COVID-19 patients show heterogeneity in clinical presentation and outcomes that makes pandemic control and strategy difficult; optimizing management requires a systems biology approach of understanding the disease. Here we sought to potentially understand and infer complex disease progression, immune regulation, and symptoms in patients infected with coronaviruses (35 SARS-CoV and 3 SARS-CoV-2 patients and 57 samples) at two different disease progression stages. Further, we compared coronavirus data with healthy individuals ( n = 16) and patients with other infections ( n = 144; all publicly available data). We applied inferential statistics (the COVID-engine platform) to RNA profiles (from limited number of samples) derived from peripheral blood mononuclear cells (PBMCs). Compared to healthy individuals, a subset of integrated blood-based gene profiles (signatures) distinguished acute-like (mimicking coronavirus-infected patients with prolonged hospitalization) from recovering-like patients. These signatures also hierarchically represented multiple (at the system level) parameters associated with PBMC including dysregulated cytokines, genes, pathways, networks of pathways/concepts, immune status, and cell types. Proof-of-principle observations included PBMC-based increases in cytokine storm-associated IL6 , enhanced innate immunity (macrophages and neutrophils), and lower adaptive T and B cell immunity in patients with acute-like disease compared to those with recovery-like disease. Patients in the recovery-like stage showed significantly enhanced TNF , IFN-γ , anti-viral, HLA-DQA1 , and HLA-F gene expression and cytolytic activity, and reduced pro-viral gene expression compared to those in the acute-like stage in PBMC. Besides, our analysis revealed overlapping genes associated with potential comorbidities (associated diabetes) and disease-like conditions (associated with thromboembolism, pneumonia, lung disease, and septicemia). Overall, our COVID-engine inferential statistics platform and study involving PBMC-based RNA profiling may help understand complex and variable system-wide responses displayed by coronavirus-infected patients with further validation.
【저자키워드】 immunology, Molecular biology, 【초록키워드】 Neutrophils, coronavirus, pandemic, Cytokines, Gene Expression, adaptive, Immunity, Hospitalization, Pneumonia, SARS-CoV, Innate immunity, immune regulation, Infection, IL6, Lung disease, Comorbidity, cytokine, Systems biology, Symptom, diabetes, outcome, heterogeneity, Anti-viral, RNA, Peripheral blood, B cell, Disease progression, management, response, Patient, Thromboembolism, PBMC, disease, patients, platform, IFN-γ, TNF, Immune status, Analysis, PBMCs, Pathways, COVID-19 patient, cell types, mononuclear cell, observation, overlapping, available data, stages, profile, healthy individuals, complex, help, HLA-DQA1, HLA-F, parameter, Genes, approach, significantly, the disease, applied, reduced, condition, dysregulated, subset, healthy individual, mimicking, increases in, cytolytic, SARS-CoV-2 patient, 【제목키워드】 immune regulation, Symptom, Disease progression, Patient, Blood, Analysis,