Thromboembolism and anticoagulant therapy during the COVID-19 pandemic: interim clinical guidance from the anticoagulation forum

Coronavirus disease 2019 (COVID-19) is a viral infection that can, in severe cases, result in cytokine storm, systemic inflammatory response and coagulopathy that is prognostic of poor outcomes. While some, but not all, laboratory findings appear similar to sepsis-associated disseminated intravascular coagulopathy (DIC), COVID-19- induced coagulopathy (CIC) appears to be more prothrombotic than hemorrhagic. It has been postulated that CIC may be an uncontrolled immunothrombotic response to COVID-19, and there is growing evidence of venous and arterial thromboembolic events in these critically ill patients. Clinicians around the globe are challenged with rapidly identifying reasonable diagnostic, monitoring and anticoagulant strategies to safely and effectively manage these patients. Thoughtful use of proven, evidence-based approaches must be carefully balanced with integration of rapidly emerging evidence and growing experience. The goal of this document is to provide guidance from the Anticoagulation Forum, a North American organization of anticoagulation providers, regarding use of anticoagulant therapies in patients with COVID-19. We discuss in-hospital and post-discharge venous thromboembolism (VTE) prevention, treatment of suspected but unconfirmed VTE, laboratory monitoring of COVID-19, associated anticoagulant therapies, and essential elements for optimized transitions of care specific to patients with COVID-19

Lepton Fluxes from Atmospheric Charm

We reexamine the charm contribution to atmospheric lepton fluxes in the context of perturbative QCD. We include next-to-leading order corrections and discuss theoretical uncertainties due to the extrapolations of the gluon distributions at small-x. We show that the charm contribution to the atmospheric muon flux becomes dominant over the conventional contribution from pion and kaon decays at energies of about 10^5 GeV. We compare our fluxes with previous calculations.Comment: 19 pages, latex, revtex, psfi

Genome modeling system: A knowledge management platform for genomics

In this work, we present the Genome Modeling System (GMS), an analysis information management system capable of executing automated genome analysis pipelines at a massive scale. The GMS framework provides detailed tracking of samples and data coupled with reliable and repeatable analysis pipelines. The GMS also serves as a platform for bioinformatics development, allowing a large team to collaborate on data analysis, or an individual researcher to leverage the work of others effectively within its data management system. Rather than separating ad-hoc analysis from rigorous, reproducible pipelines, the GMS promotes systematic integration between the two. As a demonstration of the GMS, we performed an integrated analysis of whole genome, exome and transcriptome sequencing data from a breast cancer cell line (HCC1395) and matched lymphoblastoid line (HCC1395BL). These data are available for users to test the software, complete tutorials and develop novel GMS pipeline configurations. The GMS is available at https://github.com/genome/gms

A Broadly Implementable Research Course in Phage Discovery and Genomics for First-Year Undergraduate Students

Engaging large numbers of undergraduates in authentic scientific discovery is desirable but difficult to achieve. We have developed a general model in which faculty and teaching assistants from diverse academic institutions are trained to teach a research course for first-year undergraduate students focused on bacteriophage discovery and genomics. The course is situated within a broader scientific context aimed at understanding viral diversity, such that faculty and students are collaborators with established researchers in the field. The Howard Hughes Medical Institute (HHMI) Science Education Alliance Phage Hunters Advancing Genomics and Evolutionary Science (SEA-PHAGES) course has been widely implemented and has been taken by over 4,800 students at 73 institutions. We show here that this alliance-sourced model not only substantially advances the field of phage genomics but also stimulates students’ interest in science, positively influences academic achievement, and enhances persistence in science, technology, engineering, and mathematics (STEM) disciplines. Broad application of this model by integrating other research areas with large numbers of early-career undergraduate students has the potential to be transformative in science education and research training

Self-oligomerization regulates stability of survival motor neuron protein isoforms by sequestering an SCF^Slmb degron

Spinal muscular atrophy (SMA) is caused by homozygous mutations in human SMN1. Expression of a duplicate gene (SMN2) primarily results in skipping of exon 7 and production of an unstable protein isoform, SMNΔ7. Although SMN2 exon skipping is the principal contributor to SMA severity, mechanisms governing stability of survival motor neuron (SMN) isoforms are poorly understood. We used a Drosophila model system and label-free proteomics to identify the SCFSlmb ubiquitin E3 ligase complex as a novel SMN binding partner. SCFSlmb interacts with a phosphor degron embedded within the human and fruitfly SMN YG-box oligomerization domains. Substitution of a conserved serine (S270A) interferes with SCFSlmb binding and stabilizes SMNΔ7. SMA-causing missense mutations that block multimerization of full-length SMN are also stabilized in the degron mutant background. Overexpression of SMNΔ7S270A, but not wild-type (WT) SMNΔ7, provides a protective effect in SMA model mice and human motor neuron cell culture systems. Our findings support a model wherein the degron is exposed when SMN is monomeric and sequestered when SMN forms higher-order multimers

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 hospitalization2–4 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

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

A Broadly Implementable Research Course in Phage Discovery and Genomics for First-Year Undergraduate Students

Engaging large numbers of undergraduates in authentic scientific discovery is desirable but difficult to achieve. We have developed a general model in which faculty and teaching assistants from diverse academic institutions are trained to teach a research course for first-year undergraduate students focused on bacteriophage discovery and genomics. The course is situated within a broader scientific context aimed at understanding viral diversity, such that faculty and students are collaborators with established researchers in the field. The Howard Hughes Medical Institute (HHMI) Science Education Alliance Phage Hunters Advancing Genomics and Evolutionary Science (SEA-PHAGES) course has been widely implemented and has been taken by over 4,800 students at 73 institutions. We show here that this alliance-sourced model not only substantially advances the field of phage genomics but also stimulates students’ interest in science, positively influences academic achievement, and enhances persistence in science, technology, engineering, and mathematics (STEM) disciplines. Broad application of this model by integrating other research areas with large numbers of early-career undergraduate students has the potential to be transformative in science education and research training