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Schughart K, Smith AM, Tsalik EL, Threlkeld SC, Sellers S, Fischer WA, Schreiber J, Lücke E, Cornberg M, Debarry J, Woods CW, McClain MT, Heise M. Host response to influenza infections in human blood: association of influenza severity with host genetics and transcriptomic response. Front Immunol 2024; 15:1385362. [PMID: 39192977 PMCID: PMC11347429 DOI: 10.3389/fimmu.2024.1385362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Accepted: 07/24/2024] [Indexed: 08/29/2024] Open
Abstract
Introduction Influenza virus infections are a major global health problem. Influenza can result in mild/moderate disease or progress to more severe disease, leading to high morbidity and mortality. Severity is thought to be primarily driven by immunopathology, but predicting which individuals are at a higher risk of being hospitalized warrants investigation into host genetics and the molecular signatures of the host response during influenza infections. Methods Here, we performed transcriptome and genotype analysis in healthy controls and patients exhibiting mild/moderate or severe influenza (ICU patients). A unique aspect of our study was the genotyping of all participants, which allowed us to assign ethnicities based on genetic variation and assess whether the variation was correlated with expression levels. Results We identified 169 differentially expressed genes and related molecular pathways between patients in the ICU and those who were not in the ICU. The transcriptome/genotype association analysis identified 871 genes associated to a genetic variant and 39 genes distinct between African-Americans and Caucasians. We also investigated the effects of age and sex and found only a few discernible gene effects in our cohort. Discussion Together, our results highlight select risk factors that may contribute to an increased risk of ICU admission for influenza-infected patients. This should help to develop better diagnostic tools based on molecular signatures, in addition to a better understanding of the biological processes in the host response to influenza.
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Affiliation(s)
- Klaus Schughart
- Institute of Virology Münster, University of Münster, Münster, Germany
- Department of Microbiology, Immunology and Biochemistry, University of Tennessee Health Science Center, Memphis, TN, United States
| | - Amber M. Smith
- Department of Microbiology, Immunology and Biochemistry, University of Tennessee Health Science Center, Memphis, TN, United States
- Department of Pediatrics, University of Tennessee Health Science Center, Memphis, TN, United States
| | - Ephraim L. Tsalik
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, United States
| | | | - Subhashini Sellers
- Division of Pulmonary Diseases and Critical Care Medicine, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - William A. Fischer
- Division of Pulmonary Diseases and Critical Care Medicine, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Jens Schreiber
- Clinic of Pneumology, Otto-von-Guerike University, Magdeburg, Germany
| | - Eva Lücke
- Clinic of Pneumology, Otto-von-Guerike University, Magdeburg, Germany
| | - Markus Cornberg
- Centre for Individualised Infection Medicine (CiiM), a Joint Initiative of the Helmholtz Centre for Infection Research (HZI) and Hannover Medical School (MHH), Hannover, Germany
- Department of Gastroenterology, Hepatology, Infectious Diseases and Endocrinology, Hannover Medical School (MHH), Hannover, Germany
- German Centre for Infection Research (DZIF), Partner Site Hannover-Braunschweig, Hannover, Germany
- TWINCORE Centre for Experimental and Clinical Infection Research, a Joint Venture Between the Helmholtz-Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany
| | - Jennifer Debarry
- Centre for Individualised Infection Medicine (CiiM), a Joint Initiative of the Helmholtz Centre for Infection Research (HZI) and Hannover Medical School (MHH), Hannover, Germany
- TWINCORE Centre for Experimental and Clinical Infection Research, a Joint Venture Between the Helmholtz-Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany
| | - Christopher W. Woods
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, United States
- Center for Infectious Disease Diagnostics and Innovation, Department of Medicine, Duke University School of Medicine, Durham, NC, United States
| | - Micah T. McClain
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, United States
- Center for Infectious Disease Diagnostics and Innovation, Department of Medicine, Duke University School of Medicine, Durham, NC, United States
| | - Mark Heise
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Department of Microbiology and Immunology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
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McCravy M, O’Grady N, Khan K, Betancourt-Quiroz M, Zaas AK, Treece AE, Yang Z, Que L, Henao R, Suchindran S, Ginsburg GS, Woods CW, McClain MT, Tsalik EL. Predictive signature of murine and human host response to typical and atypical pneumonia. BMJ Open Respir Res 2024; 11:e002001. [PMID: 39097412 PMCID: PMC11298752 DOI: 10.1136/bmjresp-2023-002001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2023] [Accepted: 07/08/2024] [Indexed: 08/05/2024] Open
Abstract
BACKGROUND Pneumonia due to typical bacterial, atypical bacterial and viral pathogens can be difficult to clinically differentiate. Host response-based diagnostics are emerging as a complementary diagnostic strategy to pathogen detection. METHODS We used murine models of typical bacterial, atypical bacterial and viral pneumonia to develop diagnostic signatures and understand the host's response to these types of infections. Mice were intranasally inoculated with Streptococcus pneumoniae, Mycoplasma pneumoniae, influenza or saline as a control. Peripheral blood gene expression analysis was performed at multiple time points. Differentially expressed genes were used to perform gene set enrichment analysis and generate diagnostic signatures. These murine-derived signatures were externally validated in silico using human gene expression data. The response to S. pneumoniae was the most rapid and robust. RESULTS Mice infected with M. pneumoniae had a delayed response more similar to influenza-infected animals. Diagnostic signatures for the three types of infection had 0.94-1.00 area under the receiver operator curve (auROC). Validation in five human gene expression datasets revealed auROC of 0.82-0.96. DISCUSSION This study identified discrete host responses to typical bacterial, atypical bacterial and viral aetiologies of pneumonia in mice. These signatures validated well in humans, highlighting the conserved nature of the host response to these pathogen classes.
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Affiliation(s)
- Matthew McCravy
- Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA
| | - Nicholas O’Grady
- Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA
| | - Kirin Khan
- Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA
| | | | - Aimee K Zaas
- Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA
| | - Amy E Treece
- Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA
| | - Zhonghui Yang
- Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA
| | - Loretta Que
- Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA
| | - Ricardo Henao
- Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, North Carolina, USA
| | - Sunil Suchindran
- Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA
| | - Geoffrey S Ginsburg
- Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA
| | - Christopher W Woods
- Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA
| | - Micah T McClain
- Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA
| | - Ephraim L Tsalik
- Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA
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La Distia Nora R, Putera I, Schrijver B, Singh G, Bakker M, Riasanti M, Edwar L, Susiyanti M, Aziza Y, Ten Berge JCEM, Rombach SM, van Hagen PM, Sitompul R, Dik WA. Ocular Tuberculosis Diagnosis Through Biomarkers: Clinical Relevance of Serum C1q and Whole Blood Interferon Gene Signature Score. Ocul Immunol Inflamm 2024:1-12. [PMID: 38913993 DOI: 10.1080/09273948.2024.2368670] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2024] [Accepted: 06/11/2024] [Indexed: 06/26/2024]
Abstract
PURPOSE To assess the clinical relevance of pathophysiology-based biomarkers, specifically serum C1q and whole blood interferon gene signature score (IGSS), in ocular tuberculosis (OTB) diagnosis by conducting an integrative analysis of clinical presentations and treatment response. METHODS This retrospective cohort study analysed data from 70 patients with suspected OTB at a tertiary care uveitis practice in Indonesia. Serum C1q levels and whole blood IGSS were quantified. Patients were categorized into four quadrants based on their biomarker profiles: quadrant 1 (high C1q & low IGSS), quadrant 2 (high C1q & high IGSS), quadrant 3 (low C1q & high IGSS), and quadrant 4 (low C1q & low IGSS). Characteristics of clinical presentations, work-up results, and treatment outcomes were explored according to the predefined quadrants. RESULTS We identified that the majority of OTB patients diagnosed with concurrent active pulmonary TB were in quadrant 1, 2, or 3 (20/23, 87.0%). Twenty-seven patients (27/47, 57.4%) with clinically undifferentiated uveitis were in quadrant 4 (p < 0.001). Among patients in quadrants 1, 2, and 3, completion of a full course of antitubercular treatment (ATT) was associated with a lower number of patients showing persistence or recurrence of ocular inflammation compared to those who were not fully treated with ATT (14.3% vs 85.7%, p = 0.001). CONCLUSIONS Based on the analysis of clinical features and treatment outcomes, patients with elevated levels of either or both serum C1q and whole blood IGSS may reflect active TB disease in the eye, necessitating full ATT management.
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Affiliation(s)
- Rina La Distia Nora
- Department of Ophthalmology, Faculty of Medicine, Universitas Indonesia, Cipto Mangunkusumo Hospital, Jakarta, Indonesia
- Laboratory Medical Immunology, Department of Immunology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Ikhwanuliman Putera
- Department of Ophthalmology, Faculty of Medicine, Universitas Indonesia, Cipto Mangunkusumo Hospital, Jakarta, Indonesia
- Laboratory Medical Immunology, Department of Immunology, Erasmus University Medical Center, Rotterdam, The Netherlands
- Department of Ophthalmology, Erasmus University Medical Center, Rotterdam, The Netherlands
- Department of Internal Medicine Section Allergy & Clinical Immunology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Benjamin Schrijver
- Laboratory Medical Immunology, Department of Immunology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Gurmeet Singh
- Department of Internal Medicine, Respirology and Critical Illness Division, Faculty of Medicine, Universitas Indonesia, Cipto Mangunkusumo Hospital, Jakarta, Indonesia
| | - Marleen Bakker
- Department of Pulmonary Diseases, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Mei Riasanti
- Department of Ophthalmology, Faculty of Medicine, Universitas Indonesia, Cipto Mangunkusumo Hospital, Jakarta, Indonesia
| | - Lukman Edwar
- Department of Ophthalmology, Faculty of Medicine, Universitas Indonesia, Cipto Mangunkusumo Hospital, Jakarta, Indonesia
| | - Made Susiyanti
- Department of Ophthalmology, Faculty of Medicine, Universitas Indonesia, Cipto Mangunkusumo Hospital, Jakarta, Indonesia
| | - Yulia Aziza
- Department of Ophthalmology, Faculty of Medicine, Universitas Indonesia, Cipto Mangunkusumo Hospital, Jakarta, Indonesia
| | | | - Saskia M Rombach
- Department of Internal Medicine Section Allergy & Clinical Immunology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - P Martin van Hagen
- Laboratory Medical Immunology, Department of Immunology, Erasmus University Medical Center, Rotterdam, The Netherlands
- Department of Internal Medicine Section Allergy & Clinical Immunology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Ratna Sitompul
- Department of Ophthalmology, Faculty of Medicine, Universitas Indonesia, Cipto Mangunkusumo Hospital, Jakarta, Indonesia
| | - Willem A Dik
- Laboratory Medical Immunology, Department of Immunology, Erasmus University Medical Center, Rotterdam, The Netherlands
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Chen L, Hua J, He X. Bioinformatics analysis identifies a key gene HLA_DPA1 in severe influenza-associated immune infiltration. BMC Genomics 2024; 25:257. [PMID: 38454348 PMCID: PMC10918912 DOI: 10.1186/s12864-024-10184-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Accepted: 03/04/2024] [Indexed: 03/09/2024] Open
Abstract
BACKGROUND Severe influenza is a serious global health issue that leads to prolonged hospitalization and mortality on a significant scale. The pathogenesis of this infectious disease is poorly understood. Therefore, this study aimed to identify the key genes associated with severe influenza patients necessitating invasive mechanical ventilation. METHODS The current study utilized two publicly accessible gene expression profiles (GSE111368 and GSE21802) from the Gene Expression Omnibus database. The research focused on identifying the genes exhibiting differential expression between severe and non-severe influenza patients. We employed three machine learning algorithms, namely the Least Absolute Shrinkage and Selection Operator regression model, Random Forest, and Support Vector Machine-Recursive Feature Elimination, to detect potential key genes. The key gene was further selected based on the diagnostic performance of the target genes substantiated in the dataset GSE101702. A single-sample gene set enrichment analysis algorithm was applied to evaluate the participation of immune cell infiltration and their associations with key genes. RESULTS A total of 44 differentially expressed genes were recognized; among them, we focused on 10 common genes, namely PCOLCE2, HLA_DPA1, LOC653061, TDRD9, MPO, HLA_DQA1, MAOA, S100P, RAP1GAP, and CA1. To ensure the robustness of our findings, we employed overlapping LASSO regression, Random Forest, and SVM-RFE algorithms. By utilizing these algorithms, we were able to pinpoint the aforementioned 10 genes as potential biomarkers for distinguishing between both cases of influenza (severe and non-severe). However, the gene HLA_DPA1 has been recognized as a crucial factor in the pathological condition of severe influenza. Notably, the validation dataset revealed that this gene exhibited the highest area under the receiver operating characteristic curve, with a value of 0.891. The use of single-sample gene set enrichment analysis has provided valuable insights into the immune responses of patients afflicted with severe influenza that have further revealed a categorical correlation between the expression of HLA_DPA1 and lymphocytes. CONCLUSION The findings indicated that the HLA_DPA1 gene may play a crucial role in the immune-pathological condition of severe influenza and could serve as a promising therapeutic target for patients infected with severe influenza.
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Affiliation(s)
- Liang Chen
- Department of Infectious Diseases, Taikang Xianlin Drum Tower Hospital, Affiliated Hospital of Medical College of Nanjing University, No 188, Lingshan North Road, Qixia District, Nanjing, 210046, China.
| | - Jie Hua
- Department of Gastroenterology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Xiaopu He
- Department of Geriatric Gastroenterology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
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Ratnasiri K, Zheng H, Toh J, Yao Z, Duran V, Donato M, Roederer M, Kamath M, Todd JPM, Gagne M, Foulds KE, Francica JR, Corbett KS, Douek DC, Seder RA, Einav S, Blish CA, Khatri P. Systems immunology of transcriptional responses to viral infection identifies conserved antiviral pathways across macaques and humans. Cell Rep 2024; 43:113706. [PMID: 38294906 PMCID: PMC10915397 DOI: 10.1016/j.celrep.2024.113706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 11/02/2023] [Accepted: 01/09/2024] [Indexed: 02/02/2024] Open
Abstract
Viral pandemics and epidemics pose a significant global threat. While macaque models of viral disease are routinely used, it remains unclear how conserved antiviral responses are between macaques and humans. Therefore, we conducted a cross-species analysis of transcriptomic data from over 6,088 blood samples from macaques and humans infected with one of 31 viruses. Our findings demonstrate that irrespective of primate or viral species, there are conserved antiviral responses that are consistent across infection phase (acute, chronic, or latent) and viral genome type (DNA or RNA viruses). Leveraging longitudinal data from experimental challenges, we identify virus-specific response kinetics such as host responses to Coronaviridae and Orthomyxoviridae infections peaking 1-3 days earlier than responses to Filoviridae and Arenaviridae viral infections. Our results underscore macaque studies as a powerful tool for understanding viral pathogenesis and immune responses that translate to humans, with implications for viral therapeutic development and pandemic preparedness.
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Affiliation(s)
- Kalani Ratnasiri
- Stanford Immunology Program, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Epidemiology and Population Health, Stanford University, Stanford, CA 94305, USA
| | - Hong Zheng
- Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, CA 94305, USA; Institute for Immunity, Transplantation and Infection, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Jiaying Toh
- Stanford Immunology Program, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Surgery, Division of Abdominal Transplantation, Stanford University School of Medicine, Stanford, CA 94305, USA; Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, CA 94305, USA; Institute for Immunity, Transplantation and Infection, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Zhiyuan Yao
- Department of Microbiology and Immunology, Stanford University, CA 94305, USA
| | - Veronica Duran
- Department of Microbiology and Immunology, Stanford University, CA 94305, USA
| | - Michele Donato
- Department of Surgery, Division of Abdominal Transplantation, Stanford University School of Medicine, Stanford, CA 94305, USA; Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Mario Roederer
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Megha Kamath
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - John-Paul M Todd
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Matthew Gagne
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Kathryn E Foulds
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Joseph R Francica
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Kizzmekia S Corbett
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Daniel C Douek
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Robert A Seder
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Shirit Einav
- Department of Microbiology and Immunology, Stanford University, CA 94305, USA; Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA; Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
| | - Catherine A Blish
- Stanford Immunology Program, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA; Chan Zuckerberg Biohub, San Francisco, CA 94158, USA; Medical Scientist Training Program, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Purvesh Khatri
- Department of Surgery, Division of Abdominal Transplantation, Stanford University School of Medicine, Stanford, CA 94305, USA; Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, CA 94305, USA; Institute for Immunity, Transplantation and Infection, Stanford University School of Medicine, Stanford, CA 94305, USA.
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Li Q, Qu L, Miao Y, Li Q, Zhang J, Zhao Y, Cheng R. A gene network database for the identification of key genes for diagnosis, prognosis, and treatment in sepsis. Sci Rep 2023; 13:21815. [PMID: 38071387 PMCID: PMC10710458 DOI: 10.1038/s41598-023-49311-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2023] [Accepted: 12/06/2023] [Indexed: 12/18/2023] Open
Abstract
Sepsis and sepsis-related diseases cause a high rate of mortality worldwide. The molecular and cellular mechanisms of sepsis are still unclear. We aim to identify key genes in sepsis and reveal potential disease mechanisms. Six sepsis-related blood transcriptome datasets were collected and analyzed by weighted gene co-expression network analysis (WGCNA). Functional annotation was performed in the gProfiler tool. DSigDB was used for drug signature enrichment analysis. The proportion of immune cells was estimated by the CIBERSORT tool. The relationships between modules, immune cells, and survival were identified by correlation analysis and survival analysis. A total of 37 stable co-expressed gene modules were identified. These modules were associated with the critical biology process in sepsis. Four modules can independently separate patients with long and short survival. Three modules can recurrently separate sepsis and normal patients with high accuracy. Some modules can separate bacterial pneumonia, influenza pneumonia, mixed bacterial and influenza A pneumonia, and non-infective systemic inflammatory response syndrome (SIRS). Drug signature analysis identified drugs associated with sepsis, such as testosterone, phytoestrogens, ibuprofen, urea, dichlorvos, potassium persulfate, and vitamin B12. Finally, a gene co-expression network database was constructed ( https://liqs.shinyapps.io/sepsis/ ). The recurrent modules in sepsis may facilitate disease diagnosis, prognosis, and treatment.
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Affiliation(s)
- Qingsheng Li
- Department of Pharmacy, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, Inner Mongolia, 010050, People's Republic of China
| | - Lili Qu
- Department of Pharmacy, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, Inner Mongolia, 010050, People's Republic of China
| | - Yurui Miao
- Department of Pharmacy, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, Inner Mongolia, 010050, People's Republic of China
| | - Qian Li
- Department of Pharmacy, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, Inner Mongolia, 010050, People's Republic of China
| | - Jing Zhang
- Department of Pharmacy, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, Inner Mongolia, 010050, People's Republic of China
| | - Yongxue Zhao
- Department of Pharmacy, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, Inner Mongolia, 010050, People's Republic of China
| | - Rui Cheng
- Department of Pharmacy, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, Inner Mongolia, 010050, People's Republic of China.
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Viasus D, Nonell L, Restrepo C, Figueroa F, Donado-Mazarrón C, Carratalà J. A Systematic Review of Gene Expression Studies in Critically Ill Patients with Sepsis and Community-Acquired Pneumonia. Biomedicines 2023; 11:2755. [PMID: 37893128 PMCID: PMC10604146 DOI: 10.3390/biomedicines11102755] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 09/14/2023] [Accepted: 10/08/2023] [Indexed: 10/29/2023] Open
Abstract
(1) Background: Sepsis is present in nearly 90% of critically ill patients with community-acquired pneumonia (CAP). This systematic review updates the information on studies that have assessed gene expression profiles in critically ill septic patients with CAP. (2) Methods: We searched for studies that satisfied the following criteria: (a) expression profile in critically ill patients with sepsis due to CAP, (b) presence of a control group, and (c) adult patients. Over-representation analysis was performed with clusterProfiler using the Hallmark and Reactome collections. (3) Results: A total of 4312 differentially expressed genes (DEGs) and sRNAs were included in the enrichment analysis. In the Hallmark collection, genes regulated by nuclear factor kappa B in response to tumor necrosis factor, genes upregulated by signal transducer and activator of transcription 5 in response to interleukin 2 stimulation, genes upregulated in response to interferon-gamma, genes defining the inflammatory response, a subgroup of genes regulated by MYC-version 1 (v1), and genes upregulated during transplant rejection were significantly enriched in critically ill septic patients with CAP. Moreover, 88 pathways were identified in the Reactome database. (4) Conclusions: This study summarizes the reported DEGs in critically ill septic patients with CAP and investigates their functional implications. The results highlight the complexity of immune responses during CAP.
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Affiliation(s)
- Diego Viasus
- Department of Medicine, Division of Health Sciences, Universidad del Norte and Hospital Universidad del Norte, Barranquilla 081001, Colombia
| | - Lara Nonell
- Departament de Biociències, Universitat de Vic—Universitat Central de Catalunya, 08500 Barcelona, Spain;
| | - Carlos Restrepo
- Department of Medicine, Division of Health Sciences, Universidad del Norte and Hospital Universidad del Norte, Barranquilla 081001, Colombia
| | - Fabian Figueroa
- Department of Medicine, Division of Health Sciences, Universidad del Norte and Hospital Universidad del Norte, Barranquilla 081001, Colombia
| | - Carla Donado-Mazarrón
- Department of Infectious Diseases, Bellvitge University Hospital, Bellvitge Biomedical Research Institute (IDIBELL), University of Barcelona, 08907 Barcelona, Spain;
| | - Jordi Carratalà
- Department of Infectious Diseases, Bellvitge University Hospital, Bellvitge Biomedical Research Institute (IDIBELL), University of Barcelona, 08907 Barcelona, Spain;
- Centro de Investigación Biomédica en Red de Enfermedades Infecciosas (CIBERINFEC), Instituto de Salud Carlos III, 28029 Madrid, Spain
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8
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Sundaram B, Pandian N, Mall R, Wang Y, Sarkar R, Kim HJ, Malireddi RKS, Karki R, Janke LJ, Vogel P, Kanneganti TD. NLRP12-PANoptosome activates PANoptosis and pathology in response to heme and PAMPs. Cell 2023; 186:2783-2801.e20. [PMID: 37267949 PMCID: PMC10330523 DOI: 10.1016/j.cell.2023.05.005] [Citation(s) in RCA: 82] [Impact Index Per Article: 82.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 03/17/2023] [Accepted: 05/05/2023] [Indexed: 06/04/2023]
Abstract
Cytosolic innate immune sensors are critical for host defense and form complexes, such as inflammasomes and PANoptosomes, that induce inflammatory cell death. The sensor NLRP12 is associated with infectious and inflammatory diseases, but its activating triggers and roles in cell death and inflammation remain unclear. Here, we discovered that NLRP12 drives inflammasome and PANoptosome activation, cell death, and inflammation in response to heme plus PAMPs or TNF. TLR2/4-mediated signaling through IRF1 induced Nlrp12 expression, which led to inflammasome formation to induce maturation of IL-1β and IL-18. The inflammasome also served as an integral component of a larger NLRP12-PANoptosome that drove inflammatory cell death through caspase-8/RIPK3. Deletion of Nlrp12 protected mice from acute kidney injury and lethality in a hemolytic model. Overall, we identified NLRP12 as an essential cytosolic sensor for heme plus PAMPs-mediated PANoptosis, inflammation, and pathology, suggesting that NLRP12 and molecules in this pathway are potential drug targets for hemolytic and inflammatory diseases.
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Affiliation(s)
- Balamurugan Sundaram
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Nagakannan Pandian
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Raghvendra Mall
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Yaqiu Wang
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Roman Sarkar
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Hee Jin Kim
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | | | - Rajendra Karki
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Laura J Janke
- Animal Resources Center and the Veterinary Pathology Core, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Peter Vogel
- Animal Resources Center and the Veterinary Pathology Core, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
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Chawla DG, Cappuccio A, Tamminga A, Sealfon SC, Zaslavsky E, Kleinstein SH. Benchmarking transcriptional host response signatures for infection diagnosis. Cell Syst 2022; 13:974-988.e7. [PMID: 36549274 PMCID: PMC9768893 DOI: 10.1016/j.cels.2022.11.007] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 08/04/2022] [Accepted: 11/22/2022] [Indexed: 12/24/2022]
Abstract
Identification of host transcriptional response signatures has emerged as a new paradigm for infection diagnosis. For clinical applications, signatures must robustly detect the pathogen of interest without cross-reacting with unintended conditions. To evaluate the performance of infectious disease signatures, we developed a framework that includes a compendium of 17,105 transcriptional profiles capturing infectious and non-infectious conditions and a standardized methodology to assess robustness and cross-reactivity. Applied to 30 published signatures of infection, the analysis showed that signatures were generally robust in detecting viral and bacterial infections in independent data. Asymptomatic and chronic infections were also detectable, albeit with decreased performance. However, many signatures were cross-reactive with unintended infections and aging. In general, we found robustness and cross-reactivity to be conflicting objectives, and we identified signature properties associated with this trade-off. The data compendium and evaluation framework developed here provide a foundation for the development of signatures for clinical application. A record of this paper's transparent peer review process is included in the supplemental information.
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Affiliation(s)
- Daniel G Chawla
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA
| | - Antonio Cappuccio
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Andrea Tamminga
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA
| | - Stuart C Sealfon
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Elena Zaslavsky
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
| | - Steven H Kleinstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA; Department of Pathology and Department of Immunobiology, Yale School of Medicine, New Haven, CT 06511, USA.
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10
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Rao AM, Popper SJ, Gupta S, Davong V, Vaidya K, Chanthongthip A, Dittrich S, Robinson MT, Vongsouvath M, Mayxay M, Nawtaisong P, Karmacharya B, Thair SA, Bogoch I, Sweeney TE, Newton PN, Andrews JR, Relman DA, Khatri P. A robust host-response-based signature distinguishes bacterial and viral infections across diverse global populations. Cell Rep Med 2022; 3:100842. [PMID: 36543117 PMCID: PMC9797950 DOI: 10.1016/j.xcrm.2022.100842] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Revised: 07/12/2022] [Accepted: 11/09/2022] [Indexed: 12/24/2022]
Abstract
Limited sensitivity and specificity of current diagnostics lead to the erroneous prescription of antibiotics. Host-response-based diagnostics could address these challenges. However, using 4,200 samples across 69 blood transcriptome datasets from 20 countries from patients with bacterial or viral infections representing a broad spectrum of biological, clinical, and technical heterogeneity, we show current host-response-based gene signatures have lower accuracy to distinguish intracellular bacterial infections from viral infections than extracellular bacterial infections. Using these 69 datasets, we identify an 8-gene signature to distinguish intracellular or extracellular bacterial infections from viral infections with an area under the receiver operating characteristic curve (AUROC) > 0.91 (85.9% specificity and 90.2% sensitivity). In prospective cohorts from Nepal and Laos, the 8-gene classifier distinguished bacterial infections from viral infections with an AUROC of 0.94 (87.9% specificity and 91% sensitivity). The 8-gene signature meets the target product profile proposed by the World Health Organization and others for distinguishing bacterial and viral infections.
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Affiliation(s)
- Aditya M. Rao
- Institute for Immunity, Transplantation, and Infection, Stanford University School of Medicine, 240 Pasteur Dr., Biomedical Innovation Building, Room 1553, Stanford, CA, USA,Immunology Graduate Program, Department of Medicine, Stanford University, Stanford, CA, USA
| | - Stephen J. Popper
- Division of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University, Stanford, CA, USA
| | - Sanjana Gupta
- Institute for Immunity, Transplantation, and Infection, Stanford University School of Medicine, 240 Pasteur Dr., Biomedical Innovation Building, Room 1553, Stanford, CA, USA,Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, CA, USA
| | - Viengmon Davong
- Lao-Oxford-Mahosot Hospital-Wellcome Trust Research Unit, Microbiology Laboratory, Mahosot Hospital, Vientiane, Lao PDR
| | - Krista Vaidya
- Dhulikhel Hospital, Kathmandu University Hospital, Kavrepalanchok, Nepal
| | - Anisone Chanthongthip
- Lao-Oxford-Mahosot Hospital-Wellcome Trust Research Unit, Microbiology Laboratory, Mahosot Hospital, Vientiane, Lao PDR
| | - Sabine Dittrich
- Lao-Oxford-Mahosot Hospital-Wellcome Trust Research Unit, Microbiology Laboratory, Mahosot Hospital, Vientiane, Lao PDR,Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Matthew T. Robinson
- Lao-Oxford-Mahosot Hospital-Wellcome Trust Research Unit, Microbiology Laboratory, Mahosot Hospital, Vientiane, Lao PDR,Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Manivanh Vongsouvath
- Lao-Oxford-Mahosot Hospital-Wellcome Trust Research Unit, Microbiology Laboratory, Mahosot Hospital, Vientiane, Lao PDR
| | - Mayfong Mayxay
- Lao-Oxford-Mahosot Hospital-Wellcome Trust Research Unit, Microbiology Laboratory, Mahosot Hospital, Vientiane, Lao PDR,Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK,Institute of Research and Education Development (IRED), University of Health Sciences, Ministry of Health, Vientiane, Lao PDR
| | - Pruksa Nawtaisong
- Lao-Oxford-Mahosot Hospital-Wellcome Trust Research Unit, Microbiology Laboratory, Mahosot Hospital, Vientiane, Lao PDR
| | - Biraj Karmacharya
- Dhulikhel Hospital, Kathmandu University Hospital, Kavrepalanchok, Nepal
| | - Simone A. Thair
- Institute for Immunity, Transplantation, and Infection, Stanford University School of Medicine, 240 Pasteur Dr., Biomedical Innovation Building, Room 1553, Stanford, CA, USA,Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, CA, USA
| | - Isaac Bogoch
- Department of Medicine, University of Toronto, Toronto, ON, Canada
| | | | - Paul N. Newton
- Lao-Oxford-Mahosot Hospital-Wellcome Trust Research Unit, Microbiology Laboratory, Mahosot Hospital, Vientiane, Lao PDR,Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Jason R. Andrews
- Division of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University, Stanford, CA, USA
| | - David A. Relman
- Institute for Immunity, Transplantation, and Infection, Stanford University School of Medicine, 240 Pasteur Dr., Biomedical Innovation Building, Room 1553, Stanford, CA, USA,Division of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University, Stanford, CA, USA,Department of Microbiology and Immunology, Stanford University, Stanford, CA, USA,Infectious Diseases Section, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA
| | - Purvesh Khatri
- Institute for Immunity, Transplantation, and Infection, Stanford University School of Medicine, 240 Pasteur Dr., Biomedical Innovation Building, Room 1553, Stanford, CA, USA,Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, CA, USA,Corresponding author
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11
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Ma Q, Zhang M, Zhang C, Teng X, Yang L, Tian Y, Wang J, Han D, Tan W. An automated DNA computing platform for rapid etiological diagnostics. SCIENCE ADVANCES 2022; 8:eade0453. [PMID: 36427311 PMCID: PMC9699674 DOI: 10.1126/sciadv.ade0453] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/15/2023]
Abstract
Rapid and accurate classification of the etiology for acute respiratory illness not only helps establish timely therapeutic plans but also prevents inappropriate use of antibiotics. Host gene expression patterns in peripheral blood can discriminate bacterial from viral causes of acute respiratory infection (ARI) but suffer from long turnaround time, as well as high cost resulting from the measurement methods of microarrays and next-generation sequencing. Here, we developed an automated DNA computing-based platform that can implement an in silico trained classification model at the molecular level with seven different mRNA expression patterns for accurate diagnosis of ARI etiology in 4 hours. By integrating sample loading, marker amplification, classifier implementation, and results reporting into one platform, we obtained a diagnostic accuracy of 87% in 80 clinical samples without the aid of computer and laboratory technicians. This platform creates opportunities toward an accurate, rapid, low-cost, and automated diagnosis of disease etiology in emergency departments or point-of-care clinics.
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Affiliation(s)
- Qian Ma
- Zhejiang Cancer Hospital, The Key Laboratory of Zhejiang Province for Aptamers and Theranostics, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang 310022, China
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China
- Intellinosis Biotechnologies Co. Ltd., Shanghai, China
| | - Mingzhi Zhang
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China
| | - Chao Zhang
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China
- Intellinosis Biotechnologies Co. Ltd., Shanghai, China
- Corresponding author. (D.H.); (W.T.); (C.Z.)
| | - Xiaoyan Teng
- Department of Laboratory Medicine, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai 201306, China
| | - Linlin Yang
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China
| | - Yuan Tian
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China
| | - Junyan Wang
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China
| | - Da Han
- Zhejiang Cancer Hospital, The Key Laboratory of Zhejiang Province for Aptamers and Theranostics, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang 310022, China
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China
- Corresponding author. (D.H.); (W.T.); (C.Z.)
| | - Weihong Tan
- Zhejiang Cancer Hospital, The Key Laboratory of Zhejiang Province for Aptamers and Theranostics, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang 310022, China
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China
- Corresponding author. (D.H.); (W.T.); (C.Z.)
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12
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Mousavian Z, Folkesson E, Fröberg G, Foroogh F, Correia-Neves M, Bruchfeld J, Källenius G, Sundling C. A protein signature associated with active tuberculosis identified by plasma profiling and network-based analysis. iScience 2022; 25:105652. [PMID: 36561889 PMCID: PMC9763869 DOI: 10.1016/j.isci.2022.105652] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 09/19/2022] [Accepted: 11/18/2022] [Indexed: 11/23/2022] Open
Abstract
Annually, approximately 10 million people are diagnosed with active tuberculosis (TB), and 1.4 million die of the disease. If left untreated, each person with active TB will infect 10-15 new individuals. The lack of non-sputum-based diagnostic tests leads to delayed diagnoses of active pulmonary TB cases, contributing to continued disease transmission. In this exploratory study, we aimed to identify biomarkers associated with active TB. We assessed the plasma levels of 92 proteins associated with inflammation in individuals with active TB (n = 20), latent TB (n = 14), or healthy controls (n = 10). Using co-expression network analysis, we identified one module of proteins with strong association with active TB. We removed proteins from the module that had low abundance or were associated with non-TB diseases in published transcriptomic datasets, resulting in a 12-protein plasma signature that was highly enriched in individuals with pulmonary and extrapulmonary TB and was further associated with disease severity.
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Affiliation(s)
- Zaynab Mousavian
- Division of Infectious Diseases, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
- Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- School of Mathematics, Statistics and Computer Science, College of Science, University of Tehran, Tehran, Iran
| | - Elin Folkesson
- Division of Infectious Diseases, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
- Department of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden
| | - Gabrielle Fröberg
- Division of Infectious Diseases, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Microbiology, Karolinska University Laboratory, Karolinska University Hospital, Stockholm, Sweden
| | - Fariba Foroogh
- Division of Infectious Diseases, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
- Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden
| | - Margarida Correia-Neves
- Division of Infectious Diseases, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
- Life and Health Sciences Research Institute, School of Medicine, University of Minho, Braga, Portugal
- ICVS/3B’s, PT Government Associate Laboratory, Braga, Portugal
| | - Judith Bruchfeld
- Division of Infectious Diseases, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
- Department of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden
| | - Gunilla Källenius
- Division of Infectious Diseases, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
- Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden
| | - Christopher Sundling
- Division of Infectious Diseases, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
- Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden
- Corresponding author
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13
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Chen L, Hua J, He X. Co-expression network analysis identifies potential candidate hub genes in severe influenza patients needing invasive mechanical ventilation. BMC Genomics 2022; 23:703. [PMID: 36243706 PMCID: PMC9569050 DOI: 10.1186/s12864-022-08915-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Accepted: 09/26/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Influenza is a contagious disease that affects people of all ages and is linked to considerable mortality during epidemics and occasional outbreaks. Moreover, effective immunological biomarkers are needed for elucidating aetiology and preventing and treating severe influenza. Herein, we aimed to evaluate the key genes linked with the disease severity in influenza patients needing invasive mechanical ventilation (IMV). Three gene microarray data sets (GSE101702, GSE21802, and GSE111368) from blood samples of influenza patients were made available by the Gene Expression Omnibus (GEO) database. The GSE101702 and GSE21802 data sets were combined to create the training set. Hub indicators for IMV patients with severe influenza were determined using differential expression analysis and Weighted correlation network analysis (WGCNA) from the training set. The receiver operating characteristic curve (ROC) was also used to evaluate the hub genes from the test set's diagnostic accuracy. Different immune cells' infiltration levels in the expression profile and their correlation with hub gene markers were examined using single-sample gene set enrichment analysis (ssGSEA). RESULTS In the present study, we evaluated a total of 447 differential genes. WGCNA identified eight co-expression modules, with the red module having the strongest correlation with IMV patients. Differential genes were combined to obtain 3 hub genes (HLA-DPA1, HLA-DRB3, and CECR1). The identified genes were investigated as potential indicators for patients with severe influenza who required IMV using the least absolute shrinkage and selection operator (LASSO) approach. The ROC showed the diagnostic value of the three hub genes in determining the severity of influenza. Using ssGSEA, it has been revealed that the expression of key genes was negatively correlated with neutrophil activation and positively associated with adaptive cellular immune response. CONCLUSION We evaluated three novel hub genes that could be linked to the immunopathological mechanism of severe influenza patients who require IMV treatment and could be used as potential biomarkers for severe influenza prevention and treatment.
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Affiliation(s)
- Liang Chen
- Department of Infectious Diseases, Nanjing Lishui People's Hospital, Zhongda Hospital Lishui Branch, Southeast University, Nanjing, China
| | - Jie Hua
- Department of Gastroenterology, Liyang People's Hospital, Liyang Branch Hospital of Jiangsu Province Hospital, Nanjing, China
| | - Xiaopu He
- Department of Geriatric Gastroenterology, The First Affiliated Hospital With Nanjing Medical University, No.300 Guangzhou Road, Nanjing city, 210029, Jiangsu Province, China.
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14
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Gómez-Carballa A, Rivero-Calle I, Pardo-Seco J, Gómez-Rial J, Rivero-Velasco C, Rodríguez-Núñez N, Barbeito-Castiñeiras G, Pérez-Freixo H, Cebey-López M, Barral-Arca R, Rodriguez-Tenreiro C, Dacosta-Urbieta A, Bello X, Pischedda S, Currás-Tuala MJ, Viz-Lasheras S, Martinón-Torres F, Salas A. A multi-tissue study of immune gene expression profiling highlights the key role of the nasal epithelium in COVID-19 severity. ENVIRONMENTAL RESEARCH 2022; 210:112890. [PMID: 35202626 PMCID: PMC8861187 DOI: 10.1016/j.envres.2022.112890] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Revised: 01/11/2022] [Accepted: 02/02/2022] [Indexed: 05/08/2023]
Abstract
Coronavirus Disease-19 (COVID-19) symptoms range from mild to severe illness; the cause for this differential response to infection remains unknown. Unravelling the immune mechanisms acting at different levels of the colonization process might be key to understand these differences. We carried out a multi-tissue (nasal, buccal and blood; n = 156) gene expression analysis of immune-related genes from patients affected by different COVID-19 severities, and healthy controls through the nCounter technology. Mild and asymptomatic cases showed a powerful innate antiviral response in nasal epithelium, characterized by activation of interferon (IFN) pathway and downstream cascades, successfully controlling the infection at local level. In contrast, weak macrophage/monocyte driven innate antiviral response and lack of IFN signalling activity were present in severe cases. Consequently, oral mucosa from severe patients showed signals of viral activity, cell arresting and viral dissemination to the lower respiratory tract, which ultimately could explain the exacerbated innate immune response and impaired adaptative immune responses observed at systemic level. Results from saliva transcriptome suggest that the buccal cavity might play a key role in SARS-CoV-2 infection and dissemination in patients with worse prognosis. Co-expression network analysis adds further support to these findings, by detecting modules specifically correlated with severity involved in the abovementioned biological routes; this analysis also provides new candidate genes that might be tested as biomarkers in future studies. We also found tissue specific severity-related signatures mainly represented by genes involved in the innate immune system and cytokine/chemokine signalling. Local immune response could be key to determine the course of the systemic response and thus COVID-19 severity. Our findings provide a framework to investigate severity host gene biomarkers and pathways that might be relevant to diagnosis, prognosis, and therapy.
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Affiliation(s)
- Alberto Gómez-Carballa
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria (IDIS) de Santiago, Santiago de Compostela, Spain; Unidade de Xenética, Instituto de Ciencias Forenses (INCIFOR), Facultade de Medicina, Universidade de Santiago de Compostela (USC), and GenPoB Research Group, Instituto de Investigación Sanitaria (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), Galicia, Spain; Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain
| | - Irene Rivero-Calle
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria (IDIS) de Santiago, Santiago de Compostela, Spain; Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain; Translational Pediatrics and Infectious Diseases, Department of Pediatrics, Hospital Clínico Universitario de Santiago de Compostela, Santiago de Compostela, Spain
| | - Jacobo Pardo-Seco
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria (IDIS) de Santiago, Santiago de Compostela, Spain; Unidade de Xenética, Instituto de Ciencias Forenses (INCIFOR), Facultade de Medicina, Universidade de Santiago de Compostela (USC), and GenPoB Research Group, Instituto de Investigación Sanitaria (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), Galicia, Spain; Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain
| | - José Gómez-Rial
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria (IDIS) de Santiago, Santiago de Compostela, Spain; Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain; Laboratorio de Inmunología. Servicio de Análisis Clínicos. Hospital Clínico Universitario (SERGAS), Galicia, Spain
| | - Carmen Rivero-Velasco
- Intensive Medicine Department, Hospital Clìnico Universitario de Santiago de Compostela, Galicia, Spain
| | - Nuria Rodríguez-Núñez
- Pneumology Department, Hospital Clìnico Universitario de Santiago de Compostela, Galicia, Spain
| | - Gema Barbeito-Castiñeiras
- Clinical Microbiology Unit, Complexo Hospitalario Universitario de Santiago Santiago de Compostela, Spain; Instituto de Investigación Sanitaria de Santiago, Santiago de Compostela, Spain
| | - Hugo Pérez-Freixo
- Preventive Medicine Department, Hospital Clínico Universitario de Santiago de Compostela, Spain
| | - Miriam Cebey-López
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria (IDIS) de Santiago, Santiago de Compostela, Spain; Unidade de Xenética, Instituto de Ciencias Forenses (INCIFOR), Facultade de Medicina, Universidade de Santiago de Compostela (USC), and GenPoB Research Group, Instituto de Investigación Sanitaria (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), Galicia, Spain; Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain
| | - Ruth Barral-Arca
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria (IDIS) de Santiago, Santiago de Compostela, Spain; Unidade de Xenética, Instituto de Ciencias Forenses (INCIFOR), Facultade de Medicina, Universidade de Santiago de Compostela (USC), and GenPoB Research Group, Instituto de Investigación Sanitaria (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), Galicia, Spain; Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain
| | - Carmen Rodriguez-Tenreiro
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria (IDIS) de Santiago, Santiago de Compostela, Spain; Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain; Translational Pediatrics and Infectious Diseases, Department of Pediatrics, Hospital Clínico Universitario de Santiago de Compostela, Santiago de Compostela, Spain
| | - Ana Dacosta-Urbieta
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria (IDIS) de Santiago, Santiago de Compostela, Spain; Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain; Translational Pediatrics and Infectious Diseases, Department of Pediatrics, Hospital Clínico Universitario de Santiago de Compostela, Santiago de Compostela, Spain
| | - Xabier Bello
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria (IDIS) de Santiago, Santiago de Compostela, Spain; Unidade de Xenética, Instituto de Ciencias Forenses (INCIFOR), Facultade de Medicina, Universidade de Santiago de Compostela (USC), and GenPoB Research Group, Instituto de Investigación Sanitaria (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), Galicia, Spain; Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain
| | - Sara Pischedda
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria (IDIS) de Santiago, Santiago de Compostela, Spain; Unidade de Xenética, Instituto de Ciencias Forenses (INCIFOR), Facultade de Medicina, Universidade de Santiago de Compostela (USC), and GenPoB Research Group, Instituto de Investigación Sanitaria (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), Galicia, Spain; Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain
| | - María José Currás-Tuala
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria (IDIS) de Santiago, Santiago de Compostela, Spain; Unidade de Xenética, Instituto de Ciencias Forenses (INCIFOR), Facultade de Medicina, Universidade de Santiago de Compostela (USC), and GenPoB Research Group, Instituto de Investigación Sanitaria (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), Galicia, Spain; Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain
| | - Sandra Viz-Lasheras
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria (IDIS) de Santiago, Santiago de Compostela, Spain; Unidade de Xenética, Instituto de Ciencias Forenses (INCIFOR), Facultade de Medicina, Universidade de Santiago de Compostela (USC), and GenPoB Research Group, Instituto de Investigación Sanitaria (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), Galicia, Spain; Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain
| | - Federico Martinón-Torres
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria (IDIS) de Santiago, Santiago de Compostela, Spain; Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain; Translational Pediatrics and Infectious Diseases, Department of Pediatrics, Hospital Clínico Universitario de Santiago de Compostela, Santiago de Compostela, Spain
| | - Antonio Salas
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria (IDIS) de Santiago, Santiago de Compostela, Spain; Unidade de Xenética, Instituto de Ciencias Forenses (INCIFOR), Facultade de Medicina, Universidade de Santiago de Compostela (USC), and GenPoB Research Group, Instituto de Investigación Sanitaria (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), Galicia, Spain; Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain.
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15
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Kreitmann L, Bodinier M, Fleurie A, Imhoff K, Cazalis MA, Peronnet E, Cerrato E, Tardiveau C, Conti F, Llitjos JF, Textoris J, Monneret G, Blein S, Brengel-Pesce K. Mortality Prediction in Sepsis With an Immune-Related Transcriptomics Signature: A Multi-Cohort Analysis. Front Med (Lausanne) 2022; 9:930043. [PMID: 35847809 PMCID: PMC9280291 DOI: 10.3389/fmed.2022.930043] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Accepted: 06/08/2022] [Indexed: 12/29/2022] Open
Abstract
Background Novel biomarkers are needed to progress toward individualized patient care in sepsis. The immune profiling panel (IPP) prototype has been designed as a fully-automated multiplex tool measuring expression levels of 26 genes in sepsis patients to explore immune functions, determine sepsis endotypes and guide personalized clinical management. The performance of the IPP gene set to predict 30-day mortality has not been extensively characterized in heterogeneous cohorts of sepsis patients. Methods Publicly available microarray data of sepsis patients with widely variable demographics, clinical characteristics and ethnical background were co-normalized, and the performance of the IPP gene set to predict 30-day mortality was assessed using a combination of machine learning algorithms. Results We collected data from 1,801 arrays sampled on sepsis patients and 598 sampled on controls in 17 studies. When gene expression was assayed at day 1 following admission (1,437 arrays sampled on sepsis patients, of whom 1,161 were alive and 276 (19.2%) were dead at day 30), the IPP gene set showed good performance to predict 30-day mortality, with an area under the receiving operating characteristics curve (AUROC) of 0.710 (CI 0.652-0.768). Importantly, there was no statistically significant improvement in predictive performance when training the same models with all genes common to the 17 microarray studies (n = 7,122 genes), with an AUROC = 0.755 (CI 0.697-0.813, p = 0.286). In patients with gene expression data sampled at day 3 following admission or later, the IPP gene set had higher performance, with an AUROC = 0.804 (CI 0.643-0.964), while the total gene pool had an AUROC = 0.787 (CI 0.610-0.965, p = 0.811). Conclusion Using pooled publicly-available gene expression data from multiple cohorts, we showed that the IPP gene set, an immune-related transcriptomics signature conveys relevant information to predict 30-day mortality when sampled at day 1 following admission. Our data also suggests that higher predictive performance could be obtained when assaying gene expression at later time points during the course of sepsis. Prospective studies are needed to confirm these findings using the IPP gene set on its dedicated measurement platform.
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Affiliation(s)
- Louis Kreitmann
- EA 7426 “Pathophysiology of Injury-Induced Immunosuppression”, Joint Research Unit Université Claude Bernard Lyon 1 – Hospices Civils de Lyon – bioMérieux, Lyon, France
- Open Innovation and Partnerships (OIP), bioMérieux S.A., Marcy-l’Étoile, France
| | - Maxime Bodinier
- EA 7426 “Pathophysiology of Injury-Induced Immunosuppression”, Joint Research Unit Université Claude Bernard Lyon 1 – Hospices Civils de Lyon – bioMérieux, Lyon, France
- Open Innovation and Partnerships (OIP), bioMérieux S.A., Marcy-l’Étoile, France
| | - Aurore Fleurie
- EA 7426 “Pathophysiology of Injury-Induced Immunosuppression”, Joint Research Unit Université Claude Bernard Lyon 1 – Hospices Civils de Lyon – bioMérieux, Lyon, France
- Open Innovation and Partnerships (OIP), bioMérieux S.A., Marcy-l’Étoile, France
| | - Katia Imhoff
- Data Science, bioMérieux S.A., Marcy-l’Etoile, France
| | - Marie-Angelique Cazalis
- EA 7426 “Pathophysiology of Injury-Induced Immunosuppression”, Joint Research Unit Université Claude Bernard Lyon 1 – Hospices Civils de Lyon – bioMérieux, Lyon, France
- Open Innovation and Partnerships (OIP), bioMérieux S.A., Marcy-l’Étoile, France
| | - Estelle Peronnet
- EA 7426 “Pathophysiology of Injury-Induced Immunosuppression”, Joint Research Unit Université Claude Bernard Lyon 1 – Hospices Civils de Lyon – bioMérieux, Lyon, France
- Open Innovation and Partnerships (OIP), bioMérieux S.A., Marcy-l’Étoile, France
| | - Elisabeth Cerrato
- EA 7426 “Pathophysiology of Injury-Induced Immunosuppression”, Joint Research Unit Université Claude Bernard Lyon 1 – Hospices Civils de Lyon – bioMérieux, Lyon, France
- Open Innovation and Partnerships (OIP), bioMérieux S.A., Marcy-l’Étoile, France
| | - Claire Tardiveau
- EA 7426 “Pathophysiology of Injury-Induced Immunosuppression”, Joint Research Unit Université Claude Bernard Lyon 1 – Hospices Civils de Lyon – bioMérieux, Lyon, France
- Open Innovation and Partnerships (OIP), bioMérieux S.A., Marcy-l’Étoile, France
| | - Filippo Conti
- EA 7426 “Pathophysiology of Injury-Induced Immunosuppression”, Joint Research Unit Université Claude Bernard Lyon 1 – Hospices Civils de Lyon – bioMérieux, Lyon, France
- Immunology Laboratory, Edouard Herriot Hospital – Hospices Civils de Lyon, Lyon, France
| | - Jean-François Llitjos
- EA 7426 “Pathophysiology of Injury-Induced Immunosuppression”, Joint Research Unit Université Claude Bernard Lyon 1 – Hospices Civils de Lyon – bioMérieux, Lyon, France
- Open Innovation and Partnerships (OIP), bioMérieux S.A., Marcy-l’Étoile, France
- Anaesthesia and Critical Care Medicine Department, Hospices Civils de Lyon, Edouard Herriot Hospital, Lyon, France
| | | | - Guillaume Monneret
- EA 7426 “Pathophysiology of Injury-Induced Immunosuppression”, Joint Research Unit Université Claude Bernard Lyon 1 – Hospices Civils de Lyon – bioMérieux, Lyon, France
- Immunology Laboratory, Edouard Herriot Hospital – Hospices Civils de Lyon, Lyon, France
| | - Sophie Blein
- Data Science, bioMérieux S.A., Marcy-l’Etoile, France
| | - Karen Brengel-Pesce
- EA 7426 “Pathophysiology of Injury-Induced Immunosuppression”, Joint Research Unit Université Claude Bernard Lyon 1 – Hospices Civils de Lyon – bioMérieux, Lyon, France
- Open Innovation and Partnerships (OIP), bioMérieux S.A., Marcy-l’Étoile, France
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16
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Yao L, Rey DA, Bulgarelli L, Kast R, Osborn J, Van Ark E, Fang LT, Lau B, Lam H, Teixeira LM, Neto AS, Bellomo R, Deliberato RO. Gene Expression Scoring of Immune Activity Levels for Precision Use of Hydrocortisone in Vasodilatory Shock. Shock 2022; 57:384-391. [PMID: 35081076 PMCID: PMC8868213 DOI: 10.1097/shk.0000000000001910] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Revised: 12/06/2021] [Accepted: 01/07/2022] [Indexed: 11/26/2022]
Abstract
PURPOSE Among patients with vasodilatory shock, gene expression scores may identify different immune states. We aimed to test whether such scores are robust in identifying patients' immune state and predicting response to hydrocortisone treatment in vasodilatory shock. MATERIALS AND METHODS We selected genes to generate continuous scores to define previously established subclasses of sepsis. We used these scores to identify a patient's immune state. We evaluated the potential for these states to assess the differential effect of hydrocortisone in two randomized clinical trials of hydrocortisone versus placebo in vasodilatory shock. RESULTS We initially identified genes associated with immune-adaptive, immune-innate, immune-coagulant functions. From these genes, 15 were most relevant to generate expression scores related to each of the functions. These scores were used to identify patients as immune-adaptive prevalent (IA-P) and immune-innate prevalent (IN-P). In IA-P patients, hydrocortisone therapy increased 28-day mortality in both trials (43.3% vs 14.7%, P = 0.028) and (57.1% vs 0.0%, P = 0.99). In IN-P patients, this effect was numerically reversed. CONCLUSIONS Gene expression scores identified the immune state of vasodilatory shock patients, one of which (IA-P) identified those who may be harmed by hydrocortisone. Gene expression scores may help advance the field of personalized medicine.
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Affiliation(s)
- Lijing Yao
- Department of Clinical Data Science, Endpoint Health Inc, Palo Alto, California
| | - Diego Ariel Rey
- Department of Clinical Data Science, Endpoint Health Inc, Palo Alto, California
| | - Lucas Bulgarelli
- Department of Clinical Data Science, Endpoint Health Inc, Palo Alto, California
| | - Rachel Kast
- Department of Clinical Data Science, Endpoint Health Inc, Palo Alto, California
| | - Jeff Osborn
- Department of Clinical Data Science, Endpoint Health Inc, Palo Alto, California
| | - Emily Van Ark
- Department of Clinical Data Science, Endpoint Health Inc, Palo Alto, California
| | - Li Tai Fang
- Department of Clinical Data Science, Endpoint Health Inc, Palo Alto, California
| | - Bayo Lau
- Bioinformatics Department, HypaHub Inc, San Jose, California, USA
| | - Hugo Lam
- Bioinformatics Department, HypaHub Inc, San Jose, California, USA
| | | | - Ary Serpa Neto
- Department of Critical Care Medicine, Hospital Israelita Albert Einstein, São Paulo, Brazil
- Australian and New Zealand Intensive Care Research Centre (ANZIC-RC), School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
- Department of Critical Care, Melbourne Medical School, University of Melbourne, Austin Hospital, Melbourne, Australia
- Data Analytics Research and Evaluation (DARE) Centre, Austin Hospital, Melbourne, Australia
| | - Rinaldo Bellomo
- Australian and New Zealand Intensive Care Research Centre (ANZIC-RC), School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
- Department of Critical Care, Melbourne Medical School, University of Melbourne, Austin Hospital, Melbourne, Australia
- Data Analytics Research and Evaluation (DARE) Centre, Austin Hospital, Melbourne, Australia
- Department of Intensive Care, Austin Hospital, Melbourne, Australia
- Department of Intensive Care, Royal Melbourne Hospital, Melbourne, Australia
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17
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Bodkin N, Ross M, McClain MT, Ko ER, Woods CW, Ginsburg GS, Henao R, Tsalik EL. Systematic comparison of published host gene expression signatures for bacterial/viral discrimination. Genome Med 2022; 14:18. [PMID: 35184750 PMCID: PMC8858657 DOI: 10.1186/s13073-022-01025-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Accepted: 02/09/2022] [Indexed: 12/13/2022] Open
Abstract
Background Measuring host gene expression is a promising diagnostic strategy to discriminate bacterial and viral infections. Multiple signatures of varying size, complexity, and target populations have been described. However, there is little information to indicate how the performance of various published signatures compare to one another. Methods This systematic comparison of host gene expression signatures evaluated the performance of 28 signatures, validating them in 4589 subjects from 51 publicly available datasets. Thirteen COVID-specific datasets with 1416 subjects were included in a separate analysis. Individual signature performance was evaluated using the area under the receiving operating characteristic curve (AUC) value. Overall signature performance was evaluated using median AUCs and accuracies. Results Signature performance varied widely, with median AUCs ranging from 0.55 to 0.96 for bacterial classification and 0.69–0.97 for viral classification. Signature size varied (1–398 genes), with smaller signatures generally performing more poorly (P < 0.04). Viral infection was easier to diagnose than bacterial infection (84% vs. 79% overall accuracy, respectively; P < .001). Host gene expression classifiers performed more poorly in some pediatric populations (3 months–1 year and 2–11 years) compared to the adult population for both bacterial infection (73% and 70% vs. 82%, respectively; P < .001) and viral infection (80% and 79% vs. 88%, respectively; P < .001). We did not observe classification differences based on illness severity as defined by ICU admission for bacterial or viral infections. The median AUC across all signatures for COVID-19 classification was 0.80 compared to 0.83 for viral classification in the same datasets. Conclusions In this systematic comparison of 28 host gene expression signatures, we observed differences based on a signature’s size and characteristics of the validation population, including age and infection type. However, populations used for signature discovery did not impact performance, underscoring the redundancy among many of these signatures. Furthermore, differential performance in specific populations may only be observable through this type of large-scale validation. Supplementary Information The online version contains supplementary material available at 10.1186/s13073-022-01025-x.
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18
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A 6-mRNA host response classifier in whole blood predicts outcomes in COVID-19 and other acute viral infections. Sci Rep 2022; 12:889. [PMID: 35042868 PMCID: PMC8766462 DOI: 10.1038/s41598-021-04509-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2021] [Accepted: 12/23/2021] [Indexed: 01/26/2023] Open
Abstract
Predicting the severity of COVID-19 remains an unmet medical need. Our objective was to develop a blood-based host-gene-expression classifier for the severity of viral infections and validate it in independent data, including COVID-19. We developed a logistic regression-based classifier for the severity of viral infections and validated it in multiple viral infection settings including COVID-19. We used training data (N = 705) from 21 retrospective transcriptomic clinical studies of influenza and other viral illnesses looking at a preselected panel of host immune response messenger RNAs. We selected 6 host RNAs and trained logistic regression classifier with a cross-validation area under curve of 0.90 for predicting 30-day mortality in viral illnesses. Next, in 1417 samples across 21 independent retrospective cohorts the locked 6-RNA classifier had an area under curve of 0.94 for discriminating patients with severe vs. non-severe infection. Next, in independent cohorts of prospectively (N = 97) and retrospectively (N = 100) enrolled patients with confirmed COVID-19, the classifier had an area under curve of 0.89 and 0.87, respectively, for identifying patients with severe respiratory failure or 30-day mortality. Finally, we developed a loop-mediated isothermal gene expression assay for the 6-messenger-RNA panel to facilitate implementation as a rapid assay. With further study, the classifier could assist in the risk assessment of COVID-19 and other acute viral infections patients to determine severity and level of care, thereby improving patient management and reducing healthcare burden.
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19
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Ross M, Henao R, Burke TW, Ko ER, McClain MT, Ginsburg GS, Woods CW, Tsalik EL. A comparison of host response strategies to distinguish bacterial and viral infection. PLoS One 2021; 16:e0261385. [PMID: 34905580 PMCID: PMC8670660 DOI: 10.1371/journal.pone.0261385] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 11/29/2021] [Indexed: 11/18/2022] Open
Abstract
OBJECTIVES Compare three host response strategies to distinguish bacterial and viral etiologies of acute respiratory illness (ARI). METHODS In this observational cohort study, procalcitonin, a 3-protein panel (CRP, IP-10, TRAIL), and a host gene expression mRNA panel were measured in 286 subjects with ARI from four emergency departments. Multinomial logistic regression and leave-one-out cross validation were used to evaluate the protein and mRNA tests. RESULTS The mRNA panel performed better than alternative strategies to identify bacterial infection: AUC 0.93 vs. 0.83 for the protein panel and 0.84 for procalcitonin (P<0.02 for each comparison). This corresponded to a sensitivity and specificity of 92% and 83% for the mRNA panel, 81% and 73% for the protein panel, and 68% and 87% for procalcitonin, respectively. A model utilizing all three strategies was the same as mRNA alone. For the diagnosis of viral infection, the AUC was 0.93 for mRNA and 0.84 for the protein panel (p<0.05). This corresponded to a sensitivity and specificity of 89% and 82% for the mRNA panel, and 85% and 62% for the protein panel, respectively. CONCLUSIONS A gene expression signature was the most accurate host response strategy for classifying subjects with bacterial, viral, or non-infectious ARI.
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Affiliation(s)
- Melissa Ross
- Duke University School of Medicine, Durham, NC, United States of America
| | - Ricardo Henao
- Duke Center for Applied Genomics & Precision Medicine, Duke University School of Medicine, Durham, NC, United States of America
- Department of Electrical and Computer Engineering, Duke University, Durham, NC, United States of America
| | - Thomas W. Burke
- Duke Center for Applied Genomics & Precision Medicine, Duke University School of Medicine, Durham, NC, United States of America
| | - Emily R. Ko
- Duke Center for Applied Genomics & Precision Medicine, Duke University School of Medicine, Durham, NC, United States of America
- Duke Regional Hospital, Durham, NC, United States of America
| | - Micah T. McClain
- Duke Center for Applied Genomics & Precision Medicine, Duke University School of Medicine, Durham, NC, United States of America
- Medical Service, Durham Veterans Affairs Health Care System, Durham, NC, United States of America
| | - Geoffrey S. Ginsburg
- Duke Center for Applied Genomics & Precision Medicine, Duke University School of Medicine, Durham, NC, United States of America
| | - Christopher W. Woods
- Duke Center for Applied Genomics & Precision Medicine, Duke University School of Medicine, Durham, NC, United States of America
- Medical Service, Durham Veterans Affairs Health Care System, Durham, NC, United States of America
| | - Ephraim L. Tsalik
- Duke Center for Applied Genomics & Precision Medicine, Duke University School of Medicine, Durham, NC, United States of America
- Emergency Medicine Service, Durham Veterans Affairs Health Care System, Durham, NC, United States of America
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20
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Liu Z, Huo JH, Dong WT, Sun GD, Li FJ, Zhang YN, Qin ZW, Pengna J, Wang WM. A Study Based on Metabolomics, Network Pharmacology, and Experimental Verification to Explore the Mechanism of Qinbaiqingfei Concentrated Pills in the treatment of Mycoplasma Pneumonia. Front Pharmacol 2021; 12:761883. [PMID: 34803705 PMCID: PMC8599429 DOI: 10.3389/fphar.2021.761883] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Accepted: 09/27/2021] [Indexed: 12/13/2022] Open
Abstract
Qinbaiqingfei concentrated pills (QB) are a commonly used medicine for the treatment of mycoplasma pneumonia in China, and the mechanism of action of QB needs to be studied further. Therefore, we use a combination of metabolomics and network pharmacology to clarify the mechanism of QB. Nontarget metabolomics studies were performed on rat serum, urine, and lung tissues, and 56 therapeutic biomarkers were found. Subsequently, the components of QB absorbed into the blood and lung tissues were clarified, and based on this finding, the core target of network pharmacology was predicted. The enrichment analysis of biomarkers–genes finally confirmed their close relationship with the NF-κB signaling pathway. By western blotting expression of the proteins in the lung tissue–related signaling pathways, it is finally confirmed that QB inhibits the NF-κB signaling pathway through SIRT1, IL-10 and MMP9, CTNNB1, EGFR, and other targets. It plays a role in regulating immunity, regulating metabolism, and treating diseases.
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Affiliation(s)
- Zheng Liu
- Heilongjiang Academy of Chinese Medicine, Institute of Chinese Materia Medica, Harbin, China
| | - Jin-Hai Huo
- Heilongjiang Academy of Chinese Medicine, Institute of Chinese Materia Medica, Harbin, China
| | - Wen-Ting Dong
- Heilongjiang Academy of Chinese Medicine, Institute of Chinese Materia Medica, Harbin, China
| | - Guo-Dong Sun
- Heilongjiang Academy of Chinese Medicine, Institute of Chinese Materia Medica, Harbin, China
| | - Feng-Jin Li
- Heilongjiang Academy of Chinese Medicine, Institute of Chinese Materia Medica, Harbin, China
| | - Ya-Nan Zhang
- Heilongjiang Academy of Chinese Medicine, Institute of Chinese Materia Medica, Harbin, China
| | - Zhi-Wei Qin
- Heilongjiang Academy of Chinese Medicine, Institute of Chinese Materia Medica, Harbin, China
| | - Jiang Pengna
- Heilongjiang University of Chinese Medicine, Harbin, China
| | - Wei-Ming Wang
- Heilongjiang Academy of Chinese Medicine, Institute of Chinese Materia Medica, Harbin, China
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21
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Tsalik EL, Fiorino C, Aqeel A, Liu Y, Henao R, Ko ER, Burke TW, Reller ME, Bodinayake CK, Nagahawatte A, Arachchi WK, Devasiri V, Kurukulasooriya R, McClain MT, Woods CW, Ginsburg GS, Tillekeratne LG, Schughart K. The Host Response to Viral Infections Reveals Common and Virus-Specific Signatures in the Peripheral Blood. Front Immunol 2021; 12:741837. [PMID: 34777354 PMCID: PMC8578928 DOI: 10.3389/fimmu.2021.741837] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Accepted: 09/21/2021] [Indexed: 11/13/2022] Open
Abstract
Viruses cause a wide spectrum of clinical disease, the majority being acute respiratory infections (ARI). In most cases, ARI symptoms are similar for different viruses although severity can be variable. The objective of this study was to understand the shared and unique elements of the host transcriptional response to different viral pathogens. We identified 162 subjects in the US and Sri Lanka with infections due to influenza, enterovirus/rhinovirus, human metapneumovirus, dengue virus, cytomegalovirus, Epstein Barr Virus, or adenovirus. Our dataset allowed us to identify common pathways at the molecular level as well as virus-specific differences in the host immune response. Conserved elements of the host response to these viral infections highlighted the importance of interferon pathway activation. However, the magnitude of the responses varied between pathogens. We also identified virus-specific responses to influenza, enterovirus/rhinovirus, and dengue infections. Influenza-specific differentially expressed genes (DEG) revealed up-regulation of pathways related to viral defense and down-regulation of pathways related to T cell and neutrophil responses. Functional analysis of entero/rhinovirus-specific DEGs revealed up-regulation of pathways for neutrophil activation, negative regulation of immune response, and p38MAPK cascade and down-regulation of virus defenses and complement activation. Functional analysis of dengue-specific up-regulated DEGs showed enrichment of pathways for DNA replication and cell division whereas down-regulated DEGs were mainly associated with erythrocyte and myeloid cell homeostasis, reactive oxygen and peroxide metabolic processes. In conclusion, our study will contribute to a better understanding of molecular mechanisms to viral infections in humans and the identification of biomarkers to distinguish different types of viral infections.
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Affiliation(s)
- Ephraim L. Tsalik
- Duke Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, United States
- Emergency Department Service, Durham Veterans Affairs Health Care System, Durham, NC, United States
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, United States
| | - Cassandra Fiorino
- Duke Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, United States
| | - Ammara Aqeel
- Duke Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC, United States
| | - Yiling Liu
- Duke Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, United States
| | - Ricardo Henao
- Duke Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, United States
- Department of Electrical and Computer Engineering, Duke University, Durham, NC, United States
| | - Emily R. Ko
- Duke Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, United States
- Department of Medicine, Duke Regional Hospital, Durham, NC, United States
| | - Thomas W. Burke
- Duke Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, United States
| | - Megan E. Reller
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, United States
| | | | | | | | | | | | - Micah T. McClain
- Duke Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, United States
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, United States
- Medical Service, Durham Veterans Affairs Health Care System, Durham, NC, United States
| | - Christopher W. Woods
- Duke Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, United States
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, United States
- Medical Service, Durham Veterans Affairs Health Care System, Durham, NC, United States
| | - Geoffrey S. Ginsburg
- Duke Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, United States
| | - L. Gayani Tillekeratne
- Duke Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, United States
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, United States
- Medical Service, Durham Veterans Affairs Health Care System, Durham, NC, United States
| | - Klaus Schughart
- Department of Infection Genetics, Helmholtz Centre for Infection Research, Braunschweig, Germany
- University of Veterinary Medicine Hannover, Hannover, Germany
- Department of Microbiology, Immunology and Biochemistry, University of Tennessee Health Science Center, Memphis, TN, United States
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22
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Tabone O, Verma R, Singhania A, Chakravarty P, Branchett WJ, Graham CM, Lee J, Trang T, Reynier F, Leissner P, Kaiser K, Rodrigue M, Woltmann G, Haldar P, O'Garra A. Blood transcriptomics reveal the evolution and resolution of the immune response in tuberculosis. J Exp Med 2021; 218:212624. [PMID: 34491266 PMCID: PMC8493863 DOI: 10.1084/jem.20210915] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Revised: 07/08/2021] [Accepted: 08/05/2021] [Indexed: 12/02/2022] Open
Abstract
Blood transcriptomics have revealed major characteristics of the immune response in active TB, but the signature early after infection is unknown. In a unique clinically and temporally well-defined cohort of household contacts of active TB patients that progressed to TB, we define minimal changes in gene expression in incipient TB increasing in subclinical and clinical TB. While increasing with time, changes in gene expression were highest at 30 d before diagnosis, with heterogeneity in the response in household TB contacts and in a published cohort of TB progressors as they progressed to TB, at a bulk cohort level and in individual progressors. Blood signatures from patients before and during anti-TB treatment robustly monitored the treatment response distinguishing early and late responders. Blood transcriptomics thus reveal the evolution and resolution of the immune response in TB, which may help in clinical management of the disease.
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Affiliation(s)
- Olivier Tabone
- Laboratory of Immunoregulation and Infection, The Francis Crick Institute, London, UK
| | - Raman Verma
- Department of Respiratory Sciences, National Institute for Health Research Respiratory Biomedical Research Centre, University of Leicester, UK
| | - Akul Singhania
- Laboratory of Immunoregulation and Infection, The Francis Crick Institute, London, UK
| | | | - William J Branchett
- Laboratory of Immunoregulation and Infection, The Francis Crick Institute, London, UK
| | - Christine M Graham
- Laboratory of Immunoregulation and Infection, The Francis Crick Institute, London, UK
| | - Jo Lee
- Department of Respiratory Sciences, National Institute for Health Research Respiratory Biomedical Research Centre, University of Leicester, UK
| | - Tran Trang
- Bioaster Microbiology Technology Institute, Lyon, France
| | | | | | - Karine Kaiser
- Medical Diagnostic Discovery Department, bioMérieux SA, Marcy l'Etoile, France
| | - Marc Rodrigue
- Global Medical Affairs, bioMérieux SA, Marcy l'Etoile, France
| | - Gerrit Woltmann
- Department of Respiratory Sciences, National Institute for Health Research Respiratory Biomedical Research Centre, University of Leicester, UK
| | - Pranabashis Haldar
- Department of Respiratory Sciences, National Institute for Health Research Respiratory Biomedical Research Centre, University of Leicester, UK
| | - Anne O'Garra
- Laboratory of Immunoregulation and Infection, The Francis Crick Institute, London, UK.,National Heart and Lung Institute, Imperial College London, London, UK
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23
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Tsalik EL, Henao R, Montgomery JL, Nawrocki JW, Aydin M, Lydon EC, Ko ER, Petzold E, Nicholson BP, Cairns CB, Glickman SW, Quackenbush E, Kingsmore SF, Jaehne AK, Rivers EP, Langley RJ, Fowler VG, McClain MT, Crisp RJ, Ginsburg GS, Burke TW, Hemmert AC, Woods CW. Discriminating Bacterial and Viral Infection Using a Rapid Host Gene Expression Test. Crit Care Med 2021; 49:1651-1663. [PMID: 33938716 PMCID: PMC8448917 DOI: 10.1097/ccm.0000000000005085] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
OBJECTIVES Host gene expression signatures discriminate bacterial and viral infection but have not been translated to a clinical test platform. This study enrolled an independent cohort of patients to describe and validate a first-in-class host response bacterial/viral test. DESIGN Subjects were recruited from 2006 to 2016. Enrollment blood samples were collected in an RNA preservative and banked for later testing. The reference standard was an expert panel clinical adjudication, which was blinded to gene expression and procalcitonin results. SETTING Four U.S. emergency departments. PATIENTS Six-hundred twenty-three subjects with acute respiratory illness or suspected sepsis. INTERVENTIONS Forty-five-transcript signature measured on the BioFire FilmArray System (BioFire Diagnostics, Salt Lake City, UT) in ~45 minutes. MEASUREMENTS AND MAIN RESULTS Host response bacterial/viral test performance characteristics were evaluated in 623 participants (mean age 46 yr; 45% male) with bacterial infection, viral infection, coinfection, or noninfectious illness. Performance of the host response bacterial/viral test was compared with procalcitonin. The test provided independent probabilities of bacterial and viral infection in ~45 minutes. In the 213-subject training cohort, the host response bacterial/viral test had an area under the curve for bacterial infection of 0.90 (95% CI, 0.84-0.94) and 0.92 (95% CI, 0.87-0.95) for viral infection. Independent validation in 209 subjects revealed similar performance with an area under the curve of 0.85 (95% CI, 0.78-0.90) for bacterial infection and 0.91 (95% CI, 0.85-0.94) for viral infection. The test had 80.1% (95% CI, 73.7-85.4%) average weighted accuracy for bacterial infection and 86.8% (95% CI, 81.8-90.8%) for viral infection in this validation cohort. This was significantly better than 68.7% (95% CI, 62.4-75.4%) observed for procalcitonin (p < 0.001). An additional cohort of 201 subjects with indeterminate phenotypes (coinfection or microbiology-negative infections) revealed similar performance. CONCLUSIONS The host response bacterial/viral measured using the BioFire System rapidly and accurately discriminated bacterial and viral infection better than procalcitonin, which can help support more appropriate antibiotic use.
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Affiliation(s)
- Ephraim L. Tsalik
- Durham Veterans Affairs Health Care System, Durham, NC, USA
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, USA
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Ricardo Henao
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, USA
- Department of Biostatistics and Informatics, Duke University, Durham, NC, USA
- Duke Clinical Research Institute, Durham, NC, USA
| | | | | | - Mert Aydin
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Emily C. Lydon
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Emily R. Ko
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, USA
- Duke Regional Hospital, Durham, NC, USA
| | - Elizabeth Petzold
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, USA
| | | | - Charles B. Cairns
- University of North Carolina Medical Center, Chapel Hill, NC, USA
- Drexel University, Philadelphia, PA, USA
| | - Seth W. Glickman
- University of North Carolina Medical Center, Chapel Hill, NC, USA
| | | | | | | | | | | | - Vance G. Fowler
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
- Duke Clinical Research Institute, Durham, NC, USA
| | - Micah T. McClain
- Durham Veterans Affairs Health Care System, Durham, NC, USA
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, USA
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | | | - Geoffrey S. Ginsburg
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Thomas W. Burke
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, USA
| | | | - Christopher W. Woods
- Durham Veterans Affairs Health Care System, Durham, NC, USA
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, USA
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
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24
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A single transcript for the prognosis of disease severity in COVID-19 patients. Sci Rep 2021; 11:12174. [PMID: 34108608 PMCID: PMC8190311 DOI: 10.1038/s41598-021-91754-7] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 06/01/2021] [Indexed: 12/16/2022] Open
Abstract
With many countries strapped for medical resources due to the COVID-19 pandemic, it is highly desirable to allocate the precious resources to those who need them the most. Several markers have been found to be associated with the disease severity in COVID-19 patients. However, the established markers only display modest prognostic power individually and better markers are urgently needed. The aim of this study is to investigate the potential of S100A12, a prominent marker gene for bacterial infection, in the prognosis of disease severity in COVID-19 patients. To ensure the robustness of the association, a total of 1695 samples from 14 independent transcriptome datasets on sepsis, influenza infection and COVID-19 infection were examined. First, it was demonstrated that S100A12 was a marker for sepsis and severity of sepsis. Then, S100A12 was found to be a marker for severe influenza infection, and there was an upward trend of S100A12 expression as the severity level of influenza infection increased. As for COVID-19 infection, it was found that S100A12 expression was elevated in patients with severe and critical COVID-19 infection. More importantly, S100A12 expression at hospital admission was robustly correlated with future quantitative indexes of disease severity and outcome in COVID-19 patients, superior to established prognostic markers including CRP, PCT, d-dimer, ferritin, LDH and fibrinogen. Thus, S100A12 is a valuable novel prognostic marker for COVID-19 severity and deserves more attention.
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25
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Ravichandran S, Banerjee U, Dr GD, Kandukuru R, Thakur C, Chakravortty D, Balaji KN, Singh A, Chandra N. VB 10, a new blood biomarker for differential diagnosis and recovery monitoring of acute viral and bacterial infections. EBioMedicine 2021; 67:103352. [PMID: 33906069 PMCID: PMC8099739 DOI: 10.1016/j.ebiom.2021.103352] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Revised: 04/04/2021] [Accepted: 04/07/2021] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND Precise differential diagnosis between acute viral and bacterial infections is important to enable appropriate therapy, avoid unnecessary antibiotic prescriptions and optimize the use of hospital resources. A systems view of host response to infections provides opportunities for discovering sensitive and robust molecular diagnostics. METHODS We combine blood transcriptomes from six independent datasets (n = 756) with a knowledge-based human protein-protein interaction network, identifies subnetworks capturing host response to each infection class, and derives common response cores separately for viral and bacterial infections. We subject the subnetworks to a series of computational filters to identify a parsimonious gene panel and a standalone diagnostic score that can be applied to individual samples. We rigorously validate the panel and the diagnostic score in a wide range of publicly available datasets and in a newly developed Bangalore-Viral Bacterial (BL-VB) cohort. FINDING We discover a 10-gene blood-based biomarker panel (Panel-VB) that demonstrates high predictive performance to distinguish viral from bacterial infections, with a weighted mean AUROC of 0.97 (95% CI: 0.96-0.99) in eleven independent datasets (n = 898). We devise a new stand-alone patient-wise score (VB10) based on the panel, which shows high diagnostic accuracy with a weighted mean AUROC of 0.94 (95% CI 0.91-0.98) in 2996 patient samples from 56 public datasets from 19 different countries. Further, we evaluate VB10 in a newly generated South Indian (BL-VB, n = 56) cohort and find 97% accuracy in the confirmed cases of viral and bacterial infections. We find that VB10 is (a) capable of accurately identifying the infection class in culture-negative indeterminate cases, (b) reflects recovery status, and (c) is applicable across different age groups, covering a wide spectrum of acute bacterial and viral infections, including uncharacterized pathogens. We tested our VB10 score on publicly available COVID-19 data and find that our score detected viral infection in patient samples. INTERPRETATION Our results point to the promise of VB10 as a diagnostic test for precise diagnosis of acute infections and monitoring recovery status. We expect that it will provide clinical decision support for antibiotic prescriptions and thereby aid in antibiotic stewardship efforts. FUNDING Grand Challenges India, Biotechnology Industry Research Assistance Council (BIRAC), Department of Biotechnology, Govt. of India.
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Affiliation(s)
| | - Ushashi Banerjee
- Department of Biochemistry, Indian Institute of Science, Bangalore 560012, India
| | - Gayathri Devi Dr
- Department of Microbiology, M S Ramaiah Medical College, Bangalore 560054, Karnataka, India
| | - Rooparani Kandukuru
- Department of Microbiology, M S Ramaiah Medical College, Bangalore 560054, Karnataka, India
| | - Chandrani Thakur
- Department of Biochemistry, Indian Institute of Science, Bangalore 560012, India
| | - Dipshikha Chakravortty
- Centre for Biosystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India; Department of Microbiology and Cell Biology, Indian Institute of Science, Bangalore 560012, India
| | | | - Amit Singh
- Department of Microbiology and Cell Biology, Indian Institute of Science, Bangalore 560012, India; Centre for Infectious Disease Research, Indian Institute of Science, Bangalore 560012, India
| | - Nagasuma Chandra
- IISc Mathematics Initiative, Indian Institute of Science, Bangalore 560012, India; Department of Biochemistry, Indian Institute of Science, Bangalore 560012, India; Centre for Biosystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India.
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26
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Zheng H, Rao AM, Dermadi D, Toh J, Murphy Jones L, Donato M, Liu Y, Su Y, Dai CL, Kornilov SA, Karagiannis M, Marantos T, Hasin-Brumshtein Y, He YD, Giamarellos-Bourboulis EJ, Heath JR, Khatri P. Multi-cohort analysis of host immune response identifies conserved protective and detrimental modules associated with severity across viruses. Immunity 2021; 54:753-768.e5. [PMID: 33765435 PMCID: PMC7988739 DOI: 10.1016/j.immuni.2021.03.002] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2020] [Revised: 12/03/2020] [Accepted: 03/01/2021] [Indexed: 02/08/2023]
Abstract
Viral infections induce a conserved host response distinct from bacterial infections. We hypothesized that the conserved response is associated with disease severity and is distinct between patients with different outcomes. To test this, we integrated 4,780 blood transcriptome profiles from patients aged 0 to 90 years infected with one of 16 viruses, including SARS-CoV-2, Ebola, chikungunya, and influenza, across 34 cohorts from 18 countries, and single-cell RNA sequencing profiles of 702,970 immune cells from 289 samples across three cohorts. Severe viral infection was associated with increased hematopoiesis, myelopoiesis, and myeloid-derived suppressor cells. We identified protective and detrimental gene modules that defined distinct trajectories associated with mild versus severe outcomes. The interferon response was decoupled from the protective host response in patients with severe outcomes. These findings were consistent, irrespective of age and virus, and provide insights to accelerate the development of diagnostics and host-directed therapies to improve global pandemic preparedness.
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Affiliation(s)
- Hong Zheng
- Institute for Immunity, Transplantation and Infection, School of Medicine, Stanford University, CA 94305, USA; Center for Biomedical Informatics Research, Department of Medicine, School of Medicine, Stanford University, CA 94305, USA
| | - Aditya M Rao
- Institute for Immunity, Transplantation and Infection, School of Medicine, Stanford University, CA 94305, USA; Immunology program, Stanford University, CA 94305, USA
| | - Denis Dermadi
- Institute for Immunity, Transplantation and Infection, School of Medicine, Stanford University, CA 94305, USA; Center for Biomedical Informatics Research, Department of Medicine, School of Medicine, Stanford University, CA 94305, USA
| | - Jiaying Toh
- Institute for Immunity, Transplantation and Infection, School of Medicine, Stanford University, CA 94305, USA; Immunology program, Stanford University, CA 94305, USA
| | - Lara Murphy Jones
- Institute for Immunity, Transplantation and Infection, School of Medicine, Stanford University, CA 94305, USA; Center for Biomedical Informatics Research, Department of Medicine, School of Medicine, Stanford University, CA 94305, USA; Division of Critical Care Medicine, Department of Pediatrics, School of Medicine, Stanford University, CA 94305, USA
| | - Michele Donato
- Institute for Immunity, Transplantation and Infection, School of Medicine, Stanford University, CA 94305, USA; Center for Biomedical Informatics Research, Department of Medicine, School of Medicine, Stanford University, CA 94305, USA
| | - Yiran Liu
- Institute for Immunity, Transplantation and Infection, School of Medicine, Stanford University, CA 94305, USA; Cancer Biology program, Stanford University, CA 94305, USA
| | - Yapeng Su
- Institute for Systems Biology, Seattle, WA, USA
| | - Cheng L Dai
- Institute for Systems Biology, Seattle, WA, USA
| | | | - Minas Karagiannis
- 4(th) Department of Internal Medicine, National and Kapodistrian University of Athens, Medical School, 124 62 Athens, Greece
| | - Theodoros Marantos
- 4(th) Department of Internal Medicine, National and Kapodistrian University of Athens, Medical School, 124 62 Athens, Greece
| | | | | | | | - James R Heath
- Institute for Systems Biology, Seattle, WA, USA; Department of Bioengineering, University of Washington, Seattle, WA 98195
| | - Purvesh Khatri
- Institute for Immunity, Transplantation and Infection, School of Medicine, Stanford University, CA 94305, USA; Center for Biomedical Informatics Research, Department of Medicine, School of Medicine, Stanford University, CA 94305, USA.
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27
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Farias Amorim C, O. Novais F, Nguyen BT, Nascimento MT, Lago J, Lago AS, Carvalho LP, Beiting DP, Scott P. Localized skin inflammation during cutaneous leishmaniasis drives a chronic, systemic IFN-γ signature. PLoS Negl Trop Dis 2021; 15:e0009321. [PMID: 33793565 PMCID: PMC8043375 DOI: 10.1371/journal.pntd.0009321] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Revised: 04/13/2021] [Accepted: 03/23/2021] [Indexed: 02/07/2023] Open
Abstract
Cutaneous leishmaniasis is a localized infection controlled by CD4+ T cells that produce IFN-γ within lesions. Phagocytic cells recruited to lesions, such as monocytes, are then exposed to IFN-γ which triggers their ability to kill the intracellular parasites. Consistent with this, transcriptional analysis of patient lesions identified an interferon stimulated gene (ISG) signature. To determine whether localized L. braziliensis infection triggers a systemic immune response that may influence the disease, we performed RNA sequencing (RNA-seq) on the blood of L. braziliensis-infected patients and healthy controls. Functional enrichment analysis identified an ISG signature as the dominant transcriptional response in the blood of patients. This ISG signature was associated with an increase in monocyte- and macrophage-specific marker genes in the blood and elevated serum levels IFN-γ. A cytotoxicity signature, which is a dominant feature in the lesions, was also observed in the blood and correlated with an increased abundance of cytolytic cells. Thus, two transcriptional signatures present in lesions were found systemically, although with a substantially reduced number of differentially expressed genes (DEGs). Finally, we found that the number of DEGs and ISGs in leishmaniasis was similar to tuberculosis-another localized infection-but significantly less than observed in malaria. In contrast, the cytolytic signature and increased cytolytic cell abundance was not found in tuberculosis or malaria. Our results indicate that systemic signatures can reflect what is occurring in leishmanial lesions. Furthermore, the presence of an ISG signature in blood monocytes and macrophages suggests a mechanism to limit systemic spread of the parasite, as well as enhance parasite control by pre-activating cells prior to lesion entry.
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Affiliation(s)
- Camila Farias Amorim
- Department of Pathobiology, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, United States of America
| | - Fernanda O. Novais
- Department of Pathobiology, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, United States of America
| | - Ba T. Nguyen
- Department of Pathobiology, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, United States of America
| | - Mauricio T. Nascimento
- Serviço de Imunologia, Complexo Hospitalar Universitário Professor Edgard Santos, Universidade Federal da Bahia, Salvador, Brazil
- Laboratório de Pesquisas Clínicas do Instituto de Pesquisas Gonçalo Moniz–Fiocruz, Salvador, Brazil
| | - Jamile Lago
- Serviço de Imunologia, Complexo Hospitalar Universitário Professor Edgard Santos, Universidade Federal da Bahia, Salvador, Brazil
- Laboratório de Pesquisas Clínicas do Instituto de Pesquisas Gonçalo Moniz–Fiocruz, Salvador, Brazil
| | - Alexsandro S. Lago
- Serviço de Imunologia, Complexo Hospitalar Universitário Professor Edgard Santos, Universidade Federal da Bahia, Salvador, Brazil
- Laboratório de Pesquisas Clínicas do Instituto de Pesquisas Gonçalo Moniz–Fiocruz, Salvador, Brazil
| | - Lucas P. Carvalho
- Serviço de Imunologia, Complexo Hospitalar Universitário Professor Edgard Santos, Universidade Federal da Bahia, Salvador, Brazil
- Laboratório de Pesquisas Clínicas do Instituto de Pesquisas Gonçalo Moniz–Fiocruz, Salvador, Brazil
| | - Daniel P. Beiting
- Department of Pathobiology, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, United States of America
| | - Phillip Scott
- Department of Pathobiology, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, United States of America
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Gómez-Carballa A, Barral-Arca R, Cebey-López M, Bello X, Pardo-Seco J, Martinón-Torres F, Salas A. Identification of a Minimal 3-Transcript Signature to Differentiate Viral from Bacterial Infection from Best Genome-Wide Host RNA Biomarkers: A Multi-Cohort Analysis. Int J Mol Sci 2021; 22:ijms22063148. [PMID: 33808774 PMCID: PMC8003556 DOI: 10.3390/ijms22063148] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Revised: 03/11/2021] [Accepted: 03/15/2021] [Indexed: 12/24/2022] Open
Abstract
The fight against the spread of antibiotic resistance is one of the most important challenges facing health systems worldwide. Given the limitations of current diagnostic methods, the development of fast and accurate tests for the diagnosis of viral and bacterial infections would improve patient management and treatment, as well as contribute to reducing antibiotic misuse in clinical settings. In this scenario, analysis of host transcriptomics constitutes a promising target to develop new diagnostic tests based on the host-specific response to infections. We carried out a multi-cohort meta-analysis of blood transcriptomic data available in public databases, including 11 different studies and 1209 samples from virus- (n = 695) and bacteria- (n = 514) infected patients. We applied a Parallel Regularized Regression Model Search (PReMS) on a set of previously reported genes that distinguished viral from bacterial infection to find a minimum gene expression bio-signature. This strategy allowed us to detect three genes, namely BAFT, ISG15 and DNMT1, that clearly differentiate groups of infection with high accuracy (training set: area under the curve (AUC) 0.86 (sensitivity: 0.81; specificity: 0.87); testing set: AUC 0.87 (sensitivity: 0.82; specificity: 0.86)). BAFT and ISG15 are involved in processes related to immune response, while DNMT1 is related to the preservation of methylation patterns, and its expression is modulated by pathogen infections. We successfully tested this three-transcript signature in the 11 independent studies, demonstrating its high performance under different scenarios. The main advantage of this three-gene signature is the low number of genes needed to differentiate both groups of patient categories.
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Affiliation(s)
- Alberto Gómez-Carballa
- GenPoB Research Group, Instituto de Investigación Sanitaria (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), 15706 Galicia, Spain; (A.G.-C.); (R.B.-A.); (M.C.-L.); (X.B.); (J.P.-S.)
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria de Santiago de Compostela, 15706 Galicia, Spain;
| | - Ruth Barral-Arca
- GenPoB Research Group, Instituto de Investigación Sanitaria (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), 15706 Galicia, Spain; (A.G.-C.); (R.B.-A.); (M.C.-L.); (X.B.); (J.P.-S.)
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria de Santiago de Compostela, 15706 Galicia, Spain;
| | - Miriam Cebey-López
- GenPoB Research Group, Instituto de Investigación Sanitaria (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), 15706 Galicia, Spain; (A.G.-C.); (R.B.-A.); (M.C.-L.); (X.B.); (J.P.-S.)
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria de Santiago de Compostela, 15706 Galicia, Spain;
| | - Xabier Bello
- GenPoB Research Group, Instituto de Investigación Sanitaria (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), 15706 Galicia, Spain; (A.G.-C.); (R.B.-A.); (M.C.-L.); (X.B.); (J.P.-S.)
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria de Santiago de Compostela, 15706 Galicia, Spain;
| | - Jacobo Pardo-Seco
- GenPoB Research Group, Instituto de Investigación Sanitaria (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), 15706 Galicia, Spain; (A.G.-C.); (R.B.-A.); (M.C.-L.); (X.B.); (J.P.-S.)
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria de Santiago de Compostela, 15706 Galicia, Spain;
| | - Federico Martinón-Torres
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria de Santiago de Compostela, 15706 Galicia, Spain;
- Translational Pediatrics and Infectious Diseases, Department of Pediatrics, Hospital Clínico Universitario de Santiago de Compostela, 15706 Galicia, Spain
| | - Antonio Salas
- Translational Pediatrics and Infectious Diseases, Department of Pediatrics, Hospital Clínico Universitario de Santiago de Compostela, 15706 Galicia, Spain
- Unidade de Xenética, Instituto de Ciencias Forenses, Facultade de Medicina, Universidade de Santiago de Compostela, 15706 Galicia, Spain
- Correspondence:
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29
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Mahle RE, Suchindran S, Henao R, Steinbrink JM, Burke TW, McClain MT, Ginsburg GS, Woods CW, Tsalik EL. Validation of a host gene expression test for bacterial/viral discrimination in immunocompromised hosts. Clin Infect Dis 2021; 73:605-613. [PMID: 33462581 DOI: 10.1093/cid/ciab043] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2020] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND Host gene expression has emerged as a complementary strategy to pathogen detection tests for the discrimination of bacterial and viral infection. The impact of immunocompromise on host response tests remains unknown. We evaluated a host response test discriminating bacterial, viral, and non-infectious conditions in immunocompromised subjects. METHODS An 81-gene signature was measured using RT-PCR in subjects with immunocompromise (chemotherapy, solid organ transplant, immunomodulatory agents, AIDS) with bacterial infection, viral infection, or noninfectious illness. A regularized logistic regression model trained in immunocompetent subjects was used to estimate the likelihood of each class in immunocompromised subjects. RESULTS Accuracy in the 136-subject immunocompetent training cohort was 84.6% for bacterial vs. non-bacterial discrimination and 80.8% for viral vs. non-viral discrimination. Model validation in 134 immunocompromised subjects showed overall accuracy of 73.9% for bacterial infection (p=0.04 relative to immunocompetent subjects) and 75.4% for viral infection (p=0.30). A scheme reporting results by quartile improved test utility. The highest probability quartile ruled-in bacterial and viral infection with 91.4% and 84.0% specificity, respectively. The lowest probability quartile ruled-out infection with 90.1% and 96.4% sensitivity for bacterial and viral infection, respectively. Performance was independent of the type or number of immunocompromising conditions. CONCLUSION A host gene expression test discriminated bacterial, viral, and non-infectious etiologies at a lower overall accuracy in immunocompromised patients compared to immunocompetent patients, though this difference was only significant for bacterial infection classification. With modified interpretive criteria, a host response strategy may offer clinically useful diagnostic information for patients with immunocompromise.
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Affiliation(s)
- Rachael E Mahle
- Duke University School of Medicine, Durham, North Carolina, USA
| | - Sunil Suchindran
- Duke Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA
| | - Ricardo Henao
- Duke Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.,Department of Electrical and Computer Engineering, Pratt School of Engineering, Duke University, Durham, North Carolina, USA
| | - Julie M Steinbrink
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA
| | - Thomas W Burke
- Duke Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA
| | - Micah T McClain
- Duke Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.,Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.,Medical Service, Durham VA Health Care System, Durham, North Carolina, USA
| | - Geoffrey S Ginsburg
- Duke Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA
| | - Christopher W Woods
- Duke Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.,Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.,Medical Service, Durham VA Health Care System, Durham, North Carolina, USA
| | - Ephraim L Tsalik
- Duke Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.,Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.,Emergency Medicine Service, Durham VA Health Care System, Durham, North Carolina, USA
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30
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Liu S, Huang Z, Deng X, Zou X, Li H, Mu S, Cao B. Identification of key candidate biomarkers for severe influenza infection by integrated bioinformatical analysis and initial clinical validation. J Cell Mol Med 2021; 25:1725-1738. [PMID: 33448094 PMCID: PMC7875920 DOI: 10.1111/jcmm.16275] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Revised: 12/14/2020] [Accepted: 12/29/2020] [Indexed: 12/13/2022] Open
Abstract
One of the key barriers for early identification and intervention of severe influenza cases is a lack of reliable immunologic indicators. In this study, we utilized differentially expressed genes screening incorporating weighted gene co‐expression network analysis in one eligible influenza GEO data set (GSE111368) to identify hub genes associated with clinical severity. A total of 10 genes (PBI, MMP8, TCN1, RETN, OLFM4, ELANE, LTF, LCN2, DEFA4 and HP) were identified. Gene set enrichment analysis (GSEA) for single hub gene revealed that these genes had a close association with antimicrobial response and neutrophils activity. To further evaluate these genes' ability for diagnosis/prognosis of disease developments, we adopted double validation with (a) another new independent data set (GSE101702); and (b) plasma samples collected from hospitalized influenza patients. We found that 10 hub genes presented highly correlation with disease severity. In particular, BPI and MMP8 encoding proteins in plasma achieved higher expression in severe and dead cases, which indicated an adverse disease development and suggested a frustrating prognosis. These findings provide new insight into severe influenza pathogenesis and identify two significant candidate genes that were superior to the conventional clinical indicators. These candidate genes or encoding proteins could be biomarker for clinical diagnosis and therapeutic targets for severe influenza infection.
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Affiliation(s)
- Shuai Liu
- China-Japan Friendship Hospital, National Clinical Research Center for Respiratory Diseases, Clinical Center for Pulmonary Infections, Capital Medical University, Beijing, China.,Department of Pulmonary and Critical Care Medicine, Center for Respiratory Diseases, China-Japan Friendship Hospital, Beijing, China
| | - Zhisheng Huang
- Department of Pulmonary and Critical Care Medicine, Center for Respiratory Diseases, China-Japan Friendship Hospital, Beijing, China.,Institute of Respiratory Medicine, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| | - Xiaoyan Deng
- Tsinghua University-Peking University Joint Center for Life Sciences, Tsinghua University, Beijing, China
| | - Xiaohui Zou
- China-Japan Friendship Hospital, National Clinical Research Center for Respiratory Diseases, Clinical Center for Pulmonary Infections, Capital Medical University, Beijing, China.,Department of Pulmonary and Critical Care Medicine, Center for Respiratory Diseases, China-Japan Friendship Hospital, Beijing, China.,Institute of Respiratory Medicine, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| | - Hui Li
- China-Japan Friendship Hospital, National Clinical Research Center for Respiratory Diseases, Clinical Center for Pulmonary Infections, Capital Medical University, Beijing, China.,Department of Pulmonary and Critical Care Medicine, Center for Respiratory Diseases, China-Japan Friendship Hospital, Beijing, China.,Institute of Respiratory Medicine, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| | - Shengrui Mu
- China-Japan Friendship Hospital, National Clinical Research Center for Respiratory Diseases, Clinical Center for Pulmonary Infections, Capital Medical University, Beijing, China.,Department of Pulmonary and Critical Care Medicine, Center for Respiratory Diseases, China-Japan Friendship Hospital, Beijing, China
| | - Bin Cao
- China-Japan Friendship Hospital, National Clinical Research Center for Respiratory Diseases, Clinical Center for Pulmonary Infections, Capital Medical University, Beijing, China.,Department of Pulmonary and Critical Care Medicine, Center for Respiratory Diseases, China-Japan Friendship Hospital, Beijing, China.,Institute of Respiratory Medicine, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China.,Tsinghua University-Peking University Joint Center for Life Sciences, Tsinghua University, Beijing, China
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Nicolas De Lamballerie C, Pizzorno A, Dubois J, Padey B, Julien T, Traversier A, Carbonneau J, Orcel E, Lina B, Hamelin ME, Roche M, Textoris J, Boivin G, Legras-Lachuer C, Terrier O, Rosa-Calatrava M. Human Respiratory Syncytial Virus-Induced Immune Signature of Infection Revealed by Transcriptome Analysis of Clinical Pediatric Nasopharyngeal Swab Samples. J Infect Dis 2020; 223:1052-1061. [PMID: 32726438 DOI: 10.1093/infdis/jiaa468] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2020] [Accepted: 07/24/2020] [Indexed: 11/12/2022] Open
Abstract
Human respiratory syncytial virus (HRSV) constitutes one the main causes of respiratory infection in neonates and infants worldwide. Transcriptome analysis of clinical samples using high-throughput technologies remains an important tool to better understand virus-host complex interactions in the real-life setting but also to identify new diagnosis/prognosis markers or therapeutics targets. A major challenge when exploiting clinical samples such as nasal swabs, washes, or bronchoalveolar lavages is the poor quantity and integrity of nucleic acids. In this study, we applied a tailored transcriptomics workflow to exploit nasal wash samples from children who tested positive for HRSV. Our analysis revealed a characteristic immune signature as a direct reflection of HRSV pathogenesis and highlighted putative biomarkers of interest such as IP-10, TMEM190, MCEMP1, and TIMM23.
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Affiliation(s)
- Claire Nicolas De Lamballerie
- CIRI, Centre International de Recherche en Infectiologie (Team VirPath), Université de Lyon, Inserm, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, École Normale Supérieure de Lyon, Lyon, France.,Viroscan3D SAS, Lyon, France
| | - Andrés Pizzorno
- CIRI, Centre International de Recherche en Infectiologie (Team VirPath), Université de Lyon, Inserm, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, École Normale Supérieure de Lyon, Lyon, France
| | - Julia Dubois
- CIRI, Centre International de Recherche en Infectiologie (Team VirPath), Université de Lyon, Inserm, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, École Normale Supérieure de Lyon, Lyon, France
| | - Blandine Padey
- CIRI, Centre International de Recherche en Infectiologie (Team VirPath), Université de Lyon, Inserm, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, École Normale Supérieure de Lyon, Lyon, France
| | - Thomas Julien
- CIRI, Centre International de Recherche en Infectiologie (Team VirPath), Université de Lyon, Inserm, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, École Normale Supérieure de Lyon, Lyon, France.,VirNext, Faculté de Médecine RTH Laennec, Université Claude Bernard Lyon 1, Université de Lyon, Lyon, France
| | - Aurélien Traversier
- CIRI, Centre International de Recherche en Infectiologie (Team VirPath), Université de Lyon, Inserm, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, École Normale Supérieure de Lyon, Lyon, France
| | - Julie Carbonneau
- Research Center in Infectious Diseases, Centre Hospitalier Universitaire de Quebec and Laval University, Quebec City, Quebec, Canada
| | | | - Bruno Lina
- CIRI, Centre International de Recherche en Infectiologie (Team VirPath), Université de Lyon, Inserm, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, École Normale Supérieure de Lyon, Lyon, France
| | - Marie-Eve Hamelin
- Research Center in Infectious Diseases, Centre Hospitalier Universitaire de Quebec and Laval University, Quebec City, Quebec, Canada
| | | | - Julien Textoris
- Pathophysiology of Injury-Induced Immunosuppression, Hospices Civils de Lyon, bioMérieux, Université Claude Bernard Lyon 1, Hôpital Edouard Herriot, Lyon, France
| | - Guy Boivin
- Research Center in Infectious Diseases, Centre Hospitalier Universitaire de Quebec and Laval University, Quebec City, Quebec, Canada
| | - Catherine Legras-Lachuer
- Viroscan3D SAS, Lyon, France.,Ecologie Microbienne, UMR CNRS 5557, USC INRA 1364, Université Claude Bernard Lyon 1, Université de Lyon, Villeurbanne, France
| | - Olivier Terrier
- CIRI, Centre International de Recherche en Infectiologie (Team VirPath), Université de Lyon, Inserm, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, École Normale Supérieure de Lyon, Lyon, France
| | - Manuel Rosa-Calatrava
- CIRI, Centre International de Recherche en Infectiologie (Team VirPath), Université de Lyon, Inserm, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, École Normale Supérieure de Lyon, Lyon, France.,VirNext, Faculté de Médecine RTH Laennec, Université Claude Bernard Lyon 1, Université de Lyon, Lyon, France
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32
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Gardinassi LG, Souza COS, Sales-Campos H, Fonseca SG. Immune and Metabolic Signatures of COVID-19 Revealed by Transcriptomics Data Reuse. Front Immunol 2020; 11:1636. [PMID: 32670298 PMCID: PMC7332781 DOI: 10.3389/fimmu.2020.01636] [Citation(s) in RCA: 76] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Accepted: 06/18/2020] [Indexed: 12/21/2022] Open
Abstract
The current pandemic of coronavirus disease 19 (COVID-19) has affected millions of individuals and caused thousands of deaths worldwide. The pathophysiology of the disease is complex and mostly unknown. Therefore, identifying the molecular mechanisms that promote progression of the disease is critical to overcome this pandemic. To address such issues, recent studies have reported transcriptomic profiles of cells, tissues and fluids from COVID-19 patients that mainly demonstrated activation of humoral immunity, dysregulated type I and III interferon expression, intense innate immune responses and inflammatory signaling. Here, we provide novel perspectives on the pathophysiology of COVID-19 using robust functional approaches to analyze public transcriptome datasets. In addition, we compared the transcriptional signature of COVID-19 patients with individuals infected with SARS-CoV-1 and Influenza A (IAV) viruses. We identified a core transcriptional signature induced by the respiratory viruses in peripheral leukocytes, whereas the absence of significant type I interferon/antiviral responses characterized SARS-CoV-2 infection. We also identified the higher expression of genes involved in metabolic pathways including heme biosynthesis, oxidative phosphorylation and tryptophan metabolism. A BTM-driven meta-analysis of bronchoalveolar lavage fluid (BALF) from COVID-19 patients showed significant enrichment for neutrophils and chemokines, which were also significant in data from lung tissue of one deceased COVID-19 patient. Importantly, our results indicate higher expression of genes related to oxidative phosphorylation both in peripheral mononuclear leukocytes and BALF, suggesting a critical role for mitochondrial activity during SARS-CoV-2 infection. Collectively, these data point for immunopathological features and targets that can be therapeutically exploited to control COVID-19.
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Affiliation(s)
- Luiz G. Gardinassi
- Departamento de Biociências e Tecnologia, Instituto de Patologia Tropical e Saúde Pública, Universidade Federal de Goiás, Goiânia, Brazil
| | - Camila O. S. Souza
- Departamento de Análises Clínicas, Toxicológicas e Bromatológicas, Faculdade de Ciências Farmacêuticas de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, Brazil
| | - Helioswilton Sales-Campos
- Departamento de Biociências e Tecnologia, Instituto de Patologia Tropical e Saúde Pública, Universidade Federal de Goiás, Goiânia, Brazil
| | - Simone G. Fonseca
- Departamento de Biociências e Tecnologia, Instituto de Patologia Tropical e Saúde Pública, Universidade Federal de Goiás, Goiânia, Brazil
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33
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Tillekeratne LG, Suchindran S, Ko ER, Petzold EA, Bodinayake CK, Nagahawatte A, Devasiri V, Kurukulasooriya R, Nicholson BP, McClain MT, Burke TW, Tsalik EL, Henao R, Ginsburg GS, Reller ME, Woods CW. Previously Derived Host Gene Expression Classifiers Identify Bacterial and Viral Etiologies of Acute Febrile Respiratory Illness in a South Asian Population. Open Forum Infect Dis 2020; 7:ofaa194. [PMID: 32617371 PMCID: PMC7314590 DOI: 10.1093/ofid/ofaa194] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Accepted: 05/21/2020] [Indexed: 01/21/2023] Open
Abstract
Background Pathogen-based diagnostics for acute respiratory infection (ARI) have limited ability to detect etiology of illness. We previously showed that peripheral blood-based host gene expression classifiers accurately identify bacterial and viral ARI in cohorts of European and African descent. We determined classifier performance in a South Asian cohort. Methods Patients ≥15 years with fever and respiratory symptoms were enrolled in Sri Lanka. Comprehensive pathogen-based testing was performed. Peripheral blood ribonucleic acid was sequenced and previously developed signatures were applied: a pan-viral classifier (viral vs nonviral) and an ARI classifier (bacterial vs viral vs noninfectious). Results Ribonucleic acid sequencing was performed in 79 subjects: 58 viral infections (36 influenza, 22 dengue) and 21 bacterial infections (10 leptospirosis, 11 scrub typhus). The pan-viral classifier had an overall classification accuracy of 95%. The ARI classifier had an overall classification accuracy of 94%, with sensitivity and specificity of 91% and 95%, respectively, for bacterial infection. The sensitivity and specificity of C-reactive protein (>10 mg/L) and procalcitonin (>0.25 ng/mL) for bacterial infection were 100% and 34%, and 100% and 41%, respectively. Conclusions Previously derived gene expression classifiers had high predictive accuracy at distinguishing viral and bacterial infection in South Asian patients with ARI caused by typical and atypical pathogens.
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Affiliation(s)
- L Gayani Tillekeratne
- Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.,Duke Global Health Institute, Durham, North Carolina, USA.,Infectious Diseases Service, Durham Veterans Affairs Health Care System, Durham, North Carolina, USA.,Department of Medicine, Faculty of Medicine, University of Ruhuna, Galle, Sri Lanka
| | - Sunil Suchindran
- Center for Applied Genomics and Precision Medicine, Durham, North Carolina, USA
| | - Emily R Ko
- Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.,Center for Applied Genomics and Precision Medicine, Durham, North Carolina, USA.,Program in Hospital Medicine, Duke Regional Hospital, Durham, North Carolina, USA
| | - Elizabeth A Petzold
- Center for Applied Genomics and Precision Medicine, Durham, North Carolina, USA
| | - Champica K Bodinayake
- Duke Global Health Institute, Durham, North Carolina, USA.,Department of Medicine, Faculty of Medicine, University of Ruhuna, Galle, Sri Lanka
| | - Ajith Nagahawatte
- Duke Global Health Institute, Durham, North Carolina, USA.,Department of Microbiology, Faculty of Medicine, University of Ruhuna, Galle, Sri Lanka
| | - Vasantha Devasiri
- Department of Pediatrics, Faculty of Medicine, University of Ruhuna, Galle, Sri Lanka
| | | | | | - Micah T McClain
- Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.,Infectious Diseases Service, Durham Veterans Affairs Health Care System, Durham, North Carolina, USA.,Center for Applied Genomics and Precision Medicine, Durham, North Carolina, USA
| | - Thomas W Burke
- Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.,Center for Applied Genomics and Precision Medicine, Durham, North Carolina, USA
| | - Ephraim L Tsalik
- Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.,Infectious Diseases Service, Durham Veterans Affairs Health Care System, Durham, North Carolina, USA.,Center for Applied Genomics and Precision Medicine, Durham, North Carolina, USA
| | - Ricardo Henao
- Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.,Center for Applied Genomics and Precision Medicine, Durham, North Carolina, USA
| | - Geoffrey S Ginsburg
- Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.,Center for Applied Genomics and Precision Medicine, Durham, North Carolina, USA
| | - Megan E Reller
- Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.,Duke Global Health Institute, Durham, North Carolina, USA.,Infectious Diseases Service, Durham Veterans Affairs Health Care System, Durham, North Carolina, USA
| | - Christopher W Woods
- Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.,Duke Global Health Institute, Durham, North Carolina, USA.,Infectious Diseases Service, Durham Veterans Affairs Health Care System, Durham, North Carolina, USA.,Center for Applied Genomics and Precision Medicine, Durham, North Carolina, USA
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34
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Mayhew MB, Buturovic L, Luethy R, Midic U, Moore AR, Roque JA, Shaller BD, Asuni T, Rawling D, Remmel M, Choi K, Wacker J, Khatri P, Rogers AJ, Sweeney TE. A generalizable 29-mRNA neural-network classifier for acute bacterial and viral infections. Nat Commun 2020; 11:1177. [PMID: 32132525 PMCID: PMC7055276 DOI: 10.1038/s41467-020-14975-w] [Citation(s) in RCA: 61] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2019] [Accepted: 02/13/2020] [Indexed: 02/07/2023] Open
Abstract
Improved identification of bacterial and viral infections would reduce morbidity from sepsis, reduce antibiotic overuse, and lower healthcare costs. Here, we develop a generalizable host-gene-expression-based classifier for acute bacterial and viral infections. We use training data (N = 1069) from 18 retrospective transcriptomic studies. Using only 29 preselected host mRNAs, we train a neural-network classifier with a bacterial-vs-other area under the receiver-operating characteristic curve (AUROC) 0.92 (95% CI 0.90–0.93) and a viral-vs-other AUROC 0.92 (95% CI 0.90–0.93). We then apply this classifier, inflammatix-bacterial-viral-noninfected-version 1 (IMX-BVN-1), without retraining, to an independent cohort (N = 163). In this cohort, IMX-BVN-1 AUROCs are: bacterial-vs.-other 0.86 (95% CI 0.77–0.93), and viral-vs.-other 0.85 (95% CI 0.76–0.93). In patients enrolled within 36 h of hospital admission (N = 70), IMX-BVN-1 AUROCs are: bacterial-vs.-other 0.92 (95% CI 0.83–0.99), and viral-vs.-other 0.91 (95% CI 0.82–0.98). With further study, IMX-BVN-1 could provide a tool for assessing patients with suspected infection and sepsis at hospital admission. Diagnosing acute infections based on transcriptional host response shows promise, but generalizability is wanting. Here, the authors use a co-normalization framework to train a classifier to diagnose acute infections and apply it to independent data on a targeted diagnostic platform.
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Affiliation(s)
- Michael B Mayhew
- Inflammatix, Inc., 863 Mitten Rd, Suite 104, Burlingame, CA, 94010, USA
| | | | - Roland Luethy
- Inflammatix, Inc., 863 Mitten Rd, Suite 104, Burlingame, CA, 94010, USA
| | - Uros Midic
- Inflammatix, Inc., 863 Mitten Rd, Suite 104, Burlingame, CA, 94010, USA
| | - Andrew R Moore
- Department of Medicine, Stanford University, Palo Alto, CA, 94305, USA
| | - Jonasel A Roque
- Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, Stanford University, Palo Alto, CA, 94305, USA
| | - Brian D Shaller
- Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, Stanford University, Palo Alto, CA, 94305, USA
| | - Tola Asuni
- Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, Stanford University, Palo Alto, CA, 94305, USA
| | - David Rawling
- Inflammatix, Inc., 863 Mitten Rd, Suite 104, Burlingame, CA, 94010, USA
| | - Melissa Remmel
- Inflammatix, Inc., 863 Mitten Rd, Suite 104, Burlingame, CA, 94010, USA
| | - Kirindi Choi
- Inflammatix, Inc., 863 Mitten Rd, Suite 104, Burlingame, CA, 94010, USA
| | - James Wacker
- Inflammatix, Inc., 863 Mitten Rd, Suite 104, Burlingame, CA, 94010, USA
| | - Purvesh Khatri
- Institute for Immunity, Transplantation and Infections, Stanford University, Palo Alto, CA, 94305, USA.,Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Palo Alto, CA, 94305, USA
| | - Angela J Rogers
- Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, Stanford University, Palo Alto, CA, 94305, USA
| | - Timothy E Sweeney
- Inflammatix, Inc., 863 Mitten Rd, Suite 104, Burlingame, CA, 94010, USA.
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35
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Zerbib Y, Jenkins EK, Shojaei M, Meyers AFA, Ho J, Ball TB, Keynan Y, Pisipati A, Kumar A, Kumar A, Nalos M, Tang BM, Schughart K, McLean A. Pathway mapping of leukocyte transcriptome in influenza patients reveals distinct pathogenic mechanisms associated with progression to severe infection. BMC Med Genomics 2020; 13:28. [PMID: 32066441 PMCID: PMC7027223 DOI: 10.1186/s12920-020-0672-7] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2019] [Accepted: 01/27/2020] [Indexed: 12/11/2022] Open
Abstract
Background Influenza infections produce a spectrum of disease severity, ranging from a mild respiratory illness to respiratory failure and death. The host-response pathways associated with the progression to severe influenza disease are not well understood. Methods To gain insight into the disease mechanisms associated with progression to severe infection, we analyzed the leukocyte transcriptome in severe and moderate influenza patients and healthy control subjects. Pathway analysis on differentially expressed genes was performed using a topology-based pathway analysis tool that takes into account the interaction between multiple cellular pathways. The pathway profiles between moderate and severe influenza were then compared to delineate the biological mechanisms underpinning the progression from moderate to severe influenza. Results 107 patients (44 severe and 63 moderate influenza patients) and 52 healthy control subjects were included in the study. Severe influenza was associated with upregulation in several neutrophil-related pathways, including pathways involved in neutrophil differentiation, migration, degranulation and neutrophil extracellular trap (NET) formation. The degree of upregulation in neutrophil-related pathways were significantly higher in severely infected patients compared to moderately infected patients. Severe influenza was also associated with downregulation in immune response pathways, including pathways involved in antigen presentation such as CD4+ T-cell co-stimulation, CD8+ T cell and Natural Killer (NK) cells effector functions. Apoptosis pathways were also downregulated in severe influenza patients compare to moderate and healthy controls. Conclusions These findings showed that there are changes in gene expression profile that may highlight distinct pathogenic mechanisms associated with progression from moderate to severe influenza infection.
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Affiliation(s)
- Yoann Zerbib
- Department of medical Intensive Care, Amiens University Hospital, Amiens, France. .,Department of Intensive Care Medicine, Nepean Hospital, Sydney, Australia. .,Centre for immunology and allergy research, the Westmead Institute for Medical Research, Sydney, Australia.
| | - Emily K Jenkins
- Department of Intensive Care Medicine, Nepean Hospital, Sydney, Australia
| | - Maryam Shojaei
- Department of Intensive Care Medicine, Nepean Hospital, Sydney, Australia.,Centre for immunology and allergy research, the Westmead Institute for Medical Research, Sydney, Australia
| | - Adrienne F A Meyers
- National HIV and Retrovirology Laboratories, JC Wilt infectious disease research centre, Public health agency of Canada, Winnipeg, Canada.,Department of medical microbiology and infectious diseases, University of Manitoba, Winnipeg, Canada
| | - John Ho
- National HIV and Retrovirology Laboratories, JC Wilt infectious disease research centre, Public health agency of Canada, Winnipeg, Canada.,Department of medical microbiology and infectious diseases, University of Manitoba, Winnipeg, Canada
| | - T Blake Ball
- National HIV and Retrovirology Laboratories, JC Wilt infectious disease research centre, Public health agency of Canada, Winnipeg, Canada.,Department of medical microbiology and infectious diseases, University of Manitoba, Winnipeg, Canada
| | - Yoav Keynan
- Department of internal medicine, medical microbiology and community health sciences, University of Manitoba, Winnipeg, Canada
| | - Amarnath Pisipati
- Department of medical microbiology and infectious diseases, University of Manitoba, Winnipeg, Canada.,Department of chemistry and chemical biology, Harvard University, Cambridge, USA
| | - Aseem Kumar
- Department of chemistry and biochemistry, Laurentian University, Sudbury, Canada
| | - Anand Kumar
- Section of critical care medicine and section of infectious diseases, department of medicine, medical microbiology and pharmacology, University of Manitoba, Winnipeg, Canada
| | - Marek Nalos
- Department of Intensive Care Medicine, Nepean Hospital, Sydney, Australia
| | - Benjamin M Tang
- Department of Intensive Care Medicine, Nepean Hospital, Sydney, Australia.,Centre for immunology and allergy research, the Westmead Institute for Medical Research, Sydney, Australia
| | - Klaus Schughart
- Department of Infection Genetics, Helmholtz Centre for Infection Research, Braunschweig, Germany.,University of Veterinary Medicine Hannover, Hannover, Germany.,Department of Microbiology, Immunology and Biochemistry, University of Tennessee Health Science Center, Memphis, Tennessee, Germany
| | - Anthony McLean
- Department of Intensive Care Medicine, Nepean Hospital, Sydney, Australia
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36
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Price A, Okumura A, Haddock E, Feldmann F, Meade-White K, Sharma P, Artami M, Lipkin WI, Threadgill DW, Feldmann H, Rasmussen AL. Transcriptional Correlates of Tolerance and Lethality in Mice Predict Ebola Virus Disease Patient Outcomes. Cell Rep 2020; 30:1702-1713.e6. [PMID: 32049004 PMCID: PMC11062563 DOI: 10.1016/j.celrep.2020.01.026] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2019] [Revised: 11/07/2019] [Accepted: 01/07/2020] [Indexed: 01/26/2023] Open
Abstract
Host response to infection is a major determinant of disease severity in Ebola virus disease (EVD), but gene expression programs associated with outcome are poorly characterized. Collaborative Cross (CC) mice develop strain-dependent EVD phenotypes of differential severity, ranging from tolerance to lethality. We screen 10 CC lines and identify clinical, virologic, and transcriptomic features that distinguish tolerant from lethal outcomes. Tolerance is associated with tightly regulated induction of immune and inflammatory responses shortly following infection, as well as reduced inflammatory macrophages and increased antigen-presenting cells, B-1 cells, and γδ T cells. Lethal disease is characterized by suppressed early gene expression and reduced lymphocytes, followed by uncontrolled inflammatory signaling, leading to death. We apply machine learning to predict outcomes with 99% accuracy in mice using transcriptomic profiles. This signature predicts outcomes in a cohort of EVD patients from western Africa with 75% accuracy, demonstrating potential clinical utility.
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Affiliation(s)
- Adam Price
- Center for Infection and Immunity, Columbia Mailman School of Public Health, New York, NY 10032, USA
| | - Atsushi Okumura
- Center for Infection and Immunity, Columbia Mailman School of Public Health, New York, NY 10032, USA; Laboratory of Virology, Rocky Mountain Laboratories, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT 59840, USA
| | - Elaine Haddock
- Laboratory of Virology, Rocky Mountain Laboratories, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT 59840, USA
| | - Friederike Feldmann
- Rocky Mountain Veterinary Branch, Rocky Mountain Laboratories, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT 59840, USA
| | - Kimberly Meade-White
- Laboratory of Virology, Rocky Mountain Laboratories, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT 59840, USA; Rocky Mountain Veterinary Branch, Rocky Mountain Laboratories, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT 59840, USA
| | - Pryanka Sharma
- Center for Infection and Immunity, Columbia Mailman School of Public Health, New York, NY 10032, USA
| | - Methinee Artami
- Center for Infection and Immunity, Columbia Mailman School of Public Health, New York, NY 10032, USA
| | - W Ian Lipkin
- Center for Infection and Immunity, Columbia Mailman School of Public Health, New York, NY 10032, USA
| | - David W Threadgill
- Department of Molecular and Cellular Medicine, Texas A&M University Health Science Center, College Station, TX 77843, USA; Department of Biochemistry and Biophysics, Texas A&M University, College Station, TX 77843, USA
| | - Heinz Feldmann
- Laboratory of Virology, Rocky Mountain Laboratories, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT 59840, USA
| | - Angela L Rasmussen
- Center for Infection and Immunity, Columbia Mailman School of Public Health, New York, NY 10032, USA.
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37
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Yu J, Peterson DR, Baran AM, Bhattacharya S, Wylie TN, Falsey AR, Mariani TJ, Storch GA. Host Gene Expression in Nose and Blood for the Diagnosis of Viral Respiratory Infection. J Infect Dis 2020; 219:1151-1161. [PMID: 30339221 DOI: 10.1093/infdis/jiy608] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2018] [Accepted: 10/15/2018] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND Recently there has been a growing interest in the potential for host transcriptomic analysis to augment the diagnosis of infectious diseases. METHODS We compared nasal and blood samples for evaluation of the host transcriptomic response in children with acute respiratory syncytial virus (RSV) infection, symptomatic non-RSV respiratory virus infection, asymptomatic rhinovirus infection, and virus-negative asymptomatic controls. We used nested leave-one-pair-out cross-validation and supervised principal components analysis to define small sets of genes whose expression patterns accurately classified subjects. We validated gene classification scores using an external data set. RESULTS Despite lower quality of nasal RNA, the number of genes detected by microarray in each sample type was equivalent. Nasal gene expression signal derived mainly from epithelial cells but also included a variable leukocyte contribution. The number of genes with increased expression in virus-infected children was comparable in nasal and blood samples, while nasal samples also had decreased expression of many genes associated with ciliary function and assembly. Nasal gene expression signatures were as good or better for discriminating between symptomatic, asymptomatic, and uninfected children. CONCLSUSIONS Our results support the use of nasal samples to augment pathogen-based tests to diagnose viral respiratory infection.
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Affiliation(s)
- Jinsheng Yu
- Department of Genetics, Washington University School of Medicine, St. Louis, Missouri
| | - Derick R Peterson
- Department of Biostatistics and Computational Biology, University of Rochester School of Medicine, New York
| | - Andrea M Baran
- Department of Biostatistics and Computational Biology, University of Rochester School of Medicine, New York
| | - Soumyaroop Bhattacharya
- Division of Neonatology and Pediatric Molecular and Personalized Medicine Program, Department of Pediatrics, University of Rochester School of Medicine, New York
| | - Todd N Wylie
- Department of Pediatrics, Washington University School of Medicine, St. Louis, Missouri.,McDonnell Genome Institute, Washington University School of Medicine, St. Louis, Missouri
| | - Ann R Falsey
- Department of Medicine, University of Rochester School of Medicine, New York
| | - Thomas J Mariani
- Division of Neonatology and Pediatric Molecular and Personalized Medicine Program, Department of Pediatrics, University of Rochester School of Medicine, New York
| | - Gregory A Storch
- Department of Pediatrics, Washington University School of Medicine, St. Louis, Missouri
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38
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Arshad H, Alfonso JCL, Franke R, Michaelis K, Araujo L, Habib A, Zboromyrska Y, Lücke E, Strungaru E, Akmatov MK, Hatzikirou H, Meyer-Hermann M, Petersmann A, Nauck M, Brönstrup M, Bilitewski U, Abel L, Sievers J, Vila J, Illig T, Schreiber J, Pessler F. Decreased plasma phospholipid concentrations and increased acid sphingomyelinase activity are accurate biomarkers for community-acquired pneumonia. J Transl Med 2019; 17:365. [PMID: 31711507 PMCID: PMC6849224 DOI: 10.1186/s12967-019-2112-z] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2019] [Accepted: 10/26/2019] [Indexed: 02/07/2023] Open
Abstract
Background There continues to be a great need for better biomarkers and host-directed treatment targets for community-acquired pneumonia (CAP). Alterations in phospholipid metabolism may constitute a source of small molecule biomarkers for acute infections including CAP. Evidence from animal models of pulmonary infections and sepsis suggests that inhibiting acid sphingomyelinase (which releases ceramides from sphingomyelins) may reduce end-organ damage. Methods We measured concentrations of 105 phospholipids, 40 acylcarnitines, and 4 ceramides, as well as acid sphingomyelinase activity, in plasma from patients with CAP (n = 29, sampled on admission and 4 subsequent time points), chronic obstructive pulmonary disease exacerbation with infection (COPD, n = 13) as a clinically important disease control, and 33 age- and sex-matched controls. Results Phospholipid concentrations were greatly decreased in CAP and normalized along clinical improvement. Greatest changes were seen in phosphatidylcholines, followed by lysophosphatidylcholines, sphingomyelins and ceramides (three of which were upregulated), and were least in acylcarnitines. Changes in COPD were less pronounced, but also differed qualitatively, e.g. by increases in selected sphingomyelins. We identified highly accurate biomarkers for CAP (AUC ≤ 0.97) and COPD (AUC ≤ 0.93) vs. Controls, and moderately accurate biomarkers for CAP vs. COPD (AUC ≤ 0.83), all of which were phospholipids. Phosphatidylcholines, lysophosphatidylcholines, and sphingomyelins were also markedly decreased in S. aureus-infected human A549 and differentiated THP1 cells. Correlations with C-reactive protein and procalcitonin were predominantly negative but only of mild-to-moderate extent, suggesting that these markers reflect more than merely inflammation. Consistent with the increased ceramide concentrations, increased acid sphingomyelinase activity accurately distinguished CAP (fold change = 2.8, AUC = 0.94) and COPD (1.75, 0.88) from Controls and normalized with clinical resolution. Conclusions The results underscore the high potential of plasma phospholipids as biomarkers for CAP, begin to reveal differences in lipid dysregulation between CAP and infection-associated COPD exacerbation, and suggest that the decreases in plasma concentrations are at least partially determined by changes in host target cells. Furthermore, they provide validation in clinical blood samples of acid sphingomyelinase as a potential treatment target to improve clinical outcome of CAP.
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Affiliation(s)
- Haroon Arshad
- Research Group "Biomarkers for Infectious Diseases", TWINCORE Centre for Experimental and Clinical Infection Research, Feodor-Lynen-Str. 7, 30625, Hannover, Germany
| | - Juan Carlos López Alfonso
- Department of Systems Immunology and Braunschweig Integrated Centre of Systems Biology, Helmholtz Centre for Infection Research, Brunswick, Germany
| | - Raimo Franke
- Department of Chemical Biology, Helmholtz Centre for Infection Research and German Center for Infection Research (DZIF), Brunswick, Germany
| | - Katina Michaelis
- Clinic for Pneumology, Otto-von-Guericke University, Magdeburg, Germany
| | - Leonardo Araujo
- Research Group "Biomarkers for Infectious Diseases", TWINCORE Centre for Experimental and Clinical Infection Research, Feodor-Lynen-Str. 7, 30625, Hannover, Germany.,Helmholtz Centre for Infection Research, Brunswick, Germany
| | - Aamna Habib
- Research Group "Biomarkers for Infectious Diseases", TWINCORE Centre for Experimental and Clinical Infection Research, Feodor-Lynen-Str. 7, 30625, Hannover, Germany.,Department of Chemical Biology, Helmholtz Centre for Infection Research and German Center for Infection Research (DZIF), Brunswick, Germany
| | - Yuliya Zboromyrska
- Department of Clinical Microbiology, Biomedical Diagnostic Centre (CDB), Hospital Clinic, School of Medicine, University of Barcelona, Institute of Global Health (ISGlobal), Barcelona, Spain
| | - Eva Lücke
- Clinic for Pneumology, Otto-von-Guericke University, Magdeburg, Germany
| | - Emilia Strungaru
- Clinic for Pneumology, Otto-von-Guericke University, Magdeburg, Germany
| | - Manas K Akmatov
- Research Group "Biomarkers for Infectious Diseases", TWINCORE Centre for Experimental and Clinical Infection Research, Feodor-Lynen-Str. 7, 30625, Hannover, Germany.,Helmholtz Centre for Infection Research, Brunswick, Germany
| | - Haralampos Hatzikirou
- Department of Systems Immunology and Braunschweig Integrated Centre of Systems Biology, Helmholtz Centre for Infection Research, Brunswick, Germany
| | - Michael Meyer-Hermann
- Department of Systems Immunology and Braunschweig Integrated Centre of Systems Biology, Helmholtz Centre for Infection Research, Brunswick, Germany
| | - Astrid Petersmann
- Institute for Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany.,UMG-Laboratory, University Medicine Göttingen, Göttingen, Germany
| | - Matthias Nauck
- Institute for Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany.,DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, University Medicine, Greifswald, Germany
| | - Mark Brönstrup
- Department of Chemical Biology, Helmholtz Centre for Infection Research and German Center for Infection Research (DZIF), Brunswick, Germany
| | - Ursula Bilitewski
- Department of Chemical Biology, Helmholtz Centre for Infection Research and German Center for Infection Research (DZIF), Brunswick, Germany
| | - Laurent Abel
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM, Paris, France.,Paris Descartes University, Imagine Institute, Paris, France.,Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, Rockefeller University, New York, USA
| | - Jorg Sievers
- Clinical Microbiology, GlaxoSmithKline, Collegeville, PA, USA.,Clinical Development, ViiV Healthcare, Brentford, UK
| | - Jordi Vila
- Department of Clinical Microbiology, Biomedical Diagnostic Centre (CDB), Hospital Clinic, School of Medicine, University of Barcelona, Institute of Global Health (ISGlobal), Barcelona, Spain
| | - Thomas Illig
- Hannover Unified Biobank, Hannover Medical School, Hannover, Germany
| | - Jens Schreiber
- Clinic for Pneumology, Otto-von-Guericke University, Magdeburg, Germany
| | - Frank Pessler
- Research Group "Biomarkers for Infectious Diseases", TWINCORE Centre for Experimental and Clinical Infection Research, Feodor-Lynen-Str. 7, 30625, Hannover, Germany. .,Helmholtz Centre for Infection Research, Brunswick, Germany. .,Centre for Individualised Infection Medicine, Hannover, Germany.
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39
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Tsalik EL, Khine A, Talebpour A, Samiei A, Parmar V, Burke TW, Mcclain MT, Ginsburg GS, Woods CW, Henao R, Alavie T. Rapid, Sample-to-Answer Host Gene Expression Test to Diagnose Viral Infection. Open Forum Infect Dis 2019; 6:ofz466. [PMID: 34150923 DOI: 10.1093/ofid/ofz466] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2019] [Accepted: 10/23/2019] [Indexed: 12/14/2022] Open
Abstract
Objective Distinguishing bacterial, viral, or other etiologies of acute illness is diagnostically challenging with significant implications for appropriate antimicrobial use. Host gene expression offers a promising approach, although no clinically useful test has been developed yet to accomplish this. Here, Qvella's FAST HR (Richmond Hill, Ontario, Canada) process was developed to quantify previously identified host gene expression signatures in whole blood in <45 minutes. Method Whole blood was collected from 128 human subjects (mean age 47, range 18-88) with clinically adjudicated, microbiologically confirmed viral infection, bacterial infection, noninfectious illness, or healthy controls. Stabilized mRNA was released from cleaned and stabilized RNA-surfactant complexes using e-lysis, an electrical process providing a quantitative real-time reverse transcription polymerase chain reaction-ready sample. Threshold cycle values (CT) for 10 host response targets were normalized to hypoxanthine phosphoribosyltransferase 1 expression, a control mRNA. The transcripts in the signature were specifically chosen to discriminate viral from nonviral infection (bacterial, noninfectious illness, or healthy). Classification accuracy was determined using cross-validated sparse logistic regression. Results Reproducibility of mRNA quantification was within 1 cycle as compared to the difference seen between subjects with viral versus nonviral infection (up to 5.0 normalized CT difference). Classification of 128 subjects into viral or nonviral etiologies demonstrated 90.6% overall accuracy compared to 82.0% for procalcitonin (P = .06). FAST HR achieved rapid and accurate measurement of the host response to viral infection in less than 45 minutes. Conclusions These results demonstrate the ability to translate host gene expression signatures to clinical platforms for use in patients with suspected infection. Clinical Trials Registration NCT00258869.
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Affiliation(s)
- Ephraim L Tsalik
- Duke Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.,Emergency Medicine Service, Durham Veterans Affairs Health Care System, Durham, North Carolina, USA
| | - Ayeaye Khine
- Qvella Corporation, Richmond Hill, Ontario, Canada
| | | | | | - Vilcy Parmar
- Qvella Corporation, Richmond Hill, Ontario, Canada
| | - Thomas W Burke
- Duke Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA
| | - Micah T Mcclain
- Duke Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.,Medicine Service, Durham Veterans Affairs Health Care System, Durham, North Carolina, USA
| | - Geoffrey S Ginsburg
- Duke Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA
| | - Christopher W Woods
- Duke Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.,Medicine Service, Durham Veterans Affairs Health Care System, Durham, North Carolina, USA
| | - Ricardo Henao
- Duke Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.,Pratt School of Engineering, Duke University, Durham, North Carolina, USA
| | - Tino Alavie
- Qvella Corporation, Richmond Hill, Ontario, Canada
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40
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Lydon EC, Henao R, Burke TW, Aydin M, Nicholson BP, Glickman SW, Fowler VG, Quackenbush EB, Cairns CB, Kingsmore SF, Jaehne AK, Rivers EP, Langley RJ, Petzold E, Ko ER, McClain MT, Ginsburg GS, Woods CW, Tsalik EL. Validation of a host response test to distinguish bacterial and viral respiratory infection. EBioMedicine 2019; 48:453-461. [PMID: 31631046 PMCID: PMC6838360 DOI: 10.1016/j.ebiom.2019.09.040] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2019] [Revised: 09/19/2019] [Accepted: 09/20/2019] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Distinguishing bacterial and viral respiratory infections is challenging. Novel diagnostics based on differential host gene expression patterns are promising but have not been translated to a clinical platform nor extensively tested. Here, we validate a microarray-derived host response signature and explore performance in microbiology-negative and coinfection cases. METHODS Subjects with acute respiratory illness were enrolled in participating emergency departments. Reference standard was an adjudicated diagnosis of bacterial infection, viral infection, both, or neither. An 87-transcript signature for distinguishing bacterial, viral, and noninfectious illness was measured from peripheral blood using RT-PCR. Performance characteristics were evaluated in subjects with confirmed bacterial, viral, or noninfectious illness. Subjects with bacterial-viral coinfection and microbiologically-negative suspected bacterial infection were also evaluated. Performance was compared to procalcitonin. FINDINGS 151 subjects with microbiologically confirmed, single-etiology illness were tested, yielding AUROCs 0•85-0•89 for bacterial, viral, and noninfectious illness. Accuracy was similar to procalcitonin (88% vs 83%, p = 0•23) for bacterial vs. non-bacterial infection. Whereas procalcitonin cannot distinguish viral from non-infectious illness, the RT-PCR test had 81% accuracy in making this determination. Bacterial-viral coinfection was subdivided. Among 19 subjects with bacterial superinfection, the RT-PCR test identified 95% as bacterial, compared to 68% with procalcitonin (p = 0•13). Among 12 subjects with bacterial infection superimposed on chronic viral infection, the RT-PCR test identified 83% as bacterial, identical to procalcitonin. 39 subjects had suspected bacterial infection; the RT-PCR test identified bacterial infection more frequently than procalcitonin (82% vs 64%, p = 0•02). INTERPRETATION The RT-PCR test offered similar diagnostic performance to procalcitonin in some subgroups but offered better discrimination in others such as viral vs. non-infectious illness and bacterial/viral coinfection. Gene expression-based tests could impact decision-making for acute respiratory illness as well as a growing number of other infectious and non-infectious diseases.
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Affiliation(s)
- Emily C Lydon
- Duke University School of Medicine, Durham, NC, USA; Duke University Center for Applied Genomics and Precision Medicine, Durham, NC, USA
| | - Ricardo Henao
- Duke University Department of Biostatistics and Informatics, Durham, NC, USA
| | - Thomas W Burke
- Duke University Center for Applied Genomics and Precision Medicine, Durham, NC, USA
| | - Mert Aydin
- Duke University Center for Applied Genomics and Precision Medicine, Durham, NC, USA
| | - Bradly P Nicholson
- Institute of Medical Research, Durham Veterans Affairs Medical Center, Durham, NC, USA
| | - Seth W Glickman
- University of North Carolina Medical Center, Chapel Hill, NC, USA
| | - Vance G Fowler
- Duke University Department of Medicine, Durham, NC, USA; Duke Clinical Research Institute, Durham, NC, USA
| | | | - Charles B Cairns
- University of North Carolina Medical Center, Chapel Hill, NC, USA; United Arab Emirates University, Al Ain, UAE
| | | | | | | | - Raymond J Langley
- University of South Alabama Health University Hospital, Mobile, AL, USA
| | - Elizabeth Petzold
- Duke University Center for Applied Genomics and Precision Medicine, Durham, NC, USA
| | - Emily R Ko
- Duke University Center for Applied Genomics and Precision Medicine, Durham, NC, USA; Department of Hospital Medicine, Duke Regional Hospital, Durham, NC 27705, USA
| | - Micah T McClain
- Duke University Center for Applied Genomics and Precision Medicine, Durham, NC, USA; Durham Veterans Affairs Health Care System, Durham, NC, USA
| | - Geoffrey S Ginsburg
- Duke University Center for Applied Genomics and Precision Medicine, Durham, NC, USA
| | - Christopher W Woods
- Duke University Center for Applied Genomics and Precision Medicine, Durham, NC, USA; Durham Veterans Affairs Health Care System, Durham, NC, USA.
| | - Ephraim L Tsalik
- Duke University Center for Applied Genomics and Precision Medicine, Durham, NC, USA; Durham Veterans Affairs Health Care System, Durham, NC, USA.
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41
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Unsupervised Analysis of Transcriptomics in Bacterial Sepsis Across Multiple Datasets Reveals Three Robust Clusters. Crit Care Med 2019. [PMID: 29537985 DOI: 10.1097/ccm.0000000000003084] [Citation(s) in RCA: 193] [Impact Index Per Article: 38.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
OBJECTIVES To find and validate generalizable sepsis subtypes using data-driven clustering. DESIGN We used advanced informatics techniques to pool data from 14 bacterial sepsis transcriptomic datasets from eight different countries (n = 700). SETTING Retrospective analysis. SUBJECTS Persons admitted to the hospital with bacterial sepsis. INTERVENTIONS None. MEASUREMENTS AND MAIN RESULTS A unified clustering analysis across 14 discovery datasets revealed three subtypes, which, based on functional analysis, we termed "Inflammopathic, Adaptive, and Coagulopathic." We then validated these subtypes in nine independent datasets from five different countries (n = 600). In both discovery and validation data, the Adaptive subtype is associated with a lower clinical severity and lower mortality rate, and the Coagulopathic subtype is associated with higher mortality and clinical coagulopathy. Further, these clusters are statistically associated with clusters derived by others in independent single sepsis cohorts. CONCLUSIONS The three sepsis subtypes may represent a unifying framework for understanding the molecular heterogeneity of the sepsis syndrome. Further study could potentially enable a precision medicine approach of matching novel immunomodulatory therapies with septic patients most likely to benefit.
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42
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Characterization of cellular transcriptomic signatures induced by different respiratory viruses in human reconstituted airway epithelia. Sci Rep 2019; 9:11493. [PMID: 31391513 PMCID: PMC6685967 DOI: 10.1038/s41598-019-48013-7] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2019] [Accepted: 07/29/2019] [Indexed: 11/17/2022] Open
Abstract
Acute respiratory infections, a large part being of viral origin, constitute a major public health issue. To propose alternative and/or new therapeutic approaches, it is necessary to increase our knowledge about the interactions between respiratory viruses and their primary cellular targets using the most biologically relevant experimental models. In this study, we used RNAseq to characterize and compare the transcriptomic signature of infection induced by different major respiratory viruses (Influenza viruses, hRSV and hMPV) in a model of reconstituted human airway epithelia. Our results confirm the importance of several cellular pathways commonly or specifically induced by these respiratory viruses, such as the innate immune response or antiviral defense. A very interesting common feature revealed by the global virogenomic signature shared between hRSV, hMPV and influenza viruses is the global downregulation of cilium-related gene expression, in good agreement with experimental evaluation of mucociliary clearance. Beyond providing new information about respiratory virus/host interactions, our study also underlines the interest of using biologically relevant experimental models to study human respiratory viruses.
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43
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Tang BM, Shojaei M, Teoh S, Meyers A, Ho J, Ball TB, Keynan Y, Pisipati A, Kumar A, Eisen DP, Lai K, Gillett M, Santram R, Geffers R, Schreiber J, Mozhui K, Huang S, Parnell GP, Nalos M, Holubova M, Chew T, Booth D, Kumar A, McLean A, Schughart K. Neutrophils-related host factors associated with severe disease and fatality in patients with influenza infection. Nat Commun 2019; 10:3422. [PMID: 31366921 PMCID: PMC6668409 DOI: 10.1038/s41467-019-11249-y] [Citation(s) in RCA: 99] [Impact Index Per Article: 19.8] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2018] [Accepted: 06/28/2019] [Indexed: 11/09/2022] Open
Abstract
Severe influenza infection has no effective treatment available. One of the key barriers to developing host-directed therapy is a lack of reliable prognostic factors needed to guide such therapy. Here, we use a network analysis approach to identify host factors associated with severe influenza and fatal outcome. In influenza patients with moderate-to-severe diseases, we uncover a complex landscape of immunological pathways, with the main changes occurring in pathways related to circulating neutrophils. Patients with severe disease display excessive neutrophil extracellular traps formation, neutrophil-inflammation and delayed apoptosis, all of which have been associated with fatal outcome in animal models. Excessive neutrophil activation correlates with worsening oxygenation impairment and predicted fatal outcome (AUROC 0.817-0.898). These findings provide new evidence that neutrophil-dominated host response is associated with poor outcomes. Measuring neutrophil-related changes may improve risk stratification and patient selection, a critical first step in developing host-directed immune therapy.
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Affiliation(s)
- Benjamin M Tang
- Department of Intensive Care Medicine, Nepean Hospital, Sydney, Australia. .,Centre for Immunology and Allergy Research, The Westmead Institute for Medical Research, Sydney, Australia. .,Respiratory Tract Infection Research Node, Marie Bashir Institute for Infectious Diseases and Biosecurity, Sydney, Australia.
| | - Maryam Shojaei
- Department of Intensive Care Medicine, Nepean Hospital, Sydney, Australia.,Centre for Immunology and Allergy Research, The Westmead Institute for Medical Research, Sydney, Australia
| | - Sally Teoh
- Department of Intensive Care Medicine, Nepean Hospital, Sydney, Australia
| | - Adrienne Meyers
- National HIV and Retrovirology Laboratories, JC Wilt Infectious Disease Research Centre, Public Health Agency of Canada, Department of Medical Microbiology and Infectious Disease, University of Manitoba, Winnipeg, Canada
| | - John Ho
- National HIV and Retrovirology Laboratories, JC Wilt Infectious Disease Research Centre, Public Health Agency of Canada, Department of Medical Microbiology and Infectious Disease, University of Manitoba, Winnipeg, Canada
| | - T Blake Ball
- National HIV and Retrovirology Laboratories, JC Wilt Infectious Disease Research Centre, Public Health Agency of Canada, Department of Medical Microbiology and Infectious Disease, University of Manitoba, Winnipeg, Canada
| | - Yoav Keynan
- Department of Internal Medicine, Medical Microbiology and Community Health Sciences, University of Manitoba, Winnipeg, Canada
| | - Amarnath Pisipati
- Department of Chemistry and Biological Chemistry, Harvard University, Cambridge, MA, USA
| | - Aseem Kumar
- Department of Chemistry and Biochemistry, Laurentian University, Laurentian, Canada
| | - Damon P Eisen
- Townsville Hospital, Townsville, Queensland, Australia
| | - Kevin Lai
- Department of Emergency Medicine, Westmead Hospital, Sydney, Australia
| | - Mark Gillett
- Department of Emergency Medicine, Royal North Shore Hospital, Sydney, Australia
| | - Rahul Santram
- Department of Emergency Medicine, St. Vincent Hospital, Sydney, Australia
| | - Robert Geffers
- Genome Analytics, Helmholtz Centre for Infection Research, Braunschweig, Germany
| | - Jens Schreiber
- Otto-von-Guerike University of Magdeburg, Clinic of Pneumology, Magdeburg, Germany
| | - Khyobeni Mozhui
- Department of Preventive Medicine, University of Tennessee Health Science Centre, Memphis, TN, USA
| | - Stephen Huang
- Department of Intensive Care Medicine, Nepean Hospital, Sydney, Australia
| | - Grant P Parnell
- Centre for Immunology and Allergy Research, The Westmead Institute for Medical Research, Sydney, Australia
| | - Marek Nalos
- Department of Intensive Care Medicine, Nepean Hospital, Sydney, Australia.,Department of Internal Medicine, Medical Faculty Plzen, Charles University Prague, Staré Město, Czech Republic
| | - Monika Holubova
- Biomedical Centre, Medical Faculty Plzen, Charles University Prague, Staré Město, Czech Republic
| | - Tracy Chew
- Sydney Informatic Hub, The University of Sydney, Sydney, Australia
| | - David Booth
- Centre for Immunology and Allergy Research, The Westmead Institute for Medical Research, Sydney, Australia
| | - Anand Kumar
- Section of Critical Care Medicine and Section of Infectious Diseases, Departments of Medicine, Medical Microbiology and Pharmacology, University of Manitoba, Winnipeg, Canada
| | - Anthony McLean
- Department of Intensive Care Medicine, Nepean Hospital, Sydney, Australia
| | - Klaus Schughart
- Department of Infection Genetics, Helmholtz Centre for Infection Research, Braunschweig, Germany.,University of Veterinary Medicine, Hannover, Germany.,Department of Microbiology, Immunology and Biochemistry, University of Tennessee Health Science Centre, Memphis, TN, USA
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44
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Genomic Circuitry Underlying Immunological Response to Pediatric Acute Respiratory Infection. Cell Rep 2019; 22:411-426. [PMID: 29320737 DOI: 10.1016/j.celrep.2017.12.043] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2017] [Revised: 11/03/2017] [Accepted: 12/12/2017] [Indexed: 11/23/2022] Open
Abstract
Acute respiratory tract viral infections (ARTIs) cause significant morbidity and mortality. CD8 T cells are fundamental to host responses, but transcriptional alterations underlying anti-viral mechanisms and links to clinical characteristics remain unclear. CD8 T cell transcriptional circuitry in acutely ill pediatric patients with influenza-like illness was distinct for different viral pathogens. Although changes included expected upregulation of interferon-stimulated genes (ISGs), transcriptional downregulation was prominent upon exposure to innate immune signals in early IFV infection. Network analysis linked changes to severity of infection, asthma, sex, and age. An influenza pediatric signature (IPS) distinguished acute influenza from other ARTIs and outperformed other influenza prediction gene lists. The IPS allowed a deeper investigation of the connection between transcriptional alterations and clinical characteristics of acute illness, including age-based differences in circuits connecting the STAT1/2 pathway to ISGs. A CD8 T cell-focused systems immunology approach in pediatrics identified age-based alterations in ARTI host response pathways.
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Abstract
Pneumonia is a highly prevalent disease with considerable morbidity and mortality. However, diagnosis and therapy still rely on antiquated methods, leading to the vast overuse of antimicrobials, which carries risks for both society and the individual. Furthermore, outcomes in severe pneumonia remain poor. Genomic techniques have the potential to transform the management of pneumonia through deep characterization of pathogens as well as the host response to infection. This characterization will enable the delivery of selective antimicrobials and immunomodulatory therapy that will help to offset the disorder associated with overexuberant immune responses.
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Affiliation(s)
- Samir Gautam
- Pulmonary Critical Care and Sleep Medicine, Center for Pulmonary Infection Research and Treatment, Yale University, 300 Cedar Street, TACS441, New Haven, CT 06520-8057, USA
| | - Lokesh Sharma
- Pulmonary Critical Care and Sleep Medicine, Center for Pulmonary Infection Research and Treatment, Yale University, 300 Cedar Street, TACS441, New Haven, CT 06520-8057, USA
| | - Charles S Dela Cruz
- Pulmonary Critical Care and Sleep Medicine, Center for Pulmonary Infection Research and Treatment, Yale University, 300 Cedar Street, TACS441, New Haven, CT 06520-8057, USA.
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46
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Rao S, Ghosh D, Asturias EJ, Weinberg A. What can we learn about influenza infection and vaccination from transcriptomics? Hum Vaccin Immunother 2019; 15:2615-2623. [PMID: 31116679 PMCID: PMC6930070 DOI: 10.1080/21645515.2019.1608744] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
Transcriptomics studies the set of RNA transcripts produced by the genome using high-throughput sequencing and bioinformatics. This growing field has revolutionized our understanding of host-pathogen interactions, revealing new insights into the host response to influenza infection and vaccination. Studies using transcriptomics have identified a unique immunosignature for influenza discernable from other bacterial and viral pathogens, key transcriptional factors that discriminate early from late, mild versus severe, and symptomatic versus asymptomatic infection. Recent studies evaluating the host response to influenza vaccines have revealed key differences in live versus inactivated influenza vaccines, identified early transcriptional signatures that predict hemagglutinin antibody production following vaccination, increased our understanding of how adjuvants enhance the immune response to influenza vaccine antigens, and demonstrate biologic variability in the response to vaccination due to host factors. These studies demonstrate the potential for influenza transcriptomics to be applied to clinical care, understanding the mechanisms of infection, and informing vaccine development.
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Affiliation(s)
- Suchitra Rao
- Department of Pediatrics (Infectious Diseases, Hospital Medicine, Epidemiology), University of Colorado School of Medicine and Children's Hospital Colorado, Aurora, CO, USA
| | - Debashis Ghosh
- Department of Biostatistics and Informatics, Colorado School of Public Health, Aurora, CO, USA
| | - Edwin J Asturias
- Department of Pediatrics (Pediatric Infectious Diseases), University of Colorado School of Medicine and Children's Hospital Colorado and Department of Epidemiology, Center for Global Health, Colorado School of Public Health, Aurora, CO, USA
| | - Adriana Weinberg
- Department of Medicine, Pathology and Pediatrics, University of Colorado School of Medicine, Aurora, CO, USA
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47
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Bougarn S, Boughorbel S, Chaussabel D, Marr N. A curated transcriptome dataset collection to investigate the blood transcriptional response to viral respiratory tract infection and vaccination. F1000Res 2019; 8:284. [PMID: 31231515 PMCID: PMC6567289 DOI: 10.12688/f1000research.18533.1] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/07/2019] [Indexed: 12/13/2022] Open
Abstract
The human immune defense mechanisms and factors associated with good versus poor health outcomes following viral respiratory tract infections (VRTI), as well as correlates of protection following vaccination against respiratory viruses, remain incompletely understood. To shed further light into these mechanisms, a number of systems-scale studies have been conducted to measure transcriptional changes in blood leukocytes of either naturally or experimentally infected individuals, or in individual’s post-vaccination. Here we are making available a public repository, for research investigators for interpretation, a collection of transcriptome datasets obtained from human whole blood and peripheral blood mononuclear cells (PBMC) to investigate the transcriptional responses following viral respiratory tract infection or vaccination against respiratory viruses. In total, Thirty one31 datasets, associated to viral respiratory tract infections and their related vaccination studies, were identified and retrieved from the NCBI Gene Expression Omnibus (GEO) and loaded in a custom web application designed for interactive query and visualization of integrated large-scale data. Quality control checks, using relevant biological markers, were performed. Multiple sample groupings and rank lists were created to facilitate dataset query and interpretation. Via this interface, users can generate web links to customized graphical views, which may be subsequently inserted into manuscripts to report novel findings. The GXB tool enables browsing of a single gene across projects, providing new perspectives on the role of a given molecule across biological systems in the diagnostic and prognostic following VRTI but also in identifying new correlates of protection. This dataset collection is available at:
http://vri1.gxbsidra.org/dm3/geneBrowser/list.
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Affiliation(s)
- Salim Bougarn
- Systems Biology and Immunology Department, Sidra Medicine, Doha, Qatar
| | - Sabri Boughorbel
- Systems Biology and Immunology Department, Sidra Medicine, Doha, Qatar
| | - Damien Chaussabel
- Systems Biology and Immunology Department, Sidra Medicine, Doha, Qatar
| | - Nico Marr
- Systems Biology and Immunology Department, Sidra Medicine, Doha, Qatar
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Zhou S, Ren X, Yang J, Jin Q. Evaluating the Value of Defensins for Diagnosing Secondary Bacterial Infections in Influenza-Infected Patients. Front Microbiol 2018; 9:2762. [PMID: 30524393 PMCID: PMC6256186 DOI: 10.3389/fmicb.2018.02762] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2018] [Accepted: 10/29/2018] [Indexed: 11/13/2022] Open
Abstract
Acute respiratory infections by influenza viruses are commonly causes of severe pneumonia, which can further deteriorate if secondary bacterial infections occur. Although the viral and bacterial agents are quite diverse, defensins, a set of antimicrobial peptides expressed by the host, may provide promising biomarkers that would greatly improve the diagnosis and treatment. We examined the correlations between the gene expression levels of defensins and the viral and bacterial loads in the blood on a longitudinal, precision-medical study of a severe pneumonia patient infected by influenza A H7N9 virus. We found that DEFA5 is positively correlated to the blood load of influenza A H7N9 virus (r = 0.735, p < 0.05, Spearman correlation). DEFB116 and DEFB127 are positively and DEFB108B and DEFB114 are negatively correlated to the bacterial load. Then the diagnostic potential of defensins to discriminate bacterial and viral infections was evaluated on an independent dataset with 61 bacterial pneumonia patients and 39 viral pneumonia patients infected by influenza A viruses and reached 93% accuracy. Expression levels of defensins in the blood may be of important diagnostic values in clinic to indicate viral and bacterial infections.
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Affiliation(s)
- Siyu Zhou
- MOH Key Laboratory of Systems Biology of Pathogens, Peking Union Medical College, Institute of Pathogen Biology, Chinese Academy of Medical Sciences, Beijing, China
| | - Xianwen Ren
- BIOPIC, School of Life Sciences, Peking University, Beijing, China
| | - Jian Yang
- MOH Key Laboratory of Systems Biology of Pathogens, Peking Union Medical College, Institute of Pathogen Biology, Chinese Academy of Medical Sciences, Beijing, China
| | - Qi Jin
- MOH Key Laboratory of Systems Biology of Pathogens, Peking Union Medical College, Institute of Pathogen Biology, Chinese Academy of Medical Sciences, Beijing, China
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Fukutani KF, Nascimento-Carvalho CM, Bouzas ML, Oliveira JR, Barral A, Dierckx T, Khouri R, Nakaya HI, Andrade BB, Van Weyenbergh J, de Oliveira CI. In situ Immune Signatures and Microbial Load at the Nasopharyngeal Interface in Children With Acute Respiratory Infection. Front Microbiol 2018; 9:2475. [PMID: 30473680 PMCID: PMC6238668 DOI: 10.3389/fmicb.2018.02475] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2018] [Accepted: 09/27/2018] [Indexed: 12/13/2022] Open
Abstract
Acute respiratory infection (ARI) is the most frequent cause for hospitalization in infants and young children. Using multiplexed nCounter technology to digitally quantify 600 human mRNAs in parallel with 14 virus- and 5 bacterium-specific RNAs, we characterized viral and bacterial presence in nasopharyngeal aspirates (NPA) of 58 children with ARI and determined the corresponding in situ immune profiles. NPA contained different groups of organisms and these were classified into bacterial (n = 27), viral (n = 5), codetection [containing both viral and bacterial transcripts (n = 21), or indeterminate intermediate where microbial load is below threshold (n = 5)]. We then identified differentially expressed immune transcripts (DEITs) comparing NPAs from symptomatic children vs. healthy controls, and comparing children presenting NPAs with detectable microbial load vs. indeterminate. We observed a strong innate immune response in NPAs, due to the presence of evolutionarily conserved type I Interferon (IFN)-stimulated genes (ISG), which was correlated with total bacterial and/or viral load. In comparison with indeterminate NPAs, adaptive immunity transcripts discriminated among viral, bacterial, and codetected microbial profiles. In viral NPAs, B cell transcripts were significantly enriched among DEITs, while only type III IFN was correlated with viral load. In bacterial NPAs, myeloid cells and coinhibitory transcripts were enriched and significantly correlated with bacterial load. In conclusion, digital nCounter transcriptomics provide a microbial and immunological in situ “snapshot” of the nasopharyngeal interface in children with ARI. This enabled discrimination among viral, bacterial, codetection, and indeterminate transcripts in the samples using non-invasive sampling.
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Affiliation(s)
| | - Cristiana M Nascimento-Carvalho
- School of Medicine, Federal University of Bahia, Salvador, Brazil.,Department of Pediatrics, School of Medicine, Federal University of Bahia, Salvador, Brazil
| | - Maiara L Bouzas
- School of Medicine, Federal University of Bahia, Salvador, Brazil
| | | | - Aldina Barral
- Instituto Gonçalo Moniz-FIOCRUZ, Salvador, Brazil.,School of Medicine, Federal University of Bahia, Salvador, Brazil
| | - Tim Dierckx
- Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium
| | - Ricardo Khouri
- Instituto Gonçalo Moniz-FIOCRUZ, Salvador, Brazil.,School of Medicine, Federal University of Bahia, Salvador, Brazil
| | - Helder I Nakaya
- Department of Clinical and Toxicological Analyses, School of Pharmaceutical Sciences, University of São Paulo, São Paulo, Brazil
| | - Bruno B Andrade
- Instituto Gonçalo Moniz-FIOCRUZ, Salvador, Brazil.,Multinational Organization Network Sponsoring Translational and Epidemiological Research Initiative, Fundação José Silveira, Salvador, Brazil
| | - Johan Van Weyenbergh
- Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium
| | - Camila I de Oliveira
- Instituto Gonçalo Moniz-FIOCRUZ, Salvador, Brazil.,School of Medicine, Federal University of Bahia, Salvador, Brazil
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50
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Transcriptome Analysis of Infected and Bystander Type 2 Alveolar Epithelial Cells during Influenza A Virus Infection Reveals In Vivo Wnt Pathway Downregulation. J Virol 2018; 92:JVI.01325-18. [PMID: 30111569 DOI: 10.1128/jvi.01325-18] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2018] [Accepted: 08/12/2018] [Indexed: 12/29/2022] Open
Abstract
Influenza virus outbreaks remain a serious threat to public health. A greater understanding of how cells targeted by the virus respond to the infection can provide insight into the pathogenesis of disease. Here we examined the transcriptional profile of in vivo-infected and uninfected type 2 alveolar epithelial cells (AEC) in the lungs of influenza virus-infected mice. We show for the first time the unique gene expression profiles induced by the in vivo infection of AEC as well as the transcriptional response of uninfected bystander cells. This work allows us to distinguish the direct and indirect effects of infection at the cellular level. Transcriptome analysis revealed that although directly infected and bystander AEC from infected animals shared many transcriptome changes compared to AEC from uninfected animals, directly infected cells produce more interferon and express lower levels of Wnt signaling-associated transcripts, while concurrently expressing more transcripts associated with cell death pathways, than bystander uninfected AEC. The Wnt signaling pathway was downregulated in both in vivo-infected AEC and in vitro-infected human lung epithelial A549 cells. Wnt signaling did not affect type I and III interferon production by infected A549 cells. Our results reveal unique transcriptional changes that occur within infected AEC and show that influenza virus downregulates Wnt signaling. In light of recent findings that Wnt signaling is essential for lung epithelial stem cells, our findings reveal a mechanism by which influenza virus may affect host lung repair.IMPORTANCE Influenza virus infection remains a major public health problem. Utilizing a recombinant green fluorescent protein-expressing influenza virus, we compared the in vivo transcriptomes of directly infected and uninfected bystander cells from infected mouse lungs and discovered many pathways uniquely regulated in each population. The Wnt signaling pathway was downregulated in directly infected cells and was shown to affect virus but not interferon production. Our study is the first to discern the in vivo transcriptome changes induced by direct viral infection compared to mere exposure to the lung inflammatory milieu and highlight the downregulation of Wnt signaling. This downregulation has important implications for understanding influenza virus pathogenesis, as Wnt signaling is critical for lung epithelial stem cells and lung epithelial cell differentiation. Our findings reveal a mechanism by which influenza virus may affect host lung repair and suggest interventions that prevent damage or accelerate recovery of the lung.
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