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2018. Host Gene Expression Classifiers Distinguish Bacterial and Viral Infections in Sri Lankan Patients with Acute Febrile Respiratory Illness
BACKGROUND: Acute febrile illness is a frequent cause of hospitalization in the tropics and often presents with respiratory symptoms, even when caused by nonrespiratory pathogens. Previously, host-based gene expression signatures accurately identified acute respiratory infections as being bacterial...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6253671/ http://dx.doi.org/10.1093/ofid/ofy210.1674 |
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author | Gayani Tillekeratne, L Suchindran, Sunil Ko, Emily Petzold, Elizabeth Bodinayake, Champica K Nagahawatte, Ajith Devasiri, Vasantha Kurukulasooriya, Ruvini Reller, Megan E Nicholson, Bradly P Burke, Thomas Mcclain, Micah T Tsalik, Ephraim L Henao, Ricardo Ginsburg, Geoffrey S Woods, Christopher W |
author_facet | Gayani Tillekeratne, L Suchindran, Sunil Ko, Emily Petzold, Elizabeth Bodinayake, Champica K Nagahawatte, Ajith Devasiri, Vasantha Kurukulasooriya, Ruvini Reller, Megan E Nicholson, Bradly P Burke, Thomas Mcclain, Micah T Tsalik, Ephraim L Henao, Ricardo Ginsburg, Geoffrey S Woods, Christopher W |
author_sort | Gayani Tillekeratne, L |
collection | PubMed |
description | BACKGROUND: Acute febrile illness is a frequent cause of hospitalization in the tropics and often presents with respiratory symptoms, even when caused by nonrespiratory pathogens. Previously, host-based gene expression signatures accurately identified acute respiratory infections as being bacterial or viral in a U.S. cohort. We determined signature performance in a Sri Lankan cohort with acute febrile respiratory illness (AFRI). METHODS: We enrolled patients with AFRI in Sri Lanka from July 2012 to May 2013 and collected nasopharygeal swabs, acute/ convalescent sera, and blood in PAXgene RNA tubes. Bacterial (Orientia tsutsugamushi, Leptospira spp.) and viral (influenza A/B, dengue) infections were confirmed using polymerase chain reaction, virus isolation, enzyme immunoassay, and/or microscopic agglutination testing. We extracted total RNA and performed host RNA sequencing (Illumina). We aligned reads to hg38 reference genome using Bowtie2, quantified at isoform level using Express version 1.5.1, and normalized using trimmed-mean normalization. The original model estimated three classes and separate signatures predicted bacterial infections, viral infections, and non-infectious illnesses. Regularized regression was used to predict bacterial and viral infections based on prior signatures. Accuracy was estimated using leave-one-out cross-validation. RESULTS: Among 43 patients with viral infections (14 dengue, 29 influenza) and 16 patients with bacterial infections (six Leptospira spp., 10 O. tsutsumagushi), median age was 37 years (IQR 23–51) and 49% were male. Of five respiratory symptoms (cough, sore throat, rhinitis/ congestion, shortness of breath, and pain with breathing), median (IQR) number of symptoms was 2 (1–2) for influenza, 2 (1–2) for dengue, 2 (2–3) for Leptospira spp., and 1.5 (1–2) for O. tsutsumagushi. We observed high predictive accuracy in discriminating bacterial and viral infections: AUROC 0.91 for the bacterial and AUROC 0.81 for the viral model. At enrollment, 65% of viral and 50% of bacterial AFRI patients received antibiotics. CONCLUSION: Host gene expression classifiers performed well in a Sri Lankan population with AFRI, even with nonrespiratory pathogens that may not be readily identified. Host-based diagnostics may play a critical role in improving diagnostic ability and antibiotic use globally. DISCLOSURES: E. L. Tsalik, Host Response, Inc.: Founder, Equity. G. S. Ginsburg, Host Response Inc.: Board Member, Founder, Scientific Advisor and Shareholder, Stock (currently worth <$100). C. W. Woods, Host Response, Inc.: Founder, Equity. |
format | Online Article Text |
id | pubmed-6253671 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-62536712018-11-28 2018. Host Gene Expression Classifiers Distinguish Bacterial and Viral Infections in Sri Lankan Patients with Acute Febrile Respiratory Illness Gayani Tillekeratne, L Suchindran, Sunil Ko, Emily Petzold, Elizabeth Bodinayake, Champica K Nagahawatte, Ajith Devasiri, Vasantha Kurukulasooriya, Ruvini Reller, Megan E Nicholson, Bradly P Burke, Thomas Mcclain, Micah T Tsalik, Ephraim L Henao, Ricardo Ginsburg, Geoffrey S Woods, Christopher W Open Forum Infect Dis Abstracts BACKGROUND: Acute febrile illness is a frequent cause of hospitalization in the tropics and often presents with respiratory symptoms, even when caused by nonrespiratory pathogens. Previously, host-based gene expression signatures accurately identified acute respiratory infections as being bacterial or viral in a U.S. cohort. We determined signature performance in a Sri Lankan cohort with acute febrile respiratory illness (AFRI). METHODS: We enrolled patients with AFRI in Sri Lanka from July 2012 to May 2013 and collected nasopharygeal swabs, acute/ convalescent sera, and blood in PAXgene RNA tubes. Bacterial (Orientia tsutsugamushi, Leptospira spp.) and viral (influenza A/B, dengue) infections were confirmed using polymerase chain reaction, virus isolation, enzyme immunoassay, and/or microscopic agglutination testing. We extracted total RNA and performed host RNA sequencing (Illumina). We aligned reads to hg38 reference genome using Bowtie2, quantified at isoform level using Express version 1.5.1, and normalized using trimmed-mean normalization. The original model estimated three classes and separate signatures predicted bacterial infections, viral infections, and non-infectious illnesses. Regularized regression was used to predict bacterial and viral infections based on prior signatures. Accuracy was estimated using leave-one-out cross-validation. RESULTS: Among 43 patients with viral infections (14 dengue, 29 influenza) and 16 patients with bacterial infections (six Leptospira spp., 10 O. tsutsumagushi), median age was 37 years (IQR 23–51) and 49% were male. Of five respiratory symptoms (cough, sore throat, rhinitis/ congestion, shortness of breath, and pain with breathing), median (IQR) number of symptoms was 2 (1–2) for influenza, 2 (1–2) for dengue, 2 (2–3) for Leptospira spp., and 1.5 (1–2) for O. tsutsumagushi. We observed high predictive accuracy in discriminating bacterial and viral infections: AUROC 0.91 for the bacterial and AUROC 0.81 for the viral model. At enrollment, 65% of viral and 50% of bacterial AFRI patients received antibiotics. CONCLUSION: Host gene expression classifiers performed well in a Sri Lankan population with AFRI, even with nonrespiratory pathogens that may not be readily identified. Host-based diagnostics may play a critical role in improving diagnostic ability and antibiotic use globally. DISCLOSURES: E. L. Tsalik, Host Response, Inc.: Founder, Equity. G. S. Ginsburg, Host Response Inc.: Board Member, Founder, Scientific Advisor and Shareholder, Stock (currently worth <$100). C. W. Woods, Host Response, Inc.: Founder, Equity. Oxford University Press 2018-11-26 /pmc/articles/PMC6253671/ http://dx.doi.org/10.1093/ofid/ofy210.1674 Text en © The Author(s) 2018. Published by Oxford University Press on behalf of Infectious Diseases Society of America. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Abstracts Gayani Tillekeratne, L Suchindran, Sunil Ko, Emily Petzold, Elizabeth Bodinayake, Champica K Nagahawatte, Ajith Devasiri, Vasantha Kurukulasooriya, Ruvini Reller, Megan E Nicholson, Bradly P Burke, Thomas Mcclain, Micah T Tsalik, Ephraim L Henao, Ricardo Ginsburg, Geoffrey S Woods, Christopher W 2018. Host Gene Expression Classifiers Distinguish Bacterial and Viral Infections in Sri Lankan Patients with Acute Febrile Respiratory Illness |
title | 2018. Host Gene Expression Classifiers Distinguish Bacterial and Viral Infections in Sri Lankan Patients with Acute Febrile Respiratory Illness |
title_full | 2018. Host Gene Expression Classifiers Distinguish Bacterial and Viral Infections in Sri Lankan Patients with Acute Febrile Respiratory Illness |
title_fullStr | 2018. Host Gene Expression Classifiers Distinguish Bacterial and Viral Infections in Sri Lankan Patients with Acute Febrile Respiratory Illness |
title_full_unstemmed | 2018. Host Gene Expression Classifiers Distinguish Bacterial and Viral Infections in Sri Lankan Patients with Acute Febrile Respiratory Illness |
title_short | 2018. Host Gene Expression Classifiers Distinguish Bacterial and Viral Infections in Sri Lankan Patients with Acute Febrile Respiratory Illness |
title_sort | 2018. host gene expression classifiers distinguish bacterial and viral infections in sri lankan patients with acute febrile respiratory illness |
topic | Abstracts |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6253671/ http://dx.doi.org/10.1093/ofid/ofy210.1674 |
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