Plasmodium falciparum genomic surveillance reveals spatial and temporal trends, association of genetic and physical distance, and household clustering.

Autor: Sy M; Laboratory of Parasitology and Mycology, Cheikh Anta Diop University, Aristide le Dantec Hospital, Dakar, Senegal., Deme AB; Laboratory of Parasitology and Mycology, Cheikh Anta Diop University, Aristide le Dantec Hospital, Dakar, Senegal.; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA., Warren JL; Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA., Early A; Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA, USA.; The Broad Institute of MIT and Harvard, Cambridge, MA, USA., Schaffner S; Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA, USA.; The Broad Institute of MIT and Harvard, Cambridge, MA, USA., Daniels RF; Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA, USA., Dieye B; Laboratory of Parasitology and Mycology, Cheikh Anta Diop University, Aristide le Dantec Hospital, Dakar, Senegal., Ndiaye IM; Laboratory of Parasitology and Mycology, Cheikh Anta Diop University, Aristide le Dantec Hospital, Dakar, Senegal., Diedhiou Y; Laboratory of Parasitology and Mycology, Cheikh Anta Diop University, Aristide le Dantec Hospital, Dakar, Senegal., Mbaye AM; Laboratory of Parasitology and Mycology, Cheikh Anta Diop University, Aristide le Dantec Hospital, Dakar, Senegal., Volkman SK; Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA, USA.; The Broad Institute of MIT and Harvard, Cambridge, MA, USA.; College of Natural, Behavioral and Health Sciences, Simmons University, Boston, MA, USA., Hartl DL; Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA, USA.; The Broad Institute of MIT and Harvard, Cambridge, MA, USA.; 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.; The Broad Institute of MIT and Harvard, Cambridge, MA, USA., Ndiaye D; Laboratory of Parasitology and Mycology, Cheikh Anta Diop University, Aristide le Dantec Hospital, Dakar, Senegal., Bei AK; Laboratory of Parasitology and Mycology, Cheikh Anta Diop University, Aristide le Dantec Hospital, Dakar, Senegal. amy.bei@yale.edu.; Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA, USA. amy.bei@yale.edu.; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA. amy.bei@yale.edu.
Jazyk: angličtina
Zdroj: Scientific reports [Sci Rep] 2022 Jan 18; Vol. 12 (1), pp. 938. Date of Electronic Publication: 2022 Jan 18.
DOI: 10.1038/s41598-021-04572-2
Abstrakt: Molecular epidemiology using genomic data can help identify relationships between malaria parasite population structure, malaria transmission intensity, and ultimately help generate actionable data to assess the effectiveness of malaria control strategies. Genomic data, coupled with geographic information systems data, can further identify clusters or hotspots of malaria transmission, parasite genetic and spatial connectivity, and parasite movement by human or mosquito mobility over time and space. In this study, we performed longitudinal genomic surveillance in a cohort of 70 participants over four years from different neighborhoods and households in Thiès, Senegal-a region of exceptionally low malaria transmission (entomological inoculation rate less than 1). Genetic identity (identity by state, IBS) was established using a 24-single nucleotide polymorphism molecular barcode, identity by descent was calculated from whole genome sequence data, and a hierarchical Bayesian regression model was used to establish genetic and spatial relationships. Our results show clustering of genetically similar parasites within households and a decline in genetic similarity of parasites with increasing distance. One household showed extremely high diversity and warrants further investigation as to the source of these diverse genetic types. This study illustrates the utility of genomic data with traditional epidemiological approaches for surveillance and detection of trends and patterns in malaria transmission not only by neighborhood but also by household. This approach can be implemented regionally and countrywide to strengthen and support malaria control and elimination efforts.
(© 2022. The Author(s).)
Databáze: MEDLINE
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