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1.
Int J Environ Res Public Health ; 19(4)2022 Feb 15.
Article in English | MEDLINE | ID: covidwho-1686793

ABSTRACT

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.


Subject(s)
COVID-19 , Aged , Area Under Curve , Biomarkers , COVID-19/diagnosis , Humans , SARS-CoV-2 , Severity of Illness Index
2.
Cells ; 10(11)2021 11 15.
Article in English | MEDLINE | ID: covidwho-1523882

ABSTRACT

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 CD56dimCD16brightNKG2A+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.


Subject(s)
COVID-19/immunology , Killer Cells, Natural/cytology , T-Lymphocytes/cytology , Aged , Aged, 80 and over , COVID-19/diagnosis , Cytokines/blood , Female , Hospitalization , Humans , Lymphocyte Count , Male , Middle Aged , SARS-CoV-2 , Severity of Illness Index
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