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Pathogen-specific host gene expression patterns accurately discriminated most noninfectious from infectious illnesses, and bacterial from viral causes of acute respiratory infection (ARI) in an observational study conducted in acute care settings.
The findings could have important implications for combating inappropriate antibiotic use and emerging antibiotic resistance, Dr. Ephraim L. Tsalik of the department of medicine at Duke University, Durham, N.C., and his colleagues reported online Jan. 20 in Science Translational Medicine.
The investigators analyzed peripheral whole-blood gene expression from 273 subjects with community-onset viral ARI (115 subjects), bacterial ARI (70 subjects), or noninfectious illness (88 subjects) who were seen in an emergency department, and from 44 healthy control subjects. Classifiers for bacterial ARI, viral ARI, and noninfectious causes of illness were developed, and were 87% accurate overall (Sci Transl Med. 2016;8[322]:322ra11. doi/ 10.1126/scitranslmed.aad6873).
“Bacterial ARI was identified in 83% of patients and excluded in 94% without bacterial infection. Viral ARI was identified in 90% and excluded in 92% of cases. Using the noninfectious illness classifier, infection was excluded in 86% of cases,” they wrote.
The classifiers were more accurate than procalcitonin – a widely used biomarker with some specificity for bacterial infection (86% vs. 78% accuracy in 238 available samples), and three published classifiers of bacterial vs. viral infection, and were validated in five publicly available data sets, they noted.
The gene signature patterns identified in the course of this study mark an important step toward development of a rapid blood test that could be used in clinics to guide appropriate treatment for ARIs, the investigators said.
Precision treatment of viruses
More precise ways to distinguish infections could reduce unnecessary antibiotic use and lead to more precise treatment of viruses, senior author Dr. Geoffrey S. Ginsburg, director of Duke’s Center for Applied Genomics & Precision Medicine, said in a press statement.
“Right now, we can give patients [oseltamivir] Tamiflu to help them recover from an influenza infection, but for most viral infections, the treatment is fluids and rest until it resolves. In the next 5-10 years, we will likely see new antiviral medications for common bugs like respiratory syncytial virus and even rhinovirus, and guiding treatment choices will be even more important,” he added.
Senior author Dr. Christopher W. Woods, also of Duke University, further explained in an interview that the findings are particularly exciting because “there isn’t much out there that accomplishes what we’ve done. So just about any level of accuracy is an improvement.” Further, he said the test is “a tool to aid in diagnosis, used in conjunction with the patient’s symptoms, examination, and other testing. So an imperfect test is okay, because it does not stand alone.”
Next steps include putting the assay on a testing platform that can be used at the point of care, and validating the findings in all populations, including infants, the elderly, and across ethnic groups, he said.
“The work is ongoing, and we expect to have results available within the course of an outpatient visit in the near future,” Dr. Woods, also a professor of medicine and global health, added, noting that efforts also are underway to “expand the repertoire of this approach to many different types of viral and bacterial infections and also to fungal infections, and to address the challenges of critically ill patients in intensive care units.”
This study was supported by the U.S. Defense Advanced Research Projects Agency, the National Institutes of Health, the Agency for Healthcare Research and Quality, the U.S. Department of Veterans Affairs Office of Research and Development, and an in-kind contribution from bioMérieux. The authors reported having no relevant competing interests.
Pathogen-specific host gene expression patterns accurately discriminated most noninfectious from infectious illnesses, and bacterial from viral causes of acute respiratory infection (ARI) in an observational study conducted in acute care settings.
The findings could have important implications for combating inappropriate antibiotic use and emerging antibiotic resistance, Dr. Ephraim L. Tsalik of the department of medicine at Duke University, Durham, N.C., and his colleagues reported online Jan. 20 in Science Translational Medicine.
The investigators analyzed peripheral whole-blood gene expression from 273 subjects with community-onset viral ARI (115 subjects), bacterial ARI (70 subjects), or noninfectious illness (88 subjects) who were seen in an emergency department, and from 44 healthy control subjects. Classifiers for bacterial ARI, viral ARI, and noninfectious causes of illness were developed, and were 87% accurate overall (Sci Transl Med. 2016;8[322]:322ra11. doi/ 10.1126/scitranslmed.aad6873).
“Bacterial ARI was identified in 83% of patients and excluded in 94% without bacterial infection. Viral ARI was identified in 90% and excluded in 92% of cases. Using the noninfectious illness classifier, infection was excluded in 86% of cases,” they wrote.
The classifiers were more accurate than procalcitonin – a widely used biomarker with some specificity for bacterial infection (86% vs. 78% accuracy in 238 available samples), and three published classifiers of bacterial vs. viral infection, and were validated in five publicly available data sets, they noted.
The gene signature patterns identified in the course of this study mark an important step toward development of a rapid blood test that could be used in clinics to guide appropriate treatment for ARIs, the investigators said.
Precision treatment of viruses
More precise ways to distinguish infections could reduce unnecessary antibiotic use and lead to more precise treatment of viruses, senior author Dr. Geoffrey S. Ginsburg, director of Duke’s Center for Applied Genomics & Precision Medicine, said in a press statement.
“Right now, we can give patients [oseltamivir] Tamiflu to help them recover from an influenza infection, but for most viral infections, the treatment is fluids and rest until it resolves. In the next 5-10 years, we will likely see new antiviral medications for common bugs like respiratory syncytial virus and even rhinovirus, and guiding treatment choices will be even more important,” he added.
Senior author Dr. Christopher W. Woods, also of Duke University, further explained in an interview that the findings are particularly exciting because “there isn’t much out there that accomplishes what we’ve done. So just about any level of accuracy is an improvement.” Further, he said the test is “a tool to aid in diagnosis, used in conjunction with the patient’s symptoms, examination, and other testing. So an imperfect test is okay, because it does not stand alone.”
Next steps include putting the assay on a testing platform that can be used at the point of care, and validating the findings in all populations, including infants, the elderly, and across ethnic groups, he said.
“The work is ongoing, and we expect to have results available within the course of an outpatient visit in the near future,” Dr. Woods, also a professor of medicine and global health, added, noting that efforts also are underway to “expand the repertoire of this approach to many different types of viral and bacterial infections and also to fungal infections, and to address the challenges of critically ill patients in intensive care units.”
This study was supported by the U.S. Defense Advanced Research Projects Agency, the National Institutes of Health, the Agency for Healthcare Research and Quality, the U.S. Department of Veterans Affairs Office of Research and Development, and an in-kind contribution from bioMérieux. The authors reported having no relevant competing interests.
Pathogen-specific host gene expression patterns accurately discriminated most noninfectious from infectious illnesses, and bacterial from viral causes of acute respiratory infection (ARI) in an observational study conducted in acute care settings.
The findings could have important implications for combating inappropriate antibiotic use and emerging antibiotic resistance, Dr. Ephraim L. Tsalik of the department of medicine at Duke University, Durham, N.C., and his colleagues reported online Jan. 20 in Science Translational Medicine.
The investigators analyzed peripheral whole-blood gene expression from 273 subjects with community-onset viral ARI (115 subjects), bacterial ARI (70 subjects), or noninfectious illness (88 subjects) who were seen in an emergency department, and from 44 healthy control subjects. Classifiers for bacterial ARI, viral ARI, and noninfectious causes of illness were developed, and were 87% accurate overall (Sci Transl Med. 2016;8[322]:322ra11. doi/ 10.1126/scitranslmed.aad6873).
“Bacterial ARI was identified in 83% of patients and excluded in 94% without bacterial infection. Viral ARI was identified in 90% and excluded in 92% of cases. Using the noninfectious illness classifier, infection was excluded in 86% of cases,” they wrote.
The classifiers were more accurate than procalcitonin – a widely used biomarker with some specificity for bacterial infection (86% vs. 78% accuracy in 238 available samples), and three published classifiers of bacterial vs. viral infection, and were validated in five publicly available data sets, they noted.
The gene signature patterns identified in the course of this study mark an important step toward development of a rapid blood test that could be used in clinics to guide appropriate treatment for ARIs, the investigators said.
Precision treatment of viruses
More precise ways to distinguish infections could reduce unnecessary antibiotic use and lead to more precise treatment of viruses, senior author Dr. Geoffrey S. Ginsburg, director of Duke’s Center for Applied Genomics & Precision Medicine, said in a press statement.
“Right now, we can give patients [oseltamivir] Tamiflu to help them recover from an influenza infection, but for most viral infections, the treatment is fluids and rest until it resolves. In the next 5-10 years, we will likely see new antiviral medications for common bugs like respiratory syncytial virus and even rhinovirus, and guiding treatment choices will be even more important,” he added.
Senior author Dr. Christopher W. Woods, also of Duke University, further explained in an interview that the findings are particularly exciting because “there isn’t much out there that accomplishes what we’ve done. So just about any level of accuracy is an improvement.” Further, he said the test is “a tool to aid in diagnosis, used in conjunction with the patient’s symptoms, examination, and other testing. So an imperfect test is okay, because it does not stand alone.”
Next steps include putting the assay on a testing platform that can be used at the point of care, and validating the findings in all populations, including infants, the elderly, and across ethnic groups, he said.
“The work is ongoing, and we expect to have results available within the course of an outpatient visit in the near future,” Dr. Woods, also a professor of medicine and global health, added, noting that efforts also are underway to “expand the repertoire of this approach to many different types of viral and bacterial infections and also to fungal infections, and to address the challenges of critically ill patients in intensive care units.”
This study was supported by the U.S. Defense Advanced Research Projects Agency, the National Institutes of Health, the Agency for Healthcare Research and Quality, the U.S. Department of Veterans Affairs Office of Research and Development, and an in-kind contribution from bioMérieux. The authors reported having no relevant competing interests.
FROM SCIENCE TRANSLATIONAL MEDICINE
Key clinical point: Pathogen-specific host gene expression patterns accurately discriminated most noninfectious from infectious illnesses, and bacterial from viral causes of acute respiratory infection (ARI) in an observational study.
Major finding: Classifiers for bacterial ARI, viral ARI, and noninfectious causes of illness were 87% accurate overall.
Data source: An observational cohort study involving 273 patients and 44 controls.
Disclosures: This study was supported by the U.S. Defense Advanced Research Projects Agency, the National Institutes of Health, the Agency for Healthcare Research and Quality, the U.S. Department of Veterans Affairs Office of Research and Development, and an in-kind contribution from bioMérieux. The authors reported having no relevant competing interests..
