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

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Not AvailableSoil salinity is a major problem in canal command areas which affects the fertility of the land. The village Ugar Budruk in Athani taluk of Belgaum district in Karnataka faced a major challenge of soil salinity and waterlogging since 25-30 years. Approximately 70 per cent of cultivable area of the village was affected by soil salinity and the land which was highly productive once, was partially cultivated or left barren for many years. With the effort of progressive farmers of the village about 925 ha saline land has been reclaimed through installation of subsurface drainage technology. The per hectare cost of land reclamation was estimated to Rs. 52000. The post reclamation study implied that about 77 per cent of the land was non-saline. The mean soil salinity was reduced from 6.6 to 2.52 dS/m during post-SSD showing 163 per cent reduction in soil salinity. The improved land productivity contributed to a significant increase in crop yield due to increase in farmers income to a maximum extent. The pre-SSD benefit-cost ratio of 0.56 and 0.51 were increased to 1.24 and 1.19 during post-SSD, respectively for planted and ratoon sugarcane production. The increase in benefit-cost ratio for planted and ratoon sugarcane production were about 120 and 134 per cent respectively. Though the installation of saline soil reclamation technology requires high cost, the effectiveness of the technology made the Karnataka farmers to install the technology on their own cost.Not Availabl

Assessing spatio-temporal variations in groundwater table depth and salinity using geostatistics and its relation with groundwater balance in a salt affected soil

In order to study spatio-temporal variation in groundwater table depth and salinity in shallow groundwater table area, a field study was carried out at Nain experimental farm of ICAR-Central Soil Salinity Research Institute (ICAR-CSSRI) situated in Nain village of Panipat, Haryana. Total 27 observation wells had been installed in such a way that few among them were near to working tubewell for observing groundwater fluctuation due to pumping. 8 observation wells were near to pond and remaining observation wells were distributed in the area confined between the pond and surface drains to observe effect of natural recharge taking place from water bodies on groundwater table fluctuation. Besides continuous groundwater table monitoring, periodic assessment of groundwater salinity (EC ) was also done. Spatio-temporal w behavior of groundwater table and groundwater salinity was studied using Ordinary Kriging (OK) procedure in Arc GIS 9.3 software. The variograms and krigged spatial maps were generated for pre and post monsoon seasons of 2013 and 2015. Different inflow and outflow components of groundwater were characterized using groundwater balance method. Spatial variability maps of groundwater table in pre monsoon season indicate an increase in 36% area of shallow groundwater table (<2 m below ground level-bgl) during 2013 to 2015. Whereas, area under -1 low saline groundwater (0-4 dS m ) was increased and reduction in higher -1 saline groundwater (8-16 dS m ) area was recorded during 2013 to 2015. Analysis of groundwater balance of the experimental farm revealed that this reduction in groundwater salinity and rise in groundwater level might be attributed to intrusion of fresh water from outside cultivated land and seepage from nearby water harvesting structures and drain. Based on the results, it can be concluded that geo statistical analysis provides an understanding of groundwater flow behavior and dynamics of groundwater salinity, which can be used to prioritize the area for implementing the groundwater management plan in salt affected areas.Not Availabl

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