Proteomic and Metabolomic Signatures Associated With the Immune Response in Healthy Individuals Immunized With an Inactivated SARS-CoV-2 Vaccine.

CoronaVac (Sinovac), an inactivated vaccine for SARS-CoV-2, has been widely used for immunization. However, analysis of the underlying molecular mechanisms driving CoronaVac-induced immunity is still limited. Here, we applied a systems biology approach to understand the mechanisms behind the adaptive immune response to CoronaVac in a cohort of 50 volunteers immunized with 2 doses of CoronaVac. Vaccination with CoronaVac led to an integrated immune response that included several effector arms of the adaptive immune system including specific IgM/IgG, humoral response and other immune response, as well as the innate immune system as shown by complement activation. Metabolites associated with immunity were also identified implicating the role of metabolites in the humoral response, complement activation and other immune response. Networks associated with the TCA cycle and amino acids metabolic pathways, such as phenylalanine metabolism, phenylalanine, tyrosine and tryptophan biosynthesis, and glycine, serine and threonine metabolism were tightly coupled with immunity. Critically, we constructed a multifactorial response network (MRN) to analyze the underlying interactions and compared the signatures affected by CoronaVac immunization and SARS-CoV-2 infection to further identify immune signatures and related metabolic pathways altered by CoronaVac immunization. These results help us to understand the host response to vaccination of CoronaVac and highlight the utility of a systems biology approach in defining molecular correlates of protection to vaccination.

Proteomic and Metabolomic Signatures Associated With the Immune Response in Healthy Individuals Immunized With an Inactivated SARS-CoV-2 Vaccine

CoronaVac (Sinovac), an inactivated vaccine for SARS-CoV-2, has been widely used for immunization. However, analysis of the underlying molecular mechanisms driving CoronaVac-induced immunity is still limited. Here, we applied a systems biology approach to understand the mechanisms behind the adaptive immune response to CoronaVac in a cohort of 50 volunteers immunized with 2 doses of CoronaVac. Vaccination with CoronaVac led to an integrated immune response that included several effector arms of the adaptive immune system including specific IgM/IgG, humoral response and other immune response, as well as the innate immune system as shown by complement activation. Metabolites associated with immunity were also identified implicating the role of metabolites in the humoral response, complement activation and other immune response. Networks associated with the TCA cycle and amino acids metabolic pathways, such as phenylalanine metabolism, phenylalanine, tyrosine and tryptophan biosynthesis, and glycine, serine and threonine metabolism were tightly coupled with immunity. Critically, we constructed a multifactorial response network (MRN) to analyze the underlying interactions and compared the signatures affected by CoronaVac immunization and SARS-CoV-2 infection to further identify immune signatures and related metabolic pathways altered by CoronaVac immunization. These results help us to understand the host response to vaccination of CoronaVac and highlight the utility of a systems biology approach in defining molecular correlates of protection to vaccination.

The Metabolic Changes and Immune Profiles in Patients With COVID-19.

To explore the metabolic changes and immune profiles in patients with COVID-19, we analyzed the data of patients with mild and severe COVID-19 as well as young children with COVID-19. Of the leukocytes, 47% (IQR, 33-59) were lymphocytes [2.5 × 109/L (IQR, 2.2-3.3)], and monocytes were 0.51 × 109/L (IQR, 0.45-0.57) in young children with COVID-19. In 32 mild COVID-19 patients, circulating monocytes were 0.45 × 109/L (IQR, 0.36-0.64). Twenty-one severe patients had low PO2 [57 mmHg (IQR, 50-73)] and SO2 [90% (IQR, 86-93)] and high lactate dehydrogenase [580 U/L (IQR, 447-696)], cardiac troponin I [0.07 ng/mL (IQR, 0.02-0.30)], and pro-BNP [498 pg/mL (IQR, 241-1,726)]. Serum D-dimer and FDP were 9.89 mg/L (IQR, 3.62-22.85) and 32.7 mg/L (IQR, 12.8-81.9), and a large number of RBC (46/µL (IQR, 4-242) was presented in urine, a cue of disseminated intravascular coagulation (DIC) in severe patients. Three patients had comorbidity with diabetes, and 18 patients without diabetes also presented high blood glucose [7.4 mmol/L (IQR, 5.9-10.1)]. Fifteen of 21 (71%) severe cases had urine glucose +, and nine of 21 (43%) had urine ketone body +. The increased glucose was partially caused by reduced glucose consumption of cells. Severe cases had extraordinarily low serum uric acid [176 µmol/L (IQR, 131-256)]. In the late stage of COVID-19, severe cases had extremely low CD4+ T cells and CD8+ T cells, but unusually high neutrophils [6.5 × 109/L (IQR, 4.8-9.6)], procalcitonin [0.27 ng/mL (IQR, 0.14-1.94)], C-reactive protein [66 mg/L (IQR, 25-114)] and an extremely high level of interleukin-6. Four of 21 (19%) severe cases had co-infection with fungi, and two of 21 (9%) severe cases had bacterial infection. Our findings suggest that, severe cases had acute respiratory distress syndrome (ARDS) I-III, and metabolic disorders of glucose, lipid, uric acid, etc., even multiple organ dysfunction (MODS) and DIC. Increased neutrophils and severe inflammatory responses were involved in ARDS, MODS, and DIC. With the dramatical decrease of T-lymphocytes, severe cases were susceptible to co-infect with bacteria and fungi in the late stage of COVID-19. In young children, extremely high lymphocytes and monocytes might be associated with the low morbidity of COVID-19. The significantly increased monocytes might play an important role in the recovery of patients with mild COVID-19.