Multi-objective optimization identifies a specific and interpretable COVID-19 host response signature

The identification of a COVID-19 host response signature in blood can increase understanding of SARS-CoV-2 pathogenesis and improve diagnostic tools. Applying a multi-objective optimization framework to both massive public and new multi-omics data, we identified a COVID-19 signature regulated at both transcriptional and epigenetic levels. We validated the signature’s robustness in multiple independent COVID-19 cohorts. Using public data from 8630 subjects and 53 conditions, we demonstrated no cross-reactivity with other viral and bacterial infections, COVID-19 comorbidities, and confounders. In contrast, all previously reported COVID-19 signatures were associated with significant cross-reactivity. The signature’s interpretation, based on cell-type deconvolution and single cell data analysis, revealed prominent yet complementary roles for plasmablasts and memory T cells. While the signal from plasmablasts mediated COVID-19 detection, the signal from memory T cells controlled against cross-reactivity with other viral infections. This framework identified a robust interpretable COVID-19 signature, and is broadly applicable in other disease contexts.THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV