The immune system of patients infected by SARS-CoV-2 is severely impaired. Detailed investigation of T cells and cytokine production in patients affected by COVID-19 pneumonia are urgently required. Here we show that, compared with healthy controls, COVID-19 patients' T cell compartment displays several alterations involving naïve, central memory, effector memory and terminally differentiated cells, as well as regulatory T cells and PD1 + CD57 + exhausted T cells. Significant alterations exist also in several lineage-specifying transcription factors and chemokine receptors. Terminally differentiated T cells from patients proliferate less than those from healthy controls, whereas their mitochondria functionality is similar in CD4 + T cells from both groups. Patients display significant increases of proinflammatory or anti-inflammatory cytokines, including T helper type-1 and type-2 cytokines, chemokines and galectins; their lymphocytes produce more tumor necrosis factor (TNF), interferon-γ, interleukin (IL)-2 and IL-17, with the last observation implying that blocking IL-17 could provide a novel therapeutic strategy for COVID-19.

We have deeply investigated T cell compartment, plasma cytokines and cells producing cytokines in patients affected by Covid-19. At admission, patients were lymphopenic; in all of them SARS-CoV-2 was detected in a nasopharyngeal swab specimen by real-time RT-PCR, and pneumonia was subsequently confirmed by X-rays.Detailed 18-parameter flow cytometry was performed in 21 patients and 13 controls. Coupling polychromatic cytometry with unsupervised data analysis, we found that patients show an increased amount of CD4+ T lymphocytes that were activated, exhausted, stem memory or Treg. Similar results concerning activation and exhaustion were found in the CD8+ T cell compartment, within which the differences were even greater.Measuring plasma level of 31 cytokines linked to inflammation revealed that Covid-19 showed a dramatic increase of several molecules, such as TH1 and TH2 cytokines, chemokines, galectins, pro- and anti-inflammatory mediators, confirming the importance of a massive immune activation causing the cytokine storm. Then, intracellular staining detecting the simultaneous production of different cytokines after a para-physiologic stimulus given by anti-CD3/CD28 mAbs revealed not only a high capacity to produce a variety of molecules, including TNF-a, IFN-g and IL-2, but also a significant skewing of CD4+ T cells towards the TH17 phenotype.A therapeutic approach now exists based on the administration of drugs that block IL-6 pathway, and is now consistently improving the course of the disease. IL-17 is crucial in recruiting and activating neutrophils, cells that can migrate to the lung and are heavily involved in the pathogenesis of Covid-19. We show here that a significant skewing of activated T cells towards TH17 functional phenotype exists in Covid-19 patients. Thus, we suggest that blocking IL-17 pathway by already available biological drugs that are used to treat different pathologies could be a novel, additional strategy to improve the health of patients infected by SARS-CoV-2.

Studies on the interactions between SARS‐CoV‐2 and humoral immunity are fundamental to elaborate effective therapies including vaccines. We used polychromatic flow cytometry, coupled with unsupervised data analysis and principal component analysis (PCA), to interrogate B cells in untreated patients with COVID‐19 pneumonia. COVID‐19 patients displayed normal plasma levels of the main immunoglobulin classes, of antibodies against common antigens or against antigens present in common vaccines. However, we found a decreased number of total and naïve B cells, along with decreased percentages and numbers of memory switched and unswitched B cells. On the contrary, IgM+ and IgM− plasmablasts were significantly increased. In vitro cell activation revealed that B lymphocytes showed a normal proliferation index and number of dividing cells per cycle. PCA indicated that B‐cell number, naive and memory B cells but not plasmablasts clustered with patients who were discharged, while plasma IgM level, C‐reactive protein, D‐dimer, and SOFA score with those who died. In patients with pneumonia, the derangement of the B‐cell compartment could be one of the causes of the immunological failure to control SARS‐Cov2, have a relevant influence on several pathways, organs and systems, and must be considered to develop vaccine strategies.

Purpose Cytomegalovirus (CMV) reactivation in immunocompetent critically ill patients is common and relates to a worsening outcome. In this large observational study, we evaluated the incidence and the risk factors associated with CMV reactivation and its effects on mortality in a large cohort of patients affected by coronavirus disease 2019 (COVID-19) admitted to the intensive care unit (ICU). Methods Consecutive patients with confirmed SARS-CoV-2 infection and acute respiratory distress syndrome admitted to three ICUs from February 2020 to July 2021 were included. The patients were screened at ICU admission and once or twice per week for quantitative CMV-DNAemia in the blood. The risk factors associated with CMV blood reactivation and its association with mortality were estimated by adjusted Cox proportional hazards regression models. Results CMV blood reactivation was observed in 88 patients (20.4%) of the 431 patients studied. Simplified Acute Physiology Score (SAPS) II score (HR 1031, 95% CI 1010–1053, p = 0.006), platelet count (HR 0.0996, 95% CI 0.993–0.999, p = 0.004), invasive mechanical ventilation (HR 2611, 95% CI 1223–5571, p = 0.013) and secondary bacterial infection (HR 5041; 95% CI 2852–8911, p < 0.0001) during ICU stay were related to CMV reactivation. Hospital mortality was higher in patients with (67.0%) than in patients without (24.5%) CMV reactivation but the adjusted analysis did not confirm this association (HR 1141, 95% CI 0.757–1721, p = 0.528). Conclusion The severity of illness and the occurrence of secondary bacterial infections were associated with an increased risk of CMV blood reactivation, which, however, does not seem to influence the outcome of COVID-19 ICU patients independently. Supplementary Information The online version contains supplementary material available at 10.1007/s00134-022-06716-y.

Aims The aim of this study was to estimate a 48 hour prediction of moderate to severe respiratory failure, requiring mechanical ventilation, in hospitalized patients with COVID-19 pneumonia. Methods This was an observational prospective study that comprised consecutive patients with COVID-19 pneumonia admitted to hospital from 21 February to 6 April 2020. The patients’ medical history, demographic, epidemiologic and clinical data were collected in an electronic patient chart. The dataset was used to train predictive models using an established machine learning framework leveraging a hybrid approach where clinical expertise is applied alongside a data-driven analysis. The study outcome was the onset of moderate to severe respiratory failure defined as PaO2/FiO2 ratio <150 mmHg in at least one of two consecutive arterial blood gas analyses in the following 48 hours. Shapley Additive exPlanations values were used to quantify the positive or negative impact of each variable included in each model on the predicted outcome. Results A total of 198 patients contributed to generate 1068 usable observations which allowed to build 3 predictive models based respectively on 31-variables signs and symptoms, 39-variables laboratory biomarkers and 91-variables as a composition of the two. A fourth “boosted mixed model” included 20 variables was selected from the model 3, achieved the best predictive performance (AUC = 0.84) without worsening the FN rate. Its clinical performance was applied in a narrative case report as an example. Conclusion This study developed a machine model with 84% prediction accuracy, which is able to assist clinicians in decision making process and contribute to develop new analytics to improve care at high technology readiness levels.