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Evaluating the performance of Plasmodium falciparum genetic metrics for inferring National Malaria Control Programme reported incidence in Senegal.

التفاصيل البيبلوغرافية
العنوان: Evaluating the performance of Plasmodium falciparum genetic metrics for inferring National Malaria Control Programme reported incidence in Senegal.
المؤلفون: Wong W; Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA, USA., Schaffner SF; Infectious Disease and Microbiome Program, The Broad Institute, Cambridge, MA, USA., Thwing J; Malaria Branch, Division of Parasitic Diseases and Malaria, Global Health Center, Centers for Disease Control and Prevention, Atlanta, GA, USA., Seck MC; Centre International de recherche, de formation en Genomique Appliquee et de Surveillance Sanitaire (CIGASS), Dakar, Senegal., Gomis J; Centre International de recherche, de formation en Genomique Appliquee et de Surveillance Sanitaire (CIGASS), Dakar, Senegal., Diedhiou Y; Centre International de recherche, de formation en Genomique Appliquee et de Surveillance Sanitaire (CIGASS), Dakar, Senegal., Sy N; Section de Lutte Anti-Parasitaire (SLAP) Clinic, Thies, Senegal., Ndiop M; Programme National de Lutte contre le Paludisme (PNLP), Dakar, Senegal., Ba F; Programme National de Lutte contre le Paludisme (PNLP), Dakar, Senegal., Diallo I; Programme National de Lutte contre le Paludisme (PNLP), Dakar, Senegal., Sene D; Programme National de Lutte contre le Paludisme (PNLP), Dakar, Senegal., Diallo MA; Centre International de recherche, de formation en Genomique Appliquee et de Surveillance Sanitaire (CIGASS), Dakar, Senegal., Ndiaye YD; Centre International de recherche, de formation en Genomique Appliquee et de Surveillance Sanitaire (CIGASS), Dakar, Senegal., Sy M; Centre International de recherche, de formation en Genomique Appliquee et de Surveillance Sanitaire (CIGASS), Dakar, Senegal., Sene A; Centre International de recherche, de formation en Genomique Appliquee et de Surveillance Sanitaire (CIGASS), Dakar, Senegal., Sow D; Centre International de recherche, de formation en Genomique Appliquee et de Surveillance Sanitaire (CIGASS), Dakar, Senegal., Dieye B; Centre International de recherche, de formation en Genomique Appliquee et de Surveillance Sanitaire (CIGASS), Dakar, Senegal., Tine A; Centre International de recherche, de formation en Genomique Appliquee et de Surveillance Sanitaire (CIGASS), Dakar, Senegal., Ribado J; Institute for Disease Modeling at the Bill and Melinda Gates Foundation, Seattle, WA, USA., Suresh J; Institute for Disease Modeling at the Bill and Melinda Gates Foundation, Seattle, WA, USA., Lee A; Institute for Disease Modeling at the Bill and Melinda Gates Foundation, Seattle, WA, USA., Battle KE; Institute for Disease Modeling at the Bill and Melinda Gates Foundation, Seattle, WA, USA., Proctor JL; Institute for Disease Modeling at the Bill and Melinda Gates Foundation, Seattle, WA, USA., Bever CA; Institute for Disease Modeling at the Bill and Melinda Gates Foundation, Seattle, WA, USA., MacInnis B; Infectious Disease and Microbiome Program, The Broad Institute, Cambridge, MA, USA., Ndiaye D; Centre International de recherche, de formation en Genomique Appliquee et de Surveillance Sanitaire (CIGASS), Dakar, Senegal., Hartl DL; Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA., Wirth DF; Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA, USA.; Infectious Disease and Microbiome Program, The Broad Institute, Cambridge, MA, USA., Volkman SK; Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA, USA. svolkman@hsph.harvard.edu.; Infectious Disease and Microbiome Program, The Broad Institute, Cambridge, MA, USA. svolkman@hsph.harvard.edu.; College of Natural, Behavioral, and Health Sciences, Simmons University, Boston, MA, USA. svolkman@hsph.harvard.edu.
المصدر: Malaria journal [Malar J] 2024 Mar 05; Vol. 23 (1), pp. 68. Date of Electronic Publication: 2024 Mar 05.
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: BioMed Central Country of Publication: England NLM ID: 101139802 Publication Model: Electronic Cited Medium: Internet ISSN: 1475-2875 (Electronic) Linking ISSN: 14752875 NLM ISO Abbreviation: Malar J Subsets: MEDLINE
أسماء مطبوعة: Original Publication: London : BioMed Central, [2002-
مواضيع طبية MeSH: Superinfection* , Malaria*, Humans ; Senegal/epidemiology ; Incidence ; Plasmodium falciparum/genetics
مستخلص: Background: Genetic surveillance of the Plasmodium falciparum parasite shows great promise for helping National Malaria Control Programmes (NMCPs) assess parasite transmission. Genetic metrics such as the frequency of polygenomic (multiple strain) infections, genetic clones, and the complexity of infection (COI, number of strains per infection) are correlated with transmission intensity. However, despite these correlations, it is unclear whether genetic metrics alone are sufficient to estimate clinical incidence.
Methods: This study examined parasites from 3147 clinical infections sampled between the years 2012-2020 through passive case detection (PCD) across 16 clinic sites spread throughout Senegal. Samples were genotyped with a 24 single nucleotide polymorphism (SNP) molecular barcode that detects parasite strains, distinguishes polygenomic (multiple strain) from monogenomic (single strain) infections, and identifies clonal infections. To determine whether genetic signals can predict incidence, a series of Poisson generalized linear mixed-effects models were constructed to predict the incidence level at each clinical site from a set of genetic metrics designed to measure parasite clonality, superinfection, and co-transmission rates.
Results: Model-predicted incidence was compared with the reported standard incidence data determined by the NMCP for each clinic and found that parasite genetic metrics generally correlated with reported incidence, with departures from expected values at very low annual incidence (< 10/1000/annual [‰]).
Conclusions: When transmission is greater than 10 cases per 1000 annual parasite incidence (annual incidence > 10‰), parasite genetics can be used to accurately infer incidence and is consistent with superinfection-based hypotheses of malaria transmission. When transmission was < 10‰, many of the correlations between parasite genetics and incidence were reversed, which may reflect the disproportionate impact of importation and focal transmission on parasite genetics when local transmission levels are low.
(© 2024. The Author(s).)
التعليقات: Update of: Res Sq. 2023 Nov 01;:. (PMID: 37961451)
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معلومات مُعتمدة: R21 AI141843 United States AI NIAID NIH HHS; 5R21AI141843-02 United States NH NIH HHS
تواريخ الأحداث: Date Created: 20240305 Date Completed: 20240307 Latest Revision: 20240318
رمز التحديث: 20240318
مُعرف محوري في PubMed: PMC10916253
DOI: 10.1186/s12936-024-04897-z
PMID: 38443939
قاعدة البيانات: MEDLINE
الوصف
تدمد:1475-2875
DOI:10.1186/s12936-024-04897-z