Early detection of cytokine storm and IgG levels to predict and prevent severe COVID-19 infection.

BACKGROUND

The mortality of COVID-19 is largely the result of cellular injury and inflammation of pulmonary and nonpulmonary vital tissue after severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) infection. Evidence has accumulated that this inflammation is associated with multiple cytokine overexpression, named Cytokine Storm Syndrome (CSS) or Cytokine Release Syndrome (CRS). The commonly used techniques to predict CSS/CRS and thereby severe COVID-19 are dependent on costly instrumentation and consumables, and frequent calibration and costly controls on a regular basis.

METHODS

We determined the specific cytokine gene (IL-1β, IL-6, IL-2, TGFβ, and IFN-γ) expression levels as a biomarker early in the disease process (Day-5) for severe disease using multiplex qRTPCR technique using real-time thermo-cyclers which are now available in all peripheral centers. Day-5 quantitative biomarker (C-Reactive Protein, IL-6, Ferritin, and D-Dimer) and day-7 IgG anti-SARS-CoV-2 levels were determined through the routine autoanalyzers and immune assays. We evaluated whether each of these specific biomarkers with age, gender, comorbidities, and severity can aid early detection of severity.

RESULTS

The present research identifies age > 65 years, presence of diabetes mellitus, hypertension or multimorbidity and lack of COVID-19 vaccination, and D-Dimer levels at Day-5 to be associated significantly (P value < 0.05) with severe COVID-19 infection. Crucially, Day-5 gene expression levels of IL-2, IL-6, and IFN-γ were inversely associated with COVID-19 severity and significantly lower (P < 0.05) in those with severe COVID-19 vis. healthy controls.

CONCLUSION

We propose IL-2, IL-6, and IFN-γ gene expression study through a multiplex qRTPCR assay and the D-dimer test as rapid tools to triage COVID-19 patients during management and identify need for escalating therapy.