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Selection of artemisinin partial resistance Kelch13 mutations in Uganda in 2016-22 was at a rate comparable to that seen previously in South-East Asia.
Meier-Scherling, Cecile P G; Watson, Oliver J; Asua, Victor; Ghinai, Isaac; Katairo, Thomas; Garg, Shreeya; Conrad, Melissa; Rosenthal, Philip J; Okell, Lucy C; Bailey, Jeffrey A.
Afiliação
  • Meier-Scherling CPG; Center for Computational Molecular Biology, Brown University, Providence, RI, USA.
  • Watson OJ; Medical Research Council Centre for Global Infectious Disease Analysis, Imperial College London, London, UK.
  • Asua V; Infectious Diseases Research Collaboration, Kampala, Uganda.
  • Ghinai I; Oxford University, Oxford, UK.
  • Katairo T; Infectious Diseases Research Collaboration, Kampala, Uganda.
  • Garg S; Department of Medicine, University of California San Francisco, San Francisco, CA, USA.
  • Conrad M; Department of Medicine, University of California San Francisco, San Francisco, CA, USA.
  • Rosenthal PJ; Department of Medicine, University of California San Francisco, San Francisco, CA, USA.
  • Okell LC; Medical Research Council Centre for Global Infectious Disease Analysis, Imperial College London, London, UK.
  • Bailey JA; Center for Computational Molecular Biology, Brown University, Providence, RI, USA.
medRxiv ; 2024 Feb 04.
Article em En | MEDLINE | ID: mdl-38352505
ABSTRACT

Background:

Artemisinin partial resistance, mediated by mutations in the Plasmodium falciparum Kelch13 protein (K13), rapidly spread in South-East Asia (SEA), undermining antimalarial efficacies of artemisinin-based combination therapies (ACT). Validated K13 mutations have recently arisen in Africa, but rates of increase are not well characterized.

Methods:

We investigated K13 mutation prevalence at 16 sites in Uganda (2016-2022, 6586 samples), and five sites in SEA (2003-2018, 5465 samples) by calculating selection coefficients using Bayesian mixed-effect linear models. We then tested whether SEA K13 mutation prevalence could have been forecast accurately using up to the first five years of available data and forecast future K13 mutation prevalence in Uganda.

Findings:

The selection coefficient for the prevalence of relevant K13 mutations (441L, 469F/Y, 561H, 675V) was estimated at s=0·383 (95% CrI 0·247 - 0·528) per year, a 38% relative prevalence increase. Selection coefficients across Uganda were s=0·968 (0·463 - 1·569) for 441L, s=0·153 (-0·445 - 0·727) for 469F, s=0·222 (-0·011 - 0·398) for 469Y, and s=0·152 (-0·023 - 0·312) for 675V. In SEA, the selection coefficient was s=-0·005 (-0·852 - 0·814) for 539T, s=0·574 (-0·092 - 1·201) for 580Y, and s=0·308 (0·089 - 0·536) for all validated K13 mutations. Forecast prevalences for Uganda assuming constant selection neared fixation (>95% prevalence) within a decade (2028-2033) for combined K13 mutations.

Interpretation:

The selection of K13 mutations in Uganda was at a comparable rate to that observed in SEA, suggesting K13 mutations may continue to increase quickly in Uganda.

Funding:

NIH R01AI156267, R01AI075045, and R01AI089674.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2024 Tipo de documento: Article