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Critical illness in COVID-19 is an extreme and clinically homogeneous disease phenotype that we have previously shown1 to be highly efficient for discovery of genetic associations2. Despite the advanced stage of illness at presentation, we have shown that host genetics in patients who are critically ill with COVID-19 can identify immunomodulatory therapies with strong beneficial effects in this group3. Here we analyse 24,202 cases of COVID-19 with critical illness comprising a combination of microarray genotype and whole-genome sequencing data from cases of critical illness in the international GenOMICC (11,440 cases) study, combined with other studies recruiting hospitalized patients with a strong focus on severe and critical disease: ISARIC4C (676 cases) and the SCOURGE consortium (5,934 cases). To put these results in the context of existing work, we conduct a meta-analysis of the new GenOMICC genome-wide association study (GWAS) results with previously published data. We find 49 genome-wide significant associations, of which 16 have not been reported previously. To investigate the therapeutic implications of these findings, we infer the structural consequences of protein-coding variants, and combine our GWAS results with gene expression data using a monocyte transcriptome-wide association study (TWAS) model, as well as gene and protein expression using Mendelian randomization. We identify potentially druggable targets in multiple systems, including inflammatory signalling (JAK1), monocyte–macrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).

Background The presence of headache during the acute phase of COVID-19 could be associated with the innate response and the cytokine release. We aim to compare the cytokine and interleukin profile in hospitalized COVID-19 patients at the moment of admission with and without headache during the course of the disease. Methods An observational analytic study with a case control design was performed. Hospitalized patients from a tertiary hospital with confirmed COVID-19 disease were included. Patients were classified into the headache or the control group depending on whether they presented headache not better accounted for by another headache disorder other than acute headache attributed to systemic viral infection. Several demographic and clinical variables were studies in both groups. We determined the plasmatic levels of 45 different cytokines and interleukins from the first hospitalization plasma extraction in both groups. Results One hundred and four patients were included in the study, aged 67.4 (12.8), 43.3% female. Among them, 29 (27.9%) had headache. Patients with headache were younger (61.8 vs. 69.5 years, p = 0.005) and had higher frequency of fever (96.6 vs. 78.7%, p = 0.036) and anosmia (48.3% vs. 22.7%, p = 0.016). In the comparison of the crude median values of cytokines, many cytokines were different between both groups. In the comparison of the central and dispersion parameters between the two groups, GROa, IL-10, IL1RA, IL-21, IL-22 remained statistically significant. After adjusting the values for age, sex, baseline situation and COVID-19 severity, IL-10 remained statistically significant (3.3 vs. 2.2 ng/dL, p = 0.042), with a trend towards significance in IL-23 (11.9 vs. 8.6 ng/dL, p = 0.082) and PIGF1 (1621.8 vs. 110.6 ng/dL, p = 0.071). Conclusions The higher levels of IL-10 -an anti-inflammatory cytokine- found in our sample in patients with headache may be explained as a counteract of cytokine release, reflecting a more intense immune response in these patients.

Pneumonia is the leading cause of hospital admission and mortality in coronavirus disease 2019 (COVID-19). We aimed to identify the cytokines responsible for lung damage and mortality. We prospectively recruited 108 COVID-19 patients between March and April 2020 and divided them into four groups according to the severity of respiratory symptoms. Twenty-eight healthy volunteers were used for normalization of the results. Multiple cytokines showed statistically significant differences between mild and critical patients. High HGF levels were associated with the critical group (OR = 3.51; p < 0.001; 95%CI = 1.95–6.33). Moreover, high IL-1α (OR = 1.36; p = 0.01; 95%CI = 1.07–1.73) and low IL-27 (OR = 0.58; p < 0.005; 95%CI = 0.39–0.85) greatly increased the risk of ending up in the severe group. This model was especially sensitive in order to predict critical status (AUC = 0.794; specificity = 69.74%; sensitivity = 81.25%). Furthermore, high levels of HGF and IL-1α showed significant results in the survival analysis (p = 0.033 and p = 0.011, respectively). HGF, IL-1α, and IL 27 at hospital admission were strongly associated with severe/critical COVID-19 patients and therefore are excellent predictors of bad prognosis. HGF and IL-1α were also mortality biomarkers.