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

ATP-dependent K+ channels in renal ischemia reperfusion injury

ATP-dependent K+ channels (K-ATP) account for most of the recycling of K+ which enters the proximal tubules cell via Na, K-ATPase. In the mitochondrial membrane, opening of these channels preserves mitochondrial viability and matrix volume during ischemia. We examined KATP channel modulation in renal ischemia-reperfusion injury (IRI), using an isolated perfused rat kidney (IPRK) model, in control, IRI, IRI + 200 muM diazoxide (a K-ATP opener), IRI + 10 muM glibenclamide (a K-ATP blocker) and IRI + 200 muM diazoxide + 10 muM glibenclamide groups. IRI was induced by 2 periods of warm ischemia, followed by 45 min of reperfusion. IRI significantly decreased glomerular filtration rate (GFR) and increased fractional excretion of sodium (FENa) (p < 0.01). Neither diazoxide nor glibenclamide had an effect on control kidney function other than an increase in renal vascular resistance produced by glibenclamide. Pretreatment with 200 muM diazoxide reduced the postischemic increase in FENa (p < 0.05). Adding 10 muM glibenclamide inhibited the diazoxide effect on postischemic FENa (p < 0.01). Histology showed that kidneys pretreated with glibenclamide demonstrated an increase in injure in the thick ascending limb of outer medulla (p < 0.05). Glibenclamide significantly decreased post ischemic renal vascular resistance (p < 0.05). but had no significant effect on other renal function parameters. Our results suggest that sodium reabsorption is improved by K-ATP activation and blockade of K-ATP channels during IRI has an injury enhancing effect on renal epithelial function and histology. This may be mediated through K-ATP modulation in cell and or mitochondrial inner membrane

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation; analyses timings and patterns of tumour evolution; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity; and evaluates a range of more-specialized features of cancer genomes