Severe acute respiratory syndrome caused by coronavirus 2 emerged in Wuhan (China) in December 2019 and has severely challenged the human population. NK and T cells are involved in the progression of COVID-19 infection through the ability of NK cells to modulate T-cell responses, and by the stimulation of cytokine release. No detailed investigation of the NK cell landscape in clinical SARS-CoV-2 infection has yet been reported. A total of 35 COVID-19 hospitalised patients were stratified for clinical severity and 17 healthy subjects were enrolled. NK cell subsets and T cell subsets were analysed with flow cytometry. Serum cytokines were detected with a bead-based multiplex assay. Fewer CD56^dimCD16^brightNKG2A⁺NK cells and a parallel increase in the CD56⁺CD69⁺NK, CD56⁺PD-1⁺NK, CD56⁺NKp44⁺NK subset were reported in COVID-19 than HC. A significantly higher adaptive/memory-like NK cell frequency in patients with severe disease than in those with mild and moderate phenotypes were reported. Moreover, adaptive/memory-like NK cell frequencies were significantly higher in patients who died than in survivors. Severe COVID-19 patients showed higher serum concentrations of IL-6 than mild and control groups. Direct correlation emerged for IL-6 and adaptive/memory-like NK. All these findings provide new insights into the immune response of patients with COVID-19. In particular, they demonstrate activation of NK through overexpression of CD69 and CD25 and show that PD-1 inhibitory signalling maintains an exhausted phenotype in NK cells. These results suggest that adaptive/memory-like NK cells could be the basis of promising targeted therapy for future viral infections.

Background: Krebs von den Lungen-6 (KL-6) has been proposed as a disease severity marker of COVID-19. All research articles reported the KL-6 assay detected through Fujirebio reagents by Lumipulse G600/G1200 instrument. In the present study, KL-6 assay was analysed through Tosoh AIA-360 and compared with analytical results by Lumipulse G600 in a population of COVID-19 patients. Materials and methods: Sixty-four patients (median age, IQR 67 (58–76) years), all hospitalized for COVID-19 interstitial pneumonia at Siena COVID Unit. KL-6 was measured by two methods, chemiluminescence enzyme immunoassay (CLEIA) and fluorescent enzyme immunoassay (FEIA) method by Lumipulse G600 II and AIA 360 systems, respectively. Results: KL-6 concentrations evaluated by Lumipulse G600II were significantly higher in severe than those in non-severe patients (p < 0.0001) as well as evaluating by AIA360 (p < 0.0001). Receiver operating curve (ROC) curve analysis showed that KL-6 concentrations, by Lumipuse G600II, distinguished severe from non-severe COVID-19 patients with an area under the curve (AUC) of 99.8% and the best cut-off value was 448 U/mL. AUROC between severe and non-severe COVID-19 patients using T0 KL-6 concentrations by AIA360 was 97.4% and the best cut-off value was 398 U/mL. According to T0 KL-6 concentrations in COVID-19 patients, Bland–Altman difference analysis revealed a mean bias of 78 ± 174.8; while using T1 KL-6 concentrations in COVID-19 patients, Bland–Altman difference analysis revealed a mean bias of 48 ± 126 (95% limits of agreement −199–295) between the Lumipulse G600 II and the AIA360 systems. Conclusions: In conclusion, our study demonstrated that CLEIA and FEIA methods for serum KL-6 detection are comparable and reliable. KL-6 was confirmed as an easily detectable and effective biomarker to identify severe COVID-19 patients.

Diagnosis of interstitial lung diseases (ILD) is difficult to perform. Extracellular vesicles (EVs) facilitate cell-to-cell communication, and they are released by a variety of cells. Our goal aimed to investigate EV markers in bronchoalveolar lavage (BAL) from idiopathic pulmonary fibrosis (IPF), sarcoidosis and hypersensitivity pneumonitis (HP) cohorts. ILD patients followed at Siena, Barcelona and Foggia University Hospitals were enrolled. BAL supernatants were used to isolate the EVs. They were characterized by flow cytometry assay through MACSPlex Exsome KIT. The majority of alveolar EV markers were related to the fibrotic damage. CD56, CD105, CD142, CD31 and CD49e were exclusively expressed by alveolar samples from IPF patients, while HP showed only CD86 and CD24. Some EV markers were common between HP and sarcoidosis (CD11c, CD1c, CD209, CD4, CD40, CD44, CD8). Principal component analysis distinguished the three groups based on EV markers with total variance of 60.08%. This study has demonstrated the validity of the flow cytometric method to phenotype and characterize EV surface markers in BAL samples. The two granulomatous diseases, sarcoidosis and HP, cohorts shared alveolar EV markers not revealed in IPF patients. Our findings demonstrated the viability of the alveolar compartment allowing identification of lung-specific markers for IPF and HP.

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.

Idiopathic pulmonary fibrosis (IPF) and sarcoidosis are two distinct clinical entities with different aetiology, epidemiology, risk factors, symptoms and chest imaging. A number of papers have reported an overlap of the two diseases and have suggested the existence of a distinct phenotype defined as combined sarcoidosis and idiopathic pulmonary fibrosis (CSIPF). We used the scoping review protocol to review the literature on CSIPF. We also enrolled a cohort of nine CSIPF patients and compared them with lone-IPF and fibrotic sarcoidosis patients. Our CSIPF cohort showed male prevalence and only ex-smokers. Functional assessment at baseline showed mild to moderate restrictive impairment of lung volumes in lone-IPF and CSIPF patients, associated with moderate-to-severe reduction in DLco percentages. Although all CSIPF patients were on antifibrotic treatments, functional impairment occurred in the two years of follow up. This suggests the importance of considering these patients at high risk of rapid deterioration and lung damage.

Background: The pathogenesis of sarcoidosis involves T cells and B lymphocytes that produce autoantibodies. We compared the expression of different T and B cell subsets in sarcoidosis and three B-mediated rheumatic diseases that can affect the lungs in an attempt to identify similarities and differences that distinguish these diseases. Methods: The study included patients referred to Siena University Hospital’s respiratory disease and rheumatology units. Patients were enrolled prospectively and consecutively. Healthy volunteers were also included. Multicolor flow cytometry was performed on phenotype T and B cell subsets. Multivariate analysis was carried out to reduce the dimensionality of the data. Results: Fifteen patients had a diagnosis of sarcoidosis, fourteen idiopathic inflammatory myopathies (IIM), five granulomatosis with polyangiitis (GPA), ten microscopic polyangiitis (MPA), and seven were controls. Thirty-five T and B cell subsets were phenotyped, 15 of which were significantly different in sarcoidosis, B-mediated rheumatic disorders, and controls. Principal components analysis distinguished the four groups of patients with a total explained variance of 54.7%. A decision tree was constructed to determine which clustering variables would be most useful for distinguishing sarcoidosis, IIM, MPA, and GPA. The model showed regulatory T helper cells (Th-reg) > 5.70% in 91% of sarcoidosis patients as well as Th-reg ≤ 5.70 and Th17 > 43.27 in 100% of MPA. It also showed Th-reg ≤ 5.70, Th17 ≤ 43.27 and Tfh-reg ≥ 7.81 in 100% of GPA patients, and Th-reg ≤ 5.70, Th17 ≤ 43.27 and Tfh-reg ≤ 7.81 in 100% of IIM patients. Conclusion: The immune cell profile sheds light on similarities and differences between sarcoidosis and B-mediated rheumatic diseases. Sarcoidosis and autoimmune diseases show similar patterns of cellular immune dysregulation, suggesting a common pathogenic pathway that may provide an opportunity for further understanding autoimmunity and exploring biological therapies to treat sarcoidosis.