Previously Derived Host Gene Expression Classifiers Identify Bacterial and Viral Etiologies of Acute Febrile Respiratory Illness in a South Asian Population.
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2020-06
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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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Tillekeratne, L Gayani, Sunil Suchindran, Emily R Ko, Elizabeth A Petzold, Champica K Bodinayake, Ajith Nagahawatte, Vasantha Devasiri, Ruvini Kurukulasooriya, et al. (2020). Previously Derived Host Gene Expression Classifiers Identify Bacterial and Viral Etiologies of Acute Febrile Respiratory Illness in a South Asian Population. Open forum infectious diseases, 7(6). p. ofaa194. 10.1093/ofid/ofaa194 Retrieved from https://hdl.handle.net/10161/23217.
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Scholars@Duke
Gayani Tillekeratne
Global health
Antimicrobial resistance/ stewardship
Acute respiratory tract infections
Emerging infections/ dengue
Emily Ray Ko
Clinical and translational research, COVID-19 therapeutics, clinical biomarkers for infectious disease.
Micah Thomas McClain
Ephraim Tsalik
My research at Duke has focused on understanding the dynamic between host and pathogen so as to discover and develop host-response markers that can diagnose and predict health and disease. This new and evolving approach to diagnosing illness has the potential to significantly impact individual as well as public health considering the rise of antibiotic resistance.
With any potential infectious disease diagnosis, it is difficult, if not impossible, to determine at the time of presentation what the underlying cause of illness is. For example, acute respiratory illness is among the most frequent reasons for patients to seek care. These symptoms, such as cough, sore throat, and fever may be due to a bacterial infection, viral infection, both, or a non-infectious condition such as asthma or allergies. Given the difficulties in making the diagnosis, most patients are inappropriately given antibacterials. However, each of these etiologies (bacteria, virus, or something else entirely) leaves a fingerprint embedded in the host’s response. We are very interested in finding those fingerprints and exploiting them to generate new approaches to understand, diagnose, and manage disease.
These principles also apply to sepsis, defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. Just as with acute respiratory illness, it is often difficult to identify whether infection is responsible for a patient’s critical illness. We have embarked on a number of research programs that aim to better identify sepsis; define sepsis subtypes that can be used to guide future clinical research; and to better predict sepsis outcomes. These efforts have focused on many systems biology modalities including transcriptomics, miRNA, metabolomics, and proteomics. Consequently, our Data Science team has utilized these highly complex data to develop new statistical methods, furthering both the clinical and statistical research communities.
These examples are just a small sampling of the breadth of research Dr. Tsalik and his colleagues have conducted.
In April 2022, Dr. Tsalik has joined Danaher Diagnostics as the VP and Chief Scientific Officer for Infectious Disease, where he is applying this experience in biomarkers and diagnostics to shape the future of diagnostics in ID.
Ricardo Henao
Geoffrey Steven Ginsburg
Dr. Geoffrey S. Ginsburg's research interests are in the development of novel paradigms for developing and translating genomic information into medical practice and the integration of personalized medicine into health care.
Megan Elizabeth Reller
Christopher Wildrick Woods
1. Emerging Infections
2. Global Health
3. Epidemiology of infectious diseases
4. Clinical microbiology and diagnostics
5. Bioterrorism Preparedness
6. Surveillance for communicable diseases
7. Antimicrobial resistance
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