Enhancing the Diagnosis of FIP
Feline infectious peritonitis (FIP) is a devastating infectious disease of felids infected with feline coronavirus (FCoV) that, until recently, has been challenging to diagnose, because of the non-specific clinical signs that could be related to many diseases and infections. Both chronic and acute forms of the disease occur, with cats exhibiting general signs such as pyrexia, lethargy, inappetance, anorexia and mood changes; the acute form is commonly accompanied by a build-up of viscous fluid in the chest or abdomen. The pathogenesis remains poorly understood even after decades of research; this lack of knowledge impedes diagnosis, treatment and prevention.
Accurate and timely diagnosis of FIP has always been important, however the emphasis has grown as we now have effective anti-viral treatments which can be administered to stop viral replication and in turn the pathogenesis associated with FIPV infection. A treatment course is expensive, therefore clinicians demand as much certainty as possible that the patients diagnosis is FIP before commencing treatment. It should be noted that there are several places around the globe where licensed prepartions are still unavailable.
I am a highly motivated scientist with a keen interest in virology and specifically viral diagnostics; my interest in FIP has grown from working in a laboratory well known for its involvement in FIP research.
Research themes
During the course of my PhD project, I will undertake research on a number of themes related to improving FIP diagnostics.
Specifically, I intend to:
1. Evaluate the current range of host parameters used for FIP diagnosis
2. Identify novel biomarkers using established and emerging technologies
3. Develop diagnostic models to allow quantitative FIP diagnostics
As the project develops, I will investigate the molecular epidemiology of FCoV infection and evaluate whether viral and/or host sequence data could improve diagnostic capabilities.
Collaborative Research
The project is a collaborative effort involving the School of Biodiversity, One Health and Veterinary Medicine and the Centre for Virus Research (CVR) at the University of Glasgow. My primary project supervisor is Dr Willie Weir, the clinical lead in Infectious Disease in the Veterinary Diagnostic Service and a specialist in parasitology and bioinformatics. My second supervisor is Prof Margaret Hosie, a professor of comparative virology at the CVR with an international reputation in feline virus research. Dr Simon Babayan recently joined my supervisory team. Simon is a member of the School of Biodiversity, One Health and Veterinary Medicine. He has a wealth of experience in the field of machine learning and disease modelling, as such he will be instrumental in guiding the technical aspects of this project.
Links
Schools and research institutes
School of Biodiversity, One Health and Veterinary Medicine
MRC-University of Glasgow Centre for Virus Research
Supervisor Bios
Publications
Scientia - Harnessing Machine Learning to Enhance Diagnosis of Feline Infectious Peritonitis
Full Citation
Dunbar, D., Babayan, S.A., Krumrie, S. et al. Assessing the feasibility of applying machine learning to diagnosing non-effusive feline infectious peritonitis. Sci Rep 14, 2517 (2024). https://doi.org/10.1038/s41598-024-52577-4