The evolving landscape of Long COVID: identifying dynamic molecular features to improve diagnosis, prognostication and identification of novel treatment targets

In 2023, Canada had a whopping 82% of people with SARS-CoV-2 antibodies, and one in nine of them had long COVID. Even people who don't have any symptoms have different blood proteins than before the pandemic, which means the virus has left a lasting mark on their bodies. We think that by studying the molecular changes in people with Long COVID, particularly what distinguishes those that have recovered after one year from those with persisting symptoms at 2 years, we can better diagnose and treat them. This knowledge will also help us understand the disease better and develop new treatments. To do this, we're using blood samples and data from the Biobanque québécoise de la COVID-19 (BQC19), which has a large group of people who have been followed up for up to 24 months. Our two main goals are: 1. To compare recovered and non-recovered people with Long COVID using extensive molecular data from BQC19 combined with advanced computing tools to identify the features that most distinguish recovery from ongoing disease. This information will be essential to improve diagnosis, prediction of outcomes and the identification of potential treatments. 2. To investigate a property of certain proteins that can form "unnatural" aggregates in the blood, leading to COVID-19 manifestations. Preliminary data and evidence from other groups support this mechanism. We'll use in vitro assays and state-of-the-art protein analysis methods to determine the presence and nature of these aggregates in people with Long COVID and whether they associate with clinical features of Long COVID. Our project aims to improve the long-term health of Canadians who got COVID by finding people who have Long COVID early and providing them with treatments options that support faster recovery and a return to what feels like normal daily routines.