My research is 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.
Synergy between multi-disciplinary experts is crucial to tackle the threats posed by infectious diseases and the rise in antimicrobial resistance. We have successfully assembled a team of clinical scientists, data scientists, laboratorians, clinical research coordinators, among many others. Potential collaborators are encouraged to contact us.
These examples are just a small sampling of the breadth of research Dr. Tsalik and his colleagues conduct. Please visit https://precisionmedicine.duke.edu/ for more details.
Education and Training
- Columbia University, College of Physicians and Surgeons, Ph.D. 2003
- Columbia University, College of Physicians and Surgeons, M.D. 2005
- Duke University School of Medicine, Residency, Medicine
- Duke University School of Medicine, Fellowship in Infectious Diseases, Medicine
Selected Grants and Awards
- AMR Challenge Award 2
- VTEU Task Area C Option 1 Protocol 15-0020.B1C1.0040
- Adaptive COVID-19 Treatment Trial (ACTT)
- VTEU Task Area C Option 2-3 Protocol 15-0020.B1C1.0040
- Mapping Epigenetic Memory of Exposure New To Observe (MEMENTO)
- PREdicting contagion using Systems And GEnomic analysis (PRESAGE)
- Novel host-based diagnostics of febrile illness in the warfighter
- VTEU Task Area C Option 2-2 Protocol 15-0020.B1C1.0040
- AMR Challenge Award
- VTEU Task Area C Option 2-1 Protocol 15-0020.B1C1.0040
- Novel Dialysis-Like Therapeutics in Sepsis-induced Shock and Organ Failure
- VTEU Task Area B Protocol 15-0020.B1C1.0040
- Feasibility for Predicting Warfighter Health Using Transcriptional Markers on the MAP Platform
- Validation of the host transcription diagnostic for prediction of incipient respiratory viral infection