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Classification of invasive bloodstream infections and Plasmodium falciparum malaria using autoantibodies as biomarkers.

Published version
Peer-reviewed

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Authors

Krumkamp, Ralf 
Struck, Nicole Sunaina 
Lorenz, Eva 
Zimmermann, Marlow 
Boahen, Kennedy Gyau 

Abstract

A better understanding of disease-specific biomarker profiles during acute infections could guide the development of innovative diagnostic methods to differentiate between malaria and alternative causes of fever. We investigated autoantibody (AAb) profiles in febrile children (≤ 5 years) admitted to a hospital in rural Ghana. Serum samples from 30 children with a bacterial bloodstream infection and 35 children with Plasmodium falciparum malaria were analyzed using protein microarrays (Protoplex Immune Response Assay, ThermoFisher). A variable selection algorithm was applied to identify the smallest set of AAbs showing the best performance to classify malaria and bacteremia patients. The selection procedure identified 8 AAbs of which IFNGR2 and FBXW5 were selected in repeated model run. The classification error was 22%, which was mainly due to non-Typhi Salmonella (NTS) diagnoses being misclassified as malaria. Likewise, a cluster analysis grouped patients with NTS and malaria together, but separated malaria from non-NTS infections. Both current and recent malaria are a risk factor for NTS, therefore, a better understanding about the function of AAb in disease-specific immune responses is required in order to support their application for diagnostic purposes.

Description

Funder: Projekt DEAL

Keywords

Algorithms, Autoantibodies, Biomarkers, Child, Preschool, Cluster Analysis, Female, Humans, Infant, Malaria, Falciparum, Male, Sepsis

Journal Title

Sci Rep

Conference Name

Journal ISSN

2045-2322
2045-2322

Volume Title

10

Publisher

Springer Science and Business Media LLC
Sponsorship
Deutsches Zentrum für Infektionsforschung (TTU 03.704)
Bill and Melinda Gates Foundation (OPPGH5231)