Francisco, San Francisco, CA, USA.
Lucy C OkellMedical Research Council Centre for Global Infectious Disease Analysis, Imperial College London, London, UK.
Jeffrey A BaileyCenter for Computational Molecular Biology, Brown University, Providence, RI, USA; Department of Pathology and Laboratory Medicine, Warren Alpert Medical School, Brown University, Providence, RI, USA. Electronic address: jeffrey_bailey@brown.edu.

Funding

Transmission ProjectU19AI089674 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Joaniter Immaculate Nankabirwa · 2010 to 2026
$29.3M
Resistance of Malaria Parasites to Artemisinin-Based TherapiesR01AI075045 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI ROSENTHAL, PHILIP JON · 2009 to 2024
$8.4M
Tracking the flow of malaria parasites and drug resistance within the DRC and across its bordersR01AI139520 · NIAID · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI BAILEY, JEFFREY A. · 2018 to 2023
$3.6M
Artemisinin Resistance in Africa: its emergence and evolution in RwandaR01AI156267 · NIAID · BROWN UNIVERSITY · PI BAILEY, JEFFREY A., JULIANO, JONATHAN J · 2021 to 2024
$3.0M
Surveillance to track and characterize antimalarial resistance trends in Ugandan Plasmodium falciparum parasites (STARTUP)R01AI173557 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Melissa D Conrad · 2023 to 2026
$2.9M
Resistance of Malaria Parasites to Artemisinin-Based Combination TherapiesR56AI075045 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI ROSENTHAL, PHILIP JON · 2008 to 2008
$618k
NIAID NIH HHS R01 AI075045NIAID NIH HHS R01 AI139520NIAID NIH HHS R01 AI156267NIAID NIH HHS R01 AI173557NIAID NIH HHS R56 AI075045NIAID NIH HHS U19 AI089674
6 · The paper itself

Abstract

backgroundArtemisinin partial resistance, mediated by mutations in the Plasmodium falciparum kelch13 gene (k13), rapidly spread in southeast Asia, undermining the antimalarial effectiveness of artemisinin-based combination therapies. k13 mutations have also arisen in Africa, but their rates of increase are not well characterised. We aimed to quantify the selection of k13 mutations in Africa and compare the selection with that in southeast Asia.

methodsIn this modelling study, we investigated k13 mutation allele frequency at 16 sites in Uganda (2016-22) and five sites in southeast Asia (in Cambodia, Thailand, and Viet Nam; 2003-14). The Ugandan data were obtained from annual clinical surveillance studies and the southeast Asian data were obtained from the MalariaGEN Pf7 dataset. We investigated five validated and candidate k13 mutations: Pro441Leu, Cys469Phe, Cys469Tyr, Arg561His, and Ala675Val. We calculated annual selection coefficients using Bayesian mixed-effect linear models. We then tested whether the k13 mutation allele frequency in southeast Asia could have been forecast accurately using up to the first 5 years of available data and forecast future k13 mutation allele frequency in Uganda.

findingsWe used data from 7564 samples from Uganda and 6568 samples from southeast Asia. The annual selection coefficient of evaluable k13 mutations (Pro441Leu, Cys469Phe/Tyr, Arg561His, and Ala675Val) across all sites was estimated at 0·381 (95% credible interval 0·298 to 0·472) per year, a 38% increase in relative allele frequency. Selection coefficients across Uganda were 0·494 (-0·462 to 1·410) for Pro441Leu, 0·324 (-0·629 to 1·150) for Cys469Phe, 0·383 (0·207 to 0·591) for Cys469Tyr, and 0·237 (0·087 to 0·403) for Ala675Val. In southeast Asia, the selection coefficients were 0·627 (-0·088 to 1·312) for Cys580Tyr, 0·224 (-0·903 to 1·397) for Arg539Thr, and 0·330 (-0·075 to 0·683) for all validated k13 mutations. Compared with out-of-sample data, the forecasts for southeast Asia underestimated mutation allele frequency and were of variable accuracy. Overall, forecast allele frequencies for Uganda, assuming constant selection, neared fixation (>0·95 allele frequency) within a decade (between 2031 and 2033) for combined k13 mutations.

interpretationk13 mutation selection in Uganda was similar to that observed in southeast Asia, suggesting that frequencies of k13 mutations will continue to increase quickly in Uganda. These commensurate levels of selection indicate a high potential for rapid transmission across other parts of Africa, underscoring the urgent need for treatments and policies to mitigate the spread and impact of k13 mutations.

fundingUS National Institutes of Health.

Indexed as

Drug ResistanceMalaria, FalciparumMutationPlasmodium falciparumProtozoan ProteinsSelection, GeneticAntimalarialsArtemisininsAsia, SoutheasternGene FrequencyHumansUgandaAntimalarialsartemisininArtemisininsProtozoan Proteins

Identifiers

PMID40112841
PMCPMC12128186

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.