Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 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 reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 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

Clinical aspects and outcomes of 70 patients with Middle East respiratory syndrome coronavirus infection: a single-center experience in Saudi Arabia

Objectives: To report the experience with Middle East respiratory syndrome coronavirus (MERS-CoV) infection at a single center in Saudi Arabia. Methods: Cases of laboratory-confirmed MERS-CoV occurring from October 1, 2012 to May 31, 2014 were reviewed retrospectively. Information sources included medical files, infection control outbreak investigations, and the preventive medicine database of MERS-CoV-infected patients. Data were collected on clinical and epidemiological aspects and outcomes. Results: Seventy consecutive patients were included. Patients were mostly of older age (median 62 years), male (46, 65.7%), and had healthcare acquisition of infection (39, 55.7%). Fever (43, 61.4%), dyspnea (42, 60%), and cough (38, 54.3%) were the most common symptoms. The majority developed pneumonia (63, 90%) and required intensive care (49, 70%). Infection commonly occurred in clusters. Independent risk factors for severe infection requiring intensive care included concomitant infections (odds ratio (OR) 14.13, 95% confidence interval (CI) 1.58–126.09; p = 0.018) and low albumin (OR 6.31, 95% CI 1.24–31.90; p = 0.026). Mortality was high (42, 60%), and age ≥65 years was associated with increased mortality (OR 4.39, 95% CI 2.13–9.05; p < 0.001). Conclusions: MERS-CoV can cause severe infection requiring intensive care and has a high mortality. Concomitant infections and low albumin were found to be predictors of severe infection, while age ≥65 years was the only predictor of increased mortality

Home versus Clinic Blood Pressure Monitoring: Evaluating Applicability in Hypertension Management via Telemedicine

Hypertension is a significant public health concern in Saudi Arabia, affecting 28.6% of the population. Despite the availability of effective treatments, optimal blood pressure control is not always achieved, highlighting the need for effective management strategies. This study aimed to evaluate the applicability of home, compared to clinic, blood pressure measurements for managing hypertension in the Qassim region of Saudi Arabia. The study included 85 adults undergoing antihypertensive treatment. Home blood pressure measurements were obtained during the day and the evening using automated oscillometric sphygmomanometers, whereas clinic measurements were taken during clinic hours. Home blood pressure readings were significantly lower than clinic blood pressure readings, with mean differences of 20.4 mmHg and 4.1 mmHg for systolic and diastolic blood pressures, respectively. There was a positive correlation between the clinic systolic and diastolic blood pressures (r = 0.549, p p < 0.05). This study provides insight into the applicability of home blood pressure monitoring, which may aid in the development of more effective hypertension management strategies, particularly the use of morning home blood pressure monitoring to aid treatment decisions through telehealth medicine

Accelerating Novel Candidate Gene Discovery in Neurogenetic Disorders via Whole-Exome Sequencing of Prescreened Multiplex Consanguineous Families

Our knowledge of disease genes in neurological disorders is incomplete. With the aim of closing this gap, we performed whole-exome sequencing on 143 multiplex consanguineous families in whom known disease genes had been excluded by autozygosity mapping and candidate gene analysis. This prescreening step led to the identification of 69 recessive genes not previously associated with disease, of which 33 are here described (SPDL1, TUBA3E, INO80, NID1, TSEN15, DMBX1, CLHC1, C12orf4, WDR93, ST7, MATN4, SEC24D, PCDHB4, PTPN23, TAF6, TBCK, FAM177A1, KIAA1109, MTSS1L, XIRP1, KCTD3, CHAF1B, ARV1, ISCA2, PTRH2, GEMIN4, MYOCD, PDPR, DPH1, NUP107, TMEM92, EPB41L4A, and FAM120AOS). We also encountered instances in which the phenotype departed significantly from the established clinical presentation of a known disease gene. Overall, a likely causal mutation was identified in >73% of our cases. This study contributes to the global effort toward a full compendium of disease genes affecting brain function

Whole-genome sequencing reveals host factors underlying critical COVID-19

Altres ajuts: Department of Health and Social Care (DHSC); Illumina; LifeArc; Medical Research Council (MRC); UKRI; Sepsis Research (the Fiona Elizabeth Agnew Trust); the Intensive Care Society, Wellcome Trust Senior Research Fellowship (223164/Z/21/Z); BBSRC Institute Program Support Grant to the Roslin Institute (BBS/E/D/20002172, BBS/E/D/10002070, BBS/E/D/30002275); UKRI grants (MC_PC_20004, MC_PC_19025, MC_PC_1905, MRNO2995X/1); UK Research and Innovation (MC_PC_20029); the Wellcome PhD training fellowship for clinicians (204979/Z/16/Z); the Edinburgh Clinical Academic Track (ECAT) programme; the National Institute for Health Research, the Wellcome Trust; the MRC; Cancer Research UK; the DHSC; NHS England; the Smilow family; the National Center for Advancing Translational Sciences of the National Institutes of Health (CTSA award number UL1TR001878); the Perelman School of Medicine at the University of Pennsylvania; National Institute on Aging (NIA U01AG009740); the National Institute on Aging (RC2 AG036495, RC4 AG039029); the Common Fund of the Office of the Director of the National Institutes of Health; NCI; NHGRI; NHLBI; NIDA; NIMH; NINDS.Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care or hospitalization 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