Mucosal and systemic immune dynamics associated with COVID-19 outcomes: a longitudinal prospective clinical study (preprint)

Rationale: COVID-19 severity varies widely; children and African Americans have low and high risk, respectively. Mechanistic data from these groups and the mucosa is lacking. Objectives: To quantify mucosal and systemic viral and immune dynamics in a diverse cohort to identify mechanisms underpinning COVID-19 severity and outcome predictors. Methods: In this prospective study of unvaccinated children and adults COVID-19 outcome was based on an ordinal clinical severity scale. We quantified viral RNA, antigens, antibodies, and cytokines by PCR, ELISA, and Luminex from 579 longitudinally collected blood and nasal specimens from 78 subjects including 45 women and used modeling to determine functional relationships between these data. Measurements and Main Results: COVID-19 induced unique immune responses in African Americans (n=26) and children (n=20). Mild outcome was associated with more effective coordinated responses whereas moderate and severe outcomes had rapid seroconversion, significantly higher antigen, mucosal sCD40L, MCP-3, MCP-1, MIP-1, and MIP-1{beta}, and systemic IgA, IgM, IL-6, IL-8, IL-10, IL-15, IL-1RA, and IP-10, and uncoordinated early immune responses that went unresolved. Mucosal IL-8, IL-1{beta}, and IFN-{gamma} with systemic IL-1RA and IgA predicted COVID-19 outcomes. Conclusions: We present novel mucosal data, biomarkers, and therapeutic targets from a diverse cohort. Based on our findings, children and African Americans with COVID-19 have significantly lower IL-6 and IL-17 levels which may reduce responsiveness to drugs targeting IL-6 and IL-17. Unregulated immune responses persisted indicating moderate to severe COVID-19 cases may require prolonged treatments. Reliance on slower acting adaptive responses may cause immune crisis for some adults who encounter a novel virus.

Establishing thresholds for cytokine storm and defining their relationship to disease severity in respiratory viral infections (preprint)

Previous studies have identified cytokines associated with respiratory virus infection illness outcome. However, few studies have included comprehensive cytokine panels, longitudinal analyses, and/or simultaneous assessment across the severity spectrum. This, coupled with subjective definitions of cytokine storm syndrome (CSS), have contributed to inconsistent findings of cytokine signatures, particularly with COVID severity. Here, we measured 38 plasma cytokines and compared profiles in healthy, SARS-CoV-2 infected, and multisystem inflammatory syndrome in children (MIS-C) patients (n = 169). Infected patients spanned the severity spectrum and were classified as Asymptomatic, Mild, Moderate or Severe. Our results showed acute cytokine profiles and longitudinal dynamics of IL1Ra, IL10, MIP1b, and IP10 can differentiate COVID severity groups. Only 4% of acutely infected patients exhibited hypercytokinemia. Of these subjects, 3 were Mild, 3 Moderate, and 1 Severe, highlighting the lack of association between CSS and COVID severity. Additionally, we identified IL1Ra and TNFa as potential biomarkers for patients at high risk for long COVID. Lastly, we compare hypercytokinemia profiles across COVID and influenza patients and show distinct elevated cytokine signatures, wherein influenza induces the most elevated cytokine profile. Together, these results identify key analytes that, if obtained at early time points, can predict COVID illness outcome and/or risk of complications, and provide novel insight for improving the conceptual framework of hypercytokinemia, wherein CSS is a subgroup that requires concomitant severe clinical manifestations, and including a list of cytokines that can distinguish between subtypes of hypercytokinemia.