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Diagnostic host gene signature for distinguishing enteric fever from other febrile diseases

Misdiagnosis of enteric fever is a major global health problem, resulting in patient mismanagement, antimicrobial misuse and inaccurate disease burden estimates. Applying a machine learning algorithm to host gene expression profiles, we identified a diagnostic signature, which could distinguish cult...

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Autores principales: Blohmke, Christoph J, Muller, Julius, Gibani, Malick M, Dobinson, Hazel, Shrestha, Sonu, Perinparajah, Soumya, Jin, Celina, Hughes, Harri, Blackwell, Luke, Dongol, Sabina, Karkey, Abhilasha, Schreiber, Fernanda, Pickard, Derek, Basnyat, Buddha, Dougan, Gordon, Baker, Stephen, Pollard, Andrew J, Darton, Thomas C
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6783646/
https://www.ncbi.nlm.nih.gov/pubmed/31468702
http://dx.doi.org/10.15252/emmm.201910431
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author Blohmke, Christoph J
Muller, Julius
Gibani, Malick M
Dobinson, Hazel
Shrestha, Sonu
Perinparajah, Soumya
Jin, Celina
Hughes, Harri
Blackwell, Luke
Dongol, Sabina
Karkey, Abhilasha
Schreiber, Fernanda
Pickard, Derek
Basnyat, Buddha
Dougan, Gordon
Baker, Stephen
Pollard, Andrew J
Darton, Thomas C
author_facet Blohmke, Christoph J
Muller, Julius
Gibani, Malick M
Dobinson, Hazel
Shrestha, Sonu
Perinparajah, Soumya
Jin, Celina
Hughes, Harri
Blackwell, Luke
Dongol, Sabina
Karkey, Abhilasha
Schreiber, Fernanda
Pickard, Derek
Basnyat, Buddha
Dougan, Gordon
Baker, Stephen
Pollard, Andrew J
Darton, Thomas C
author_sort Blohmke, Christoph J
collection PubMed
description Misdiagnosis of enteric fever is a major global health problem, resulting in patient mismanagement, antimicrobial misuse and inaccurate disease burden estimates. Applying a machine learning algorithm to host gene expression profiles, we identified a diagnostic signature, which could distinguish culture‐confirmed enteric fever cases from other febrile illnesses (area under receiver operating characteristic curve > 95%). Applying this signature to a culture‐negative suspected enteric fever cohort in Nepal identified a further 12.6% as likely true cases. Our analysis highlights the power of data‐driven approaches to identify host response patterns for the diagnosis of febrile illnesses. Expression signatures were validated using qPCR, highlighting their utility as PCR‐based diagnostics for use in endemic settings.
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spelling pubmed-67836462019-10-17 Diagnostic host gene signature for distinguishing enteric fever from other febrile diseases Blohmke, Christoph J Muller, Julius Gibani, Malick M Dobinson, Hazel Shrestha, Sonu Perinparajah, Soumya Jin, Celina Hughes, Harri Blackwell, Luke Dongol, Sabina Karkey, Abhilasha Schreiber, Fernanda Pickard, Derek Basnyat, Buddha Dougan, Gordon Baker, Stephen Pollard, Andrew J Darton, Thomas C EMBO Mol Med Articles Misdiagnosis of enteric fever is a major global health problem, resulting in patient mismanagement, antimicrobial misuse and inaccurate disease burden estimates. Applying a machine learning algorithm to host gene expression profiles, we identified a diagnostic signature, which could distinguish culture‐confirmed enteric fever cases from other febrile illnesses (area under receiver operating characteristic curve > 95%). Applying this signature to a culture‐negative suspected enteric fever cohort in Nepal identified a further 12.6% as likely true cases. Our analysis highlights the power of data‐driven approaches to identify host response patterns for the diagnosis of febrile illnesses. Expression signatures were validated using qPCR, highlighting their utility as PCR‐based diagnostics for use in endemic settings. John Wiley and Sons Inc. 2019-08-30 2019-10 /pmc/articles/PMC6783646/ /pubmed/31468702 http://dx.doi.org/10.15252/emmm.201910431 Text en © 2019 The Authors. Published under the terms of the CC BY 4.0 license This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Articles
Blohmke, Christoph J
Muller, Julius
Gibani, Malick M
Dobinson, Hazel
Shrestha, Sonu
Perinparajah, Soumya
Jin, Celina
Hughes, Harri
Blackwell, Luke
Dongol, Sabina
Karkey, Abhilasha
Schreiber, Fernanda
Pickard, Derek
Basnyat, Buddha
Dougan, Gordon
Baker, Stephen
Pollard, Andrew J
Darton, Thomas C
Diagnostic host gene signature for distinguishing enteric fever from other febrile diseases
title Diagnostic host gene signature for distinguishing enteric fever from other febrile diseases
title_full Diagnostic host gene signature for distinguishing enteric fever from other febrile diseases
title_fullStr Diagnostic host gene signature for distinguishing enteric fever from other febrile diseases
title_full_unstemmed Diagnostic host gene signature for distinguishing enteric fever from other febrile diseases
title_short Diagnostic host gene signature for distinguishing enteric fever from other febrile diseases
title_sort diagnostic host gene signature for distinguishing enteric fever from other febrile diseases
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6783646/
https://www.ncbi.nlm.nih.gov/pubmed/31468702
http://dx.doi.org/10.15252/emmm.201910431
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