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Exploration of Plasmodium vivax transmission dynamics and recurrent infections in the Peruvian Amazon using whole genome sequencing

Overview of attention for article published in Genome Medicine, July 2018
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  • Good Attention Score compared to outputs of the same age (69th percentile)

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Title
Exploration of Plasmodium vivax transmission dynamics and recurrent infections in the Peruvian Amazon using whole genome sequencing
Published in
Genome Medicine, July 2018
DOI 10.1186/s13073-018-0563-0
Pubmed ID
Authors

Annie N. Cowell, Hugo O. Valdivia, Danett K. Bishop, Elizabeth A. Winzeler

Abstract

Plasmodium vivax poses a significant challenge to malaria elimination due to its ability to cause relapsed infections from reactivation of dormant liver parasites called hypnozoites. We analyzed 69 P. vivax whole genome sequences obtained from subjects residing in three different villages along the Peruvian Amazon. This included 23 paired P. vivax samples from subjects who experienced recurrent P. vivax parasitemia following observed treatment with chloroquine and primaquine. Genomic DNA was extracted from whole blood samples collected from subjects. P. vivax DNA was enriched using selective whole genome amplification and whole genome sequencing. We used single nucleotide polymorphisms (SNPs) from the core P. vivax genome to determine characteristics of the parasite population using discriminant analysis of principal components, maximum likelihood estimation of individual ancestries, and phylogenetic analysis. We estimated the relatedness of the paired samples by calculating the number of segregating sites and using a hidden Markov model approach to estimate identity by descent. We present a comprehensive dataset of population genetics of Plasmodium vivax in the Peruvian Amazonian. We define the parasite population structure in this region and demonstrate a novel method for distinguishing homologous relapses from reinfections or heterologous relapses with improved accuracy. The parasite population in this area was quite diverse with an estimated five subpopulations and evidence of a highly heterogeneous ancestry of some of the isolates, similar to previous analyses of P. vivax in this region. Pairwise comparison of recurrent infections determined that there were 12 homologous relapses and 3 likely heterologous relapses with highly related parasites. To the best of our knowledge, this is the first large-scale study to evaluate recurrent P. vivax infections using whole genome sequencing. Whole genome sequencing is a high-resolution tool that can identify P. vivax homologous relapses with increased sensitivity, while also providing data about drug resistance and parasite population genetics. This information is important for evaluating the efficacy of known and novel antirelapse medications in endemic areas and thus advancing the campaign to eliminate malaria.

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The data shown below were collected from the profiles of 11 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 73 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 73 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 21%
Student > Ph. D. Student 10 14%
Student > Bachelor 8 11%
Student > Master 7 10%
Professor 4 5%
Other 9 12%
Unknown 20 27%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 20 27%
Medicine and Dentistry 11 15%
Agricultural and Biological Sciences 7 10%
Veterinary Science and Veterinary Medicine 3 4%
Computer Science 3 4%
Other 4 5%
Unknown 25 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 September 2018.
All research outputs
#5,949,230
of 23,577,654 outputs
Outputs from Genome Medicine
#1,014
of 1,466 outputs
Outputs of similar age
#100,044
of 329,054 outputs
Outputs of similar age from Genome Medicine
#22
of 27 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 1,466 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.9. This one is in the 30th percentile – i.e., 30% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 329,054 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.
We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.