Dear Editor,The pandemic of coronavirus disease 2019 (COVID-19) has stressed and overloaded the existing medical capacity worldwide. From a more pragmatic perspective, the early detection of patients who may experience rapid clinical deterioration will enable prompt interventions and avert disease progression. 1 T cell exhaustion, immunothrombotic dysregulation, as well as complement-associated microvascular injury are considered as the hallmarks of disease severity in COVID-19. [2][3][4][5] It is generally accepted that the identification of useful surrogates, for example, IL-6, TNFα, MIP1α, LDH, ferritin, D-dimer, CK, etc., to represent as immune response to COVID-19 infection is crucial. 3,4,6 Nevertheless, no individual parameter was so far predictive of immune-thrombotic dysregulation fueled by a maladaptive host inflammatory response in severe infection with SARS-CoV-2. [7][8][9] We, therefore, consider to develop potential solutions for forecasting thrombotic complications prior to clinicopathological exacerbation.By incorporating whole blood transcriptome profiling and multi-omics analysis, our study characterized immunological and hematological perturbations with respect to different categories of severity (i.e., healthy donors vs. mild or moderate vs. severe vs. critical illness). Functional diversity was found among those groups by unsupervised hierarchical clustering of differential expression profiles (Figure 1A, left). Circus plots revealed that the differentially expressed genes (DEGs) were enriched into the key processes, that is, neutrophil activation, platelet activation, blood coagulation, complement receptormediated signaling pathway, leukocyte activation, and cytokines production. In contrast, the downregulated DEGs were functionally linked with lymphocyte activation/proliferation/differentiation/migration, gamma delta (γδ) and alpha beta (αβ) T cells activation, and so on (Figure 1A, right, and B). More specifically, the This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.