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 Efficient and early triage of hospitalized Covid-19 patients to detect those with higher risk of severe disease is essential for appropriate case management. Methods We trained, validated, and externally tested a machine-learning model to early identify patients who will die or require mechanical ventilation during hospitalization from clinical and laboratory features obtained at admission. A development cohort with 918 Covid-19 patients was used for training and internal validation, and 352 patients from another hospital were used for external testing. Performance of the model was evaluated by calculating the area under the receiver-operating-characteristic curve (AUC), sensitivity and specificity. Results A total of 363 of 918 (39.5%) and 128 of 352 (36.4%) Covid-19 patients from the development and external testing cohort, respectively, required mechanical ventilation or died during hospitalization. In the development cohort, the model obtained an AUC of 0.85 (95% confidence interval [CI], 0.82 to 0.87) for predicting severity of disease progression. Variables ranked according to their contribution to the model were the peripheral blood oxygen saturation (SpO2)/fraction of inspired oxygen (FiO2) ratio, age, estimated glomerular filtration rate, procalcitonin, C-reactive protein, updated Charlson comorbidity index and lymphocytes. In the external testing cohort, the model performed an AUC of 0.83 (95% CI, 0.81 to 0.85). This model is deployed in an open source calculator, in which Covid-19 patients at admission are individually stratified as being at high or non-high risk for severe disease progression. Conclusions This machine-learning model, applied at hospital admission, predicts risk of severe disease progression in Covid-19 patients.

Nitric oxide is now established as a biological mediator of clinical relevance. The present study investigated the production of nitric oxide by lympho-mononuclear leukocytes from alcoholic patients with either hepatitis or cirrhosis. The study included 42 patients, 12 without any liver disease and 30 alcoholic patients, 13 of whom had histologically confirmed cirrhosis and 17 alcoholic hepatitis. Cells were obtained from peripheral blood by density gradient and incubated in sterile conditions in RPMI 1640 for 6 h at 37 degrees C. Culture supernatants were assayed for nitrite concentration using the Griess reaction. Cells from cirrhotic but not from hepatopathic patients showed significantly higher nitrite production than controls (cirrhotic, 0.36 +/- 0.07; hepatopathic, 0.13 +/- 0.02; control: 0.25 +/- 0.05 nmol/10(6) cells/6 h). In cirrhotic patients L-Nitro-arginine methylester inhibited nitrite production (0.18 +/- 0.05). These data suggest that alcoholic cirrhotic but nonhepatopathic patients show an increased nitric oxide production by blood lymphomononuclear cells. This production could be involved in the systemic vasodilation in cirrhotic patients.

Iatrogenic sexual dysfunction (SD) caused by antihypertensive (AH) compounds, provoking sexual desire, orgasm or arousal dysfunction, is a common clinical adverse event. Unfortunately, it is often underestimated and underreported by clinicians and prescribers in clinical practice, deteriorating the adherence and patient quality of life. The objective of this study was to investigate the frequency of SD in patients treated with different antihypertensive compounds; a real-life naturalistic and cross-sectional study in patients receiving AH treatment was carried out. Method: A total of 256 patients were included in the study (188 males and 68 females who met the inclusion and exclusion criteria). The validated Psychotropic-Related Sexual Dysfunction Questionnaire (PRSexDQ-SALSEX) was transversally applied once at least every two months following the onset of the treatment in order to measure possible AH-related SD. Although the spontaneous reporting of SD was very low (6.81% females/24.8% males), 66.40% of the patients reported impaired sexual function through the SALSEX questionnaire after the treatment onset, as follows: decreased desire (55.8% females/54.2% males), delayed orgasm (42.6%/45.7%), anorgasmia (42.6%/43.6%) and arousal difficulties (53%/59.6%). The average frequency of moderate to severe iatrogenic SD was 66.4% with AH in monotherapy as follows: angiotensin II receptor antagonists (ARBs), 29.8%; calcium antagonists, 40%; diuretics, 42.9%; beta blockers, 43.8%; and angiotensin-converting enzyme (ACE) inhibitors, 77.8%. Combined treatments showed a higher percentage of main SD (70.3%): diuretic + ACE inhibitor, 42.3%; ARB + calcium antagonist, 55.6%; diuretic + calcium antagonist, 68.8%; and diuretic + ARB, 74.2%. The greatest risk factors associated with SD were poor general health, age over 60 with a comorbid coronary or musculoskeletal disease, mood disorder and diuretic +ARB combined therapy. Conclusion: SD is common in patients treated with antihypertensive drugs, and it is still underreported. The most harmful treatment deteriorating sexual function was the combination of diuretic +ARB, while the least harmful was monotherapy with ARBs. More research is needed on the clinical management of this problem to preserve the quality of life of patients and their partners.