Clinical severity classes in COVID-19 pneumonia have distinct immunological profiles, facilitating risk stratification by machine learning - Wiffen, Laura; D’Cruz, Leon Gerard; Brown, Thomas; Higenbottam, Tim W.; Bernstein, Jonathan A.; Campbell, Courtney; Moellman, Joseph; Ghosh, Debajyoti; Richardson, Clive; Weston-Davies, Wynne; Chauhan, Anoop J. (Frontiers in Immunology, 2023)
Objective: Clinical triage in COVID-19 places a heavy burden on senior clinicians during a pandemic situation. However, risk-stratification based on serum biomarker bio-profiling could be implemented by a larger, non-specialist workforce.Method: CASCADE-patients (n=72), (clinical-trials.gov: NCT04453527), classified as mild, moderate, or severe (by support needed to maintain SpO2 > 93%), and healthy controls (HC, n=20), were bioprofiled using 76 immunological biomarkers and compared using ANOVA. Spearman-correlation analysis on biomarker-pairs were visualised via heat-maps. Linear Discriminant Analysis (LDA) models were generated to identify patients likely to deteriorate. An X-Gradient-boost (XGB) model trained on CASCADE data to triage patients as mild, moderate, and severe, was retrospectively employed to classify CORONET patients (n=7) treated with nomacopan.The LDA models, distinctly discriminated between deteriorators, non-deteriorators and HC, with IL27, IP10, MDC, Ferritin, C5 and sC5b-9 among the key predictor variables during deterioration.C3a and C5 was elevated in all severity classes vs HC (p<0.05). sC5b-9 was elevated in "moderate" and "severe" categories vs HC (p<0.001). Heatmap analysis shows pairwise increase of negatively correlated pairs with IL27. The XGB model indicated sC5b-9, IL8, MCP1, ProthrombinF1&2 were key discriminators in nomacopan treated patients (CORONET study).: Distinct immunological fingerprints from serum biomarkers, exist within different severity classes of COVID-19, and harnessing them using machine-learning enabled development of clinically useful triage and prognostic tools. Complement mediated lung-injury play a key role in COVID-19 pneumonia, preliminary results hint the usefulness of a C5-inhibitor in COVID-19 recovery.