Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)

Retrieval analysis of a failed TriboFit polycarbonate urethane acetabular buffer

The purpose of this research was to determine the failure mechanisms and damage features of a TriboFit acetabular buffer implanted directly against a native, prepared acetabulum which was revised after 11months. Retrieval analyses were carried out via light microscopy, gravimetric wear assessment, and observer scoring of visible damage features on the buffer. The volume of material abraded from the backside of the buffer was estimated via three-dimensional reconstruction using a laser scanner. Scanning electron microscopy was used to confirm damage features and mechanisms. Severe abrasion to the backside of the buffer was the primary damage feature, while stippling damage was seen on the articular surface of the buffer. Material loss due to backside abrasion was approximated to be between 0.13360.085 g (gravimetric analyses) and 0.19360.053 g (three-dimensional reconstruction). Implantation of the TriboFit buffer against the patient’s native acetabulum without a metal backing allowed for significant movement of the buffer against the bone, resulting in the abrasion seen on this implant. The stippling damage on the articular surface indicates an adhesive wear mechanism which exacerbates movement of the buffer against the acetabulum, thereby increasing backside abrasion. </jats:p

Damage Assessment of Retrieved Birmingham Monoblock Cups: Is Conversion to Dual-Mobility Head a Viable Revision Option?

© 2017 Elsevier Inc. Background: A novel revision technique for failed hip resurfacings involves retention of the acetabular cup, if well-fixed, which is mated to dual-mobility (DM) prosthesis in a traditional hip replacement configuration. It is unknown whether existing damage on the retained cup will result in unacceptable wear of the DM prosthesis. Methods: Thirty retrieved Birmingham (Smith & Nephew) monoblock cups were visually scored for damage features and area of coverage. Surface roughness measurements were obtained within each damage feature as well as reference points on each cup. Analysis of prior metal-on-metal wear was also performed to determine the maximum change in diameter of the cup. Results: Scratching and grooving (deep, singular scratches) were the most common damage features. Overall bearing surface roughness was estimated as 0.059 μm (±0.030 μm) based on percent area coverage of each damage feature. Dimensional change of the bearing surface was negligible for most cups (18 of 30) but ranged from 0.20 to 0.38 mm for the most severely worn samples (5 of 30). Conclusion: Average surface roughness of the retrieved Birmingham cups was low, suggesting an expected 10%-20% increase in DM prosthesis wear. Similarly, dimensional change of the cup due to prior wear is not believed to significantly affect wear. Our findings support the use of a DM head in appropriate scenarios but suggest caution when applied to younger, more active patients whom may be adversely affected by increased prosthesis wear in the long term

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