Protocol: A metabolomic analysis of convalescent inflammatory conditions
K Dunstan I., C Anthony D., Ladds E.
Background ‘The term ‘long covid’ describes persistent symptoms following infection with SARS-CoV-2 that are not explained by an alternative diagnosis. It embraces a number of globally used terms and reported prevalence is highly variable. In the United Kingdom (UK) in 2023, approximately 2.9% of the population were thought to be affected. The condition manifests in a constellation of fluctuant symptoms, which persist beyond the acute infection and frequently profoundly impact an individual’s functional and relational capacity. The underlying mechanisms remain imperfectly understood and there is great demand for diagnostic tools that distinguish long covid from other chronic conditions. This study aims to utilise metabolomics to develop such a test and identify potential pathophysiological mechanisms. Methods Blood and urine samples will be collected at two timepoints at least 9 months apart from non-hospitalised individuals with a previous confirmed COVID-19 infection. This population will be divided into those who recovered completely within six weeks and those who continue to experience persistent symptoms. Samples will be analysed using 1H NMR spectroscopy and the resultant metabolomic profiles will be subject to multivariate pattern recognition techniques. This will produce mathematical models capable of distinguishing these long covid and control groups. Symptoms, potential confounders, and qualitative narrative data will be collected alongside this process to add deeper richness to the subsequent analysis. Primary Outcome The creation of a diagnostic test for long covid using 1H NMR metabolomics. Secondary Outcomes The development of algorithms that predict the severity and chronicity of long covid, identification of subgroup differences in metabolomic and immune profiles, and triangulation with symptom and narrative data to produce a deeper understanding of the patient experience. Conclusion This study seeks to advance the understanding of long covid using advanced multi-omic and narrative techniques, which may offer potential diagnostic and therapeutic avenues.