A molecular barcode and web-based data analysis tool to identify imported Plasmodium vivax malaria

Hidayat Trimarsanto; Roberto Amato; Richard D Pearson; Edwin Sutanto; Rintis Noviyanti; Leily Trianty; Jutta Marfurt; Zuleima Pava; Diego F Echeverry; Tatiana M Lopera-Mesa; Lidia M Montenegro; Alberto Tobón-Castaño; Matthew J Grigg; Bridget Barber; Timothy William; Nicholas M Anstey; Sisay Getachew; Beyene Petros; Abraham Aseffa; Ashenafi Assefa; Awab G Rahim; Nguyen H Chau; Tran T Hien; Mohammad S Alam; Wasif A Khan; Benedikt Ley; Kamala Thriemer; Sonam Wangchuck; Yaghoob Hamedi; Ishag Adam; Yaobao Liu; Qi Gao; Kanlaya Sriprawat; Marcelo U Ferreira; Moses Laman; Alyssa Barry; Ivo Mueller; Marcus V G Lacerda; Alejandro Llanos-Cuentas; Srivicha Krudsood; Chanthap Lon; Rezika Mohammed; Daniel Yilma; Dhelio B Pereira; Fe E J Espino; Cindy S Chu; Iván D Vélez; Chayadol Namaik-Larp; Maria F Villegas; Justin A Green; Gavin Koh; Julian C Rayner; Eleanor Drury; Sónia Gonçalves; Victoria Simpson; Olivo Miotto; Alistair Miles; Nicholas J White; Francois Nosten; Dominic P Kwiatkowski; Ric N Price; Sarah Auburn

doi:10.1038/s42003-022-04352-2

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A molecular barcode and web-based data analysis tool to identify imported Plasmodium vivax malaria

Journal article

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Peer reviewed

A molecular barcode and web-based data analysis tool to identify imported Plasmodium vivax malaria

Hidayat Trimarsanto, Roberto Amato, Richard D Pearson, Edwin Sutanto, Rintis Noviyanti, Leily Trianty, Jutta Marfurt, Zuleima Pava, Diego F Echeverry, Tatiana M Lopera-Mesa, …

Communications biology, Vol.5(1), pp.1411-1411

23/12/2022

DOI: https://doi.org/10.1038/s42003-022-04352-2

PMID: 36564617

Abstract

Humans

Internet

Likelihood Functions

Malaria

Malaria, Vivax - diagnosis

Malaria, Vivax - genetics

Plasmodium vivax - genetics

Traditionally, patient travel history has been used to distinguish imported from autochthonous malaria cases, but the dormant liver stages of Plasmodium vivax confound this approach. Molecular tools offer an alternative method to identify, and map imported cases. Using machine learning approaches incorporating hierarchical fixation index and decision tree analyses applied to 799 P. vivax genomes from 21 countries, we identified 33-SNP, 50-SNP and 55-SNP barcodes (GEO33, GEO50 and GEO55), with high capacity to predict the infection's country of origin. The Matthews correlation coefficient (MCC) for an existing, commonly applied 38-SNP barcode (BR38) exceeded 0.80 in 62% countries. The GEO panels outperformed BR38, with median MCCs > 0.80 in 90% countries at GEO33, and 95% at GEO50 and GEO55. An online, open-access, likelihood-based classifier framework was established to support data analysis (vivaxGEN-geo). The SNP selection and classifier methods can be readily amended for other use cases to support malaria control programs.

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Title: A molecular barcode and web-based data analysis tool to identify imported Plasmodium vivax malaria
Creators - without role: Hidayat Trimarsanto - Charles Darwin University
Roberto Amato - Wellcome Sanger Institute
Richard D Pearson - Wellcome Sanger Institute
Edwin Sutanto - Eijkman Institute for Molecular Biology
Rintis Noviyanti - Eijkman Institute for Molecular Biology
Leily Trianty - Eijkman Institute for Molecular Biology
Jutta Marfurt - Charles Darwin University
Zuleima Pava - Charles Darwin University
Diego F Echeverry - Centro Internacional de Entrenamiento e Investigaciones Medicas
Tatiana M Lopera-Mesa - Universidad de Antioquia
Lidia M Montenegro - Universidad de Antioquia
Alberto Tobón-Castaño - Universidad de Antioquia
Matthew J Grigg - Charles Darwin University
Bridget Barber - Menzies School of Health Research
Timothy William - Queen Elizabeth Hospital
Nicholas M Anstey - Charles Darwin University
Sisay Getachew - Addis Ababa University
Beyene Petros - Addis Ababa University
Abraham Aseffa - Armauer Hansen Research Institute
Ashenafi Assefa - Ethiopian Public Health Institute
Awab G Rahim - Mahidol Oxford Tropical Medicine Research Unit
Nguyen H Chau - Oxford University Clinical Research Unit
Tran T Hien - Oxford University Clinical Research Unit
Mohammad S Alam - Infectious Diseases Division, International Centre for Diarrheal Diseases Research, Dhaka, Bangladesh
Wasif A Khan - International Centre for Diarrhoeal Disease Research
Benedikt Ley - Charles Darwin University
Kamala Thriemer - Charles Darwin University
Sonam Wangchuck - Royal Centre for Disease Control
Yaghoob Hamedi - Hormozgan University of Medical Sciences
Ishag Adam - University of Khartoum
Yaobao Liu - Jiangsu Institute of Parasitic Diseases
Qi Gao - Jiangsu Institute of Parasitic Diseases
Kanlaya Sriprawat - Shoklo Malaria Research Unit
Marcelo U Ferreira - Universidade de São Paulo
Moses Laman - Papua New Guinea Institute of Medical Research
Alyssa Barry - Deakin University
Ivo Mueller - Walter and Eliza Hall Institute of Medical Research
Marcus V G Lacerda - Fundação de Medicina Tropical
Alejandro Llanos-Cuentas - Universidad Peruana Cayetano Heredia
Srivicha Krudsood - Mahidol University
Chanthap Lon - Armed Forces Research Institute of Medical Science
Rezika Mohammed - University of Gondar
Daniel Yilma - Jimma University
Dhelio B Pereira - Medicina
Fe E J Espino - Research Institute for Tropical Medicine
Cindy S Chu - Mahidol University
Iván D Vélez - Universidad de Antioquia
Chayadol Namaik-Larp - Umphang Hospital, Tak, Thailand
Maria F Villegas - CIUDAD
Justin A Green - GlaxoSmithKline
Gavin Koh - GlaxoSmithKline, Brentford, UK
Julian C Rayner - Wellcome Sanger Institute
Eleanor Drury - Wellcome Sanger Institute
Sónia Gonçalves - Wellcome Sanger Institute
Victoria Simpson - Wellcome Sanger Institute
Olivo Miotto - Wellcome Sanger Institute
Alistair Miles - Wellcome Sanger Institute
Nicholas J White - University of Oxford
Francois Nosten - Shoklo Malaria Research Unit
Dominic P Kwiatkowski - Wellcome Sanger Institute
Ric N Price - Charles Darwin University
Sarah Auburn - Mahidol Oxford Tropical Medicine Research Unit
Publication Details: Communications biology, Vol.5(1), pp.1411-1411
Grant note: 204911 / Wellcome Trust M006212 / Medical Research Council 206194/Z/17/Z / Wellcome Trust 200909 / Wellcome Trust
Identifiers: 9928722508331
Academic Unit: Qassim University; Jazan University
Language: English
Resource Type: Journal article