Dynamic gene expression analysis reveals distinct severity phases of immune and cellular dysregulation in COVID-19

Background: COVID-19 patients experience dynamic changes in immune and cellular function over time with potential clinical implications. However, there is insufficient research investigating, on a gene expression level, the mechanisms that become activated or suppressed over time as patients deteriorate or recover, which can inform use of repurposed and novel drugs as therapies. Objective: To investigate longitudinal changes in gene expression profiles throughout the COVID-19 disease timeline. Methods: Three-hundred whole blood samples from 128 adult patients were collected during hospitalization from COVID-19, with up to five samples per patient. Transcriptome sequencing (RNA-Seq), differential gene expression analysis and pathway enrichment was performed. Drug-gene set enrichment analysis was used to identify FDA-approved medications that could inhibit critical genes and proteins at each disease phase. Prognostic gene-expression signatures were generated using machine learning to distinguish 3 disease stages. Results: Samples were longitudinally grouped by clinical criteria and gene expression into six disease phases: Mild, Moderate, Severe, Critical, Recovery, and Discharge. Distinct mechanisms with differing trajectories during COVID-19 hospitalization were apparent. Antiviral responses peaked early in COVID-19, while heme metabolism pathways became active much later during disease. Adaptive immune dysfunction, inflammation, and metabolic derangements were most pronounced during phases with higher disease severity, while hemostatic abnormalities were elevated early and persisted throughout the disease course. Drug-gene set enrichment analysis predicted repurposed medications for potential use, including platelet inhibitors in early disease, antidiabetic medications for patients with increased disease severity, and dasatinib throughout the disease course. Disease phases could be categorized using specific gene signatures for prognosis and treatment selection. Disease phases were also highly correlated to previously developed sepsis endotypes, indicating that severity and disease timing were significant contributors to heterogeneity observed in sepsis and COVID-19. Conclusions: Higher temporal resolution of longitudinal mechanisms in COVID-19 revealed multiple immune and cellular changes that were activated at different phases of COVID-19. Understanding how a patient's gene expression profile changes over time can permit more accurate risk stratification of patients and provide time-dependent personalized treatments with repurposed medications. This creates an opportunity for timely intervention before patients transition to a more severe phase, potentially accelerating patients to recovery. ### Competing Interest Statement The authors have declared no competing interest.