Multi-system metabolomic age gap to dissect long COVID-related health outcomes

We are what we eat. As we age, our body's metabolism changes, and these changes can be used to measure our "biological age". By comparing our biological age to our chronological age, we can observe if someone is ageing faster or slower than expected. This age gap has already been used to predict how likely someone is to have a stroke or develop type 2 diabetes. In this project, we are using these models to predict who will get long COVID, a disease that impacts 1 in 6 of all Canadians who contracted the COVID-19 virus. People with long COVID have been shown to have fatigue, brain fog, or even heart problems - but it seems to impact people differently. That's why we are building models that target specific organs in the body to more accurately disentangle why one person would have brain fog while the other constantly feels tired. By linking biological age to long COVID outcomes, we will investigate the heterogeneity of long COVID. We hope this research will allow us to better predict who will contract long COVID, how they will be impacted, and ultimately, identify treatment targets for people still suffering from long COVID.