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

Polycystic ovary syndrome with hyperandrogenism is characterized by an increased risk of hepatic steatosis compared to nonhyperandrogenic PCOS phenotypes and healthy controls, independent of obesity and insulin resistance

Polycystic ovary syndrome (PCOS) affects up to 20% of women of reproductive age and is clinically characterized by irregular menstrual cycles, hyperandrogenism, infertility, or subfertility, frequently with a characteristic ovarian morphology on ultrasonographic examination. There is no consensus as to the most appropriate diagnostic criteria, which incorporate multiple possible phenotypes, but the critical difference between the criteria is whether hyperandrogenism is a prerequisite feature (1) or not (2). The etiology of PCOS is complex and not completely understood. Nevertheless, a central pathophysiological feature of PCOS is insulin resistance, which cannot be fully explained by the frequent association with obesity because PCOS women are more insulin resistant than healthy controls matched for body mass index (BMI) (3). Different distributions of body fat, for example increased abdominal fat in PCOS relative to controls matched for BMI, could potentially contribute to the insulin resistance in this patient group (4, 5). Visceral fat mass strongly correlates with the degree of insulin resistance and other aspects of the metabolic syndrome in women with PCOS (5, 6). Moreover, in healthy normal-weight and obese individuals, liver fat is also highly correlated with insulin resistance and other features of the metabolic syndrome (7, 8). There is some evidence of an increased prevalence of nonalcoholic fatty liver disease (NAFLD) in PCOS, using a variety of diagnostic and surrogate methods. NAFLD represents a disease spectrum, ranging from hepatic steatosis, characterized by deposition of triglycerides in the hepatocytes, through to nonalcoholic steatohepatitis (NASH), characterized by hepatocyte injury, inflammation, and fibrosis, which can in turn progress to cirrhosis (9). Using liver transaminases or ultrasonography to infer the presence of hepatic steatosis, a number of studies have demonstrated a high risk of hepatic steatosis in women with PCOS (10–13). Indirect methods have also been used to detect NASH, the intermediate stage in the NAFLD spectrum. Tan et al. (14) demonstrated a high prevalence of NASH in PCOS using levels of the apoptotic marker cytokeratin-18 as a surrogate index. Based on such literature, it has been suggested that women with PCOS should be screened for liver disease at an earlier age than is currently recommended for the general population (15). However, to our knowledge there have been no carefully controlled studies to address the clinically relevant question as to whether PCOS represents a specific risk factor for the development of NAFLD, or whether the increased risk of NAFLD in PCOS is mediated by the high prevalence of concomitant obesity. This latter possibility is suggested by the results of a small study in lean, insulin-resistant PCOS women demonstrating no increased risk of NAFLD (16). Using proton magnetic resonance spectroscopy (1H-MRS), a well-validated, noninvasive method for measuring liver fat content that correlates closely with liver fat determined histologically (17), it is possible to precisely determine liver fat rather than a more semiquantitative method such as ultrasonography. Thus, the aim of this study was to: 1) determine whether women with PCOS have increased liver fat, determined by 1H-MRS, compared with healthy controls of similar age and BMI; and 2) examine whether a specific phenotype of PCOS is more strongly associated with NAFLD than other phenotypes. We hypothesize that hyperandrogenic PCOS women will have increased liver fat independent of body composition

UMVU estimation of the reliability function of the generalized life distributions

Generalized life distributions, hazard-rate, reliability function, stress-strength model,