Purpose: Characterization of immune system heterogeneity in COVID‐19 patients by comparing the inflammatory markers heparin‐binding protein (HBP), serum amyloid A protein (SAA), IL‐6, and C‐reactive protein (CRP) in relation to viral burden, immune response, and tissue damage. Also, determine if prolonged elevations in these markers are associated with long‐term symptoms of COVID‐19. Methods: This study enrolled 106 hospitalized patients with PCR‐confirmed diagnoses of COVID‐19. Blood samples were collected within 24 h of admission ( t _24h ), at 48 h ( t _48h ), 7 days ( t _7d ), and long‐term, greater than 1 month, post discharge ( t _LongTerm ). Serum levels of HBP, SAA, IL‐6, and CRP were measured using a commercial point‐of‐care device. Viral burden was assessed via serum viral spike S‐protein serum levels and specific immunoglobulins G, M, and D against S&N proteins, and SARS‐CoV‐2 proteins were quantified. Tissue injury was evaluated by measuring HMGB‐1 levels. Clinical data were reviewed retrospectively. Healthy individual samples served as controls. Results: COVID‐19 patients exhibited significantly elevated serum HBP and SAA compared to healthy controls. SAA levels normalized over 1 month, whereas HBP, CRP, and IL‐6 remained persistently elevated. Patients requiring intensive care unit (ICU) admission, endotracheal intubation, or extracorporeal membrane oxygen (ECMO) demonstrated higher CRP, IL‐6, and HBP at initial assessment. However, after 48 h, only IL‐6 was elevated in patients who subsequently expired. No significant correlations emerged between serum HBP levels and HMGB‐1, viral spike protein levels, or antibodies against SARS‐CoV‐2 proteins. Pre‐existing or acquired comorbidities did not significantly influence HBP or SAA concentrations. An analysis of biomarker profiles identified four distinct patient clusters, each characterized by unique inflammatory patterns that remained stable over time. Specifically, Cluster 1 exhibited low IL‐6 with high SAA and CRP. Cluster 2 had low HBP with the highest IL‐6. Cluster 3 demonstrated low SAA and CRP levels, and Cluster 4 exhibited robust inflammatory responses across all markers except IL‐6. Conclusions: The persistence of inflammatory markers suggests ongoing inflammatory responses post‐COVID‐19 infection. Significant heterogeneity observed in inflammatory responses upon admission indicates multiple distinct inflammatory phenotypes, which may have implications for clinical outcomes and management strategies.

Purpose: Recent discoveries have pointed to the role of IGFALS immunological response to viral challenges, potentially leading to the emergence of a cytokine storm. Here, we investigate if serum IGFALS during the acute response to SARS-CoV-2 will not be likely to accompany immune response during acute phase and convalescence. Patients and Methods: We recruited patients hospitalized with PCR-confirmed SARS-CoV-2 infection in 2020 and have blood collected after securing consent (t_adm), at 48 hours (t_48hrs), 7 days (t_7d), and after discharge from hospital (t_long). IGFALS and IGF-1 in serum were measured to assess dynamics of the illness and compared against non-specific inflammatory (C-reactive protein, IL-6) markers. Serum titers of IgG against proteins S and N assessed specific viral responses. Serum HMGB-1 was measured to assess level of necrosis. Demographic and clinical data were collected using electronic health records (EHR). Survival was determined at six months from admission. Results: No difference between serum IGFALS and IGF-1 levels was seen across the studied time points. IGFALS_adm showed significant positive correlations with IGFALS_48hrs (r²=0.18; p< 0.001), IGFALS_7d (r²= 0.19; p=0.004), and IGFALS_long (r² = 0.23; p=0.045). IGFALS correlated negatively with IGF-1 but positively with growth hormone. IGFALS_adm showed significant inverse correlations with serum levels of HMGB1_adm (r²= 0.26; p = < 0.001) and t_48hr (r² = 0.27; p< 0.001). A significant correlation in the case of IGFALS_48hrs and CRP_48hrs (r² = 0.09, p = 0.021), IGFALS_long and CRP_long (r² = 0.271, p=0.039) was seen. Similar correlations were seen at 48 hours of sampling time for IL-6 (r² = 0.14, p=0.006). In terms of specific antiviral response, we observed that serum IGFALS_adm demonstrated correlation levels of serum IgG_adm (r² = 0.09, p=0.024). A positive correlation was found between length of stay in hospital or ICU and serum IGFALS_48hrs. Conclusion: Though IGFALS serum levels did not change significantly during SARS-CoV-2 infection, we observed correlations with markers of tissue destruction, C-reactive protein, IL-6, and length of hospital stay.

The immune system’s response to an invading pathogen is the critical determinant in recovery from illness. Here, we hypothesize that the immune response will swiftly follow classical activation and a resolution trajectory in patients with the rapid evolution of symptoms if challenged by a viral pathogen for the first time. Alternatively, a dysregulated response will be signified by a protracted clinical trajectory. Consequently, we enrolled 106 patients during the first wave of COVID-19 and collected their blood within 24 h, 48 h, 7 days, and over 28 days from symptoms onset. The pathogenic burden was measured via serum levels of the S-spike protein and specific immunoglobulin titers against the S and N proteins of SARS-CoV-2. The nonspecific immunological response was gauged using interleukin 6, leukocytosis, and C-reactive protein. Coagulation status was assessed. Several serum biomarkers were used as surrogates of clinical outcomes. We identified four clusters depending on the onset of symptoms (immediate [A], 6 days [B], 12 days [C], and over 21 days [D]). High variability in the S-spike protein in cluster A was present. The corresponding immunoglobulin titer was random. Only procalcitonin differentiated clusters in terms of markers of nonspecific inflammation. Coagulation markers were not significantly different between clusters. Serum surrogates on cardiomyopathy and neuronal pathology exhibited significant variability. Implementation of ECMO or noninvasive ventilation was more prominent in cluster C and D. Interestingly, SOFA or APACHE II scores were not different between nominal (A and B) versus dysregulated clusters (C and D).