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Although the COVID-19 disease has developed into a worldwide pandemic, its pathophysiology remains to be fully understood. Insulin-degrading enzyme (IDE), a zinc-metalloprotease with a high affinity for insulin, has been found in the interactomes of multiple SARS-CoV-2 proteins. However, the relevance of IDE in the innate and adaptative immune responses elicited by circulating peripheral blood mononuclear cells is unknown. Here, we show that IDE is highly expressed on the surface of circulating monocytes, T-cells (both CD4+ and CD4−), and, to a lower extent, in B-cells from healthy controls. Notably, IDE’s surface expression was upregulated on monocytes from COVID-19 patients at diagnosis, and it was increased in more severe patients. However, IDE’s surface expression was downregulated (relative to healthy controls) 3 months after hospital discharge in all the studied immune subsets, with this effect being more pronounced in males than in females, and thus it was sex-dependent. Additionally, IDE levels in monocytes, CD4+ T-cells, and CD4− T-cells were inversely correlated with circulating insulin levels in COVID-19 patients (both at diagnosis and after hospital discharge). Of note, high glucose and insulin levels downregulated IDE surface expression by ~30% in the monocytes isolated from healthy donors, without affecting its expression in CD4+ T-cells and CD4− T-cells. In conclusion, our studies reveal the sex- and metabolism-dependent regulation of IDE in monocytes, suggesting that its regulation might be important for the recruitment of immune cells to the site of infection, as well as for glucometabolic control, in COVID-19 patients.

Coronavirus disease 2019 (COVID-19) affects the population unequally, with a greater impact on older and immunosuppressed people. Hence, we performed a prospective experimental cohort study to characterise the effect of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination in immune-compromised patients (older adults and oncohaematologic patients), compared with healthy counterparts, based on deep characterisation of the circulating immune cell subsets. While acquired humoral and cellular memory did not predict subsequent infection 18 months after full vaccination, spectral and computational cytometry revealed several subsets within the CD8 T-cells, B-cells, natural killer (NK) cells, monocytes and TEMRA Tγδ cells that were differentially expressed in individuals who were subsequently infected and not infected not just following immunisation, but also prior to vaccination. Of note, we found up to seven clusters within the TEMRA Tγδ cell population, with some of them being expanded and others decreased in subsequently infected individuals. Moreover, some of these cellular clusters were also related to COVID-19-induced hospitalisation in oncohaematologic patients. Therefore, we have identified a cellular signature that even before vaccination is related to COVID-19 vulnerability as opposed to the acquisition of cellular and/or humoral memory following vaccination with SARS-CoV-2 messenger RNA (mRNA) vaccines.

The immune cellular landscape from the gastric mucosa remains largely unknown despite its relevance in several inflammatory conditions. Human gastric biopsies were obtained from the antrum, body and incisura from 10 individuals to obtain lamina propria mononuclear cells that were further characterized by spectral cytometry. Phenotypic hierarchical analyses identified a total of 52 different immune cell subsets within the human gastric mucosa revealing that T-cells (> 60%) and NK cells (> 20%) were the main populations. Within T-cells, CD4 + and CD8 + were equally represented with both subsets displaying mainly a memory and effector phenotype. NK cells, on the contrary, were largely of the early phenotype. No regional differences were observed for any subsets among the 3 locations. Following unsupervised analysis, a total of 82 clusters were found. Again, no differences were observed amongst locations although a great degree of inter-individual variability was found, largely influenced by the presence of H. pylori infection and dyspepsia. We have unraveled the human gastric immune cellular subset composition and a unique interindividual immune fingerprint with no inter-regional variations.

Background: Growth arrest-specific factor 6 (GAS6) and the Tyro3, AXL, and MERTK (TAM) receptors counterbalance pro-inflammatory responses. AXL is a candidate receptor for SARS-CoV-2, particularly in the respiratory system, and the GAS6/AXL axis is targeted in current clinical trials against COVID-19. However, GAS6 and TAMs have not been evaluated in COVID-19 patients at emergency admission. Methods: Plasma GAS6, AXL, and MERTK were analyzed in 132 patients consecutively admitted to the emergency ward during the first peak of COVID-19. Results: GAS6 levels were higher in the SARS-CoV-2-positive patients, increasing progressively with the severity of the disease. Patients with initial GAS6 at the highest quartile had the worst outcome, with a 3-month survival of 65%, compared to a 90% survival for the rest. Soluble AXL exhibited higher plasma concentration in deceased patients, without significant differences in MERTK among SARS-CoV-2-positive groups. GAS6 mRNA was mainly expressed in alveolar cells and AXL in airway macrophages. Remarkably, THP-1 human macrophage differentiation neatly induces AXL, and its inhibition (bemcentinib) reduced cytokine production in human macrophages after LPS challenge. Conclusions: Plasma GAS6 and AXL levels reflect COVID-19 severity and could be early markers of disease prognosis, supporting a relevant role of the GAS6/AXL system in the immune response in COVID-19.

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care 1 or hospitalization 2 – 4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling ( IL10RB and PLSCR1 ), leucocyte differentiation ( BCL11A ) and blood-type antigen secretor status ( FUT2 ). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase ( ATP11A ), and increased expression of a mucin ( MUC1 )—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules ( SELE , ICAM5 and CD209 ) and the coagulation factor F8 , all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease. Whole-genome sequencing, transcriptome-wide association and fine-mapping analyses in over 7,000 individuals with critical COVID-19 are used to identify 16 independent variants that are associated with severe illness in COVID-19.

Antigen tests or polymerase chain reaction (PCR) amplification are currently COVID-19 diagnostic tools. However, developing complementary diagnosis tools is mandatory. Thus, we performed a plasma cytokine array in COVID-19 patients to identify novel diagnostic biomarkers. A discovery–validation study in two independent prospective cohorts was performed. The discovery cohort included 136 COVID-19 and non-COVID-19 patients recruited consecutively from 24 March to 11 April 2020. Forty-five cytokines’ quantification by the MAGPIX system (Luminex Corp., Austin, TX, USA) was performed in plasma samples. The validation cohort included 117 patients recruited consecutively from 15 to 25 April 2020 for validating results by ELISA. COVID-19 patients showed different levels of multiple cytokines compared to non-COVID-19 patients. A single chemokine, IP-10, accurately identified COVID-19 patients who required hospital admission (AUC: 0.962; 95%CI (0.933–0.992); p < 0.001)). The results were validated in an independent cohort by multivariable analysis (OR: 25.573; 95%CI (8.127–80.469); p < 0.001) and AUROC (AUC: 0.900; 95%CI (0.846–0.954); p < 0.001). Moreover, showing IP-10 plasma levels over 173.35 pg/mL identified COVID-19 with higher sensitivity (86.20%) than the first SARS-CoV-2 PCR. Our discover–validation study identified IP-10 as a robust biomarker in clinical practice for COVID-19 diagnosis at hospital. Therefore, IP-10 could be used as a complementary tool in clinical practice, especially in emergency departments.

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