Stratification of hospitalized COVID-19 patients into clinical severity progression groups by immuno-phenotyping and machine learning

Quantitative or qualitative differences in immunity may drive clinical severity in COVID-19. Although longitudinal studies to record the course of immunological changes are ample, they do not necessarily predict clinical progression at the time of hospital admission. Here we show, by a machine learning approach using serum pro-inflammatory, anti-inflammatory and anti-viral cytokine and anti-SARS-CoV-2 antibody measurements as input data, that COVID-19 patients cluster into three distinct immune phenotype groups. These immune-types, determined by unsupervised hierarchical clustering that is agnostic to severity, predict clinical course. The identified immune-types do not associate with disease duration at hospital admittance, but rather reflect variations in the nature and kinetics of individual patient's immune response. Thus, our work provides an immune-type based scheme to stratify COVID-19 patients at hospital admittance into high and low risk clinical categories with distinct cytokine and antibody profiles that may guide personalized therapy. Developing predictive methods to identify patients with high risk of severe COVID-19 disease is of crucial importance. Authors show here that by measuring anti-SARS-CoV-2 antibody and cytokine levels at the time of hospital admission and integrating the data by unsupervised hierarchical clustering/machine learning, it is possible to predict unfavourable outcome

Upregulation of endothelial cell adhesion molecules characterizes veins close to granulomatous infiltrates in the renal cortex of cats with feline infectious peritonitis and is indirectly triggered by feline infectious peritonitis virus-infected monocytes in vitro

One of the most characteristic pathological changes in cats that have succumbed to feline infectious peritonitis (FIP) is a multifocal granulomatous phlebitis. Although it is now well established that leukocyte extravasation elicits the inflammation typically associated with FIP lesions, relatively few studies have aimed at elucidating this key pathogenic event. The upregulation of adhesion molecules on the endothelium is a prerequisite for stable leukocyte-endothelial cell (EC) adhesion that necessarily precedes leukocyte diapedesis. Therefore, the present work focused on the expression of the EC adhesion molecules and possible triggers of EC activation during the development of FIP. Immunofluorescence analysis revealed that the endothelial expression of P-selectin, E-selectin, intercellular adhesion molecule 1 (ICAM-1) and vascular cell adhesion molecule 1 (VCAM-1) was elevated in veins close to granulomatous infiltrates in the renal cortex of FIP patients compared to non-infiltrated regions and specimens from healthy cats. Next, we showed that feline venous ECs become activated when exposed to supernatant from feline infectious peritonitis virus (FIPV)-infected monocytes, as indicated by increased adhesion molecule expression. Active viral replication seemed to be required to induce the EC-stimulating activity in monocytes. Finally, adhesion assays revealed an increased adhesion of naive monocytes to ECs treated with supernatant from FIPV-infected monocytes. Taken together, our results strongly indicate that FIPV activates ECs to increase monocyte adhesion by an indirect route, in which proinflammatory factors released from virus-infected monocytes act as key intermediates