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Title:A multi-platform approach to identify a blood-based host protein signature for distinguishing between bacterial and viral infections in febrile children (PERFORM) : a multi-cohort machine learning study
Authors:ID Jackson, Heather R. (Author)
ID Zandstra, Judith (Author)
ID Menikou, Stephanie (Author)
ID Hamilton, Melissa Shea (Author)
ID McArdle, Andrew J (Author)
ID Fischer, Roman (Author)
ID Thorne, Adam M (Author)
ID Pokorn, Marko (Author)
ID Kolnik, Mojca (Research coworker)
ID Vincek, Katarina (Research coworker)
ID Plankar Srovin, Tina (Research coworker)
ID Bahovec, Natalija (Research coworker)
ID Prunk, Petra (Research coworker)
ID Osterman, Veronika (Research coworker)
ID Avramoska, Tanja (Research coworker), et al.
Files:.pdf PDF - Presentation file, download (959,11 KB)
MD5: 0334F6CA3B50C6C2830F83F66CE88449
 
URL URL - Source URL, visit https://www.thelancet.com/journals/landig/article/PIIS2589-7500(23)00149-8/fulltext
 
Language:English
Typology:1.01 - Original Scientific Article
Organization:Logo UKC LJ - Ljubljana University Medical Centre
Abstract:Background: Differentiating between self-resolving viral infections and bacterial infections in children who are febrile is a common challenge, causing difficulties in identifying which individuals require antibiotics. Studying the host response to infection can provide useful insights and can lead to the identification of biomarkers of infection with diagnostic potential. This study aimed to identify host protein biomarkers for future development into an accurate, rapid point-of-care test that can distinguish between bacterial and viral infections, by recruiting children presenting to health-care settings with fever or a history of fever in the previous 72 h. Methods: In this multi-cohort machine learning study, patient data were taken from EUCLIDS, the Swiss Pediatric Sepsis study, the GENDRES study, and the PERFORM study, which were all based in Europe. We generated three high-dimensional proteomic datasets (SomaScan and two via liquid chromatography tandem mass spectrometry, referred to as MS-A and MS-B) using targeted and untargeted platforms (SomaScan and liquid chromatography mass spectrometry). Protein biomarkers were then shortlisted using differential abundance analysis, feature selection using forward selection-partial least squares (FS-PLS; 100 iterations), along with a literature search. Identified proteins were tested with Luminex and ELISA and iterative FS-PLS was done again (25 iterations) on the Luminex results alone, and the Luminex and ELISA results together. A sparse protein signature for distinguishing between bacterial and viral infections was identified from the selected proteins. The performance of this signature was finally tested using Luminex assays and by calculating disease risk scores. Findings: 376 children provided serum or plasma samples for use in the discovery of protein biomarkers. 79 serum samples were collected for the generation of the SomaScan dataset, 147 plasma samples for the MS-A dataset, and 150 plasma samples for the MS-B dataset. Differential abundance analysis, and the first round of feature selection using FS-PLS identified 35 protein biomarker candidates, of which 13 had commercial ELISA or Luminex tests available. 16 proteins with ELISA or Luminex tests available were identified by literature review. Further evaluation via Luminex and ELISA and the second round of feature selection using FS-PLS revealed a six-protein signature: three of the included proteins are elevated in bacterial infections (SELE, NGAL, and IFN-gamma), and three are elevated in viral infections (IL18, NCAM1, and LG3BP). Performance testing of the signature using Luminex assays revealed area under the receiver operating characteristic curve values between 89 center dot 4% and 93 center dot 6%. Interpretation: This study has led to the identification of a protein signature that could be ultimately developed into a blood-based point-of-care diagnostic test for rapidly diagnosing bacterial and viral infections in febrile children. Such a test has the potential to greatly improve care of children who are febrile, ensuring that the correct individuals receive antibiotics.
Keywords:C-reactive protein, antibiotic overuse, virus-infection, resistance
Publication status:Published
Publication version:Version of Record
Year of publishing:2023
Number of pages:str. e774-e785
Numbering:Vol. 5, issue 11
PID:20.500.12556/DiRROS-28127 New window
UDC:616-053.2
ISSN on article:2589-7500
DOI:10.1016/S2589-7500(23)00149-8 New window
COBISS.SI-ID:243409667 New window
Note:Nasl. z nasl. zaslona; Opis z dne 22. 7. 2025;
Publication date in DiRROS:10.03.2026
Views:78
Downloads:37
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Record is a part of a journal

Title:The Lancet : Digital health.
Publisher:Elsevier Ltd.
ISSN:2589-7500
COBISS.SI-ID:529859865 New window

Document is financed by a project

Funder:EC - European Commission
Project number:668303
Name:Personalised Risk assessment in febrile illness to Optimise Real-life Management across the European Union
Acronym:PERFORM

Funder:EC - European Commission
Project number:279185
Name:The genetic basis of meningococcal and other life threatening bacterial infections of childhood
Acronym:EUCLIDS

Funder:WT - Wellcome Trust
Project number:206508
Name:Understanding and diagnosing infectious diseases using multi-level 'omics data

Funder:Other - Other funder or multiple funders

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

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