PenQuest Volume 1, Number 2

Table of Contents for this Volume: Untitled by Julie Ambrose Night by Judith Gallo Untitled by Judy Gozdur the shamans by Charles Riddles Untitled by Jerry Connell Untitled by Laura Woods Untitled by LEMA Wicked Bird by Laura Jo Last Untitled by Rick Dentos Untitled by Jeni Moody Untitled by Bettie W. Kwibs Untitled by Joann Stagg The Protector Stood by Laura Jo Last Visions of Salome by Charles Riddles Untitled by Thomas Tutten Kennesaw Line by Don Ova-Dunaway Stone Blood by Mary Ellen C. Wofford Untitled by Roger Whitt Jr. Untitled by C. Wingate Untitled by Doug Dorey Untitled by Karen Blumberg Untitled by Beverly Oviatt Untitled by Virginia Shrader The Crapulous Credo of Charles C. by Charles Riddles the brave and the true by David Reed Untitled by Charles Gutierrez Canoe Creek by Patricia Kraft Untitled by Linda Bobinger The Man in the Iron Lung by Patricia Kraft Untitled by Roger Whitt, Jr. Childish Things by Kathleen Gay Untitled by Joseph Avanzini The Lover by Mary S. Aken Untitled by Ann Harrington And He Taketh Away by David Reed Untitled by Mary Graham Untitled by Melody A. Cummons Untitled by Karen Blumberg To The Poets by Judith Gallo Untitled by Ann Harringto

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)

Genetic mechanisms of critical illness in Covid-19.

Host-mediated lung inflammation is present,1 and drives mortality,2 in critical illness caused by Covid-19. Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development.3 Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study(GWAS) in 2244 critically ill Covid-19 patients from 208 UK intensive care units (ICUs). We identify and replicate novel genome-wide significant associations, on chr12q24.13 (rs10735079, p=1.65 [Formula: see text] 10-8) in a gene cluster encoding antiviral restriction enzyme activators (OAS1, OAS2, OAS3), on chr19p13.2 (rs2109069, p=2.3 [Formula: see text] 10-12) near the gene encoding tyrosine kinase 2 (TYK2), on chr19p13.3 (rs2109069, p=3.98 [Formula: see text] 10-12) within the gene encoding dipeptidyl peptidase 9 (DPP9), and on chr21q22.1 (rs2236757, p=4.99 [Formula: see text] 10-8) in the interferon receptor gene IFNAR2. We identify potential targets for repurposing of licensed medications: using Mendelian randomisation we found evidence in support of a causal link from low expression of IFNAR2, and high expression of TYK2, to life-threatening disease; 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. Large-scale randomised clinical trials will be essential before any change to clinical practice

Structural and kinetic differences between human and Aspergillus fumigatus D-glucosamine-6-phosphate N-acetyltransferase

International audienceAspergillus fumigatus is the causative agent of aspergillosis, a frequently invasive colonisation of the lungs of immunocompromised patients. Glucosamine-6-phosphate N-acetyltransferase (GNA1) catalyses the acetylation of glucosamine-6-phosphate (GlcN-6P) to N-acetylglucosamine-6-phosphate (GlcNAc-6P), a key intermediate in the UDP-GlcNAc biosynthetic pathway. Gene disruption of gna1 in yeast and Candida albicans has provided genetic validation of the enzyme as a potential target. An understanding of potential active site differences between the human and A. fumigatus enzymes is required to enable further work aimed at identifying selective inhibitors for the fungal enzyme. Here, we describe crystal structures of both human and A. fumigatus GNA1, as well as their kinetic characterization. The structures show significant differences in the sugar binding site, with in particular several non-conservative substitutions near the phosphate binding pocket. Mutagenesis targeting these differences revealed drastic effects on steady-state kinetics, suggesting that the differences could be exploitable with small molecule inhibitors

Pregnancy and neonatal outcomes of COVID -19: coreporting of common outcomes from PAN-COVID and AAP-SONPM registries

Objective Few large cohort studies have reported data on maternal, fetal, perinatal and neonatal outcomes associated with severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection in pregnancy. We report the outcome of infected pregnancies from a collaboration formed early during the pandemic between the investigators of two registries, the UK and Global Pregnancy and Neonatal outcomes in COVID‐19 (PAN‐COVID) study and the American Academy of Pediatrics (AAP) Section on Neonatal–Perinatal Medicine (SONPM) National Perinatal COVID‐19 Registry. Methods This was an analysis of data from the PAN‐COVID registry (1 January to 25 July 2020), which includes pregnancies with suspected or confirmed maternal SARS‐CoV‐2 infection at any stage in pregnancy, and the AAP‐SONPM National Perinatal COVID‐19 registry (4 April to 8 August 2020), which includes pregnancies with positive maternal testing for SARS‐CoV‐2 from 14 days before delivery to 3 days after delivery. The registries collected data on maternal, fetal, perinatal and neonatal outcomes. The PAN‐COVID results are presented overall for pregnancies with suspected or confirmed SARS‐CoV‐2 infection and separately in those with confirmed infection. Results We report on 4005 pregnant women with suspected or confirmed SARS‐CoV‐2 infection (1606 from PAN‐COVID and 2399 from AAP‐SONPM). For obstetric outcomes, in PAN‐COVID overall and in those with confirmed infection in PAN‐COVID and AAP‐SONPM, respectively, maternal death occurred in 0.5%, 0.5% and 0.2% of cases, early neonatal death in 0.2%, 0.3% and 0.3% of cases and stillbirth in 0.5%, 0.6% and 0.4% of cases. Delivery was preterm (< 37 weeks' gestation) in 12.0% of all women in PAN‐COVID, in 16.1% of those women with confirmed infection in PAN‐COVID and in 15.7% of women in AAP‐SONPM. Extreme preterm delivery (< 27 weeks' gestation) occurred in 0.5% of cases in PAN‐COVID and 0.3% in AAP‐SONPM. Neonatal SARS‐CoV‐2 infection was reported in 0.9% of all deliveries in PAN‐COVID overall, in 2.0% in those with confirmed infection in PAN‐COVID and in 1.8% in AAP‐SONPM; the proportions of neonates tested were 9.5%, 20.7% and 87.2%, respectively. The rates of a small‐for‐gestational‐age (SGA) neonate were 8.2% in PAN‐COVID overall, 9.7% in those with confirmed infection and 9.6% in AAP‐SONPM. Mean gestational‐age‐adjusted birth‐weight Z‐scores were −0.03 in PAN‐COVID and −0.18 in AAP‐SONPM. Conclusions The findings from the UK and USA registries of pregnancies with SARS‐CoV‐2 infection were remarkably concordant. Preterm delivery affected a higher proportion of women than expected based on historical and contemporaneous national data. The proportions of pregnancies affected by stillbirth, a SGA infant or early neonatal death were comparable to those in historical and contemporaneous UK and USA data. Although maternal death was uncommon, the rate was higher than expected based on UK and USA population data, which is likely explained by underascertainment of women affected by milder or asymptomatic infection in pregnancy in the PAN‐COVID study, although not in the AAP‐SONPM study. The data presented support strong guidance for enhanced precautions to prevent SARS‐CoV‐2 infection in pregnancy, particularly in the context of increased risks of preterm delivery and maternal mortality, and for priority vaccination of pregnant women and women planning pregnancy. Copyright © 2021 ISUOG. Published by John Wiley & Sons Ltd

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

AbstractThe 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.</jats:p