Paolo Cameli

Coronavirus disease 2019 (COVID-19) may determine a multisystemic chronic syndrome after resolution of SARS-CoV-2 infection in a significant percentage of patients. Persistent cytokine dysregulation can contribute to long-lasting inflammation and tissue damage, resulting in the diverse, often debilitating symptoms experienced by some patients (so-called long COVID syndrome). The aim of our study was to evaluate the value of a panel of serum biomarkers of severity and prognosis in patients hospitalized for COVID-19 and also as predictive factors for the development of post-COVID lung sequelae after discharge from the hospital. All blood sampling was performed in the first 24 h after admission to the hospital. Serum analyte concentrations of IL-4, IL-2, CXCL10 (IP-10), IL-1β, TNF-α, CCL2 (MCP-1), IL-17A, IL-6, IL-10, IFN-γ, IL-12p70 and TGF-β1 were quantified by bead-based multiplex LEGENDplex™ analysis and commercially available ELISA kits. A total of 108 COVID-19 patients were enrolled in the study. Comparative analysis of these proteins showed higher levels of TGF-β and IL-6 and lower levels of RBP-4 and IL-10 in the severe group. Age, adiponectin, IL-8 and IL-32 resulted as the best predictors for survival. Moreover, IL-1β, IL17A, TNF-α, TGF-β, IL-4 and IL-6 were significantly higher in patients who showed HRCT evidence of fibrotic interstitial alterations at follow-up than patients who did not. The initial inflammatory status of patients on admission to the hospital with COVID-19, as reflected by the present panel of adipose tissue-related biomarkers and cytokines, offered insights into medium-term prognosis.

Background: Serum mid-regional proadrenomedullin (MR-proADM) has emerged as a marker of organ failure (mainly lungs and kidneys) and poor prognosis in patients admitted to intensive care (IC); some reports also suggest it and other markers, such as Krebs von den Lungen-6 (KL-6) and interleukin-6 (IL-6), as a prognostic biomarker of COVID-19. The aim of the study was to evaluate the performance MR-proADM in hospitalized COVID-19 patients for predicting in-hospital mortality and need for non-invasive or invasive respiratory support. Methods: We enrolled 74 patients hospitalized in the COVID Unit of Siena Hospital from March to May 2020, for whom serum samples were available on admission for assay of MR-proADM, KL-6 and IL-6. Demographic data, comorbidities, medical history and clinical laboratory data on days 1–3 of admission and Simplified Acute Physiology Score and Simplified Organ Failure Assessment scores calculated at day 1 were collected retrospectively, as well as mortality and IC admission data. Results: 12 patients died in hospital (16%) and 14 patients were admitted to IC (19%). Serum concentrations of MR-proADM on admission and on day 1 were higher among non-survivors than among survivors (p = 0.015 and p = 0.045, respectively), while those on day 3 were not significantly different. Patients needing respiratory support had higher MR-proADM concentrations on admission than the others (p = 0.046), and those requiring invasive mechanical ventilation had higher MR-proADM on day 1 (p = 0.017). Serum concentrations of KL-6 and IL-6 were significantly higher in non-survivors (p = 0.03 and p = 0.004, respectively). ROC curve analysis showed that serum MR-proADM on day 1 had the best accuracy in predicting death and/or IC admission (AUC = 0.9583, p = 0.0006); the combination of all three biomarkers further improved the accuracy of prediction of death or IC admission (AUC = 0.9793; p = 0.00004). Conclusions: Our data sustain the potential of serum MR-proADM as a reliable prognostic biomarker of hospitalized COVID-19 patients and confirms the utility of the three markers in the management and risk stratification of hospitalized patients. The markers are collected mini-invasively and are quick to analyze and cost-effective.

Background: Fractional exhaled nitric oxide (FeNO) is a biomarker of airway inflammation associated with airway hyper-responsiveness and type-2 inflammation. Its role in the management of severe asthmatic patients undergoing biologic treatment, as well as FeNO dynamics during biologic treatment, is largely unexplored. Purpose: The aim was to evaluate published data contributing to the following areas: (1) FeNO as a predictive biomarker of response to biologic treatment; (2) the influence of biologic treatment in FeNO values; (3) FeNO as a biomarker for the prediction of exacerbations in patients treated with biologics. Methods: The systematic search was conducted on the Medline database through the Pubmed search engine, including all studies from 2009 to the present. Results: Higher baseline values of FeNO are associated with better clinical control in patients treated with omalizumab, dupilumab, and tezepelumab. FeNO dynamics during biologic treatment highlights a clear reduction in FeNO values in patients treated with anti-IL4/13 and anti-IL13, as well as in patients treated with tezepelumab. During the treatment, FeNO may help to predict clinical worsening and to differentiate eosinophilic from non-eosinophilic exacerbations. Conclusions: Higher baseline FeNO levels appear to be associated with a greater benefit in terms of clinical control and reduction of exacerbation rate, while FeNO dynamics during biologic treatment remains a largely unexplored issue since few studies have investigated it as a primary outcome. FeNO remains detectable during biologic treatment, but its potential utility as a biomarker of clinical control is still unclear and represents an interesting research area to be developed.