A molecular barcode and online tool to identify and map imported infection with Plasmodium vivax
<jats:title>Abstract</jats:title><jats:p>Imported cases present a considerable challenge to the elimination of malaria. Traditionally, patient travel history has been used to identify imported cases, but the long-latency liver stages confound this approach in <jats:italic>Pla...
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| Format: | Journal article |
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Cold Spring Harbor Laboratory
2019
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| _version_ | 1826261006633926656 |
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| author | Trimarsanto, H Amato, R Pearson, RD Sutanto, E Noviyanti, R Trianty, L Marfurt, J Pava, Z Echeverry, DF Lopera-Mesa, TM Montenegro, LM Tobón-Castaño, A Grigg, MJ Barber, B William, T Anstey, NM Getachew, S Petros, B Aseffa, A Assefa, A Rahim, AG Chau, NH Hien, TT Alam, MS Khan, WA Ley, B Thriemer, K Wangchuck, S Hamedi, Y Adam, I Liu, Y Gao, Q Sriprawat, K Ferreira, MU Barry, A Mueller, I Drury, E Goncalves, S Simpson, V Miotto, O Miles, A White, NJ Nosten, F Kwiatkowski, DP Price, RN Auburn, S |
| author_facet | Trimarsanto, H Amato, R Pearson, RD Sutanto, E Noviyanti, R Trianty, L Marfurt, J Pava, Z Echeverry, DF Lopera-Mesa, TM Montenegro, LM Tobón-Castaño, A Grigg, MJ Barber, B William, T Anstey, NM Getachew, S Petros, B Aseffa, A Assefa, A Rahim, AG Chau, NH Hien, TT Alam, MS Khan, WA Ley, B Thriemer, K Wangchuck, S Hamedi, Y Adam, I Liu, Y Gao, Q Sriprawat, K Ferreira, MU Barry, A Mueller, I Drury, E Goncalves, S Simpson, V Miotto, O Miles, A White, NJ Nosten, F Kwiatkowski, DP Price, RN Auburn, S |
| author_sort | Trimarsanto, H |
| collection | OXFORD |
| description | <jats:title>Abstract</jats:title><jats:p>Imported cases present a considerable challenge to the elimination of malaria. Traditionally, patient travel history has been used to identify imported cases, but the long-latency liver stages confound this approach in <jats:italic>Plasmodium vivax</jats:italic>. Molecular tools to identify and map imported cases offer a more robust approach, that can be combined with drug resistance and other surveillance markers in high-throughput, population-based genotyping frameworks. Using a machine learning approach incorporating hierarchical FST (HFST) and decision tree (DT) analysis applied to 831 <jats:italic>P. vivax</jats:italic> genomes from 20 countries, we identified a 28-Single Nucleotide Polymorphism (SNP) barcode with high capacity to predict the country of origin. The Matthews correlation coefficient (MCC), which provides a measure of the quality of the classifications, ranging from −1 (total disagreement) to 1 (perfect prediction), exceeded 0.9 in 15 countries in cross-validation evaluations. When combined with an existing 37-SNP <jats:italic>P. vivax</jats:italic> barcode, the 65-SNP panel exhibits MCC scores exceeding 0.9 in 17 countries with up to 30% missing data. As a secondary objective, several genes were identified with moderate MCC scores (median MCC range from 0.54-0.68), amenable as markers for rapid testing using low-throughput genotyping approaches. A likelihood-based classifier framework was established, that supports analysis of missing data and polyclonal infections. To facilitate investigator-lead analyses, the likelihood framework is provided as a web-based, open-access platform (vivaxGEN-geo) to support the analysis and interpretation of data produced either at the 28-SNP core or full 65-SNP barcode. These tools can be used by malaria control programs to identify the main reservoirs of infection so that resources can be focused to where they are needed most.</jats:p> |
| first_indexed | 2024-03-06T19:14:45Z |
| format | Journal article |
| id | oxford-uuid:17f70fbf-1010-485c-99aa-9c2cf41a7032 |
| institution | University of Oxford |
| last_indexed | 2024-03-06T19:14:45Z |
| publishDate | 2019 |
| publisher | Cold Spring Harbor Laboratory |
| record_format | dspace |
| spelling | oxford-uuid:17f70fbf-1010-485c-99aa-9c2cf41a70322022-03-26T10:40:41ZA molecular barcode and online tool to identify and map imported infection with Plasmodium vivaxJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:17f70fbf-1010-485c-99aa-9c2cf41a7032Symplectic Elements at OxfordCold Spring Harbor Laboratory2019Trimarsanto, HAmato, RPearson, RDSutanto, ENoviyanti, RTrianty, LMarfurt, JPava, ZEcheverry, DFLopera-Mesa, TMMontenegro, LMTobón-Castaño, AGrigg, MJBarber, BWilliam, TAnstey, NMGetachew, SPetros, BAseffa, AAssefa, ARahim, AGChau, NHHien, TTAlam, MSKhan, WALey, BThriemer, KWangchuck, SHamedi, YAdam, ILiu, YGao, QSriprawat, KFerreira, MUBarry, AMueller, IDrury, EGoncalves, SSimpson, VMiotto, OMiles, AWhite, NJNosten, FKwiatkowski, DPPrice, RNAuburn, S<jats:title>Abstract</jats:title><jats:p>Imported cases present a considerable challenge to the elimination of malaria. Traditionally, patient travel history has been used to identify imported cases, but the long-latency liver stages confound this approach in <jats:italic>Plasmodium vivax</jats:italic>. Molecular tools to identify and map imported cases offer a more robust approach, that can be combined with drug resistance and other surveillance markers in high-throughput, population-based genotyping frameworks. Using a machine learning approach incorporating hierarchical FST (HFST) and decision tree (DT) analysis applied to 831 <jats:italic>P. vivax</jats:italic> genomes from 20 countries, we identified a 28-Single Nucleotide Polymorphism (SNP) barcode with high capacity to predict the country of origin. The Matthews correlation coefficient (MCC), which provides a measure of the quality of the classifications, ranging from −1 (total disagreement) to 1 (perfect prediction), exceeded 0.9 in 15 countries in cross-validation evaluations. When combined with an existing 37-SNP <jats:italic>P. vivax</jats:italic> barcode, the 65-SNP panel exhibits MCC scores exceeding 0.9 in 17 countries with up to 30% missing data. As a secondary objective, several genes were identified with moderate MCC scores (median MCC range from 0.54-0.68), amenable as markers for rapid testing using low-throughput genotyping approaches. A likelihood-based classifier framework was established, that supports analysis of missing data and polyclonal infections. To facilitate investigator-lead analyses, the likelihood framework is provided as a web-based, open-access platform (vivaxGEN-geo) to support the analysis and interpretation of data produced either at the 28-SNP core or full 65-SNP barcode. These tools can be used by malaria control programs to identify the main reservoirs of infection so that resources can be focused to where they are needed most.</jats:p> |
| spellingShingle | Trimarsanto, H Amato, R Pearson, RD Sutanto, E Noviyanti, R Trianty, L Marfurt, J Pava, Z Echeverry, DF Lopera-Mesa, TM Montenegro, LM Tobón-Castaño, A Grigg, MJ Barber, B William, T Anstey, NM Getachew, S Petros, B Aseffa, A Assefa, A Rahim, AG Chau, NH Hien, TT Alam, MS Khan, WA Ley, B Thriemer, K Wangchuck, S Hamedi, Y Adam, I Liu, Y Gao, Q Sriprawat, K Ferreira, MU Barry, A Mueller, I Drury, E Goncalves, S Simpson, V Miotto, O Miles, A White, NJ Nosten, F Kwiatkowski, DP Price, RN Auburn, S A molecular barcode and online tool to identify and map imported infection with Plasmodium vivax |
| title | A molecular barcode and online tool to identify and map imported infection with Plasmodium vivax |
| title_full | A molecular barcode and online tool to identify and map imported infection with Plasmodium vivax |
| title_fullStr | A molecular barcode and online tool to identify and map imported infection with Plasmodium vivax |
| title_full_unstemmed | A molecular barcode and online tool to identify and map imported infection with Plasmodium vivax |
| title_short | A molecular barcode and online tool to identify and map imported infection with Plasmodium vivax |
| title_sort | molecular barcode and online tool to identify and map imported infection with plasmodium vivax |
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