New susceptibility loci for severe COVID-19 by detailed GWAS analysis in European populations (preprint)

Due to the highly variable clinical phenotype of Coronavirus disease 2019 (COVID-19), deepening the host genetic contribution to severe COVID-19 may further improve our understanding about underlying disease mechanisms. Here, we describe an extended GWAS meta-analysis of 3,260 COVID-19 patients with respiratory failure and 12,483 population controls from Italy, Spain, Norway and Germany, as well as hypothesis-driven targeted analysis of the human leukocyte antigen (HLA) region and chromosome Y haplotypes. We include detailed stratified analyses based on age, sex and disease severity. In addition to already established risk loci, our data identify and replicate two genome-wide significant loci at 17q21.31 and 19q13.33 associated with severe COVID-19 with respiratory failure. These associations implicate a highly pleiotropic ~0.9-Mb 17q21.31 inversion polymorphism, which affects lung function and immune and blood cell counts, and the NAPSA gene, involved in lung surfactant protein production, in COVID-19 pathogenesis.

Regional performance variation in external validation of four prediction models for severity of COVID-19 at hospital admission: An observational multi-centre cohort study (preprint)

BackgroundSeveral prediction models for coronavirus disease-19 (COVID-19) have been published. Prediction models should be externally validated to assess their performance before implementation. This observational cohort study aimed to validate published models of severity for hospitalized patients with COVID-19 using clinical and laboratory predictors. MethodsPrediction models fitting relevant inclusion criteria were chosen for validation. The outcome was either mortality or a composite outcome of mortality and ICU admission (severe disease). 1295 patients admitted with symptoms of COVID-19 at Kings Cross Hospital (KCH) in London, United Kingdom, and 307 patients at Oslo University Hospital (OUH) in Oslo, Norway were included. The performance of the models was assessed in terms of discrimination and calibration. ResultsWe identified two models for prediction of mortality (referred to as Xie and Zhang1) and two models for prediction of severe disease (Allenbach and Zhang2). The performance of the models was variable. For prediction of mortality Xie had good discrimination at OUH with an area under the receiver-operating characteristic (AUROC) 0.87 [95 % confidence interval (CI) 0.79-0.95] and acceptable discrimination at KCH, AUROC 0.79 [0.76-0.82]. In prediction of severe disease, Allenbach had acceptable discrimination (OUH AUROC 0.81 [0.74-0.88] and KCH AUROC 0.72 [0.68-0.75]). The Zhang models had moderate to poor discrimination. Initial calibration was poor for all models but improved with recalibration. ConclusionsThe performance of the four prediction models was variable. The Xie model had the best discrimination for mortality, while the Allenbach model had acceptable results for prediction of severe disease.

Increased Interleukin-6 and Macrophage Chemoattractant Protein-1 are associated with Respiratory Failure in COVID-19 (preprint)

Background: In SARS-CoV-2 infection there is an urgent need to identify patients that will progress to severe COVID-19 and may benefit from targeted treatment.Objectives: Analyze plasma cytokines in COVID-19 patients and investigate their association with respiratory failure (RF) and treatment in Intensive Care Unit (ICU). Method: Hospitalized patients (n=34) with confirmed COVID-19 were recruited into a prospective cohort study. Clinical data and blood samples were collected at inclusion and after 2-5 and 7-10 days. RF was defined as PaO2/FiO2 ratio (P/F) <40kPa. Plasma cytokines were analyzed by a Human Cytokine 27-plex assay. Measurements and Results: COVID-19 patients with RF and/or treated in ICU showed overall increased systemic cytokine levels. Plasma IL-6, IL-8, G-CSF, MCP-1, MIP-1α levels were negatively correlated with P/F, whereas combinations of IL-6, IP-10, IL-1ra and MCP-1 showed the best association with RF in ROC analysis (AUC 0.79-0.80, p<0.05). During hospitalization the decline was most significant for IP-10 (P<0.001). Conclusion: Elevated levels of pro-inflammatory cytokines were present in patients with severe COVID-19. IL-6 and MCP-1 were inversely correlated with P/F with the largest AUC in ROC analyses and should be further explored as biomarkers to identify patients at risk for severe RF and as targets for improved treatment strategies.