Investigating the etiologies of non-malarial febrile illness in Senegal using metagenomic sequencing

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作者
Zoë C. Levine
Aita Sene
Winnie Mkandawire
Awa B. Deme
Tolla Ndiaye
Mouhamad Sy
Amy Gaye
Younouss Diedhiou
Amadou M. Mbaye
Ibrahima M. Ndiaye
Jules Gomis
Médoune Ndiop
Doudou Sene
Marietou Faye Paye
Bronwyn L. MacInnis
Stephen F. Schaffner
Daniel J. Park
Aida S. Badiane
Andres Colubri
Mouhamadou Ndiaye
Ngayo Sy
Pardis C. Sabeti
Daouda Ndiaye
Katherine J. Siddle
机构
[1] Broad Institute of Harvard and MIT,Department of Parasitology
[2] Harvard Graduate Program in Biological and Biomedical Science,Department of Immunology and Infectious Diseases
[3] Harvard/MIT MD-PhD Program,Department of Organismic and Evolutionary Biology
[4] Cheikh Anta Diop University Dakar,Department of Molecular Microbiology and Immunology
[5] Centre International de Recherche et de Formation en Génomique Appliquée et de la Surveillance Sanitaire,undefined
[6] University of Massachusetts Medical School,undefined
[7] Programme National de lutte contre le Paludisme,undefined
[8] Ministère de la Santé,undefined
[9] Harvard T.H. Chan School of Public Health,undefined
[10] Harvard University,undefined
[11] Harvard University,undefined
[12] Service de Lutte Anti Parasitaire,undefined
[13] Howard Hughes Medical Institute,undefined
[14] Brown University,undefined
来源
Nature Communications | / 15卷
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摘要
The worldwide decline in malaria incidence is revealing the extensive burden of non-malarial febrile illness (NMFI), which remains poorly understood and difficult to diagnose. To characterize NMFI in Senegal, we collected venous blood and clinical metadata in a cross-sectional study of febrile patients and healthy controls in a low malaria burden area. Using 16S and untargeted sequencing, we detected viral, bacterial, or eukaryotic pathogens in 23% (38/163) of NMFI cases. Bacteria were the most common, with relapsing fever Borrelia and spotted fever Rickettsia found in 15.5% and 3.8% of cases, respectively. Four viral pathogens were found in a total of 7 febrile cases (3.5%). Sequencing also detected undiagnosed Plasmodium, including one putative P. ovale infection. We developed a logistic regression model that can distinguish Borrelia from NMFIs with similar presentation based on symptoms and vital signs (F1 score: 0.823). These results highlight the challenge and importance of improved diagnostics, especially for Borrelia, to support diagnosis and surveillance.
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