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Population-based genomic study of Plasmodium vivax malaria in seven Brazilian states and across South America

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LANCET REGIONAL HEALTH-AMERICAS
卷 18, 期 -, 页码 -

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ELSEVIER
DOI: 10.1016/j.lana.2022.100420

关键词

Malaria; Plasmodium; Plasmodium vivax; Non-falciparum malaria; Brazil; South America; Whole genome sequencing; Population genetics; Vector-borne diseases; Drug resistance; Genomics

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Through whole genome sequencing of P. vivax isolates from 7 Brazilian states, researchers have identified distinct genetic diversity of P. vivax parasites in Brazil compared to other global regions. They have also discovered mutations in genes under selective pressure linked to antimalarial drugs and mosquito vectors. This study provides important insights into the population structure of P. vivax in Brazil and can inform future research and control measures.
Background Brazil is a unique and understudied setting for malaria, with complex foci of transmission associated with human and environmental conditions. An understanding of the population genomic diversity of P. vivax parasites across Brazil can support malaria control strategies.Methods Through whole genome sequencing of P. vivax isolates across 7 Brazilian states, we use population genomic approaches to compare genetic diversity within country (n = 123), continent (6 countries, n = 315) and globally (26 countries, n = 885).Findings We confirm that South American isolates are distinct, have more ancestral populations than the other global regions, with differentiating mutations in genes under selective pressure linked to antimalarial drugs (pvmdr1, pvdhfr-ts) and mosquito vectors (pvcrmp3, pvP45/48, pvP47). We demonstrate Brazil as a distinct parasite population, with signals of selection including ABC transporter (PvABCI3) and PHIST exported proteins.Interpretation Brazil has a complex population structure, with evidence of P. simium infections and Amazonian parasites separating into multiple clusters. Overall, our work provides the first Brazil-wide analysis of P. vivax population structure and identifies important mutations, which can inform future research and control measures.Funding AI is funded by an MRC LiD PhD studentship. TGC is funded by the Medical Research Council (Grant no. MR/M01360X/1, MR/N010469/1, MR/R025576/1, MR/R020973/1 and MR/X005895/1). SC is funded by Medical Research Council UK grants (MR/M01360X/1, MR/R025576/1, MR/R020973/1 and MR/X005895/1) and Blooms-bury SET (ref. CCF17-7779). FN is funded by The Shloklo Malaria Research Unit -part of the Mahidol Oxford Research Unit, supported by the Wellcome Trust (Grant no. 220211). ARSB is funded by Sao Paulo Research Foundation -FAPESP (Grant no. 2002/09546-1). RLDM is funded by Brazilian National Council for Scientific and Technological Development -CNPq (Grant no. 302353/2003-8 and 471605/2011-5); CRFM is funded by FAPESP (Grant no. 2020/06747-4) and CNPq (Grant no. 302917/2019-5 and 408636/2018-1); JGD is funded by FAPESP fellowships (2016/13465-0 and 2019/12068-5) and CNPq (Grant no. 409216/2018-6).Copyright & COPY; 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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