A miRNA Host Response Signature Accurately Discriminates Acute Respiratory Infection Etiologies
Background: Acute respiratory infections (ARIs) are the leading indication for antibacterial prescriptions despite a viral etiology in the majority of cases. The lack of available diagnostics to discriminate viral and bacterial etiologies contributes to this discordance. Recent efforts have focused...
| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2018-12-01
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| Series: | Frontiers in Microbiology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/article/10.3389/fmicb.2018.02957/full |
| _version_ | 1818990115710566400 |
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| author | Gregory D. Poore Gregory D. Poore Emily R. Ko Emily R. Ko Ashlee Valente Ricardo Henao Kelsey Sumner Christopher Hong Thomas W. Burke Marshall Nichols Micah T. McClain Micah T. McClain Micah T. McClain Erich S. Huang Erich S. Huang Geoffrey S. Ginsburg Geoffrey S. Ginsburg Christopher W. Woods Christopher W. Woods Christopher W. Woods Ephraim L. Tsalik Ephraim L. Tsalik Ephraim L. Tsalik |
| author_facet | Gregory D. Poore Gregory D. Poore Emily R. Ko Emily R. Ko Ashlee Valente Ricardo Henao Kelsey Sumner Christopher Hong Thomas W. Burke Marshall Nichols Micah T. McClain Micah T. McClain Micah T. McClain Erich S. Huang Erich S. Huang Geoffrey S. Ginsburg Geoffrey S. Ginsburg Christopher W. Woods Christopher W. Woods Christopher W. Woods Ephraim L. Tsalik Ephraim L. Tsalik Ephraim L. Tsalik |
| author_sort | Gregory D. Poore |
| collection | DOAJ |
| description | Background: Acute respiratory infections (ARIs) are the leading indication for antibacterial prescriptions despite a viral etiology in the majority of cases. The lack of available diagnostics to discriminate viral and bacterial etiologies contributes to this discordance. Recent efforts have focused on the host response as a source for novel diagnostic targets although none have explored the ability of host-derived microRNAs (miRNA) to discriminate between these etiologies.Methods: In this study, we compared host-derived miRNAs and mRNAs from human H3N2 influenza challenge subjects to those from patients with Streptococcus pneumoniae pneumonia. Sparse logistic regression models were used to generate miRNA signatures diagnostic of ARI etiologies. Generalized linear modeling of mRNAs to identify differentially expressed (DE) genes allowed analysis of potential miRNA:mRNA relationships. High likelihood miRNA:mRNA interactions were examined using binding target prediction and negative correlation to further explore potential changes in pathway regulation in response to infection.Results: The resultant miRNA signatures were highly accurate in discriminating ARI etiologies. Mean accuracy was 100% [88.8–100; 95% Confidence Interval (CI)] in discriminating the healthy state from S. pneumoniae pneumonia and 91.3% (72.0–98.9; 95% CI) in discriminating S. pneumoniae pneumonia from influenza infection. Subsequent differential mRNA gene expression analysis revealed alterations in regulatory networks consistent with known biology including immune cell activation and host response to viral infection. Negative correlation network analysis of miRNA:mRNA interactions revealed connections to pathways with known immunobiology such as interferon regulation and MAP kinase signaling.Conclusion: We have developed novel human host-response miRNA signatures for bacterial and viral ARI etiologies. miRNA host response signatures reveal accurate discrimination between S. pneumoniae pneumonia and influenza etiologies for ARI and integrated analyses of the host-pathogen interface are consistent with expected biology. These results highlight the differential miRNA host response to bacterial and viral etiologies of ARI, offering new opportunities to distinguish these entities. |
| first_indexed | 2024-12-20T19:49:15Z |
| format | Article |
| id | doaj.art-f135afe118c14397b5a49f351c01fca4 |
| institution | Directory Open Access Journal |
| issn | 1664-302X |
| language | English |
| last_indexed | 2024-12-20T19:49:15Z |
| publishDate | 2018-12-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Microbiology |
| spelling | doaj.art-f135afe118c14397b5a49f351c01fca42022-12-21T19:28:21ZengFrontiers Media S.A.Frontiers in Microbiology1664-302X2018-12-01910.3389/fmicb.2018.02957414039A miRNA Host Response Signature Accurately Discriminates Acute Respiratory Infection EtiologiesGregory D. Poore0Gregory D. Poore1Emily R. Ko2Emily R. Ko3Ashlee Valente4Ricardo Henao5Kelsey Sumner6Christopher Hong7Thomas W. Burke8Marshall Nichols9Micah T. McClain10Micah T. McClain11Micah T. McClain12Erich S. Huang13Erich S. Huang14Geoffrey S. Ginsburg15Geoffrey S. Ginsburg16Christopher W. Woods17Christopher W. Woods18Christopher W. Woods19Ephraim L. Tsalik20Ephraim L. Tsalik21Ephraim L. Tsalik22Department of Biomedical Engineering, Duke University, Durham, NC, United StatesCenter for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, United StatesCenter for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, United StatesDepartment of Hospital Medicine, Duke Regional Hospital, Durham, NC, United StatesCenter for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, United StatesCenter for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, United StatesCenter for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, United StatesCenter for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, United StatesCenter for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, United StatesCenter for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, United StatesCenter for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, United StatesDivision of Infectious Diseases, Duke University School of Medicine, Durham, NC, United StatesMedicine Service, Durham VA Medical Center, Durham, NC, United StatesDepartment of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC, United StatesDuke Clinical and Translational Science Institute, Durham, NC, United StatesDepartment of Biomedical Engineering, Duke University, Durham, NC, United StatesCenter for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, United StatesCenter for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, United StatesDivision of Infectious Diseases, Duke University School of Medicine, Durham, NC, United StatesMedicine Service, Durham VA Medical Center, Durham, NC, United StatesCenter for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, United StatesDivision of Infectious Diseases, Duke University School of Medicine, Durham, NC, United StatesEmergency Medicine Service, Durham VA Health Care System, Durham, NC, United StatesBackground: Acute respiratory infections (ARIs) are the leading indication for antibacterial prescriptions despite a viral etiology in the majority of cases. The lack of available diagnostics to discriminate viral and bacterial etiologies contributes to this discordance. Recent efforts have focused on the host response as a source for novel diagnostic targets although none have explored the ability of host-derived microRNAs (miRNA) to discriminate between these etiologies.Methods: In this study, we compared host-derived miRNAs and mRNAs from human H3N2 influenza challenge subjects to those from patients with Streptococcus pneumoniae pneumonia. Sparse logistic regression models were used to generate miRNA signatures diagnostic of ARI etiologies. Generalized linear modeling of mRNAs to identify differentially expressed (DE) genes allowed analysis of potential miRNA:mRNA relationships. High likelihood miRNA:mRNA interactions were examined using binding target prediction and negative correlation to further explore potential changes in pathway regulation in response to infection.Results: The resultant miRNA signatures were highly accurate in discriminating ARI etiologies. Mean accuracy was 100% [88.8–100; 95% Confidence Interval (CI)] in discriminating the healthy state from S. pneumoniae pneumonia and 91.3% (72.0–98.9; 95% CI) in discriminating S. pneumoniae pneumonia from influenza infection. Subsequent differential mRNA gene expression analysis revealed alterations in regulatory networks consistent with known biology including immune cell activation and host response to viral infection. Negative correlation network analysis of miRNA:mRNA interactions revealed connections to pathways with known immunobiology such as interferon regulation and MAP kinase signaling.Conclusion: We have developed novel human host-response miRNA signatures for bacterial and viral ARI etiologies. miRNA host response signatures reveal accurate discrimination between S. pneumoniae pneumonia and influenza etiologies for ARI and integrated analyses of the host-pathogen interface are consistent with expected biology. These results highlight the differential miRNA host response to bacterial and viral etiologies of ARI, offering new opportunities to distinguish these entities.https://www.frontiersin.org/article/10.3389/fmicb.2018.02957/fullpersonalized medicinemicro RNAtranscriptomerespiratory tract infectionsmolecular diagnosticshost-pathogen interaction |
| spellingShingle | Gregory D. Poore Gregory D. Poore Emily R. Ko Emily R. Ko Ashlee Valente Ricardo Henao Kelsey Sumner Christopher Hong Thomas W. Burke Marshall Nichols Micah T. McClain Micah T. McClain Micah T. McClain Erich S. Huang Erich S. Huang Geoffrey S. Ginsburg Geoffrey S. Ginsburg Christopher W. Woods Christopher W. Woods Christopher W. Woods Ephraim L. Tsalik Ephraim L. Tsalik Ephraim L. Tsalik A miRNA Host Response Signature Accurately Discriminates Acute Respiratory Infection Etiologies Frontiers in Microbiology personalized medicine micro RNA transcriptome respiratory tract infections molecular diagnostics host-pathogen interaction |
| title | A miRNA Host Response Signature Accurately Discriminates Acute Respiratory Infection Etiologies |
| title_full | A miRNA Host Response Signature Accurately Discriminates Acute Respiratory Infection Etiologies |
| title_fullStr | A miRNA Host Response Signature Accurately Discriminates Acute Respiratory Infection Etiologies |
| title_full_unstemmed | A miRNA Host Response Signature Accurately Discriminates Acute Respiratory Infection Etiologies |
| title_short | A miRNA Host Response Signature Accurately Discriminates Acute Respiratory Infection Etiologies |
| title_sort | mirna host response signature accurately discriminates acute respiratory infection etiologies |
| topic | personalized medicine micro RNA transcriptome respiratory tract infections molecular diagnostics host-pathogen interaction |
| url | https://www.frontiersin.org/article/10.3389/fmicb.2018.02957/full |
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