Detecting and Deciphering post COVID with Dogs, Metabolomics and Machine Learning (COVID Dogolomics)
Project leader: Prof. Dr. Holger A. Volk
Research fields
- Basic and translational research on post COVID
Who is involved?
- Prof. Dr. Holger A. Volk (Project leader, TiHo)
- Prof. Dr. med. Georg Behrens (MHH)
- Prof. Dr. med. Alexandra Dopfer-Jablonka (MHH)
- Prof. Dr. med. Tobias Welte (MHH)
- Prof. Dr. Thomas Illig (MHH)
- Prof. Dr. Karsten Hiller (TU BS)
- Dr. Tushar More (TU BS)
What is the aim?
Underlying mechanisms of post COVID Syndrome are unknown and may involve viral persistence, immune dysregulation or persistent inflammation. Post COVID symptoms are non-specific, overlap to Sjögren’s Syndrome or Chronic Fatigue Syndrome (CFS), and the diagnosis relies on a previous SARS-CoV-2 infection. As most people have now stopped testing for SARS-CoV-2 when they have respiratory symptoms, this will become more challenging. Thus, there is clear need for improving objective diagnostic tools for post COVID.
Our previous studies provide compelling evidence for the ability of dogs to reliably detect acute SARS-CoV-2 infections via olfaction. We have preliminary evidence that dogs have the ability to detect post COVID. In this project, our interdisciplinary research team will use an innovative and synergistic approach based on 1) trained medical detection dogs, 2) immunologically characterised post COVID, Sjögren’s Syndrome and CFS patient cohorts, and 3) volatile organic compounds detected by metabolomics and machine learning. Our aim is to decrypt the key odour structure of post COVID recognised by the dogs. This will aid in identification, whether viral remnants or unique reprogrammed metabolic pathways are involved in the post COVID pathogenesis. Our approach can potentially be translated for identification of other difficult to diagnose diseases and the development of an “electronic nose”.