Multi-omics identify LRRC15 as a COVID-19 severity predictor and persistent pro-thrombotic signals in convalescence

Abstract

AbstractPatients with end-stage kidney disease (ESKD) are at high risk of severe COVID-19. Here, we performed longitudinal blood sampling of ESKD haemodialysis patients with COVID-19, collecting samples pre-infection, serially during infection, and after clinical recovery. Using plasma proteomics, and RNA-sequencing and flow cytometry of immune cells, we identified transcriptomic and proteomic signatures of COVID-19 severity, and found distinct temporal molecular profiles in patients with severe disease. Supervised learning revealed that the plasma proteome was a superior indicator of clinical severity than the PBMC transcriptome. We showed that both the levels and trajectory of plasma LRRC15, a proposed co-receptor for SARS-CoV-2, are the strongest predictors of clinical outcome. Strikingly, we observed that two months after the acute infection, patients still display dysregulated gene expression related to vascular, platelet and coagulation pathways, including PF4 (platelet factor 4), which may explain the prolonged thrombotic risk following COVID-19.